Real Time Moving Prosthetic.
It's an innovative technology,improvising the prosthetic field with the application of Artificial Neural Network technology.Unlike anyother prosthetic hand, this has a Real Time data accquisition system which varies the data set according to the input signal.This is customisable to any amputee. The hardware was developed by simple and easily available materials.We have come up with a new technology in the prosthetic field.
Bionics is an aid to technology that is bridging the gap between human limitation and potential. This presentation deals with the details of bionics and different milestones implemented.
Neurorobotics and Advances in rehabilitation engineeringBhaskarBorgohain4
Advances in robotics,mechatronics,cyborgs and disruptive technologies for heptics, brain machine interfaces and neurorobotics are bringing a sea change to the field of rehabilitation engineering. Carbon fibre cheetah blades, Bionic arms, c legs are helping the amputees to the extent that amputees can now run in competitive sports at the level of summer Olympics.
Bionics is an aid to technology that is bridging the gap between human limitation and potential. This presentation deals with the details of bionics and different milestones implemented.
Neurorobotics and Advances in rehabilitation engineeringBhaskarBorgohain4
Advances in robotics,mechatronics,cyborgs and disruptive technologies for heptics, brain machine interfaces and neurorobotics are bringing a sea change to the field of rehabilitation engineering. Carbon fibre cheetah blades, Bionic arms, c legs are helping the amputees to the extent that amputees can now run in competitive sports at the level of summer Olympics.
This presentation aims at providing information about the various concepts involved in bestowing rehabilitation to the individuals having sensory disabilities.
This paper describes the design and fabrication of a novel artificial hand based on a “biomechatronic” and cybernetic approach. The approach is aimed at providing “natural” sensory-motor co-ordination, biomimetic mechanisms, force and position sensors, actuators and control, and by interfacing the hand with the peripheral nervous system.
At the end of this presentation, you will be able to understand what is physiotherapy and what kind of robotic devices we use. Those robotic devices have been very helpful but it can be a little challenging for us to utilize all the types of devices. The physiotherapist should know about the devices that he/she uses and have experience with it and that can be a disadvantage of the robotic devices. We have a lot of types of robotic devices for all kinds of disabilities. The patients can have more confidence and be more focused during the sessions. The devices have been an advantage for physiotherapists as well. It helps physiotherapists not to burnout during the sessions. Especially patients with disabilities like difficulty walking or even standing up. The future of physiotherapy and robotic devices is still in progress and let's see what it can bring us.
As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to making some pretty spectacular science fiction into reality. Imagine transmitting signals directly to someone's brain that would allow them to see, hear or feel specific sensory inputs. Consider the potential to manipulate computers or machinery with nothing more than a thought. It isn't about convenience, for severely disabled people, development of a brain-computer interface (BCI) could be the most important technological breakthrough in decades.
A Brain-computer interface, sometimes called a direct neural interface or a brain-machine interface, is a direct communication pathway between a brain and an external device. It is the ultimate in development of human-computer interfaces or HCI. BCIs being the recent development in HCI there are many realms to be explored. After experimentation three types of BCIs have been developed namely Invasive BCIs, Partially-invasive BCIs, Non-invasive BCIs.
Servo Based 5 Axis Robotic Arm Project ReportRobo India
Robo India presents a project report on servo motor based 5 axis robotic arm.
This project is operated through PC software that is made in Visual Basic. AVR family's Atmel Atmega 8 is used in controller board, it runs on Arduino IDE platform.
Detailed mechnical drawings of all of the parts are also given.
We welcome all of your views and queries.
Thanks & Regards
Team Robo India
www.roboindia.com
info@roboindia.com
This presentation aims at providing information about the various concepts involved in bestowing rehabilitation to the individuals having sensory disabilities.
This paper describes the design and fabrication of a novel artificial hand based on a “biomechatronic” and cybernetic approach. The approach is aimed at providing “natural” sensory-motor co-ordination, biomimetic mechanisms, force and position sensors, actuators and control, and by interfacing the hand with the peripheral nervous system.
At the end of this presentation, you will be able to understand what is physiotherapy and what kind of robotic devices we use. Those robotic devices have been very helpful but it can be a little challenging for us to utilize all the types of devices. The physiotherapist should know about the devices that he/she uses and have experience with it and that can be a disadvantage of the robotic devices. We have a lot of types of robotic devices for all kinds of disabilities. The patients can have more confidence and be more focused during the sessions. The devices have been an advantage for physiotherapists as well. It helps physiotherapists not to burnout during the sessions. Especially patients with disabilities like difficulty walking or even standing up. The future of physiotherapy and robotic devices is still in progress and let's see what it can bring us.
As the power of modern computers grows alongside our understanding of the human brain, we move ever closer to making some pretty spectacular science fiction into reality. Imagine transmitting signals directly to someone's brain that would allow them to see, hear or feel specific sensory inputs. Consider the potential to manipulate computers or machinery with nothing more than a thought. It isn't about convenience, for severely disabled people, development of a brain-computer interface (BCI) could be the most important technological breakthrough in decades.
A Brain-computer interface, sometimes called a direct neural interface or a brain-machine interface, is a direct communication pathway between a brain and an external device. It is the ultimate in development of human-computer interfaces or HCI. BCIs being the recent development in HCI there are many realms to be explored. After experimentation three types of BCIs have been developed namely Invasive BCIs, Partially-invasive BCIs, Non-invasive BCIs.
Servo Based 5 Axis Robotic Arm Project ReportRobo India
Robo India presents a project report on servo motor based 5 axis robotic arm.
This project is operated through PC software that is made in Visual Basic. AVR family's Atmel Atmega 8 is used in controller board, it runs on Arduino IDE platform.
Detailed mechnical drawings of all of the parts are also given.
We welcome all of your views and queries.
Thanks & Regards
Team Robo India
www.roboindia.com
info@roboindia.com
Our update for the beginning of 2014, about self-directed evolution from the constraint of biology to a substrate-independent mind (SIM) and personality, a process alluded to in science fiction with the oft-confusing term "uploading". In this talk, I present the most realistic development route to SIM via whole brain emulation (WBE), neural prostheses and neural interfaces. I describe how I contribute to make this happen, as effectively as I can, through my work as it is presented at carboncopies.org. Then, I draw your attention to the most significant development in the field at this moment, an opportunity for a widely applicable Platform for high resolution neural interfaces. That platform has the potential in the near-term to provide the access needed for true brain machine interfaces, cognitive neural prostheses and the type of data acquisition that is essential for whole brain emulation.
Implanted Neural Prosthetics - an IntroductionJennifer French
Explains the benefits of neural prostheses, or devices that can restore motor, sensory or cognitive function that might have been damaged as a result of a spinal cord injury or disease (SCI/D). It will provide an introduction to a new model to make neural prosthesis more accessible for those living with SCI/D.
Explains the benefits of neural prostheses, or devices that can restore motor, sensory or cognitive function that might have been damaged as a result of a spinal cord injury or disease (SCI/D). It will provide an introduction to a new model to make neural prosthesis more accessible for those living with SCI/D.
The Neuroprosthetics is an emerging field in the Health Care & Engineering Sector.
In this Technology a Specialized Chip is implanted in the Brain & by using Electronic & Mechanical Components the Brain Waves in converted into respective Mechanical Movements.
Neuroprosthetics is specifically used for patients suffering from Paralysis, Amoyotropic Lateral Sclerosis & Multiple Sclerosis.
This Field is in its Initial Stage in terms of Research specifically in India.This field requires a lot of research specially for India & Developing Countries.
Neuroprosthetics will be an Transforming World for Health Sector in the future.
This video explains Lumbar Disc Replacement in Detail. When degenerative disc disease begins to affect the spine this is called degenerative disc disease. This video highlights the history, epidemiology, and treatment options both conservative and surgical. If you or someone you know needs to be seen in regards to Lumbar Disc Replacement feel free to look us up online www.beverlyspine.com or www.santamonicaspine.com OR call toll free 1-8SPINECAL-1
The thought of mind-controlled prosthetics might sound like something out of the "Star Wars" movies. Yet thanks to the company DARPA, this could soon become a reality/
Article Overview "Reach and grasp by people with tetraplegia using a neurally...Ilya Kuzovkin
This presentation is article overview given at the Computational Neuroscience seminar in the University of Tartu. In my opinion at the moment this is the most prominent BCI system out there.
Recognition of new gestures using myo armband for myoelectric prosthetic appl...IJECEIAES
Myoelectric prostheses are a viable solution for people with amputations. The chal- lenge in implementing a usable myoelectric prosthesis lies in accurately recognizing different hand gestures. The current myoelectric devices usually implement very few hand gestures. In order to approximate a real hand functionality, a myoelectric prosthesis should implement a large number of hand and finger gestures. However, increasing number of gestures can lead to a decrease in recognition accuracy. In this work a Myo armband device is used to recognize fourteen gestures (five build in gestures of Myo armband in addition to nine new gestures). The data in this research is collected from three body-able subjects for a period of 7 seconds per gesture. The proposed method uses a pattern recognition technique based on Multi-Layer Perceptron Neural Network (MLPNN). The results show an average accuracy of 90.5% in recognizing the proposed fourteen gestures.
A robotic arm is a Programmable mechanical arm which copies the functions of the human arm. They
are widely used in industries. Human robot-controlled interfaces mainly focus on providing rehabilitation to
amputees in order to overcome their amputation or disability leading them to live a normal life. The major
objective of this project is to develop a movable robotic arm controlled by EMG signals from the muscles of the
upper limb. In this system, our main aim is on providing a low 2-dimensional input derived from emg to move the
arm. This project involves creating a prosthesis system that allows signals recorded directly from the human body.
The arm is mainly divided into 2 parts, control part and moving part. Movable part contains the servo motor
which is connected to the Arduino Uno board, and it helps in developing a motion in accordance with the EMG
signals acquired from the body. The control part is the part that is controlled by the operation according to the
movement of the amputee. Mainly the initiation of the movement for the threshold fixed in the coding. The major
aim of the project is to provide an affordable and easily operable device that helps even the poor sections of the
amputated society to lead a happier and normal life by mimicking the functions of the human arm in terms of both
the physical, structural as well as functional aspects.
Special Report: Medical Robotics
Self-propelled nanobots that deliver drugs inside the human body...novel sensors that improve the safety and precision of industrial robots...a dynamic hydrogel material that makes building soft robotic devices as simple as assembling a LEGO set. These are just a few of the medical robotics innovations you'll read about in this compendium of recent articles from the editors of Medical Design Briefs and Tech Briefs magazines.
Correlation Analysis of Electromyogram SignalsIJMTST Journal
An inability to adapt myoelectric interfaces to a user’s unique style of hand motion. The system also adapts
the motion style of an opposite limb. These are the important factors inhibiting the practical application of
myoelectric interfaces. This is mainly attributed to the individual differences in the exhibited electromyogram
(EMG) signals generated by the muscles of different limbs. In this project myoelectric interface easily adapts
the signal from the users and maintains good movement recognition performance. At the initial stage the
myoelectric signal is extracted from the user by using the data acquisition system. A new set of features
describing the movements of user’s is extracted and the user’s features are classifed using SVM
classification. The given signal is then compared with the database signal with the accuracy of 90.910 %
across all the EMG signals.
EMG Driven IPMC Based Artificial Muscle FingerAbida Zama
The medical, rehabilitation and bio-mimetic technology demands human actuated devices which can support in the daily life activities such as functional assistance or functional substitution of human organs. These devices can be used in the form of prosthetic, skeletal and artificial muscles devices. However, we still have some difficulties in the practical use of these devices. The major challenges to overcome are the acquisition of the user’s intention from his or her bionic signals and to provide with an appropriate control signal for the device. Also, we need to consider the mechanical design issues such as lightweight and small size with flexible behavior etc. For the bionic signals, the electromyography (EMG) signal can be used to control these devices, which reflect the muscles motion, and can be acquired from the body surface. We are familiar with the fact that Ionic polymer metal composite (IPMC) has tremendous potential as an artificial muscle. In place of the supply voltage from external source for actuating an IPMC, EMG signal can be used where EMG electrodes show a reliable approach to extract voltage signal from body. Using this voltage signal via EMG sensor, IPMC can illustrate the bio-mimetic behavior through the movement of human muscles. Therefore, an IPMC is used as an artificial muscle finger for the bio-mimetic/micro robot.
Low-cost and open-source anthropomorphic prosthetics hand using linear actuatorsTELKOMNIKA JOURNAL
A robust, low cost, open-source, and low power consumption in the research of prosthetics hand is essential. The purpose of this study is to develop a low-cost, open-source anthropomorphic prosthetics hand using linear actuator based on electromyography (EMG) signal control. The main advantages of this proposed method are the low-cost, lightweight and simplicity of controlling the prosthetic hand using only single channel. This is achieved by evaluating the DC motor and exploring number of locations of the EMG signal. The development of prosthetics hand consists of 3D anthropomorphic hand design, active electrodes, microcontroller, and linear actuator. The active electrodes recorded the EMG signal from extensor carpi radialis longus. The built-in EMG amplifier on the electrode amplified the EMG signal. Further, the A/D converter in the Arduino microcontroller converted the analog signal into digital. A filtering process consisted of bandpass and notch filter was performed before it used as a control signal. The linear actuator controlled each finger for flexion and extension motion. In the assessment of the design, the prosthetic hand capable of grasping ten objects. In this study, the cost and weight of the prosthetics hand are 471.99 US$ and 0.531 kg, respectively. This study has demonstrated the design of low cost and opensource of prosthetics hand with reasonable cost and lightweight. Furthermore, this development could be applied to amputee subjects.
Comparative analysis of machine learning algorithms on myoelectric signal fro...IAESIJAI
Control strategies of smart hand prosthesis-based myoelectric signals in recent years don't provide the patients with the sensation of biological control of prostheses hand fingers. Therefore, in current work hyperparameters optimization in machine learning algorithm and hand gesture recognition techniques were applied to the myoelectric signal-based on residual muscles contraction of the amputees corresponding to intact forearm limb movement to improve their biological control. In this paper, myoelectric signals are extracted using the MYO armband to recognize ten gestures from ten volunteers (healthy and transradial amputation) on the forearm, thereafter the noise of myoelectric signals using a notch filter (NF) is removed. The proposed classification system involved two machine learning algorithms: (1) the decision tree (DT), tri-layered neural network (TLNN), k-nearest-neighbor (KNN), support vector machine (SVM) and ensemble boosted tree (EBT) classifiers. (2) the optimized machine learning classifiers, i.e., OKNN, OSVM, OEBT with optical diffraction tomography (ODT) and ommatidia detecting algorithm (ODA). The experimental results of classifiers comparison pointed out an algorithm that outperformed with high accuracy is OEBT closely followed by OKNN achieves an accuracy of 97.8% and 97.1% for intact forearm limb, while for transradial amputation with an accuracy of 91.9% and 91.4%, respectively.
International Journal of Engineering Research and Applications (IJERA) is an open access online peer reviewed international journal that publishes research and review articles in the fields of Computer Science, Neural Networks, Electrical Engineering, Software Engineering, Information Technology, Mechanical Engineering, Chemical Engineering, Plastic Engineering, Food Technology, Textile Engineering, Nano Technology & science, Power Electronics, Electronics & Communication Engineering, Computational mathematics, Image processing, Civil Engineering, Structural Engineering, Environmental Engineering, VLSI Testing & Low Power VLSI Design etc.
OPTIMIZATION OF NEURAL NETWORK ARCHITECTURE FOR BIOMECHANIC CLASSIFICATION TA...ijaia
Electromyogram signals (EMGs) contain valuable information that can be used in man-machine interfacing between human users and myoelectric prosthetic devices. However, EMG signals are
complicated and prove difficult to analyze due to physiological noise and other issues. Computational
intelligence and machine learning techniques, such as artificial neural networks (ANNs), serve as powerful
tools for analyzing EMG signals and creating optimal myoelectric control schemes for prostheses. This
research examines the performance of four different neural network architectures (feedforward, recurrent,
counter propagation, and self organizing map) that were tasked with classifying walking speed when given
EMG inputs from 14 different leg muscles. Experiments conducted on the data set suggest that self
organizing map neural networks are capable of classifying walking speed with greater than 99% accuracy.
he main idea of the current work is to use a wireless Electroencephalography (EEG) headset as a remote control for the mouse cursor of a personal computer. The proposed system uses EEG signals as a communication link between brains and computers. Signal records obtained from the PhysioNet EEG dataset were analyzed using the Coif lets wavelets and many features were extracted using different amplitude estimators for the wavelet coefficients. The extracted features were inputted into machine learning algorithms to generate the decision rules required for our application. The suggested real time implementation of the system was tested and very good performance was achieved. This system could be helpful for disabled people as they can control computer applications via the imagination of fists and feet movements in addition to closing eyes for a short period of time
Embedded system for upper-limb exoskeleton based on electromyography controlTELKOMNIKA JOURNAL
A major problem in an exoskeleton based on electromyography (EMG) control with pattern recognition-based is the need for more time to train and to calibrate the system in order able to adapt for different subjects and variable. Unfortunately, the implementation of the joint prediction on an embedded system for the exoskeleton based on the EMG control with non-pattern recognition-based is very rare. Therefore, this study presents an implementation of elbow-joint angle prediction on an embedded system to control an upper limb exoskeleton based on the EMG signal. The architecture of the system consisted of a bio-amplifier, an embedded ARMSTM32F429 microcontroller, and an exoskeleton unit driven by a servo motor. The elbow joint angle was predicted based on the EMG signal that is generated from biceps. The predicted angle was obtained by extracting the EMG signal using a zero-crossing feature and filtering the EMG feature using a Butterworth low pass filter. This study found that the range of root mean square error and correlation coefficients are 8°-16° and 0.94-0.99, respectively which suggest that the predicted angle is close to the desired angle and there is a high relationship between the predicted angle and the desired angle.
Current motorized limb prostheses provide rudimentary functionality for the application in everyday life. Together with a
poor cosmetic appearance, this is the reason why a large percentage of amputees do not use their prosthetic device regularly. This
paper seeks to present an overview of current state of the art research on neural interfaces. The focus lies on non-invasive
recording with EMG and especially High-Density EMG sensors. Additionally, direct machine learning and pattern recognition
algorithms for the decoding of the recorded signals are discussed. Finally, promising research directions for advanced prosthesis
control will be discussed. The bionic arm uses EMG signals to control each action of the hand. In order to control them, we need to
record the EMG signal for different actions. And compare it with real-time values to move the hand in a different manner. There
are separate servo motors to control the actions of each finger separately. So these are programmed by using microcontrollers.
Abstract: This paper gives about an idea about the issues concerning the integration of artificial limbs. This paper includes on overview of research finding on the development of BIONIC ARMS that are used as prosthetic arms. Controlling by the sensory feedback system. The system are used on vibration and electrical system and combination of the two methods.
DEVELOPMENT OF MOTION CONTROL ALGORITHM FOR LOWER LIMB EXOSKELETONE WITH SIMU...DAXESHPATEL81
‘Exoskeleton’ can be interpreted into two different terms Exo-
meaning the external and ‘skeleton’- meaning rigid structure for any living organisms.
Exoskeletons are used to perform task which are usually beyond the boundaries of
human in their comfort environment. The exoskeletons can either be autonomous or
operator depended on the task to be fulfilled. Usually an ideal exoskeleton should be
able to perform any tasks which are done by human but with greater capacity and
durability. As our topic being one of the most fancy and fiction like equipment it has
been able to draw much wider attention than any other in the field of Robotics. But
such a topic composes two very different fields of Applied Sciences – Robotics and
Biology. In order to fully utilize these fields in development of Exoskeleton one must
possess a keen knowledge of all aspects of these both separate fields. So a new
Branch of Applied sciences has been introduced called ‘Bionics’
DEVELOPMENT OF MOTION CONTROL ALGORITHM FOR LOWER LIMB EXOSKELETONE WITH SIMU...DAXESHPATEL81
‘Exoskeleton’ can be interpreted into two different terms Exo-
meaning the external and ‘skeleton’- meaning rigid structure for any living organisms.
Exoskeletons are used to perform task which are usually beyond the boundaries of
human in their comfort environment. The exoskeletons can either be autonomous or
operator depended on the task to be fulfilled. Usually an ideal exoskeleton should be
able to perform any tasks which are done by human but with greater capacity and
durability. As our topic being one of the most fancy and fiction like equipment it has
been able to draw much wider attention than any other in the field of Robotics. But
such a topic composes two very different fields of Applied Sciences – Robotics and
Biology. In order to fully utilize these fields in development of Exoskeleton one must
possess a keen knowledge of all aspects of these both separate fields. So a new
Branch of Applied sciences has been introduced called ‘Bionics’
Similar to Prosthetic hand using Artificial Neural Network (20)
CRISPR-Cas9, a revolutionary gene-editing tool, holds immense potential to reshape medicine, agriculture, and our understanding of life. But like any powerful tool, it comes with ethical considerations.
Unveiling CRISPR: This naturally occurring bacterial defense system (crRNA & Cas9 protein) fights viruses. Scientists repurposed it for precise gene editing (correction, deletion, insertion) by targeting specific DNA sequences.
The Promise: CRISPR offers exciting possibilities:
Gene Therapy: Correcting genetic diseases like cystic fibrosis.
Agriculture: Engineering crops resistant to pests and harsh environments.
Research: Studying gene function to unlock new knowledge.
The Peril: Ethical concerns demand attention:
Off-target Effects: Unintended DNA edits can have unforeseen consequences.
Eugenics: Misusing CRISPR for designer babies raises social and ethical questions.
Equity: High costs could limit access to this potentially life-saving technology.
The Path Forward: Responsible development is crucial:
International Collaboration: Clear guidelines are needed for research and human trials.
Public Education: Open discussions ensure informed decisions about CRISPR.
Prioritize Safety and Ethics: Safety and ethical principles must be paramount.
CRISPR offers a powerful tool for a better future, but responsible development and addressing ethical concerns are essential. By prioritizing safety, fostering open dialogue, and ensuring equitable access, we can harness CRISPR's power for the benefit of all. (2998 characters)
CHAPTER 1 SEMESTER V - ROLE OF PEADIATRIC NURSE.pdfSachin Sharma
Pediatric nurses play a vital role in the health and well-being of children. Their responsibilities are wide-ranging, and their objectives can be categorized into several key areas:
1. Direct Patient Care:
Objective: Provide comprehensive and compassionate care to infants, children, and adolescents in various healthcare settings (hospitals, clinics, etc.).
This includes tasks like:
Monitoring vital signs and physical condition.
Administering medications and treatments.
Performing procedures as directed by doctors.
Assisting with daily living activities (bathing, feeding).
Providing emotional support and pain management.
2. Health Promotion and Education:
Objective: Promote healthy behaviors and educate children, families, and communities about preventive healthcare.
This includes tasks like:
Administering vaccinations.
Providing education on nutrition, hygiene, and development.
Offering breastfeeding and childbirth support.
Counseling families on safety and injury prevention.
3. Collaboration and Advocacy:
Objective: Collaborate effectively with doctors, social workers, therapists, and other healthcare professionals to ensure coordinated care for children.
Objective: Advocate for the rights and best interests of their patients, especially when children cannot speak for themselves.
This includes tasks like:
Communicating effectively with healthcare teams.
Identifying and addressing potential risks to child welfare.
Educating families about their child's condition and treatment options.
4. Professional Development and Research:
Objective: Stay up-to-date on the latest advancements in pediatric healthcare through continuing education and research.
Objective: Contribute to improving the quality of care for children by participating in research initiatives.
This includes tasks like:
Attending workshops and conferences on pediatric nursing.
Participating in clinical trials related to child health.
Implementing evidence-based practices into their daily routines.
By fulfilling these objectives, pediatric nurses play a crucial role in ensuring the optimal health and well-being of children throughout all stages of their development.
We understand the unique challenges pickleball players face and are committed to helping you stay healthy and active. In this presentation, we’ll explore the three most common pickleball injuries and provide strategies for prevention and treatment.
India Clinical Trials Market: Industry Size and Growth Trends [2030] Analyzed...Kumar Satyam
According to TechSci Research report, "India Clinical Trials Market- By Region, Competition, Forecast & Opportunities, 2030F," the India Clinical Trials Market was valued at USD 2.05 billion in 2024 and is projected to grow at a compound annual growth rate (CAGR) of 8.64% through 2030. The market is driven by a variety of factors, making India an attractive destination for pharmaceutical companies and researchers. India's vast and diverse patient population, cost-effective operational environment, and a large pool of skilled medical professionals contribute significantly to the market's growth. Additionally, increasing government support in streamlining regulations and the growing prevalence of lifestyle diseases further propel the clinical trials market.
Growing Prevalence of Lifestyle Diseases
The rising incidence of lifestyle diseases such as diabetes, cardiovascular diseases, and cancer is a major trend driving the clinical trials market in India. These conditions necessitate the development and testing of new treatment methods, creating a robust demand for clinical trials. The increasing burden of these diseases highlights the need for innovative therapies and underscores the importance of India as a key player in global clinical research.
The dimensions of healthcare quality refer to various attributes or aspects that define the standard of healthcare services. These dimensions are used to evaluate, measure, and improve the quality of care provided to patients. A comprehensive understanding of these dimensions ensures that healthcare systems can address various aspects of patient care effectively and holistically. Dimensions of Healthcare Quality and Performance of care include the following; Appropriateness, Availability, Competence, Continuity, Effectiveness, Efficiency, Efficacy, Prevention, Respect and Care, Safety as well as Timeliness.
Leading the Way in Nephrology: Dr. David Greene's Work with Stem Cells for Ki...Dr. David Greene Arizona
As we watch Dr. Greene's continued efforts and research in Arizona, it's clear that stem cell therapy holds a promising key to unlocking new doors in the treatment of kidney disease. With each study and trial, we step closer to a world where kidney disease is no longer a life sentence but a treatable condition, thanks to pioneers like Dr. David Greene.
Medical Technology Tackles New Health Care Demand - Research Report - March 2...pchutichetpong
M Capital Group (“MCG”) predicts that with, against, despite, and even without the global pandemic, the medical technology (MedTech) industry shows signs of continuous healthy growth, driven by smaller, faster, and cheaper devices, growing demand for home-based applications, technological innovation, strategic acquisitions, investments, and SPAC listings. MCG predicts that this should reflects itself in annual growth of over 6%, well beyond 2028.
According to Chris Mouchabhani, Managing Partner at M Capital Group, “Despite all economic scenarios that one may consider, beyond overall economic shocks, medical technology should remain one of the most promising and robust sectors over the short to medium term and well beyond 2028.”
There is a movement towards home-based care for the elderly, next generation scanning and MRI devices, wearable technology, artificial intelligence incorporation, and online connectivity. Experts also see a focus on predictive, preventive, personalized, participatory, and precision medicine, with rising levels of integration of home care and technological innovation.
The average cost of treatment has been rising across the board, creating additional financial burdens to governments, healthcare providers and insurance companies. According to MCG, cost-per-inpatient-stay in the United States alone rose on average annually by over 13% between 2014 to 2021, leading MedTech to focus research efforts on optimized medical equipment at lower price points, whilst emphasizing portability and ease of use. Namely, 46% of the 1,008 medical technology companies in the 2021 MedTech Innovator (“MTI”) database are focusing on prevention, wellness, detection, or diagnosis, signaling a clear push for preventive care to also tackle costs.
In addition, there has also been a lasting impact on consumer and medical demand for home care, supported by the pandemic. Lockdowns, closure of care facilities, and healthcare systems subjected to capacity pressure, accelerated demand away from traditional inpatient care. Now, outpatient care solutions are driving industry production, with nearly 70% of recent diagnostics start-up companies producing products in areas such as ambulatory clinics, at-home care, and self-administered diagnostics.
2. ABSTRACT
The scientific researches in the field of rehabilitation engineering are increasingly providing
mechanisms in order to help people with disability to perform simple tasks of day-to-day.
Several studies have been carried out highlighting the advantages of using muscle signal in order to
control rehabilitation devices, such as experimental prostheses.
This project use of forearm surface electromyography (sEMG) signals for classification of several
movements of the arm using just three pairs of surface electrodes located in strategic places.
Electromyography (EMG) is the control interface for modern, upper limb prosthetics.
Signal classification by Artificial Neural Network.
Cost effective
3. INTRODUCTION
The development of systems managed by myoelectric signals with the intention to reproduce the human arm
movement is far from perfect, which makes it the target of many investigations
Control of prosthesis based on the intention of the user .
Amputees are able to generate standardized myoelectric signals.
The proposed system uses only 3 pairs of electrodes .
More precise than conventional limb prosthetic
4. BACKGROUND INFORMATION
Current Prosthetic Hand using Technology
BCI TECHNOLOGY
The mind-to-movement system that allows a quadriplegic man to control a computer using
only his thoughts is a scientific milestone. It was reached, in large part, through the brain gate
system.
The Brain Gate System is based on Cyber kinetics platform technology to sense, transmit,
analyze and apply the language of neurons.
The principle of operation behind the Brain Gate System is that with intact brain function, brain
signals are generated even though they are not sent to the arms, hands and legs.
5. MYO ELECTRIC HAND
Myo electric uses a battery and electronic motors to function.
Once it is attached, the prosthetic uses electronic sensors
to detect minute muscle nerve, and EMG activity.
It then translates this muscle activity (as triggered by the user) into information that its
electric motors use to control the artificial limbs movements.
The end result is that the artificial limb moves much like a natural limb, according
the mental stimulus of the user.
The user can even control the strength and speed of the limb’s movements and grip by
varying his or her muscle intensity.
6. LITERATURE SURVEY
Classification of Surface Electromyographic Signal for Prosthesis Control
Application
2010 IEEE EMBS Conference on Biomedical Engineering & Sciences (IECBES 2010
KualaLumpurMalaysia, Siti A. Ahmadi, Asnor J. Ishak, Sawal Ali
This describes the classification stage of an electro myographic (EMG) control system for prosthetic
hand application.
Moving ApEn was used as main method to extract features from the two channels of surface EMG
signal at the forearm of the upper limb.
12. PROTOTYPE 3
Less weight
Easy to carry
Easy movements
Can hold objects
Elastic Band for Automatic closing
Upgradable
MATERIALS USED
THERMOPLASTICS WOOD ETC.
13. FEASIBILITY OF THE TOPIC
The costs of commercially available myoelectric hands are very high, ranging in price from 3-4
lacs.We were able to develop a prototype hand with similar functionally to the more
sophisticated myoelectric hands on the market.It roughly costs up to fifty thousand rupees . A
new technology is devised for manufacturing the Prosthetic hand while making it easily
affordable.
14. PLATFORM OF THE TOPIC
HARDWARE
Microcontroller
EMG sensor
EMG electrode and pads
Servo motor
PVC pipe
Nylon string
17. Project plan
Work done
Selection of the Materials.
Designing the prosthetic.
Shipment of the Hardware parts.
Prepared the initializing and training codes for the working.
Completed the source code for motor drive.
Developed the prototype
19. CONCLUSION
The proposed system uses only 3 pair of electrodes for the signal acquisition process.
The signal processing comprises of initialization, training and testing.
Artificial Neural Network is configured with three hidden layers
The no: of values for input sector is equal to the no: of output sector.
Particular data sets of EMG from amputees are loaded for the processing.