Final Year IEEE Project 2013-2014  - Bio Medical Engineering Project Title and Abstract
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Final Year IEEE Project 2013-2014 - Bio Medical Engineering Project Title and Abstract



Final Year IEEE Project 2013-2014 - Bio Medical Engineering Project Title and Abstract

Final Year IEEE Project 2013-2014 - Bio Medical Engineering Project Title and Abstract



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Final Year IEEE Project 2013-2014  - Bio Medical Engineering Project Title and Abstract Final Year IEEE Project 2013-2014 - Bio Medical Engineering Project Title and Abstract Document Transcript

  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, 13 Years of Experience Automated Services 24/7 Help Desk Support Experience & Expertise Developers Advanced Technologies & Tools Legitimate Member of all Journals Having 1,50,000 Successive records in all Languages More than 12 Branches in Tamilnadu, Kerala & Karnataka. Ticketing & Appointment Systems. Individual Care for every Student. Around 250 Developers & 20 Researchers
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, 227-230 Church Road, Anna Nagar, Madurai – 625020. 0452-4390702, 4392702, + 91-9944793398., S.P.Towers, No.81 Valluvar Kottam High Road, Nungambakkam, Chennai - 600034. 044-42072702, +91-9600354638, 15, III Floor, SI Towers, Melapudur main Road, Trichy – 620001. 0431-4002234, + 91-9790464324. 577/4, DB Road, RS Puram, Opp to KFC, Coimbatore – 641002 0422- 4377758, +91-9677751577.
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, Plot No: 4, C Colony, P&T Extension, Perumal puram, Tirunelveli- 627007. 0462-2532104, +919677733255, 1st Floor, A.R.IT Park, Rasi Color Scan Building, Ramanathapuram - 623501. 04567-223225, 74, 2nd floor, K.V.K Complex,Upstairs Krishna Sweets, Mettur Road, Opp. Bus stand, Erode-638 011. 0424-4030055, +91- 9677748477 No: 88, First Floor, S.V.Patel Salai, Pondicherry – 605 001. 0413– 4200640 +91-9677704822 TNHB A-Block,, Opp: Hotel Ganesh Near Busstand. Salem – 636007, 0427-4042220, +91-9894444716.
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, ETPL BME-001 Convolving Engineering and Medical Pedagogies for Training of Tomorrow's Health Care Professionals Abstract: Several fundamental benefits justify why biomedical engineering and medicine should form a more convergent alliance, especially for the training of tomorrow's physicians and biomedical engineers. Herein, we review the rationale underlying the benefits. Biological discovery has advanced beyond the era of molecular biology well into today's era of molecular systems biology, which focuses on understanding the rules that govern the behavior of complex living systems. This has important medical implications. To realize cost-effective personalized medicine, it is necessary to translate the advances in molecular systems biology to higher levels of biological organization (organ, system, and organismal levels) and then to develop new medical therapeutics based on simulation and medical informatics analysis. Higher education in biological and medical sciences must adapt to a new set of training objectives. This will involve a shifting away from reductionist problem solving toward more integrative, continuum, and predictive modeling approaches which traditionally have been more associated with engineering science. Future biomedical engineers and MDs must be able to predict clinical response to therapeutic intervention. Medical education will involve engineering pedagogies, wherein basic governing rules of complex system behavior and skill sets in manipulating these systems to achieve a practical desired outcome are taught. Similarly, graduate biomedical engineering programs will include more practical exposure to clinical problem solving. ETPL BME-002 Accurate Dialysis Dose Evaluation and Extrapolation Algorithms During Online Optical Dialysis Monitoring Abstract: The aim of this study was to propose an improved method for accurate dialysis dose evaluation and extrapolation by means of Kt/$V$ from online UV-absorbance measurements for real time and continuous treatment monitoring. The study included a total of 24 treatments from ten uremic patients, seven of whom were male and three females. All patients were on chronic thrice-weekly hemodialysis therapy. The study included both stable and unstable treatments. A known signal processing algorithm, Levenberg–Marquardt, and the newly developed SMART were utilized for the removal of disturbances not relevant for dialysis dose evaluation. Finally, the results were compared with the Kt/$V$ values based on the blood samples. The new data processing algorithm, SMART, removes disturbances, helps estimate the online Kt/$V$ with significant precision increase and without any time delay, and more effectively predicts the end Kt/$V$ for the treatment than the known algorithms. ETPL BME-003 Toward Robot-Assisted Neurosurgical Lasers Abstract: Despite the potential increase in precision and accuracy, laser technology is not widely used in neurological surgery. This in part relates to challenges associated with the early introduction of lasers into neurosurgery. Considerable advances in laser technology have occurred, which together with robotic technology could create an ideal platform for neurosurgical application. In this study, a 980-nm contact diode laser was integrated with neuroArm. Preclinical evaluation involved partial hepatectomy, bilateral
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, nephrectomy, splenectomy, and bilateral submandibular gland excision in a Sprague-Dawley rat model (n = 50). Total surgical time, blood loss as weight of surgical gauze before and after the procedure, and the incidence of thermal, vascular, or lethal injury were recorded and converted to an overall performance score. Thermal damage was evaluated in the liver using tissue samples stained with hematoxylin and eosin. Clinical studies involved step-wise integration of the 980-nm laser system into four neurosurgical cases. Results demonstrate the successful integration of contact laser technology into microsurgery, with and without robotic assistance. In preclinical studies, the laser improved microsurgical performance and reduced thermal damage, while neuroArm decreased intra- and intersurgeon variability. Clinical studies demonstrate dutility in meningioma resection (n = 4). Together, laser and robotic technology offered a more consistent, expedient, and precise tool for microsurgery. ETPL BME-004 Relevance of Laser Doppler and Laser Speckle Techniques for Assessing Vascular Function: State of the Art and Future Trend Abstract: In clinical and research applications, the assessment of vascular function has become of major importance to evaluate and follow the evolution of cardiovascular pathologies, diabetes, hypertension, or foot ulcers. Therefore, the development of engineering methodologies able to monitor noninvasively blood vessel activities-such as endothelial function-is a significant and emerging challenge. Laser-based techniques have been used to respond-as much as possible-to these requirements. Among them, laser Doppler flowmetry (LDF) and laser Doppler imaging (LDI) were proposed a few decades ago. They provide interesting vascular information but possess drawbacks that prevent an easy use in some clinical situations. Recently, the laser speckle contrast imaging (LSCI) technique, a noninvasive camera-based tool, was commercialized and overcomes some of the LDF and LDI weaknesses. Our paper describes how-using engineering methodologies-LDF, LDI, and LSCI can meet the challenging clinician needs in assessing vascular function, with a special focus on the state of the art and future trends. ETPL BME-005 Quantitative Analysis of Locomotive Behavior of Human Sperm Head and Tail Abstract: Sperm selection plays a significant role in in vitro fertilization (IVF). Approaches for assessing sperm quality include noninvasive techniques based on sperm morphology and motility as well as invasive techniques for checking DNA integrity. In 2006, a new device using hyaluronic acid (HA)- coated dish for sperm selection was cleared by the Food and Drug Administration (FDA) and entered IVF clinics. In this technique, only sperms with DNA integrity bind to the HA droplet, after which these bound sperm stop revealing head motion and their tail movement becomes more vigorous. However, selecting a single sperm cell from among HA-bound sperms is ad hoc in IVF clinics. Different from existing sperm tracking algorithms that are largely limited to tracking sperm head only and are only able to track one sperm at a time, this paper presents a multisperm tracking algorithm that tracks both sperm heads and low-contrast sperm tails. The tracking results confirm a significant correlation between sperm head velocity and tail beating amplitude, demonstrate that sperms bound to HA generally have a higher velocity (before binding) than those sperms that are not able to bind to HA microdots, and quantitatively reveal that HA-bound sperms' tail beating amplitudes are different among HA-bound sperms.
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, ETPL BME-006 Grand Challenge: Applying Regulatory Science and Big Data to Improve Medical Device Innovation Abstract: Understanding how proposed medical devices will interface with humans is a major challenge that impacts both the design of innovative new devices and approval and regulation of existing devices. Today, designing and manufacturing medical devices requires extensive and expensive product cycles. Bench tests and other preliminary analyses are used to understand the range of anatomical conditions, and animal and clinical trials are used to understand the impact of design decisions upon actual device success. Unfortunately, some scenarios are impossible to replicate on the bench, and competitive pressures often accelerate initiation of animal trials without sufficient understanding of parameter selections. We believe that these limitations can be overcome through advancements in data-driven and simulation-based medical device design and manufacturing, a research topic that draws upon and combines emerging work in the areas of Regulatory Science and Big Data. We propose a cross- disciplinary grand challenge to develop and holistically apply new thinking and techniques in these areas to medical devices in order to improve and accelerate medical device innovation. ETPL BME-007 Coaxial Needle Insertion Assistant With Enhanced Force Feedback Abstract: Many medical procedures involving needle insertion into soft tissues, such as anesthesia, biopsy, brachytherapy, and placement of electrodes, are performed without image guidance. In such procedures, haptic detection of changing tissue properties at different depths during needle insertion is important for needle localization and detection of subsurface structures. However, changes in tissue mechanical properties deep inside the tissue are difficult for human operators to sense, because the relatively large friction force between the needle shaft and the surrounding tissue masks the smaller tip forces. A novel robotic coaxial needle insertion assistant, which enhances operator force perception, is presented. This one-degree-of-freedom cable-driven robot provides to the operator a scaled version of the force applied by the needle tip to the tissue, using a novel design and sensors that separate the needle tip force from the shaft friction force. The ability of human operators to use the robot to detect membranes embedded in artificial soft tissue was tested under the conditions of 1) tip force and shaft force feedback, and 2) tip force only feedback. The ratio of successful to unsuccessful membrane detections was significantly higher (up to 50%) when only the needle tip force was provided to the user. ETPL BME-008 Reducing False Intracranial Pressure Alarms Using Morphological Waveform Features Abstract: False alarms produced by patient monitoring systems in intensive care units are a major issue that causes alarm fatigue, waste of human resources, and increased patient risks. While alarms are typically triggered by manually adjusted thresholds, the trend and patterns observed prior to threshold crossing are generally not used by current systems. This study introduces and evaluates, a smart alarm detection system for intracranial pressure signal (ICP) that is based on advanced pattern recognition methods. Models are trained in a supervised fashion from a comprehensive dataset of 4791 manually
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, labeled alarm episodes extracted from 108 neurosurgical patients. The comparative analysis provided between spectral regression, kernel spectral regression, and support vector machines indicates the significant improvement of the proposed framework in detecting false ICP alarms in comparison to a threshold-based technique that is conventionally used. Another contribution of this work is to exploit an adaptive discretization to reduce the dimensionality of the input features. The resulting features lead to a decrease of 30% of false ICP alarms without compromising sensitivity. ETPL BME-009 Grand Challenges in Bioengineered Nanorobotics for Cancer Therapy Abstract: One of the grand challenges currently facing engineering, life sciences, and medicine is the development of fully functional nanorobots capable of sensing, decision making, and actuation. These nanorobots may aid in cancer therapy, site-specific drug delivery, circulating diagnostics, advanced surgery, and tissue repair. In this paper, we will discuss, from a bioinspired perspective, the challenges currently facing nanorobotics, including core design, propulsion and power generation, sensing, actuation, control, decision making, and system integration. Using strategies inspired from microorganisms, we will discuss a potential bioengineered nanorobot for cancer therapy. ETPL BME-010 Neuromodulation for Brain Disorders: Challenges and Opportunities Abstract: The field of neuromodulation encompasses a wide spectrum of interventional technologies that modify pathological activity within the nervous system to achieve a therapeutic effect. Therapies including deep brain stimulation, intracranial cortical stimulation, transcranial direct current stimulation, and transcranial magnetic stimulation have all shown promising results across a range of neurological and neuropsychiatric disorders. While the mechanisms of therapeutic action are invariably different among these approaches, there are several fundamental neuroengineering challenges that are commonly applicable to improving neuromodulation efficacy. This paper reviews the state-of-the-art of neuromodulation for brain disorders and discusses the challenges and opportunities available for clinicians and researchers interested in advancing neuromodulation therapies. ETPL BME-011 Minimizing Cytosol Dilution in Whole-Cell Patch-Clamp Experiments Abstract: During a conventional whole-cell patch clamp experiment, diffusible cytosolic ions or molecules absent in the pipette solution can become diluted by a factor of one million or more, leading to diminished current or fluorescent signals. Existing methods to prevent or limit cytosol diffusion include reducing the diameter of the pipette's orifice, adding cytosolic extract or physiological entities to the pipette solution, and using the perforated patch clamp configuration. The first method introduces measurement error in recorded signals from increased series resistance and the latter two are cumbersome to perform. In addition, most perforated patch configurations, prevent investigators from using test compounds in the pipette solution. We present a method to overcome these limitations by minimizing
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, cytosol dilution using a novel pipette holder. Cell-attached configuration is obtained with the pipette filled with pipette solution. Most of the pipette solution is then replaced with mineral oil so that cytosol dilution can be minimized in whole-cell configuration. To accomplish this requires a suction line and two Ag/AgCl electrodes inside the pipette. Testing our novel pipette holder with Chinese Hamster Ovarian cells, we demonstrate cytosol dilution factors between 76 and 234. For large cells with somas greater than 40 μm, cytosol dilution factors of 10 or less are achievable. ETPL BME-012 Engineering Stem Cells For Future Medicine Abstract: Despite their great potential in regenerative medicine applications, stem cells (especially pluripotent ones) currently show a limited clinical success, partly due to a lack of biological knowledge, but also due to a lack of specific and advanced technological instruments able to overcome the current boundaries of stem cell functional maturation and safe/effective therapeutic delivery. This paper aims at describing recent insights, current limitations, and future horizons related to therapeutic stem cells, by analyzing the potential of different bioengineering disciplines in bringing stem cells toward a safe clinical use. First, we clarify how and why stem cells should be properly engineered and which could be in a near future the challenges and the benefits connected with this process. Second, we identify different routes toward stem cell differentiation and functional maturation, relying on chemical, mechanical, topographical, and direct/indirect physical stimulation. Third, we highlight how multiscale modeling could strongly support and optimize stem cell engineering. Finally, we focus on future robotic tools that could provide an added value to the extent of translating basic biological knowledge into clinical applications, by developing ad hoc enabling technologies for stem cell delivery and control. ETPL BME-013 Surgical Robotics Through a Keyhole: From Today's Translational Barriers to Tomorrow's ―Disappearing‖ Robots, Abstract: In the last century, engineering advances have transformed the practice of surgery. Keyhole surgical techniques offer a number of advantages over traditional open approaches including less postoperative pain, fewer wound complications, and reduced length of stay in hospital. However, they also present considerable technical challenges, particularly to surgeons performing new operative approaches, such as those through natural orifices. Advances in surgical robots have improved surgical visualization, dexterity, and manipulation consistency, thus greatly enhancing surgical performance and patient care. Clinically, however, robotic surgery is still in its infancy, and its use has remained limited to relatively few operations. In the paper, we will discuss the economic-, clinical-, and research-related factors that may act as barriers to the widespread utilization and development of surgical robots. In overcoming these barriers through a synergistic effort of both engineering and medicine, we highlight our future vision of robotic surgery, in both the short and long term. ETPL BME-014 Continuous Detection of Muscle Aspect Ratio Using Keypoint Tracking in Ultrasonography
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, Abstract: Muscle aspect ratio of cross-sectional area is one of the most widely used parameters for quantifying muscle function in both diagnosis and rehabilitation assessment. Ultrasound imaging has been frequently used to noninvasively study the characteristics of human muscles as a reliable method. However, the aspect ratio measurement is traditionally conducted by the manual digitization of reference points; thus, it is subjective, time-consuming, and prone to errors. In this paper, a novel method is proposed to continuously detect the muscle aspect ratio. Two keypoint pairs are manually digitized on the lateral and longitudinal borders at the first frame, and automatically tracked by an optical flow technique at the subsequent frames. The muscle aspect ratio is thereby obtained based on the estimated muscle width and thickness. Six ultrasound sequences from different subjects are used to evaluate this method, and the overall coefficient of multiple correlation of the results between manual and proposed methods is 0.97 ± 0.02. The linear regression shows that a good linear correlation ETPL BME-015 Multi-Field-of-View Framework for Distinguishing Tumor Grade in ER+ Breast Cancer From Entire Histopathology Slides Abstract: Modified Bloom–Richardson (mBR) grading is known to have prognostic value in breast cancer (BCa), yet its use in clinical practice has been limited by intra- and interobserver variability. The development of a computerized system to distinguish mBR grade from entire estrogen receptor-positive (ER+) BCa histopathology slides will help clinicians identify grading discrepancies and improve overall confidence in the diagnostic result. In this paper, we isolate salient image features characterizing tumor morphology and texture to differentiate entire hematoxylin and eosin (H and E) stained histopathology slides based on mBR grade. The features are used in conjunction with a novel multi-field-of-view (multi- FOV) classifier—a whole-slide classifier that extracts features from a multitude of FOVs of varying sizes—to identify important image features at different FOV sizes. Image features utilized include those related to the spatial arrangement of cancer nuclei (i.e., nuclear architecture) and the textural patterns within nuclei (i.e., nuclear texture). Using slides from 126 ER+ patients (46 low, 60 intermediate, and 20 high mBR grade), our grading system was able to distinguish low versus high, low versus intermediate, and intermediate versus high grade patients with area under curve values of 0.93, 0.72, and 0.74, respectively. Our results suggest that the multi-FOV classifier is able to 1) successfully discriminate low, medium, and high mBR grade and 2) identify specific image features at different FOV sizes that are important for distinguishing mBR grade in H and E stained ER+ BCa histology slides. ETPL BME-016 Simplified Design Equations for Class-E Neural Prosthesis Transmitters Abstract: Extreme miniaturization of implantable electronic devices is recognized as essential for the next generation of neural prostheses, owing to the need for minimizing the damage and disruption of the surrounding neural tissue. Transcutaneous power and data transmission via a magnetic link remains the most effective means of powering and controlling implanted neural prostheses. Reduction in the size of the coil, within the neural prosthesis, demands the generation of a high-intensity radio frequency magnetic field from the extracoporeal transmitter. The Class-E power amplifier circuit topology has been
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, recognized as a highly effective means of producing large radio frequency currents within the transmitter coil. Unfortunately, design of a Class-E circuit is most often fraught by the need to solve a complex set of equations so as to implement both the zero-voltage-switching and zero-voltage-derivative-switching conditions that are required for efficient operation. This paper presents simple explicit design equations for designing the Class-E circuit topology. Numerical design examples are presented to illustrate the design procedure. ETPL BME-017 A 3-D Reconstruction Solution to Current Density Imaging Based on Acoustoelectric Effect by Deconvolution: A Simulation Study Abstract: Hybrid imaging modality combining ultrasound scanning and electrical current density imaging through the acoustoelectric (AE) effect may potentially provide solutions to imaging electrical activities and properties of biological tissues with high spatial resolution. In this study, a 3-D reconstruction solution to ultrasound current source density imaging (UCSDI) by means of Wiener deconvolution is proposed and evaluated through computer simulations. As compared to previous 2-D UCSDI problem, in a 3-D volume conductor with broadly distributed current density field, the AE signal becomes a 3-D convolution between the electric field and the acoustic field, and effective 3-D reconstruction algorithm has not been developed so far. In the proposed method, a 3-D ultrasound scanning is performed while the corresponding AE signals are collected from multiple electrode pairs attached on the surface of the imaging object. From the collected AE signals, the acoustic field and electric field were first decoupled by Wiener deconvolution. Then, the current density distribution was reconstructed by inverse projection. Our simulations using artificial current fields in homogeneous phantoms suggest that the proposed method is feasible and robust against noise. It is also shown that using the proposed method, it is feasible to reconstruct 3-D current density distribution in an inhomogeneous conductive medium. ETPL BME-018 Applying Combined Optical Tweezers and Fluorescence Microscopy Technologies to Manipulate Cell Adhesions for Cell-to-Cell Interaction Study Abstract: Cell-to-cell interactions are important for the regulation of various cell activities, such as proliferation, differentiation, and apoptosis. This paper presents an approach to studying cell-to-cell interactions at a single-cell level through manipulating cell adhesions with optical tweezers. Experiments are performed on leukemia cancer cells and stromal cells to demonstrate the feasibility of this method. After the adhesion properties of leukemia cells on stromal cells are characterized, fluorescence intensity is used as a label to study the Wnt signaling pathway of leukemia cells. The activities of the Wnt signaling pathway of K562 cells on M210B4 and HS5 cells are examined based on fluorescence analysis. The reliability of the fluorescence imaging is confirmed through comparison with traditional flow cytometry analysis. The proposed approach will offer new avenues to investigate otherwise inaccessible mechanisms in cell-to-cell interactions. ETPL BME-019 Far-Field RF Powering of Implantable Devices: Safety Considerations
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, Abstract: Far-field RF powering is an attractive solution to the challenge of remotely powering devices implanted in living tissue. The purpose of this study is to characterize the peak obtainable power levels in a wireless myoelectric sensor implanted in a patient while maintaining safe local temperature and RF powering conditions. This can serve as a guide for the design of onboard electronics in related medical implants and provide motivation for more efficient power management strategies for implantable integrated circuits. Safe powering conditions and peak received power levels are established using a simplified theoretical analysis and Federal Communications Commission-established limits for radiating antennas. These conditions are subsequently affirmed and improved upon using the finite-element method and temperature modeling in bovine muscle. ETPL BME-020 Blood Perfusion Values of Laser Speckle Contrast Imaging and Laser Doppler Flowmetry: Is a Direct Comparison Possible? Abstract: Laser Doppler flowmetry (LDF) and laser speckle contrast imaging (LSCI) allow the monitoring of microvascular blood perfusion. The relationship between the measurements obtained by these two techniques remains unclear. In the present contribution, we demonstrate, experimentally and theoretically, that skin blood flow measurements obtained by LDF and LSCI techniques cannot be compared directly even after ―classical‖ normalization procedure. This technical problem is generated by the nonlinear relationship existing between LDF and LSCI flow data. The experiments have been performed on five healthy voluntary subjects (forearm) by using repeated ischemia/reperfusion cycles to induce the necessary skin blood flow changes. LDF and LSCI data were simultaneously acquired on the same region of interest. Considering the importance of this problem from the clinical point of view, it is concluded that the definition of new corrected algorithms for LSCI is probably a mandatory step that must be taken into account if LDF and LSCI blood flow have to be compared. ETPL BME-021 Assessing the Effects of Pharmacological Agents on Respiratory Dynamics Using Time- Series Modeling Abstract: Developing quantitative descriptions of how stimulant and depressant drugs affect the respiratory system is an important focus in medical research. Respiratory variables-respiratory rate, tidal volume, and end tidal carbon dioxide-have prominent temporal dynamics that make it inappropriate to use standard hypothesis-testing methods that assume independent observations to assess the effects of these pharmacological agents. We present a polynomial signal plus autoregressive noise model for analysis of continuously recorded respiratory variables. We use a cyclic descent algorithm to maximize the conditional log likelihood of the parameters and the corrected Akaike's information criterion to choose simultaneously the orders of the polynomial and the autoregressive models. In an analysis of respiratory rates recorded from anesthetized rats before and after administration of the respiratory stimulant methylphenidate, we use the model to construct within-animal z-tests of the drug effect that take account of the time-varying nature of the mean respiratory rate and the serial dependence in rate measurements. We correct for the effect of model lack-of-fit on our inferences by also computing bootstrap confidence intervals for the average difference in respiratory rate pre- and postmethylphenidate treatment. Our time-
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, series modeling quantifies within each animal the substantial increase in mean respiratory rate and respiratory dynamics following methylphenidate administration. This paradigm can be readily adapted to analyze the dynamics of other respiratory variables before and after pharmacologic treatments. ETPL BME-022 2-D–3-D Frequency Registration Using a Low-Dose Radiographic System for Knee Motion Estimation Abstract: In this paper, a new method is presented to study the feasibility of the pose and the position estimation of bone structures using a low-dose radiographic system, the entrepreneurial operating system (designed by EOS-Imaging Company). This method is based on a 2-D-3-D registration of EOS bi-planar X-ray images with an EOS 3-D reconstruction. This technique is relevant to such an application thanks to the EOS ability to simultaneously make acquisitions of frontal and sagittal radiographs, and also to produce a 3-D surface reconstruction with its attached software. In this paper, the pose and position of a bone in radiographs is estimated through the link between 3-D and 2-D data. This relationship is established in the frequency domain using the Fourier central slice theorem. To estimate the pose and position of the bone, we define a distance between the 3-D data and the radiographs, and use an iterative optimization approach to converge toward the best estimation. In this paper, we give the mathematical details of the method. We also show the experimental protocol and the results, which validate our approach. ETPL BME-023 The Transesophageal Echocardiography Simulator Based on Computed Tomography Images Abstract: Simulators are a new tool in education in many fields, including medicine, where they greatly improve familiarity with medical procedures, reduce costs, and, importantly, cause no harm to patients. This is so in the case of transesophageal echocardiography (TEE), in which the use of a simulator facilitates spatial orientation and helps in case studies. The aim of the project described in this paper is to simulate an examination by TEE. This research makes use of available computed tomography data to simulate the corresponding echocardiographic view. This paper describes the essential characteristics that distinguish these two modalities and the key principles of the wave phenomena that should be considered in the simulation process, taking into account the conditions specific to the echocardiography. The construction of the CT2TEE (Web-based TEE simulator) is also presented. The considerations include ray-tracing and ray-casting techniques in the context of ultrasound beam and artifact simulation. An important aspect of the interaction with the user is raised. ETPL BME-024 Quantitative Evaluation of Two-Factor Analysis Applied to Hepatic Perfusion Study Using Contrast-enhanced Ultrasound, Abstract: Focal liver lesions (FLLs) are usually quantitatively assessed by time-intensity curves (TICs) extracted from contrast-enhanced ultrasound (CEUS) image sequences. To overcome the subjectivity of manual region of interest (ROI) selection and automatically extract TICs, a novel factor analysis method called replace approximation (RA) was proposed. Assuming that the two factors are the arterial and portal
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, vein phases, respectively, the high-dimensional time-series data are mapped into 1-D space, where the TIC at each pixel in the image becomes a point along a one-dimensional axis. The RA method aims to seek two apexes corresponding to the factor curves (the targeted TICs) in the subspace. This method was tested on 18 free-breathing datasets with respiratory motion correction. The experimental results showed that the RA method extracted physiological factor curves and the corresponding factor images efficiently. The mean correlation coefficient between the factor curves and the corresponding ROI measurements was 0.95 ± 0.02. Furthermore, the wash-in time ratio indexes of FLLs derived from the factor curves were used to perform parametric imaging, which could represent the characteristics of different types of FLLs. These results indicate that two-factor analysis has the potential to perform quantitative analysis of hepatic perfusion, which would be helpful to the differential diagnosis of FLLs. ETPL BME-025 Evaluation of Optical Coherence Tomography for the Measurement of the Effects of Activators and Anticoagulants on the Blood Coagulation In Vitro Abstract: Optical properties of human blood during coagulation were studied using optical coherence tomography (OCT) and the parameter of clotting time derived from the 1/$e$ light penetration depth $(d_{1/e})$ versus time was developed in our previous work. In this study, in order to know if a new OCT test can characterize the blood-coagulation process under different treatments in vitro, the effects of two different activators (calcium ions and thrombin) and anticoagulants, i.e., acetylsalicylic acid (ASA, a well-known drug aspirin) and melagatran (a direct thrombin inhibitor), at various concentrations are evaluated. A swept-source OCT system with a 1300 nm center wavelength is used for detecting the blood-coagulation process in vitro under a static condition. A dynamic study of $d_{1/e}$ reveals a typical behavior due to coagulation induced by both calcium ions and thrombin, and the clotting time is concentration-dependent. Dose-dependent ASA and melagatran prolong the clotting times. ASA and melagatran have different effects on blood coagulation. As expected, melagatran is much more effective than ASA in anticoagulation by the OCT measurements. The OCT assay appears to be a simple method for the measurement of blood coagulation to assess the effects of activators and anticoagulants, which can be used for activator and anticoagulant screening. ETPL BME-026 Classification of Simultaneous Movements Using Surface EMG Pattern Recognition Abstract: Advanced upper limb prostheses capable of actuating multiple degrees of freedom (DOFs) are now commercially available. Pattern recognition algorithms that use surface electromyography (EMG) signals show great promise as multi-DOF controllers. Unfortunately, current pattern recognition systems are limited to activate only one DOF at a time. This study introduces a novel classifier based on Bayesian theory to provide classification of simultaneous movements. This approach and two other classification strategies for simultaneous movements were evaluated using nonamputee and amputee subjects classifying up to three DOFs, where any two DOFs could be classified simultaneously. Similar results were found for nonamputee and amputee subjects. The new approach, based on a set of conditional parallel classifiers was the most promising with errors significantly less ( $p < 0.05$) than a single linear discriminant analysis (LDA) classifier or a parallel approach. For three-DOF classification, the
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, conditional parallel approach had error rates of 6.6% on discrete and 10.9% on combined motions, while the single LDA had error rates of 9.4% on discrete and 14.1% on combined motions. The low error rates demonstrated suggest than pattern recognition techniques on surface EMG can be extended to identify simultaneous movements, which could provide more life-like motions for amputees compared to exclusively classifying sequential movements. ETPL BME-027 Simultaneous Design of FIR Filter Banks and Spatial Patterns for EEG Signal Classification Abstract: The spatial weights for electrodes called common spatial pattern (CSP) are known to be effective in EEG signal classification for motor imagery-based brain-computer interface (MI-BCI). To achieve accurate classification in CSP, it is necessary to find frequency bands that relate to brain activities associated with BCI tasks. Several methods that determine such a set of frequency bands have been proposed. However, the existing methods cannot find the multiple frequency bands by using only learning data. To address this problem, we propose discriminative filter bank CSP (DFBCSP) that designs finite impulse response filters and the associated spatial weights by optimizing an objective function which is a natural extension of that of CSP. The optimization is conducted by sequentially and alternatively solving subproblems into which the original problem is divided. By experiments, it is shown that DFBCSP can effectively extract discriminative features for MI-BCI. Moreover, experimental results exhibit that DFBCSP can detect and extract the bands related to brain activities of motor imagery. ETPL BME-028 Development of Surrogate Spinal Cords for the Evaluation of Electrode Arrays Used in Intraspinal Implants Abstract: We report the development of a surrogate spinal cord for evaluating the mechanical suitability of electrode arrays for intraspinal implants. The mechanical and interfacial properties of candidate materials (including silicone elastomers and gelatin hydrogels) for the surrogate cord were tested. The elastic modulus was characterized using dynamic mechanical analysis, and compared with values of actual human spinal cords from the literature. Forces required to indent the surrogate cords to specified depths were measured to obtain values under static conditions. Importantly, to quantify surface properties in addition to mechanical properties normally considered, interfacial frictional forces were measured by pulling a needle out of each cord at a controlled rate. The measured forces were then compared to those obtained from rat spinal cords. Formaldehyde-crosslinked gelatin, 12 wt% in water, was identified as the most suitable material for the construction of surrogate spinal cords. To demonstrate the utility of surrogate spinal cords in evaluating the behavior of various electrode arrays, cords were implanted with two types of intraspinal electrode arrays (one made of individual microwires and another of microwires anchored with a solid base), and cord deformation under elongation was evaluated. The results demonstrate that the surrogate model simulates the mechanical and interfacial properties of the spinal cord, and enables in vitro screening of intraspinal implants. ETPL BME-029 Compressed Sensing for Energy-Efficient Wireless Telemonitoring of Noninvasive Fetal ECG Via Block Sparse Bayesian Learning
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, Abstract: Fetal ECG (FECG) telemonitoring is an important branch in telemedicine. The design of a telemonitoring system via a wireless body area network with low energy consumption for ambulatory use is highly desirable. As an emerging technique, compressed sensing (CS) shows great promise in compressing/reconstructing data with low energy consumption. However, due to some specific characteristics of raw FECG recordings such as nonsparsity and strong noise contamination, current CS algorithms generally fail in this application. This paper proposes to use the block sparse Bayesian learning framework to compress/reconstruct nonsparse raw FECG recordings. Experimental results show that the framework can reconstruct the raw recordings with high quality. Especially, the reconstruction does not destroy the interdependence relation among the multichannel recordings. This ensures that the independent component analysis decomposition of the reconstructed recordings has high fidelity. Furthermore, the framework allows the use of a sparse binary sensing matrix with much fewer nonzero entries to compress recordings. Particularly, each column of the matrix can contain only two nonzero entries. This shows that the framework, compared to other algorithms such as current CS algorithms and wavelet algorithms, can greatly reduce code execution in CPU in the data compression stage. ETPL BME-030 Clinical Validation of the Quick Dynamic Insulin Sensitivity Test Abstract: The quick dynamic insulin sensitivity test (DISTq) can yield an insulin sensitivity result immediately after a 30-min clinical protocol. The test uses intravenous boluses of 10 g glucose and 1 U insulin at $t$ = 1 and 11 min, respectively, and measures glucose levels in samples taken at $t$ = 0, 10, 20, and 30 min. The low clinical cost of the protocol is enabled via robust model formulation and a series of population-derived relationships that estimate insulin pharmacokinetics as a function of insulin sensitivity ( SI). Fifty individuals underwent the gold standard euglycaemic clamp (EIC) and DISTq within an eight-day period.SI values from the EIC and two DISTq variants (four-sample DISTq and two- sample DISTq30) were compared with correlation, Bland–Altman and receiver operator curve analyses. DISTq and DISTq30 correlated well with the EIC [$R$ = 0.76 and 0.75, and receiver operator curve c- index = 0.84 and 0.85, respectively]. The median differences between EIC and DISTq/DISTq30 SI values were 13% and 22%, respectively. The DISTq estimation method predicted individual insulin responses without specific insulin assays with relative accuracy and thus high equivalence to EIC SI values was achieved. DISTq produced very inexpensive, relatively accurate immediate results, and can thus enable a number of applications that are impossible with established SI tests. ETPL BME-031 Spine Image Fusion Via Graph Cuts Abstract: This study investigates a novel CT/MR spine image fusion algorithm based on graph cuts. This algorithm allows physicians to visually assess corresponding soft tissue and bony detail on a single image eliminating mental alignment and correlation needed when both CT and MR images are required for diagnosis. We state the problem as a discrete multilabel optimization of an energy functional that balances the contributions of three competing terms: (1) a squared error, which encourages the solution to be
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, similar to the MR input, with a preference to strong MR edges; (2) a squared error, which encourages the solution to be similar to the CT input, with a preference to strong CT edges; and (3) a prior, which favors smooth solutions by encouraging neighboring pixels to have similar fused-image values. We further introduce a transparency-labeling formulation, which significantly reduces the computational load. The proposed graph-cut fusion guarantees nearly global solutions, while avoiding the pix elation artifacts that affect standard wavelet-based methods. We report several quantitative evaluations/comparisons over 40 pairs of CT/MR images acquired from 20 patients, which demonstrate a very competitive performance in comparisons to the existing methods. We further discuss various case studies, and give a representative sample of the results. ETPL BME-032 Cross-Scale Coefficient Selection for Volumetric Medical Image Fusion Abstract: Joint analysis of medical data collected from different imaging modalities has become a common clinical practice. Therefore, image fusion techniques, which provide an efficient way of combining and enhancing information, have drawn increasing attention from the medical community. In this paper, we propose a novel cross-scale fusion rule for multiscale-decomposition-based fusion of volumetric medical images taking into account both intrascale and interscale consistencies. An optimal set of coefficients from the multiscale representations of the source images is determined by effective exploitation of neighborhood information. An efficient color fusion scheme is also proposed. Experiments demonstrate that our fusion rule generates better results than existing rules. ETPL BME-033 Estimation of Tool Pose Based on Force–Density Correlation During Robotic Drilling Abstract: The application of image-guided systems with or without support by surgical robots relies on the accuracy of the navigation process, including patient-to-image registration. The surgeon must carry out the procedure based on the information provided by the navigation system, usually without being able to verify its correctness beyond visual inspection. Misleading surrogate parameters such as the fiducial registration error are often used to describe the success of the registration process, while a lack of methods describing the effects of navigation errors, such as those caused by tracking or calibration, may prevent the application of image guidance in certain accuracy-critical interventions. During minimally invasive mastoidectomy for cochlear implantation, a direct tunnel is drilled from the outside of the mastoid to a target on the cochlea based on registration using landmarks solely on the surface of the skull. Using this methodology, it is impossible to detect if the drill is advancing in the correct direction and that injury of the facial nerve will be avoided. To overcome this problem, a tool localization method based on drilling process information is proposed. The algorithm estimates the pose of a robot-guided surgical tool during a drilling task based on the correlation of the observed axial drilling force and the heterogeneous bone density in the mastoid extracted from 3-D image data. We present here one possible implementation of this method tested on ten tunnels drilled into three human cadaver specimens where an average tool localization accuracy of 0.29 mm was observed.
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, ETPL BME-034 Ephaptic Coupling in Cardiac Myocytes Abstract: While it is widely believed that conduction in cardiac tissue is regulated by gap junctions, recent experimental evidence suggests that the extracellular space may play a significant role in action potential propagation. Cardiac tissue with low gap junctional coupling still exhibits conduction, with conflicting degrees of slowing that may be due to variations in the extracellular space. Inhomogeneities in the extracellular space caused by the complex cellular structure in cardiac tissue can lead to ephaptic, or field effect, coupling. Here, we present data from simulations of a cylindrical strand of cells in which we see the dramatic effect highly resistant extracellular spaces have on propagation velocity. We find that ephaptic effects occur in all areas of small extracellular spaces and are not restricted to the junctional cleft between cells. This previously unrecognized type of field coupling, which we call lateral coupling, can allow conduction in the absence of gap junctions. We compare our results with the classically used cable theory, demonstrating the quantitative difference in propagation velocity arising from the cellular geometry. Ephaptic effects are shown to be highly dependent upon parameter values, frequently enhancing, but sometimes decreasing propagation speed. Our mathematical analysis incorporates the inhomogeneities in the extracellular microdomains that cannot be directly measured by experimental techniques and will aid in optimizing cardiac treatments that require manipulation of the cellular geometry and understanding heart functionality. ETPL BME-035 Raven-II: An Open Platform for Surgical Robotics Research Abstract: The Raven-II is a platform for collaborative research on advances in surgical robotics. Seven universities have begun research using this platform. The Raven-II system has two 3-DOF spherical positioning mechanisms capable of attaching interchangeable four DOF instruments. The Raven-II software is based on open standards such as Linux and ROS to maximally facilitate software development. The mechanism is robust enough for repeated experiments and animal surgery experiments, but is not engineered to sufficient safety standards for human use. Mechanisms in place for interaction among the user community and dissemination of results include an electronic forum, an online software SVN repository, and meetings and workshops at major robotics conferences. ETPL BME-036 Compressed Sensing of EEG for Wireless Telemonitoring With Low Energy Consumption and Inexpensive Hardware Abstract: Telemonitoring of electroencephalogram (EEG) through wireless body-area networks is an evolving direction in personalized medicine. Among various constraints in designing such a system, three important constraints are energy consumption, data compression, and device cost. Conventional data compression methodologies, although effective in data compression, consumes significant energy and cannot reduce device cost. Compressed sensing (CS), as an emerging data compression methodology, is promising in catering to these constraints. However, EEG is nonsparse in the time domain and also nonsparse in transformed domains (such as the wavelet domain). Therefore, it is extremely difficult for
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, current CS algorithms to recover EEG with the quality that satisfies the requirements of clinical diagnosis and engineering applications. Recently, block sparse Bayesian learning (BSBL) was proposed as a new method to the CS problem. This study introduces the technique to the telemonitoring of EEG. Experimental results show that its recovery quality is better than state-of-the-art CS algorithms, and sufficient for practical use. These results suggest that BSBL is very promising for telemonitoring of EEG and other nonsparse physiological signals. ETPL BME-037 The Alpha Band of the Resting Electroencephalogram Under Pulsed and Continuous Radio Frequency Exposures Abstract: The effect of GSM-like electromagnetic fields with the resting electroencephalogram (EEG) alpha band activity was investigated in a double-blind cross-over experimental paradigm, testing the hypothesis that pulsed but not continuous radio frequency (RF) exposure would affect alpha activity, and the hypothesis that GSM-like pulsed low frequency fields would affect alpha. Seventy-two healthy volunteers attended a single recording session where the eyes open resting EEG activity was recorded. Four exposure intervals were presented (sham, pulsed modulated RF, continuous RF, and pulsed low frequency) in a counterbalanced order where each exposure lasted for 20 min. Compared to sham, a suppression of the global alpha band activity was observed under the pulsed modulated RF exposure, and this did not differ from the continuous RF exposure. No effect was seen in the extremely low frequency condition. That there was an effect of pulsed RF that did not differ significantly from continuous RF exposure does not support the hypothesis that ―pulsed‖ RF is required to produce EEG effects. The results support the view that alpha is altered by RF electromagnetic fields, but suggest that the pulsing nature of the fields is not essential for this effect to occur. ETPL BME-038 A Wireless Robot for Networked Laparoscopy Abstract: State-of-the-art laparoscopes for minimally invasive abdominal surgery are encumbered by cabling for power, video, and light sources. Although these laparoscopes provide good image quality, they interfere with surgical instruments, occupy a trocar port, require an assistant in the operating room to control the scope, have a very limited field of view, and are expensive. MARVEL is a wireless Miniature Anchored Robotic Videoscope for Expedited Laparoscopy that addresses these limitations by providing an inexpensive in vivo wireless camera module (CM) that eliminates the surgical-tool bottleneck experienced by surgeons in current laparoscopic endoscopic single-site (LESS) procedures. The MARVEL system includes1) multiple CMs that feature awirelessly controlled pan/tilt camera platform, which enable a full hemisphere field of view inside the abdominal cavity, wirelessly adjustable focus, and a multiwavelength illumination control system; 2) a master control module that provides a near-zero latency video wireless communications link, independent wireless control for multiple MARVEL CMs, digital zoom; and 3) a wireless human-machine interface that gives the surgeon full control over CM functionality. The research reported in this paper is the first step in developing a suite of semiautonomous wirelessly controlled and networked robotic cyberphysical devices to enable a paradigm shift in
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, minimally invasive surgery and other domains such as wireless body area networks. ETPL BME-039 Quantifying Limb Movements in Epileptic Seizures Through Color-Based Video Analysis Abstract: This paper proposes a color-based video analytic system for quantifying limb movements in epileptic seizure monitoring. The system utilizes colored pyjamas to facilitate limb segmentation and tracking. Thus, it is unobtrusive and requires no sensor/marker attached to patient's body. We employ Gaussian mixture models in background/foreground modeling and detect limbs through a coarse-to-fine paradigm with graph-cut-based segmentation. Next, we estimate limb parameters with domain knowledge guidance and extract displacement and oscillation features from movement trajectories for seizure detection/analysis. We report studies on sequences captured in an epilepsy monitoring unit. Experimental evaluations show that the proposed system has achieved comparable performance to EEG-based systems in detecting motor seizures. ETPL BME-040 Automatic Segmentation of Antenatal 3-D Ultrasound Images Abstract: The development of 3-D ultrasonic probes and 3-D ultrasound (3DUS) imaging offers new functionalities that call for specific image processing developments. In this paper, we propose an original method for the segmentation of the utero-fetal unit (UFU) from 3DUS volumes, acquired during the first trimester of gestation. UFU segmentation is required for a number of tasks, such as precise organ delineation, 3-D modeling, quantitative measurements, and evaluation of the clinical impact of 3-D imaging. The segmentation problem is formulated as the optimization of a partition of the image into two classes of tissues: the amniotic fluid and the fetal tissues. A Bayesian formulation of the partition problem integrates statistical models of the intensity distributions in each tissue class and regularity constraints on the contours. An energy functional is minimized using a level set implementation of a deformable model to identify the optimal partition. We propose to combine Rayleigh, Normal, Exponential, and Gamma distribution models to compute the region homogeneity constraints. We tested the segmentation method on a database of 19 antenatal 3DUS images. Promising results were obtained, showing the flexibility of the level set formulation and the interest of learning the most appropriate statistical models according to the idiosyncrasies of the data and the tissues. The segmentation method was shown to be robust to different types of initialization and to provide accurate results, with an average overlap measure of 0.89 when comparing with manual segmentations. ETPL BME-041 Simultaneously Identifying All True Vessels From Segmented Retinal Images Abstract: Measurements of retinal blood vessel morphology have been shown to be related to the risk of cardiovascular diseases. The wrong identification of vessels may result in a large variation of these measurements, leading to a wrong clinical diagnosis. In this paper, we address the problem of automatically identifying true vessels as a postprocessing step to vascular structure segmentation. We
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, model the segmented vascular structure as a vessel segment graph and formulate the problem of identifying vessels as one of finding the optimal forest in the graph given a set of constraints. We design a method to solve this optimization problem and evaluate it on a large real-world dataset of 2446 retinal images. Experiment results are analyzed with respect to actual measurements of vessel morphology. The results show that the proposed approach is able to achieve 98.9% pixel precision and 98.7% recall of the true vessels for clean segmented retinal images, and remains robust even when the segmented image is noisy. ETPL BME-042 Safety Auxiliary Feedback Element for the Artificial Pancreas in Type 1 Diabetes Abstract: The artificial pancreas aims at the automatic delivery of insulin for glycemic control in patients with type 1 diabetes, i.e., closed-loop glucose control. One of the challenges of the artificial pancreas is to avoid controller overreaction leading to hypoglycemia, especially in the late postprandial period. In this study, an original proposal based on sliding mode reference conditioning ideas is presented as a way to reduce hypoglycemia events induced by a closed-loop glucose controller. The method is inspired in the intuitive advantages of two-step constrained control algorithms. It acts on the glucose reference sent to the main controller shaping it so as to avoid violating given constraints on the insulin-on-board. Some distinctive features of the proposed strategy are that 1) it provides a safety layer which can be adjusted according to medical criteria; 2) it can be added to closed-loop controllers of any nature; 3) it is robust against sensor failures and overestimated prandial insulin doses; and 4) it can handle nonlinear models. The method is evaluated in silico with the ten adult patients available in the FDA-accepted UVA simulator. ETPL BME-043 Cuffless Differential Blood Pressure Estimation Using Smart Phones Abstract: Smart phones today have become increasingly popular with the general public for their diverse functionalities such as navigation, social networking, and multimedia facilities. These phones are equipped with high-end processors, high-resolution cameras, and built-in sensors such as accelerometer, orientation-sensor, and light-sensor. According to comScore survey, 26.2% of U.S. adults use smart phones in their daily lives. Motivated by this statistic and the diverse capability of smart phones, we focus on utilizing them for biomedical applications. We present a new application of the smart phone with its built-in camera and microphone replacing the traditional stethoscope and cuff-based measurement technique, to quantify vital signs such as heart rate and blood pressure. We propose two differential blood pressure estimating techniques using the heartbeat and pulse data. The first method uses two smart phones whereas the second method replaces one of the phones with a customized external microphone. We estimate the systolic and diastolic pressure in the two techniques by computing the pulse pressure and the stroke volume from the data recorded. By comparing the estimated blood pressure values with those measured using a commercial blood pressure meter, we obtained encouraging results of 95-100% accuracy. ETPL BME-044 Design and Implementation of a Wireless Capsule Suitable for Autofluorescence Intensity Detection in Biological Tissues
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, Abstract: We report on the design, fabrication, testing, and packaging of a miniaturized system capable of detecting autofluorescence (AF) from mammalian intestinal tissue. The system comprises an application- specific integrated circuit (ASIC), light-emitting diode, optical filters, control unit, and radio transmitter. The ASIC contains a high-voltage charge pump and single-photon avalanche diode detector (SPAD). The charge pump biases the SPAD above its breakdown voltage to operate in Geiger mode. The SPAD offers a photon detection efficiency of 37% at 520 nm, which corresponds to the AF emission peak of the principle human intestinal fluorophore, flavin adenine dinucleotide. The ASIC was fabricated using a commercial triple-well high-voltage CMOS process. The complete device operates at 3 V and draws an average of 7.1 mA, enabling up to 23 h of continuous operation from two 165-mAh SR44 batteries. ETPL BME-045 A Dynamic Risk Score to Identify Increased Risk for Heart Failure Decompensation Abstract: A method for combining heart failure (HF) diagnostic information in a Bayesian belief network (BBN) framework to improve the ability to identify when patients are at risk for HF hospitalization (HFH) is investigated in this paper. Implantable devices collect HF related diagnostics, such as intrathoracic impedance, atrial fibrillation (AF) burden, ventricular rate during AF, night heart rate, heart rate variability, and patient activity, on a daily basis. Features were extracted that encoded information regarding out of normal range values as well as temporal changes at weekly and monthly time scales. A BBN is used to combine the features to generate a risk score defined as the probability of a HFH given the diagnostic evidence. Patients with a very high risk score at follow-up are 15 times more likely to have a HFH in the next 30 days compared to patients with a low-risk score. The combined score has improved ability to identify patients at risk for HFH compared to the individual diagnostic parameters. A score of this nature allows clinicians to manage patients by exception; a patient with higher risk score needs more attention than a patient with lower risk score. ETPL BME-046 Design and Optimization of Reaction Chamber and Detection System in Dynamic Labs-on-Chip for Proteins Detection Abstract: In this paper, the lab-on-chip section for a protein assay is designed and optimized. To avoid severe reliability problems related to activated surface stability, a dynamic assay approach is adopted: protein-to-protein neutralization is performed while proteins diffuse freely in the reaction chamber. The related refraction index change is detected via an integrated interferometer. The structure is also design to provide a functional test of the reference protein solution, which is generally required for qualification for medical uses. ETPL BME-047 An Approach to Rapid Calculation of Temperature Change in Tissue Using Spatial Filters to Approximate Effects of Thermal Conduction Abstract: We present an approach to performing rapid calculations of temperature within tissue by interleaving, at regular time intervals, 1) an analytical solution to the Pennes (or other desired) bioheat
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, equation excluding the term for thermal conduction and 2) application of a spatial filter to approximate the effects of thermal conduction. Here, the basic approach is presented with attention to filter design. The method is applied to a few different cases relevant to magnetic resonance imaging, and results are compared to those from a full finite-difference (FD) implementation of the Pennes bioheat equation. It is seen that results of the proposed method are in reasonable agreement with those of the FD approach, with about 15% difference in the calculated maximum temperature increase, but are calculated in a fraction of the time, requiring less than 2% of the calculation time for the FD approach in the cases evaluated. ETPL BME-048 Noninvasive Biomagnetic Detection of Isolated Ischemic Bowel Segments Abstract: The slow wave activity was measured in the magnetoenterogram (MENG) of normal porcine subjects ( N = 5) with segmental intestinal ischemia. The correlation changes in enteric slow wave activity were determined in MENG and serosal electromyograms (EMG). MENG recordings show significant changes in the frequency and power distribution of enteric slow-wave signals during segmental ischemia, and these changes agree with changes observed in the serosal EMG. There was a high degree of correlation between the frequency of the electrical activity recorded in MENG and in serosal EMG (r = 0.97). The percentage of power distributed in brady- and normoenteric frequency ranges exhibited significant segmental ischemic changes. Our results suggest that noninvasive MENG detects ischemic changes in isolated small bowel segments. ETPL BME-049 A New Strategy for Model Order Identification and Its Application to Transfer Entropy for EEG Signals Analysis Abstract: The background objective of this study is to analyze electrenocephalographic (EEG) signals recorded with depth electrodes during seizures in patients with drug-resistant epilepsy. Usually, different phases are observed during the seizure evolution, including a fast onset activity. We aim to ascertain how cerebral structures get involved during this phase, in particular whether some structures ―drive‖ other ones. Regarding a recent theoretical information measure, namely the transfer entropy (TE), we propose two criteria, the first one is based on Akaike's information criterion, the second on the Bayesian information criterion, to derive models’ orders that constitute crucial parameters in the TE estimation. A normalized index, named partial transfer entropy (PTE), allows for quantifying the contribution or the influence of a signal to the global information flow between a pair of signals. Experiments are first conducted on linear autoregressive models, then on a physiology-based model, and finally on real intracerebral EEG epileptic signals to detect and identify directions of causal interdependence. Results support the relevance of the new measures for characterizing the information flow propagation whatever unidirectional or bidirectional interactions. ETPL BME-050 Surface Electrocardiogram Reconstruction From Intracardiac Electrograms Using a Dynamic Time Delay Artificial Neural Network Abstract: This study proposes a method to facilitate the remote follow up of patients suffering from
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, cardiac pathologies and treated with an implantable device, by synthesizing a 12-lead surface ECG from the intracardiac electrograms (EGM) recorded by the device. Two methods (direct and indirect), based on dynamic time-delay artificial neural networks (TDNNs) are proposed and compared with classical linear approaches. The direct method aims to estimate 12 different transfer functions between the EGM and each surface ECG signal. The indirect method is based on a preliminary orthogonalization phase of the available EGM and ECG signals, and the application of the TDNN between these orthogonalized signals, using only three transfer functions. These methods are evaluated on a dataset issued from 15 patients. Correlation coefficients calculated between the synthesized and the real ECG show that the proposed TDNN methods represent an efficient way to synthesize 12-lead ECG, from two or four EGM and perform better than the linear ones. We also evaluate the results as a function of the EGM configuration. Results are also supported by the comparison of extracted features and a qualitative analysis performed by a cardiologist. ETPL BME-051 Segmentation of Dermoscopy Images Using Wavelet Networks Abstract: This paper introduces a new approach for the segmentation of skin lesions in dermoscopic images based on wavelet network (WN). The WN presented here is a member of fixed-grid WNs that is formed with no need of training. In this WN, after formation of wavelet lattice, determining shift and scale parameters of wavelets with two screening stage and selecting effective wavelets, orthogonal least squares algorithm is used to calculate the network weights and to optimize the network structure. The existence of two stages of screening increases globality of the wavelet lattice and provides a better estimation of the function especially for larger scales. R, G, and B values of a dermoscopy image are considered as the network inputs and the network structure formation. Then, the image is segmented and the skin lesions exact boundary is determined accordingly. The segmentation algorithm were applied to 30 dermoscopic images and evaluated with 11 different metrics, using the segmentation result obtained by a skilled pathologist as the ground truth. Experimental results show that our method acts more effectively in comparison with some modern techniques that have been successfully used in many medical imaging problems. ETPL BME-052 Prediction of Uterine Contractions Using Knowledge-Assisted Sequential Pattern Analysis Abstract: The usage of the systemic opioid remifentanil in relieving the labor pain has attracted much attention recently. An optimal dosing regimen for administration of remifentanil during labor relies on anticipating the timing of uterine contractions. These predictions should be made early enough to maximize analgesia efficacy during contractions and minimize the impact of the medication between contractions. We have designed a knowledge-assisted sequential pattern analysis framework to 1) predict the intrauterine pressure in real time; 2) anticipate the next contraction; and 3) develop a sequential association rule mining approach to identify the patterns of the contractions from historical patient tracings (HT).
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, ETPL BME-053 Development of a Wireless Sensor for the Measurement of Chicken Blood Flow Using the Laser Doppler Blood Flow Meter Technique Abstract: Here, we report the development of an integrated laser Doppler blood flow micrometer for chickens. This sensor weighs only 18 g and is one of the smallest-sized blood flow meters, with no wired line, these are features necessary for attaching the sensor to the chicken. The structure of the sensor chip consists of two silicon cavities with a photo diode and a laser diode, which was achieved using the microelectromechanical systems technique, resulting in its small size and significantly low power consumption. In addition, we introduced an intermittent measuring arrangement in the measuring system to reduce power consumption and to enable the sensor to work longer. We were successfully able to measure chicken blood flow for five consecutive days, and discovered that chicken blood flow shows daily fluctuations. ETPL BME-054 Validation of Statistical Channel Models for 60 GHz Radio Systems in Hospital Environments Abstract: Statistical channel models for $hbox{60}$ GHz communications systems in hospital environments are validated using channel capacity and throughput of a physical layer as figures of merit. The channel models are validated by comparing the performance figures with channels from the measurements and the channel models. The throughput evaluation is based on system specifications given by the IEEE 802.15.3 c standard for high data rate wireless personal area networks, namely orthogonal frequency division multiplexing and single carrier transmissions. The channel capacity serves as a metric of the potential of the two transmission schemes since it defines the upper bound of the throughput. The capacity is derived based on the signal formats of the transmission schemes. The capacity shows that $hbox{97}$ % of the measurement results are within $2sigma$ range of the modeled results. The throughput shows that the channel models predict the maximum achievable throughput of the measured channels precisely, while the mean throughput in some cases shows difference because of the interpolation effect of the small-scale fading in the statistical channel models. Due to the interpolation effect, the channel model is more suitable for a precise analysis of the outage performance than the measurements where the number of channel samples is limited and the worst faded channels are not necessarily included. ETPL BME-055 Multistructure Large Deformation Diffeomorphic Brain Registration Abstract: Whole brain MRI registration has many useful applications in group analysis and morphometry, yet accurate registration across different neuropathological groups remains challenging. Structure-specific information, or anatomical guidance, can be used to initialize and constrain registration to improve accuracy and robustness. We describe here a multistructure diffeomorphic registration approach that uses concurrent subcortical and cortical shape matching to guide the overall registration. Validation experiments carried out on openly available datasets demonstrate comparable or improved alignment of subcortical and cortical brain structures over leading brain registration algorithms. We also demonstrate
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, that a group-wise average atlas built with multistructure registration accounts for greater intersubject variability and provides more sensitive tensor-based morphometry measurements ETPL BME-056 ECG Signal Quality During Arrhythmia and Its Application to False Alarm Reduction Abstract: An automated algorithm to assess electrocardiogram (ECG) quality for both normal and abnormal rhythms is presented for false arrhythmia alarm suppression of intensive care unit (ICU) monitors. A particular focus is given to the quality assessment of a wide variety of arrhythmias. Data from three databases were used: the Physionet Challenge 2011 dataset, the MIT-BIH arrhythmia database, and the MIMIC II database. The quality of more than 33 000 single-lead 10 s ECG segments were manually assessed and another 12 000 bad-quality single-lead ECG segments were generated using the Physionet noise stress test database. Signal quality indices (SQIs) were derived from the ECGs segments and used as the inputs to a support vector machine classifier with a Gaussian kernel. This classifier was trained to estimate the quality of an ECG segment. Classification accuracies of up to 99% on the training and test set were obtained for normal sinus rhythm and up to 95% for arrhythmias, although performance varied greatly depending on the type of rhythm. Additionally, the association between 4050 ICU alarms from the MIMIC II database and the signal quality, as evaluated by the classifier, was studied. Results suggest that the SQIs should be rhythm specific and that the classifier should be trained for each rhythm call independently. This would require a substantially increased set of labeled data in order to train an accurate algorithm. ETPL BME-057 Tissue Classification Using Ultrasound-Induced Variations in Acoustic Backscattering Features Abstract: Ultrasound (US) radio-frequency (RF) time series is an effective tissue classification method that enables accurate cancer diagnosis, but the mechanisms underlying this method are not completely understood. This paper presents a model to describe the variations in tissue temperature and sound speed that take place during the RF time series scanning procedures and relate these variations to US backscattering. The model was used to derive four novel characterization features. These features were used to classify three animal tissues, and they obtained accuracies as high as 88.01%. The performance of the proposed features was compared with RF time series features proposed in a previous study. The results indicated that the US-induced variations in tissue temperature and sound speed, which were used to derive the proposed features, were important contributors to the tissue typing capabilities of the RF time series. Simulations carried out to estimate the heating induced during the scanning procedure employed in this study showed temperature rises lower than 2 °C. The model and results presented in this paper can be used to improve the RF time series. ETPL BME-058 On-Chip Systolic Networks for Real-Time Tracking of Pairwise Correlations Between Neurons in a Large-Scale Network Abstract: The correlation map of neurons emerges as an important mathematical framework for a
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, spectrum of applications including neural circuit modeling, neurologic disease bio-marking and neuroimaging. However, constructing a correlation map is computationally expensive, especially when the number of neurons is large. This paper proposes a hardware design using hierarchical systolic arrays to calculate pairwise correlations between neurons. Through mapping a computationally efficient algorithm for cross-correlation onto a massively parallel structure, the hardware is able to construct the correlation maps in a much shorter time. The proposed architecture was evaluated using a field programmable gate array. The results show that the computational delay of the hardware for constructing correlation maps increases linearly with the number of neurons, whereas the growth of delay is quadratic for a software-based serial approach. Also, the efficiency of our method for detecting abnormal behaviors of neural circuits is demonstrated by analyzing correlation maps of retinal neurons. ETPL BME-059 An Online Failure Detection Method of the Glucose Sensor-Insulin Pump System: Improved Overnight Safety of Type-1 Diabetic Subjects Abstract: Sensors for real-time continuous glucose monitoring (CGM) and pumps for continuous subcutaneous insulin infusion (CSII) have opened new scenarios for Type-1 diabetes treatment. However, occasional failures of either CGM or CSII may expose diabetic patients to possibly severe risks, especially overnight (e.g., inappropriate insulin administration). In this contribution, we present a method to detect in real time such failures by simultaneously using CGM and CSII data streams and a black-box model of the glucose-insulin system. First, an individualized state-space model of the glucose-insulin system is identified offline from CGM and CSII data collected during a previous monitoring. Then, this model, CGM and CSII real-time data streams are used online to obtain predictions of future glucose concentrations together with their confidence intervals by exploiting a Kalman filtering approach. If glucose values measured by the CGM sensor are not consistent with the predictions, a failure alert is generated in order to mitigate the risks for patient safety. The method is tested on 100 virtual patients created by using the UVA/Padova Type-1 diabetic simulator. Three different types of failures have been simulated: spike in the CGM profile, loss of sensitivity of glucose sensor, and failure in the pump delivery of insulin. Results show that, in all cases, the method is able to correctly generate alerts, with a very limited number of false negatives and a number of false positives, on average, lower than 10%. The use of the method in three subjects supports the simulation results, demonstrating that the accuracy of the method in generating alerts in presence of failures of the CGM sensor-CSII pump system can significantly improve safety of Type-1 diabetic patients overnight ETPL BME-060 Quantitative Evaluation of Transform Domains for Compressive Sampling-Based Recovery of Sparsely Sampled Volumetric OCT Images Abstract: Recently, compressive sampling has received significant attention as an emerging technique for rapid volumetric imaging. We have previously investigated volumetric optical coherence tomography (OCT) image acquisition using compressive sampling techniques and showed that it was possible to recover image volumes from a subset of sampled images. Our previous findings used the multidimensional wavelet transform as the domain of sparsification for recovering OCT image volumes. In this report, we analyzed and compared the potential and efficiency of three other image transforms to
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, reconstruct the same volumetric OCT image. Two quantitative measures, the mean square error and the structural similarity index, were applied to compare the quality of the reconstructed volumetric images. We observed that fast Fourier transformation and wavelet both are capable of reconstructing OCT image volumes for the orthogonal sparse sampling masks used in this report, but with different merits. ETPL BME-061 The Use of a Bone-Anchored Device as a Hard-Wired Conduit for Transmitting EMG Signals From Implanted Muscle Electrodes Abstract: The use of a bone-anchored device to transmit electrical signals from internalized muscle electrodes was studied in a sheep model. The bone-anchored device was used as a conduit for the passage of a wire connecting an internal epimysial electrode to an external signal-recording device. The bone- anchored device was inserted into an intact tibia and the electrode attached to the adjacent M. peroneus tertius. ―Physiological‖ signals with low signal-to-noise ratios were successfully obtained over a 12-week period by walking the sheep on a treadmill. Reliable transmission of multiple muscle signals across the skin barrier is essential for providing intuitive, biomimetic upper limb prostheses. This technology has the potential to provide a better functional and reliable solution for upper limb amputee rehabilitation: attachment and control. ETPL BME-062 The iFit: An Integrated Physical Fitness Testing System to Evaluate the Degree of Physical Fitness of the Elderly Abstract: This paper presents an integrated physical fitness testing system (iFit) that evaluates the physical fitness of older adults. The intent of the test is to help them manage and promote their health and mitigate the effects of aging. National protocols of physical fitness were implemented to support the assessment. The proposed system encompasses four modules of physical fitness assessment for both users and medical professionals. The test information will be recorded and managed through a wireless sensor network that will enable a better understanding of users' fitness states. Furthermore, the iFit has been validated by a test session attended by elderly participants. The results show that there is a significant correlation between iFit use in the test of flexibility, grip strength, and balance, compared to conventional methods. ETPL BME-063 Multichannel Weighted Speech Classification System for Prediction of Major Depression in Adolescents Abstract: Early identification of adolescents at high imminent risk for clinical depression could significantly reduce the burden of the disease. This study demonstrated that acoustic speech analysis and classification can be used to determine early signs of major depression in adolescents, up to two years before they meet clinical diagnostic criteria for the full-blown disorder. Individual contributions of four different types of acoustic parameters [prosodic, glottal, Teager's energy operator (TEO), and spectral] to depression-related changes of speech characteristics were examined. A new computational methodology for the early prediction of depression in adolescents was developed and tested. The novel aspect of this methodology is in the introduction of multichannel classification with a weighted decision procedure. It
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, was observed that single-channel classification was effective in predicting depression with a desirable specificity-to-sensitivity ratio and accuracy higher than chance level only when using glottal or prosodic features. The best prediction performance was achieved with the new multichannel method, which used four features (prosodic, glottal, TEO, and spectral). In the case of the person-based approach with two sets of weights, the new multichannel method provided a high accuracy level of 73% and the sensitivity-to- specificity ratio of 79%/67% for predicting future depression. ETPL BME-064 Improved Multimodality Data Fusion of Late Gadolinium Enhancement MRI to Left Ventricular Voltage Maps in Ventricular Tachycardia Ablation Abstract: Electroanatomical voltage mapping (EAVM) is commonly performed prior to catheter ablation of scar-related ventricular tachycardia (VT) to locate the arrhythmic substrate and to guide the ablation procedure. EAVM is used to locate the position of the ablation catheter and to provide a 3-D reconstruction of left-ventricular anatomy and scar. However, EAVM measurements only represent the endocardial scar with no transmural or epicardial information. Furthermore, EAVM is a time-consuming procedure, with a high operator dependence and has low sampling density, i.e., spatial resolution. Late gadolinium enhancement (LGE) magnetic resonance imaging (MRI) allows noninvasive assessment of scar morphology that can depict 3-D scar architecture. Despite the potential use of LGE as a roadmap for VT ablation for identification of arrhythmogenic substrate, its utility has been very limited. To allow for identification of VT substrate, a correlation is needed between the substrates identified by EAVM as the gold standard and LGE-MRI scar characteristics. To do so, a system must be developed to fuse the datasets from these modalities. In this study, a registration pipeline for the fusion of LGE-MRI and EAVM data is presented. A novel surface registration algorithm is proposed, integrating the matching of global scar areas as an additional constraint in the registration process. A preparatory landmark registration is initially performed to expedite the convergence of the algorithm. Numerical simulations were performed to evaluate the accuracy of the registration in the presence of errors in identifying landmarks in EAVM or LGE-MRI datasets as well as additional errors due to respiratory or cardiac motion. Subsequently, the accuracy of the proposed fusion system was evaluated in a cohort of ten patients undergoing VT ablation where both EAVM and LGE-MRI data were available. Compared to landmark registration and surface registration, the presented method achieved significant improvemen- in registration error. The proposed data fusion system allows the fusion of EAVM and LGE-MRI data in VT ablation with registration errors less than 3.5 mm. ETPL BME-065 A Navigation Platform for Guidance of Beating Heart Transapical Mitral Valve Repair Abstract: Traditional surgical approaches for repairing diseased mitral valves (MVs) have relied on placing the patient on cardiopulmonary bypass (on pump), stopping the heart and accessing the arrested heart directly. However, because this approach has the potential for adverse neurological, vascular, and immunological sequelae, less invasive beating heart alternatives are desirable. Emerging beating heart techniques have been developed to offer high-risk patients MV repair using ultrasound guidance alone without stopping the heart. This paper describes the first porcine trials of the NeoChord DS1000
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, (Minnetonka, MN), employed to attach neochordae to a MV leaflet using the traditional ultrasound- guided protocol augmented by dynamic virtual geometric models. The distance errors of the tracked tool tip from the intended midline trajectory (5.2 ± 2.4 mm versus 16.8 ± 10.9 mm, p = 0.003), navigation times (16.7 ± 8.0 s versus 92.0 ± 84.5 s, p = 0.004), and total path lengths (225.2 ± 120.3 mm versus 1128.9 ± 931.1 mm, p = 0.003) were significantly shorter in the augmented ultrasound compared to navigation with ultrasound alone,1 indicating a substantial improvement in the safety and simplicity of the procedure. ETPL BME-066 A Wideband Dual-Antenna Receiver for Wireless Recording From Animals Behaving in Large Arenas Abstract: A low-noise wideband receiver (Rx) is presented for a multichannel wireless implantable neural recording (WINeR) system that utilizes time-division multiplexing of pulse width modulated (PWM) samples. The WINeR-6 Rx consists of four parts: 1) RF front end; 2) signal conditioning; 3) analog output (AO); and 4) field-programmable gate array (FPGA) back end. The RF front end receives RF- modulated neural signals in the 403-490 MHz band with a wide bandwidth of 18 MHz. The frequency- shift keying (FSK) PWM demodulator in the FPGA is a time-to-digital converter with 304 ps resolution, which converts the analog pulse width information to 16-bit digital samples. Automated frequency tracking has been implemented in the Rx to lock onto the free-running voltage-controlled oscillator in the transmitter (Tx). Two antennas and two parallel RF paths are used to increase the wireless coverage area. BCI-2000 graphical user interface has been adopted and modified to acquire, visualize, and record the recovered neural signals in real time. The AO module picks three demultiplexed channels and converts them into analog signals for direct observation on an oscilloscope. One of these signals is further amplified to generate an audio output, offering users the ability to listen to ongoing neural activity. Bench-top testing of the Rx performance with a 32-channel WINeR-6 Tx showed that the input referred noise of the entire system at a Tx-Rx distance of 1.5 m was 4.58 μVrms with 8-bit resolution at 640 kSps. In an in vivo experiment, location-specific receptive fields of hippocampal place cells were mapped during a behavioral experiment in which a rat completed 40 laps in a large circular track. Results were compared against those acquired from the same animal and the same set of electrodes by a commercial hardwired recording system to validate the wirelessly recorded signals. ETPL BME-067 iBalance-ABF: A Smartphone-Based Audio-Biofeedback Balance System Abstract: This paper proposes an implementation of a Kalman filter, using inertial sensors of a smartphone, to estimate 3-D angulation of the trunk. The developed system monitors the trunk angular evolution during bipedal stance and helps the user to improve balance through a configurable and integrated auditory-biofeedback (ABF) loop. A proof-of-concept study was performed to assess the effectiveness of this so-called iBalance-ABF-smartphone-based audio-biofeedback system-in improving balance during bipedal standing. Results showed that young healthy individuals were able to efficiently use ABF on sagittal trunk tilt to improve their balance in the medial-lateral direction. These findings suggest that the iBalance-ABF system as a telerehabilitation system could represent a suitable solution for
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, ambient assisted living technologies. ETPL BME-068 A Reconfigurable Digital Filterbank for Hearing-Aid Systems With a Variety of Sound Wave Decomposition Plans Abstract: Current hearing-aid systems have fixed sound wave decomposition plans due to the use of fixed filterbanks, thus cannot provide enough flexibility for the compensation of different hearing impairment cases. In this paper, a reconfigurable filterbank that consists of a multiband-generation block and a subband-selection block is proposed. Different subbands can be produced according to the control parameters without changing the structure of the filterbank system. The use of interpolation, decimation, and frequency-response masking enables us to reduce the computational complexity by realizing the entire system with only three prototype filters. Reconfigurability of the proposed filterbank enables hearing-impaired people to customize hearing aids based on their own specific conditions to improve their hearing ability. We show, by means of examples, that the proposed filterbank can achieve a better matching to the audiogram and has smaller complexity compared with the fixed filterbank. The drawback of the proposed method is that the throughput delay is relatively long (>20 ms), which needs to be further reduced before it can be used in a real hearing-aid application. ETPL BME-069 A Fully Constrained Optimization Method for Time-Resolved Multispectral Fluorescence Lifetime Imaging Microscopy Data Unmixing Abstract: This paper presents a new unmixing methodology of multispectral fluorescence lifetime imaging microscopy (m-FLIM) data, in which the spectrum is defined as the combination of time-domain fluorescence decays at multiple emission wavelengths. The method is based on a quadratic constrained optimization (CO) algorithm that provides a closed-form solution under equality and inequality restrictions. In this paper, it is assumed that the time-resolved fluorescence spectrum profiles of the constituent components are linearly independent and known a priori. For comparison purposes, the standard least squares (LS) solution and two constrained versions nonnegativity constrained least squares (NCLS) and fully constrained least squares (FCLS) (Heinz and Chang, 2001) are also tested. Their performance was evaluated by using synthetic simulations, as well as imaged samples from fluorescent dyes and ex vivo tissue. In all the synthetic evaluations, the CO obtained the best accuracy in the estimations of the proportional contributions. CO could achieve an improvement ranging between 41% and 59% in the relative error compared to LS, NCLS, and FCLS at different signal-to-noise ratios. A liquid mixture of fluorescent dyes was also prepared and imaged in order to provide a controlled scenario with real data, where CO and FCLS obtained the best performance. The CO and FCLS were also tested with 20 ex vivo samples of human coronary arteries, where the expected concentrations are qualitatively known. A certainty measure was employed to assess the confidence in the estimations made by each algorithm. The experiments confirmed a better performance of CO, since this method is optimal with respect to equality and inequality restrictions in the linear unmixing formulation. Thus, the evaluation showed that CO achieves an accurate characterization of the samples. Furthermore, CO is a computational efficient alternative to estimate the abundance of components in m-FLIM data, since a global optima-
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, solution is always guaranteed in a closed form. ETPL BME-070 An Integrated μLED Optrode for Optogenetic Stimulation and Electrical Recording Abstract: In this letter, we developed an integrated neural probe prototype for optogenetic stimulation by microscale light-emitting diode (μLED) and simultaneous recording of neural activities with microelectrodes on a single-polyimide platform. Optogenetics stimulates in vivo neural circuits with high- cellular specificity achieved by genetic targeting and precise temporal resolution by interaction of light- gated ion channels with optical beam. In our newly developed optrode probe, during optogenetic stimulation of neurons, continuous sensing of neuronal activities in vicinity of the activation site can provide feedback to stimulation or examine local responses in signal pathways. In the device, focusing the light from the μLED was achieved with an integrated photo-polymerized lens. The efficacy of the optrode for cortical stimulation and recording was tested on mice visual cortex neurons expressing channelrhodopsin-2. Stimulation intensity and frequency-dependent spiking activities of visual cortex were recorded. Our device has shown advantages over fiber-coupled laser-based optrode in terms of closed-loop integration, single-implant compactness and lower electrical power requirements, which would be clinically applicable for future prosthetic applications in personalized medicine. ETPL BME-071 Electrosurgical Vessel Sealing Tissue Temperature: Experimental Measurement and Finite Element Modeling Abstract: The temporal and spatial tissue temperature profile in electrosurgical vessel sealing was experimentally measured and modeled using finite element modeling (FEM). Vessel sealing procedures are often performed near the neurovascular bundle and may cause collateral neural thermal damage. Therefore, the heat generated during electrosurgical vessel sealing is of concern among surgeons. Tissue temperature in an in vivo porcine femoral artery sealed using a bipolar electrosurgical device was studied. Three FEM techniques were incorporated to model the tissue evaporation, water loss, and fusion by manipulating the specific heat, electrical conductivity, and electrical contact resistance, respectively. These three techniques enable the FEM to accurately predict the vessel sealing tissue temperature profile. The averaged discrepancy between the experimentally measured temperature and the FEM predicted temperature at three thermistor locations is less than 7%. The maximum error is 23.9%. Effects of the three FEM techniques are also quantified. ETPL BME-072 Debye Parameter Extraction for Characterizing Interaction of Terahertz Radiation With Human Skin Tissue Abstract: This paper is concerned with parameter extraction for the double Debye model, which is used for analytically determining human skin permittivity. These parameters are thought to be the origin of contrast in terahertz (THz) images of skin cancer. The existing extraction methods could generate Debye models, which track their measurements accurately at frequencies higher than 1 THz but poorly at lower frequencies, where the majority of permittivity contrast between healthy and diseased skin tissues is
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, actually observed. We propose a global optimization-based parameter extraction, which results in globally accurate tracking and thus supports the full validity of the Debye model for simulating human skin permittivity in the whole usable THz frequencies. Numerical results confirm viability of our novel methodology. ETPL BME-073 Coefficient-Free Blood Pressure Estimation Based on Pulse Transit Time–Cuff Pressure Dependence Abstract: Oscillometry is a popular technique for automatic estimation of blood pressure (BP). However, most of the oscillometric algorithms rely on empirical coefficients for systolic and diastolic pressure evaluation that may differ in various patient populations, rendering the technique unreliable. A promising complementary technique for automatic estimation of BP, based on the dependence of pulse transit time (PTT) on cuff pressure (CP) (PTT-CP mapping), has been proposed in the literature. However, a theoretical grounding for this technique and a nonparametric BP estimation approach are still missing. In this paper, we propose a novel coefficient-free BP estimation method based on PTT-CP dependence. PTT is mathematically modeled as a function of arterial lumen area under the cuff. It is then analytically shown that PTT-CP mappings computed from various points on the arterial pulses can be used to directly estimate systolic, diastolic, and mean arterial pressure without empirical coefficients. Analytical results are cross-validated with a pilot investigation on ten healthy subjects where 150 simultaneous electrocardiogram and oscillometric BP recordings are analyzed. The results are encouraging whereby the mean absolute errors of the proposed method in estimating systolic and diastolic pressures are 5.31 and 4.51 mmHg, respectively, relative to the Food and Drug Administration approved Omron monitor. Our work thus shows promise toward providing robust and objective BP estimation in a variety of patients and monitoring situations. ETPL BME-074 Ontology for Heart Rate Turbulence Domain From The Conceptual Model of SNOMED-CT Abstract: Electronic health record (EHR) automates the clinician workflow, allowing evidence-based decision support and quality management. We aimed to start a framework for domain standardization of cardiovascular risk stratification into the EHR, including risk indices whose calculation involves ECG signal processing. We propose the use of biomedical ontologies completely based on the conceptual model of SNOMED-CT, which allows us to implement our domain in the EHR. In this setting, the present study focused on the heart rate turbulence (HRT) domain, according to its concise guidelines and clear procedures for parameter calculations. We used 289 concepts from SNOMED-CT, and generated 19 local extensions (new concepts) for the HRT specific concepts not present in the current version of SNOMED-CT. New concepts included averaged and individual ventricular premature complex tachograms, initial sinus acceleration for turbulence onset, or sinusal oscillation for turbulence slope. Two representative use studies were implemented: first, a prototype was inserted in the hospital information system for supporting HRT recordings and their simple follow up by medical societies; second, an advanced support for a prospective scientific research, involving standard and emergent signal processing algorithms in the HRT indices, was generated and then tested in an example database of 27 Holter patients. Concepts of the proposed HRT ontology are publicly available through a terminology server,
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, hence their use in any information system will be straightforward due to the interoperability provided by SNOMED-CT. ETPL BME-075 Dynamical Nonstationarity of Resting EEGs in Patients With Attention- Deficit/Hyperactivity Disorder (AD/HD) Abstract: This study applied dynamical nonstationarity analysis (DNA) to the resting EEGs of patients with attention-deficit/hyperactivity disorder (AD/HD). We aimed to assess and characterize AD/HD using features based on the local and global duration of dynamical microstate. We hypothesized that AD/HD patients would have difficulties in maintaining stable cognitive states (e.g., attention deficit and impulsivity) and that they would thus exhibit EEGs with temporal dynamics distinct from normal controls, i.e., rapidly and frequently changing dynamics. To test this hypothesis, we recorded EEGs from 12 adolescent subjects with AD/HD and 11 age-matched healthy subjects in the resting state with eyes closed and eyes open. We found that AD/HD patients exhibited significantly faster changes in dynamics than controls in the right temporal region during the eyes closed condition, but slower changes in dynamics in the frontal region during the eyes open condition. AD/HD patients exhibited a disruption in the rate of change of dynamics in the frontotemporal region at rest, probably due to executive and attention processes. We suggest that the DNA using complementary local and global features based on the duration of dynamical microstates could be a useful tool for the clinical diagnosis of subjects with AD/HD. ETPL BME-076 Classification and Staging of Chronic Liver Disease From Multimodal Data Abstract: Chronic liver disease (CLD) is most of the time an asymptomatic, progressive, and ultimately potentially fatal disease. In this study, an automatic hierarchical procedure to stage CLD using ultrasound images, laboratory tests, and clinical records are described. The first stage of the proposed method, called clinical based classifier (CBC), discriminates healthy from pathologic conditions. When nonhealthy conditions are detected, the method refines the results in three exclusive pathologies in a hierarchical basis: 1) chronic hepatitis; 2) compensated cirrhosis; and 3) decompensated cirrhosis. The features used as well as the classifiers (Bayes, Parzen, support vector machine, and $k$ -nearest neighbor) are optimally selected for each stage. A large multimodal feature database was specifically built for this study containing 30 chronic hepatitis cases, 34 compensated cirrhosis cases, and 36 decompensated cirrhosis cases, all validated after histopathologic analysis by liver biopsy. The CBC classification scheme outperformed the nonhierachical one against all scheme, achieving an overall accuracy of 98.67% for the normal detector, 87.45% for the chronic hepatitis detector, and 95.71% for the cirrhosis detector. ETPL BME-077 The Use of Ensemble Empirical Mode Decomposition With Canonical Correlation Analysis as a Novel Artifact Removal Technique Abstract: Biosignal measurement and processing is increasingly being deployed in ambulatory situations particularly in connected health applications. Such an environment dramatically increases the likelihood of artifacts which can occlude features of interest and reduce the quality of information available in the
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, signal. If multichannel recordings are available for a given signal source, then there are currently a considerable range of methods which can suppress or in some cases remove the distorting effect of such artifacts. There are, however, considerably fewer techniques available if only a single-channel measurement is available and yet single-channel measurements are important where minimal instrumentation complexity is required. This paper describes a novel artifact removal technique for use in such a context. The technique known as ensemble empirical mode decomposition with canonical correlation analysis (EEMD-CCA) is capable of operating on single-channel measurements. The EEMD technique is first used to decompose the single-channel signal into a multidimensional signal. The CCA technique is then employed to isolate the artifact components from the underlying signal using second- order statistics. The new technique is tested against the currently available wavelet denoising and EEMD- ICA techniques using both electroencephalography and functional near-infrared spectroscopy data and is shown to produce significantly improved results. ETPL BME-078 Smart Anesthesia Manager ^{rm TM} (SAM)—A Real-time Decision Support System for Anesthesia Care during Surgery Abstract: Anesthesia information management systems (AIMS) are being increasingly used in the operating room to document anesthesia care. We developed a system, Smart Anesthesia ManagerTM (SAM) that works in conjunction with an AIMS to provide clinical and billing decision support. SAM interrogates AIMS database in near real time, detects issues related to clinical care, billing and compliance, and material waste. Issues and the steps for their resolution are brought to the attention of the anesthesia provider in real time through ―pop-up‖ messages overlaid on top of AIMS screens or text pages. SAM improved compliance to antibiotic initial dose and redose to 99.3 ± 0.7% and 83.9 ± 3.4% from 88.5 ± 1.4% and 62.5 ± 1.6%, respectively. Beta-blocker protocol compliance increased to 94.6 ± 3.5% from 60.5 ± 8.6%. Inadvertent gaps (>;15 min) in blood pressure monitoring were reduced to 34 ± 30 min/1000 cases from 192 ± 58 min/1000 cases. Additional billing charge capture of invasive lines procedures worth $144,732 per year and 1,200 compliant records were achieved with SAM. SAM was also able to reduce wastage of inhalation anesthetic agents worth $120,168 per year. ETPL BME-079 High-Accuracy Patient-to-Image Registration for the Facilitation of Image-Guided Robotic Microsurgery on the Head Abstract: Image-guided microsurgery requires accuracies an order of magnitude higher than today's navigation systems provide. A critical step toward the achievement of such low-error requirements is a highly accurate and verified patient-to-image registration. With the aim of reducing target registration error to a level that would facilitate the use of image-guided robotic microsurgery on the rigid anatomy of the head, we have developed a semiautomatic fiducial detection technique. Automatic force-controlled localization of fiducials on the patient is achieved through the implementation of a robotic-controlled tactile search within the head of a standard surgical screw. Precise detection of the corresponding fiducials in the image data is realized using an automated model-based matching algorithm on high- resolution, isometric cone beam CT images. Verification of the registration technique on phantoms demonstrated that through the elimination of user variability, clinically relevant target registration errors of approximately 0.1 mm could be achieved.
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, ETPL BME-080 Biologically Derived Companding Algorithm for High Dynamic Range Mammography Images Abstract: The screening mammography is currently the best procedure available for early detection of the breast cancer. The acquired mammograms are high dynamic range (HDR) images having a 12 bit grayscale resolution. When viewed by a radiologist, a single image must be examined several times, each time focusing on a different intensity range. We have developed a biologically derived mammography companding (BDMC) algorithm for compression, expansion, and enhancement of mammograms, in a fully automatic way. The BDMC is comprised of two main processing stages: 1) preliminary processing operations which include standardization of the intensity range and expansion of the intensities which belong to the low intensity range. 2) Adaptively companding the HDR range by integrating multiscale contrast measures. The algorithm's performance has been preliminarily clinically tested on dozens of mammograms in collaboration with experienced radiologists. It appears that the suggested method succeeds in presenting all of the clinical information, including all the abnormalities, in a single low dynamic range companded image. This companded and enhanced image is not degraded more than the HDR image and can be analyzed without the need for professional workstation and its specific enhancement software. ETPL BME-081 Advantages and Limitations of Using Matrix Pencil Method for the Modal Analysis of Medical Percussion Signals Abstract: Although clinical percussion remains one of the most widespread traditional noninvasive methods for diagnosing pulmonary disease, the available analysis of physical characteristics of the percussion sound using modern signal processing techniques is still quite limited. The majority of existing literature on the subject reports either time-domain or spectral analysis methods. However, Fourier analysis, which represents the signal as a sum of infinite periodic harmonics, is not naturally suited for decomposition of short and aperiodic percussion signals. Broadening of the spectral peaks due to damping leads to their overlapping and masking of the lower amplitude peaks, which could be important for the fine-level signal classification. In this study, an attempt is made to automatically decompose percussion signals into a sum of exponentially damped harmonics, which in this case form a more natural basis than Fourier harmonics and thus allow for a more robust representation of the signal in the parametric space. The damped harmonic decomposition of percussion signals recorded on healthy volunteers in clinical setting is performed using the matrix pencil method, which proves to be quite robust in the presence of noise and well suited for the task. ETPL BME-082 A Fast CT and CT-Fluoroscopy Registration Algorithm With Respiratory Motion Compensation for Image-Guided Lung Intervention Abstract: CT-fluoroscopy (CTF) is an efficient imaging technique for guiding percutaneous lung intervention such as biopsy and ablation. In CTF-guided procedures, four to ten axial images are captured in a very short time period during breath holding to provide near real-time feedback of patients' anatomy so that physicians can adjust the needle as it is advanced toward a target lesion. Although popularly used
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, in clinics, this procedure requires frequent scans to guide the needle, which may cause increased procedure time, complication rates, and radiation exposure to both clinicians and patients. In addition, CTF only generates a limited number of 2-D axial images and does not provide sufficient 3-D anatomical information. Therefore, how to provide volumetric anatomical information using CTF while reducing intraoperative scan is an important and challenging problem. In this paper, we propose a fast CT-CTF deformable registration algorithm that warps the inhale preprocedural CT onto the intraprocedural CTF for guidance in 3-D. In the algorithm, the deformation in the transverse plane is modeled using 2-D B- Spline, and the deformation along z-direction is regularized by smoothness constraint. A respiratory motion compensation framework is also incorporated for accurate registration. A parallel implementation strategy is adopted to accomplish the registration in several seconds. With electromagnetic tracking, the needle position can be superimposed onto the deformed inhale CT image, thereby providing 3-D image guidance during breath holding. Experiments were conducted using both simulated CTF images with known deformation and real CTF images captured during lung cancer biopsy studies. The experiments demonstrated satisfactory registration results of our proposed fast CT-CTF registration algorithm. ETPL BME-083 Impact of Visual Features on the Segmentation of Gastroenterology Images Using Normalized Cuts Abstract: Gastroenterology imaging is an essential tool to detect gastrointestinal cancer in patients. Computer-assisted diagnosis is desirable to help us improve the reliability of this detection. However, traditional computer vision methodologies, mainly segmentation, do not translate well to the specific visual characteristics of a gastroenterology imaging scenario. In this paper, we propose a novel method for the segmentation of gastroenterology images from two distinct imaging modalities and organs: chromoendoscopy (CH) and narrow-band imaging (NBI) from stomach and esophagus, respectively. We have used various visual features individually and their combinations (edgemaps, creaseness, and color) in normalized cuts image segmentation framework to segment ground truth datasets of 142 CH and 224 NBI images. Experiments show that an integration of edgemaps and creaseness in normalized cuts gives the best segmentation performance resulting in high-quality segmentations of the gastroenterology images. ETPL BME-084 Objective Skill Evaluation for Laparoscopic Training Based on Motion Analysis Abstract: Performing laparoscopic surgery requires several skills, which have never been required for conventional open surgery. Surgeons experience difficulties in learning and mastering these techniques. Various training methods and metrics have been developed to assess and improve surgeon's operative abilities. While these training metrics are currently widely being used, skill evaluation methods are still far from being objective in the regular laparoscopic skill education. This study proposes a methodology of defining a processing model that objectively evaluates surgical movement performance in the routine laparoscopic training course. Our approach is based on the analysis of kinematic data describing the movements of surgeon's upper limbs. An ultraminiaturized wearable motion capture system (Waseda Bioinstrumentation system WB-3), therefore, has been developed to measure and analyze these
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, movements. The data processing model was trained by using the subjects' motion features acquired from the WB-3 system and further validated to classify the expertise levels of the subjects with different laparoscopic experience. Experimental results show that the proposed methodology can be efficiently used both for quantitative assessment of surgical movement performance, and for the discrimination between expert surgeons and novices. ETPL BME-085 Feature-Preserving Smoothing of Diffusion Weighted Images Using Nonstationarity Adaptive Filtering Abstract: Although promising for studying the microstructure of in vivo tissues, the performance and the potentiality of diffusion tensor magnetic resonance imaging are hampered by the presence of high-level noise in diffusion weighted (DW) images. This paper proposes a novel smoothing approach, called the nonstationarity adaptive filtering, which estimates the intensity of a pixel by averaging intensities in its adaptive homogeneous neighborhood. The latter is determined according to five constraints and spatiodirectional nonstationarity measure maps. The proposed approach is compared with an anisotropic diffusion method used in DW image smoothing. Experimental results on both synthetic and real human DW images show that the proposed method achieves a better compromise between the smoothness of homogeneous regions and the preservation of desirable features such as boundaries, even for highly noisy data, thus leading to homogeneously consistent tensor fields and consequently more coherent fibers. ETPL BME-086 Sparse Reconstruction of Breast MRI Using Homotopic L_0 Minimization in a Regional Sparsified Domain Abstract: The use of MRI for early breast examination and screening of asymptomatic women has become increasing popular, given its ability to provide detailed tissue characteristics that cannot be obtained using other imaging modalities such as mammography and ultrasound. Recent application- oriented developments in compressed sensing theory have shown that certain types of magnetic resonance images are inherently sparse in particular transform domains, and as such can be reconstructed with a high level of accuracy from highly undersampled k-space data below Nyquist sampling rates using homotopic L0 minimization schemes, which holds great potential for significantly reducing acquisition time. An important consideration in the use of such homotopic L0 minimization schemes is the choice of sparsifying transform. In this paper, a regional differential sparsifying transform is investigated for use within a homotopic L0 minimization framework for reconstructing breast MRI. By taking local regional characteristics into account, the regional differential sparsifying transform can better account for signal variations and fine details that are characteristic of breast MRI than the popular finite differential transform, while still maintaining strong structure fidelity. Experimental results show that good breast MRI reconstruction accuracy can be achieved compared to existing methods. ETPL BME-087 On-Shoe Wearable Sensors for Gait and Turning Assessment of Patients With Parkinson's Disease Abstract: Assessment of locomotion through simple tests such as timed up and go (TUG) or walking trials
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, can provide valuable information for the evaluation of treatment and the early diagnosis of people with Parkinson's disease (PD). Common methods used in clinics are either based on complex motion laboratory settings or simple timing outcomes using stop watches. The goal of this paper is to present an innovative technology based on wearable sensors on-shoe and processing algorithm, which provides outcome measures characterizing PD motor symptoms during TUG and gait tests. Our results on ten PD patients and ten age-matched elderly subjects indicate an accuracy ± precision of 2.8 ± 2.4 cm/s and 1.3 ± 3.0 cm for stride velocity and stride length estimation compared to optical motion capture, with the advantage of being practical to use in home or clinics without any discomfort for the subject. In addition, the use of novel spatio-temporal parameters, including turning, swing width, path length, and their intercycle variability, was also validated and showed interesting tendencies for discriminating patients in ON and OFF states and control subjects. ETPL BME-088 Photon Efficiency Optimization in Time-Correlated Single Photon Counting Technique for Fluorescence Lifetime Imaging Systems Abstract: In time-correlated single photon counting (TCSPC) systems, the maximum signal throughput is limited by the occurrence of pile-up and other effects. In many biological applications that exhibit high levels of fluorescence intensity (FI), pile-up-related distortions yield serious distortions in the fluorescence lifetime (FLT) calculation as well as significant decrease in the signal-to-noise ratio (SNR). Recent developments that allow the use of high-repetition-rate light sources (in the range of 50-100 MHz) in fluorescence lifetime imaging (FLIM) experiments enable minimization of pile-up-related distortions. However, modern TCSPC configurations that use high-repetition-rate excitation sources for FLIM suffer from dead-time-related distortions that cause unpredictable distortions of the FI signal. In this study, the loss of SNR is described by F- value as it is typically done in FLIM systems. This F-value describes the relation of the relative standard deviation in the estimated FLT to the relative standard deviation in FI measurements. Optimization of the F-value allows minimization of signal distortion, as well as shortening of the acquisition time for certain samples. We applied this method for Fluorescein, Rhodamine B, and Erythrosine fluorescent solutions that have different FLT values (4 ns, 1.67 ns, and 140 ps, respectively). ETPL BME-089 Matching Pursuit and Source Deflation for Sparse EEG/MEG Dipole Moment Estimation Abstract: In this paper, we propose novel matching pursuit (MP)-based algorithms for EEG/MEG dipole source localization and parameter estimation for multiple measurement vectors with constant sparsity. The algorithms combine the ideas of MP for sparse signal recovery and source deflation, as employed in estimation via alternating projections. The source-deflated matching pursuit (SDMP) approach mitigates the problem of residual interference inherent in sequential MP-based methods or recursively applied (RAP)-MUSIC. Furthermore, unlike prior methods based on alternating projection, SDMP allows one to efficiently estimate the dipole orientation in addition to its location. Simulations show that the proposed algorithms outperform existing techniques under various conditions, including those with highly correlated sources. Results using real EEG data from auditory experiments are also presented to illustrate
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, the performance of these algorithms. ETPL BME-090 Multiparameter Respiratory Rate Estimation From the Photoplethysmogram Abstract: We present a novel method for estimating respiratory rate in real time from the photoplethysmogram (PPG) obtained from pulse oximetry. Three respiratory-induced variations (frequency, intensity, and amplitude) are extracted from the PPG using the Incremental-Merge Segmentation algorithm. Frequency content of each respiratory-induced variation is analyzed using fast Fourier transforms. The proposed Smart Fusion method then combines the results of the three respiratory- induced variations using a transparent mean calculation. It automatically eliminates estimations considered to be unreliable because of detected presence of artifacts in the PPG or disagreement between the different individual respiratory rate estimations. The algorithm has been tested on data obtained from 29 children and 13 adults. Results show that it is important to combine the three respiratory-induced variations for robust estimation of respiratory rate. The Smart Fusion showed trends of improved estimation (mean root mean square error 3.0 breaths/min) compared to the individual estimation methods (5.8, 6.2, and 3.9 breaths/min). The Smart Fusion algorithm is being implemented in a mobile phone pulse oximeter device to facilitate the diagnosis of severe childhood pneumonia in remote areas. ETPL BME-091 Non-Contact ECG Sensing Employing Gradiometer Electrodes Abstract: Noncontact, capacitive electrocardiogram (ECG) measurements are complicated by motion artifacts from the relative movement between the ECG electrodes and the subject. To compensate for such motion we propose to employ first and second order gradiometer electrode designs. A MATLAB-based simulation tool to enable assessment of different electrode configurations and placements on human subjects has been developed to guide the refinement of electrode designs. Experimental measurements of the sensitivity, motion artifact cancellation, and common mode rejection for various prototype designs were conducted with human subjects. Second order gradiometer electrode designs appear to give the best performance as measured by signal to noise plus distortion ratio. Finally, both gradiometer designs were compared with standard ECG recording methods and showed less than 1% beat detection mismatch employing an open source beat detection algorithm. ETPL BME-092 Surgical Robot System for Single-Port Surgery With Novel Joint Mechanism Abstract: Single-port surgery is a new surgical method performed by inserting several surgical tools and a laparoscope through an umbilical incision. Compared with conventional laparoscopic surgery, the smaller incision in this procedure produces a lower amount of trauma, which leads to shorter hospitalization. However, with the current laparoscopic tools and surgical robots, the surgeon must overcome several difficulties, such as a limited range of motion and collisions between the surgical instruments and the laparoscope. This paper proposes a new surgical robot system for single-port surgery that uses a novel
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, joint mechanism. The proposed joint mechanism is suitable for surgical instruments with multiple degrees of freedom (DOF). Thus, it can prevent hysteresis of the joint and achieve more accurate motion with a large force. A 6-DOF surgical instrument with this joint mechanism can avoid collisions between surgical tools or arms and approach the surgical target more easily than a conventional straight surgical tool. The external arm with 2-DOF passive joints can extend the workspace of the system during surgery. Preliminary tests and validations were performed with a prototype of the system. ETPL BME-093 Center of Mass Acceleration Feedback Control of Standing Balance by Functional Neuromuscular Stimulation Against External Postural Perturbations Abstract: This study investigated the use of center of mass (COM) acceleration feedback for improving performance of a functional neuromuscular stimulation control system to restore standing function to a subject with complete, thoracic-level spinal cord injury. The approach for linearly relating changes in muscle stimulation to changes in COM acceleration was verified experimentally and subsequently produced data to create an input-output map driven by sensor feedback. The feedback gains were systematically tuned to reduce upper extremity (UE) loads applied to an instrumented support device while resisting external postural disturbances. Total body COM acceleration was accurately estimated (>;89% variance explained) using 3-D outputs of two accelerometers mounted on the pelvis and torso. Compared to constant muscle stimulation employed clinically, feedback control of stimulation reduced UE loading by 33%. COM acceleration feedback is advantageous in constructing a standing neuroprosthesis since it provides the basis for a comprehensive control synergy about a global, dynamic variable and requires minimal instrumentation. Future work should include tuning and testing the feedback control system during functional reaching activity that is more indicative of activities of daily living. ETPL BME-094 An Interactive Approach to Multiobjective Clustering of Gene Expression Patterns Abstract: Some recent studies have posed the problem of data clustering as a multiobjective optimization problem, where several cluster validity indices are simultaneously optimized to obtain tradeoff clustering solutions. A number of cluster validity index measures are available in the literature. However, none of the measures can perform equally well in all kinds of datasets. Depending on the dataset properties and its inherent clustering structure, different cluster validity measures perform differently. Therefore, it is important to find the best set of validity indices that should be optimized simultaneously to obtain good clustering results. In this paper, a novel interactive genetic algorithm-based multiobjective approach is proposed that simultaneously finds the clustering solution as well as evolves the set of validity measures that are to be optimized simultaneously. The proposed method interactively takes the input from the human decision maker (DM) during execution and adaptively learns from that input to obtain the final set of validity measures along with the final clustering result. The algorithm is applied for clustering real-life benchmark gene expression datasets and its performance is compared with that of several other existing clustering algorithms to demonstrate its effectiveness. The results indicate that the proposed method
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, outperforms the other existing algorithms for all the datasets considered here. ETPL BME-095 Gene-Expression-Based Cancer Subtypes Prediction Through Feature Selection and Transductive SVM Abstract: With the advancement of microarray technology, gene expression profiling has shown great potential in outcome prediction for different types of cancers. Microarray cancer data, organized as samples versus genes fashion, are being exploited for the classification of tissue samples into benign and malignant or their subtypes. They are also useful for identifying potential gene markers for each cancer subtype, which helps in successful diagnosis of particular cancer type. Nevertheless, small sample size remains a bottleneck to design suitable classifiers. Traditional supervised classifiers can only work with labeled data. On the other hand, a large number of microarray data that do not have adequate follow-up information are disregarded. A novel approach to combine feature (gene) selection and transductive support vector machine (TSVM) is proposed. We demonstrated that 1) potential gene markers could be identified and 2) TSVMs improved prediction accuracy as compared to the standard inductive SVMs (ISVMs). A forward greedy search algorithm based on consistency and a statistic called signal-to-noise ratio were employed to obtain the potential gene markers. The selected genes of the microarray data were then exploited to design the TSVM. Experimental results confirm the effectiveness of the proposed technique compared to the ISVM and low-density separation method in the area of semisupervised cancer classification as well as gene-marker identification. ETPL BME-096 Bilinear Modeling of EMG Signals to Extract User-Independent Features for Multiuser Myoelectric Interface Abstract: In this study, we propose a multiuser myoelectric interface that can easily adapt to novel users. When a user performs different motions (e.g., grasping and pinching), different electromyography (EMG) signals are measured. When different users perform the same motion (e.g., grasping), different EMG signals are also measured. Therefore, designing a myoelectric interface that can be used by multiple users to perform multiple motions is difficult. To cope with this problem, we propose for EMG signals a bilinear model that is composed of two linear factors: 1) user dependent and 2) motion dependent. By decomposing the EMG signals into these two factors, the extracted motion-dependent factors can be used as user-independent features. We can construct a motion classifier on the extracted feature space to develop the multiuser interface. For novel users, the proposed adaptation method estimates the user- dependent factor through only a few interactions. The bilinear EMG model with the estimated user- dependent factor can extract the user-independent features from the novel user data. We applied our proposed method to a recognition task of five hand gestures for robotic hand control using four-channel EMG signals measured from subject forearms. Our method resulted in 73% accuracy, which was statistically significantly different from the accuracy of standard nonmultiuser interfaces, as the result of a two-sample t -test at a significance level of 1%. ETPL BME-097 Fetal ECG Extraction by Extended State Kalman Filtering Based on Single-Channel Recordings
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, Abstract: In this paper, we present an extended nonlinear Bayesian filtering framework for extracting electrocardiograms (ECGs) from a single channel as encountered in the fetal ECG extraction from abdominal sensor. The recorded signals are modeled as the summation of several ECGs. Each of them is described by a nonlinear dynamic model, previously presented for the generation of a highly realistic synthetic ECG. Consequently, each ECG has a corresponding term in this model and can thus be efficiently discriminated even if the waves overlap in time. The parameter sensitivity analysis for different values of noise level, amplitude, and heart rate ratios between fetal and maternal ECGs shows its effectiveness for a large set of values of these parameters. This framework is also validated on the extractions of fetal ECG from actual abdominal recordings, as well as of actual twin magnetocardiograms. ETPL BME-098 Automatic Segmentation and Measurement of Pleural Effusions on CT Abstract: Pleural effusion is an important biomarker for the diagnosis of many diseases. We develop an automated method to evaluate pleural effusion on CT scans, the measurement of which is prohibitively time consuming when performed manually. The method is based on parietal and visceral pleura extraction, active contour models, region growing, Bezier surface fitting, and deformable surface modeling. Twelve CT scans with three manual segmentations were used to validate the automatic segmentation method. The method was then applied on 91 additional scans for visual assessment. The segmentation method yielded a correlation coefficient of 0.97 and a Dice coefficient of 0.72 ± 0.13 when compared to a professional manual segmentation. The visual assessment estimated 83% cases with negligible or small segmentation errors, 14% with medium errors, and 3% with large errors. ETPL BME-099 A Novel Approach to Reducing Number of Sensing Units for Wearable Gait Analysis Systems Abstract: Gait analysis methods to estimate spatiotemporal measures, based on two, three or four gyroscopes attached on lower limbs have been discussed in the literature. The most common approach to reduce the number of sensing units is to simplify the underlying biomechanical gait model. In this study, we propose a novel method based on prediction of movements of thighs from movements of shanks. Datasets from three previous studies were used. Data from the first study (ten healthy subjects and ten with Parkinson's disease) were used to develop and calibrate a system with only two gyroscopes attached on shanks. Data from two other studies (36 subjects with hip replacement, seven subjects with coxarthrosis, and eight control subjects) were used for comparison with the other methods and for assessment of error compared to a motion capture system. Results show that the error of estimation of stride length compared to motion capture with the system with four gyroscopes and our new method based on two gyroscopes was close ( -0.8 ±6.6 versus 3.8 ±6.6 cm). An alternative with three sensing units did not show better results (error: -0.2 ±8.4 cm). Finally, a fourth that also used two units but with a simpler gait model had the highest bias compared to the reference (error: -25.6 ±7.6 cm). We concluded that it is feasible to estimate movements of thighs from movements of shanks to reduce number of needed sensing units from 4 to 2 in context of ambulatory gait analysis.
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, ETPL BME-100 Enabling Large-Scale Ground-Truth Acquisition and System Evaluation in Wireless Health Abstract: Large-scale activity monitoring is a core component of systems aiming to improve our ability to manage fitness, deliver care, and diagnose conditions. While much research has been devoted to the accurate classification of motion, the challenges arising from scaling to large communities have received little attention. This paper introduces the problem of scaling, and addresses two of the most important issues: enabling robust large-scale ground-truth acquisition and building a common database for systems comparison. This paper presents a voice powered mobile acquisition system with efficient annotation tools and an extendable online searchable activity database with 331 datasets totaling over 700 h with 8 sensing modalities and 15 activities. ETPL BME-101 Prostate Brachytherapy Training With Simulated Ultrasound and Fluoroscopy Images Abstract: In this paper, a novel computer-based virtual training system for prostate brachytherapy is presented. This system incorporates, in a novel way, prior methodologies of ultrasound image synthesis and haptic transrectal ultrasound (TRUS) transducer interaction in a complete simulator that allows a trainee to maneuver the needle and the TRUS, to see the resulting patient-specific images and feel the interaction forces. The simulated TRUS images reflect the volumetric tissue deformation and comprise validated appearance models for the needle and implanted seeds. Rendered haptic forces use validated models for needle shaft flexure and friction, tip cutting, and deflection due to bevel. This paper also presents additional new features that make the simulator complete, in the sense that all aspects of the brachytherapy procedure as practiced at many cancer centers are simulated, including simulations of seed unloading, fluoroscopy imaging, and transversal/sagittal TRUS plane switching. For real-time rendering, methods for fast TRUS-needle-seed image formation are presented. In addition, the simulator computes real-time dosimetry, allowing a trainee to immediately see the consequence of planning changes. The simulation is also patient specific, as it allows the user to import the treatment plan for a patient together with the imaging data in order for a physician to practice an upcoming procedure or for a medical resident to train using typical implant scenarios or rarely encountered cases. ETPL BME-102 Ultrasound Probe and Needle-Guide Calibration for Robotic Ultrasound Scanning and Needle Targeting Abstract: Image-to-robot registration is a typical step for robotic image-guided interventions. If the imaging device uses a portable imaging probe that is held by a robot, this registration is constant and has been commonly named probe calibration. The same applies to probes tracked by a position measurement device. We report a calibration method for 2-D ultrasound probes using robotic manipulation and a planar calibration rig. Moreover, a needle guide that is attached to the probe is also calibrated for ultrasound- guided needle targeting. The method is applied to a transrectal ultrasound (TRUS) probe for robot- assisted prostate biopsy. Validation experiments include TRUS-guided needle targeting accuracy tests. This paper outlines the entire process from the calibration to image-guided targeting. Freehand TRUS-
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, guided prostate biopsy is the primary method of diagnosing prostate cancer, with over 1.2 million procedures performed annually in the U.S. alone. However, freehand biopsy is a highly challenging procedure with subjective quality control. As such, biopsy devices are emerging to assist the physician. Here, we present a method that uses robotic TRUS manipulation. A 2-D TRUS probe is supported by a 4- degree-of-freedom robot. The robot performs ultrasound scanning, enabling 3-D reconstructions. Based on the images, the robot orients a needle guide on target for biopsy. The biopsy is acquired manually through the guide. In vitro tests showed that the 3-D images were geometrically accurate, and an image- based needle targeting accuracy was 1.55 mm. These validate the probe calibration presented and the overall robotic system for needle targeting. Targeting accuracy is sufficient for targeting small, clinically significant prostatic cancer lesions, but actual in vivo targeting will include additional error components that will have to be determined. ETPL BME-103 Magnetic Fluid Hyperthermia Modeling Based on Phantom Measurements and Realistic Breast Model Abstract: Magnetic fluid hyperthermia (MFH) is a minimally invasive procedure that destroys cancer cells. It is based on a superparamagnetic heat phenomenon and consists in feeding a ferrofluid into a tumor, and then applying an external electromagnetic field, which leads to apoptosis. The strength of the magnetic field, optimal dose of the ferrofluid, the volume of the tumor and the safety standards have to be taken into consideration when MFH treatment is planned. In this study, we have presented the novel complementary investigation based both on the experiments and numerical methodology connected with female breast cancer. We have conducted experiments on simplified female breast phantoms with numerical analysis and then we transferred the results on an anatomically-like breast model. ETPL BME-104 An Extended Dynamometer Setup to Improve the Accuracy of Knee Joint Moment Assessment Abstract: This paper analyzes an extended dynamometry setup that aims at obtaining accurate knee joint moments. The main problem of the standard setup is the misalignment of the joint and the dynamometer axes of rotation due to nonrigid fixation, and the determination of the joint axis of rotation by palpation. The proposed approach 1) combines 6-D registration of the contact forces with 3-D motion capturing (which is a contribution to the design of the setup); 2) includes a functional axis of rotation in the model to describe the knee joint (which is a contribution to the modeling); and 3) calculates joint moments by a model-based 3-D inverse dynamic analysis. Through a sensitivity analysis, the influence of the accuracy of all model parameters is evaluated. Dynamics resulting from the extended setup are quantified, and are compared to those provided by the dynamometer. Maximal differences between the 3-D joint moment resulting from the inverse dynamics and measured by the dynamometer were 16.4 N $cdot$m (16.9%) isokinetically and 18.3 N $cdot$m (21.6%) isometrically. The calculated moment is most sensitive to the orientation and location of the axis of rotation. In conclusion, more accurate experimental joint moments are obtained using a model-based 3-D inverse dynamic approach that includes a good estimate of the pose of the joint axis.
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, ETPL BME-105 Automatic Monocular System for Human Fall Detection Based on Variations in Silhouette Area Abstract: Population of old generation is growing in most countries. Many of these seniors are living alone at home. Falling is among the most dangerous events that often happen and may need immediate medical care. Automatic fall detection systems could help old people and patients to live independently. Vision-based systems have advantage over wearable devices. These visual systems extract some features from video sequences and classify fall and normal activities. These features usually depend on camera's view direction. Using several cameras to solve this problem increases the complexity of the final system. In this paper, we propose to use variations in silhouette area that are obtained from only one camera. We use a simple background separation method to find the silhouette. We show that the proposed feature is view invariant. Extracted feature is fed into a support vector machine for classification. Simulation of the proposed method using a publicly available dataset shows promising results. ETPL BME-106 Evoked Electromyography-Based Closed-Loop Torque Control in Functional Electrical Stimulation Abstract: This paper proposed a closed-loop torque control strategy of functional electrical stimulation (FES) with the aim of obtaining an accurate, safe, and robust FES system. Generally, FES control systems are faced with the challenge of how to deal with time-variant muscle dynamics due to physiological and biochemical factors (such as fatigue). The degraded muscle force needs to be compensated in order to ensure the accuracy of the motion restored by FES. Another challenge concerns the fact that implantable sensors are unavailable to feedback torque information for FES in humans. As FES-evoked electromyography (EMG) represents the activity of stimulated muscles, and also enables joint torque prediction as presented in our previous studies, here we propose an EMG-feedback predictive controller of FES to control joint torque adaptively. EMG feedback contributes to taking the activated muscle state in the FES torque control system into account. The nature of the predictive controller facilitates prediction of the muscle mechanical response and the system can therefore control joint torque from EMG feedback and also respond to time-variant muscle state changes. The control performance, fatigue compensation and aggressive control suppression capabilities of the proposed controller were evaluated and discussed through experimental and simulation studies. ETPL BME-107 Controlling a Human–Computer Interface System With a Novel Classification Method that Uses Electrooculography Signals Abstract: Electrooculography (EOG) signals can be used to control human–computer interface (HCI) systems, if properly classified. The ability to measure and process these signals may help HCI users to overcome many of the physical limitations and inconveniences in daily life. However, there are currently no effective multidirectional classification methods for monitoring eye movements. Here, we describe a classification method used in a wireless EOG-based HCI device for detecting eye movements in eight directions. This device includes wireless EOG signal acquisition components, wet electrodes and an EOG signal classification algorithm. The EOG classification algorithm is based on extracting features from the
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, electrical signals corresponding to eight directions of eye movement (up, down, left, right, up-left, down- left, up-right, and down-right) and blinking. The recognition and processing of these eight different features were achieved in real-life conditions, demonstrating that this device can reliably measure the features of EOG signals. This system and its classification procedure provide an effective method for identifying eye movements. Additionally, it may be applied to study eye functions in real-life conditions in the near future. ETPL BME-108 Prostate Segmentation in MR Images Using Discriminant Boundary Features Abstract: Segmentation of the prostate in magnetic resonance image has become more in need for its assistance to diagnosis and surgical planning of prostate carcinoma. Due to the natural variability of anatomical structures, statistical shape model has been widely applied in medical image segmentation. Robust and distinctive local features are critical for statistical shape model to achieve accurate segmentation results. The scale invariant feature transformation (SIFT) has been employed to capture the information of the local patch surrounding the boundary. However, when SIFT feature being used for segmentation, the scale and variance are not specified with the location of the point of interest. To deal with it, the discriminant analysis in machine learning is introduced to measure the distinctiveness of the learned SIFT features for each landmark directly and to make the scale and variance adaptive to the locations. As the gray values and gradients vary significantly over the boundary of the prostate, separate appearance descriptors are built for each landmark and then optimized. After that, a two stage coarse-to- fine segmentation approach is carried out by incorporating the local shape variations. Finally, the experiments on prostate segmentation from MR image are conducted to verify the efficiency of the proposed algorithms. ETPL BME-109 Moveable Wire Electrode Microchamber for Nanosecond Pulsed Electric-Field Delivery Abstract: In this paper, an electromagnetic characterization of a moveable wire electrode microchamber for nanosecond pulse delivery is proposed. The characterization of the exposure system was carried out through experimental measurements and numerical simulations. The frequency and time domain analyses demonstrate the utility of the proposed assembly for delivering pulses as short as 2.5 ns. High-voltage measurements (~1.2 kV) were also performed using pulse generators based on two different technologies with applied pulse durations of 5.0 and 2.5 ns. Validation of the delivery system was accomplished with biological experiments involving cell electroporation with 2.5 and 5.0 ns, 10-MV/m pulsed electric fields. A dose-dependent area increase (osmotic swelling) of the Jurkat cells was observed with pulses as short as 2.5 ns. ETPL BME-110 Quantifying the Interfibrillar Spacing and Fibrillar Orientation of the Aortic Extracellular Matrix Using Histology Image Processing: Toward Multiscale Modeling Abstract: An essential part of understanding tissue microstructural mechanics is to establish quantitative measures of the morphological changes. Given the complex, highly localized, and interactive architecture
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, of the extracellular matrix, developing techniques to reproducibly quantify the induced microstructural changes has been found to be challenging. In this paper, a new method for quantifying the changes in the fibrillar organization is developed using histology images. A combinatorial frequency–spatial image processing approach was developed based on the Fourier and Hough transformations of histology images to measure interfibrillar spacing and fibrillar orientation, respectively. The method was separately applied to the inner and outer wall thickness of native- and elastin-isolated aortic tissues under different loading states. Results from both methods were interpreted in a complementary manner to obtain a more complete understanding of morphological changes due to tissue deformations at the microscale. The observations were consistent in quantifying the observed morphological changes during tissue deformations and in explaining such changes in terms of tissue-scale phenomena. The findings of this study could pave the way for more rigorous modeling of structure–property relationships in soft tissues, with implications extendable to cardiovascular constitutive modeling and tissue engineering. ETPL BME-111 Massively Parallel Energy Space Exploration for Uncluttered Visualization of Vascular Structures Abstract: Images captured using computed tomography and magnetic resonance angiography are used in the examination of the abdominal aorta and its branches. The examination of all clinically relevant branches simultaneously in a single 2-D image without any misleading overlaps facilitates the diagnosis of vascular abnormalities. This problem is called uncluttered single-image visualization (USIV). We can solve the USIV problem by assigning energy-based scores to visualization candidates and then finding the candidate that optimizes the score; this approach is similar to the manner in which the protein side-chain placement problem has been solved. To obtain near-optimum images, we need to explore the energy space extensively, which is often time consuming. This paper describes a method for exploring the energy space in a massively parallel fashion using graphics processing units. According to our experiments, in which we used 30 images obtained from five patients, the proposed method can reduce the total visualization time substantially. We believe that the proposed method can make a significant contribution to the effective visualization of abdominal vascular structures and precise diagnosis of related abnormalities. ETPL BME-112 Spatial Variability of the 12-Lead Surface ECG as a Tool for Noninvasive Prediction of Catheter Ablation Outcome in Persistent Atrial Fibrillation Abstract: Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia encountered in clinical practice. Radiofrequency catheter ablation (CA) is increasingly employed to treat this disease, yet the selection of persistent AF patients who will benefit from this treatment remains a challenging task. Several parameters of the surface electrocardiogram (ECG) have been analyzed in previous works to predict AF termination by CA, such as fibrillatory wave (f-wave) amplitude. However, they are usually manually computed and only a subset of electrodes is inspected. In this study, a novel perspective of the role of f-wave amplitude as a potential noninvasive predictor of CA outcome is adopted by exploring ECG interlead spatial variability. An automatic procedure for atrial amplitude computation based on cubic Hermite interpolation is first proposed. To describe the global f-wave peak-to-peak amplitude
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, distribution, signal contributions from multiple leads are then combined by condensing the most representative features of the atrial signal in a reduced-rank approximation based on principal component analysis (PCA). We show that exploiting ECG spatial diversity by means of this PCA-based multilead approach does not only increase the robustness to electrode selection, but also substantially improves the predictive power of the amplitude parameter. ETPL BME-113 Reduction of the Linear Reflex Gain Explained From the M1–M2 Refractory Period Abstract: Linear system identification methods combined with neuromechanical modeling enable the quantification of reflex gains from recorded joint angular perturbation, torque, and/or electromyography (EMG). However, the stretch reflex response as recorded by EMG consists of multiple consecutive activation volleys (M1 and M2 responses) separated by a period of reduced activity and is nonlinearly related to joint perturbation. The goal of this study is to assess to what extent linear assumptions hold when quantifying these reflexive responses. Series of ramp-and-hold angular perturbations with fixed velocity but different ramp durations (and, therefore, different amplitudes) were applied to the wrist joint of seven healthy volunteers. Evoked EMG responses were compared to the reflex response estimated from a common linear reflex model relating EMG to perturbation velocity. Model fits described the measured EMG responses best when the perturbation and M1 response durations were equivalent. With increasing perturbation duration, i.e., amplitude, EMG response increased but reflex gain decreased due to the inert period after M1, which is believed to be related to alignment of the refractory period of the motoneurons. For angular joint perturbations exceeding the M1 duration (coinciding with 2° of wrist joint rotation in this study), reflex gain variation may be largely explained from a shortcoming of the linear model in describing the nonlinear reflex response, and in particular the period of low reflexive activity after M1. ETPL BME-114 Spectral Analysis for Nonstationary and Nonlinear Systems: A Discrete-Time-Model- Based Approach Abstract: A new frequency-domain analysis framework for nonlinear time-varying systems is introduced based on parametric time-varying nonlinear autoregressive with exogenous input models. It is shown how the time-varying effects can be mapped to the generalized frequency response functions (FRFs) to track nonlinear features in frequency, such as intermodulation and energy transfer effects. A new mapping to the nonlinear output FRF is also introduced. A simulated example and the application to intracranial electroencephalogram data are used to illustrate the theoretical results. ETPL BME-115 A Handheld Electromagnetically Actuated Fiber Optic Raster Scanner for Reflectance Confocal Imaging of Biological Tissues Abstract: We present a hand-held device aimed for reflectance-mode confocal imaging of biological tissues. The device consists of a light carrying optical fiber and a miniaturized raster scanner located at the distal end of the fiber. It is fabricated by mounting a polarization maintaining optical fiber on a cantilever beam that is attached to another beam such that their bending axes are perpendicular to each
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli, other. Fiber scanner is driven by electromagnetic forces and enables large fiber deflections with low driving currents. Optical resolutions of the system are 1.55 and 8.45 μm in the lateral and axial directions, respectively. Functionality of the system is demonstrated by obtaining confocal images of a fly wing and a human colon tissue sample. ETPL BME-116 "A Kinematic Human-Walking Model for the Normal-Gait-Speed Estimation Using Tri-Axial Acceleration Signals at Waist Location Abstract: This study aims at estimating the human walking speed using wearable accelerometers by proposing a novel virtual inverted pendulum model. This model not only keeps the important characteristics of both the biped rolling-foot and the inverted pendulum model, but also makes the speed estimation feasible using human body acceleration. Rather than using statistical methods, the proposed kinematic walking model enables calibration of the parameters during walking using only one tri-axial accelerometer on the waist that collects the user's body acceleration. In addition, this model also includes the effect of rotation of the waist within a walking cycle, which improves the estimation accuracy. Experimental results for a group of humans show a 0.58% absolute error mean and 0.72% error deviation, which is far better than the results of other known studies with accelerometers mounted on the upper body. ETPL BME-117 Topology and Random-Walk Network Representation of Cardiac Dynamics for Localization of Myocardial Infarction Abstract: While detection of acute cardiac disorders such as myocardial infarction (MI) from electrocardiogram (ECG) and vectorcardiogram (VCG) has been widely reported, identification of MI locations from these signals, pivotal for timely therapeutic and prognostic interventions, remains a standing issue. We present an approach for MI localization based on representing complex spatiotemporal patterns of cardiac dynamics as a random-walk network reconstructed from the evolution of VCG signals across a 3-D state space. Extensive tests with signals from the PTB database of the PhysioNet databank suggest that locations of MI can be determined accurately (sensitivity of ∼88% and specificity of ∼92%) from tracking certain consistently estimated invariants of this random-walk representation.
  • Elysium Technologies Private Limited Singapore | Madurai | Chennai | Trichy | Coimbatore | Cochin | Ramnad | Pondicherry | Trivandrum | Salem | Erode | Tirunelveli,