- The study monitored 11 anesthetized pigs during induced hypoxic cardiac arrest using multiple vital sign sensors to record heart rate, blood pressure, etc.
- The researchers used OntoSpace software to calculate a measure called OntoSpace Complexity (OSC) based on the interconnectedness and entropy of the full monitoring system.
- They found that OSC increased sharply an average of 5 minutes before the pigs experienced loss of arterial pulsation, while most individual vital signs did not change significantly until closer to loss of pulsation.
- Monitoring systems-level complexity through OSC may provide earlier warning of deterioration compared to individual vital signs and could help with crisis anticipation in decision support systems.
Measuring Work in Single Isolated Cardiomyocytes: Replicating the Cardiac CycleInsideScientific
A special webinar for basic cardiovascular researchers interested in a novel technique for measuring work output and replicating the four phases of the cardiac cycle at the single cell level.
The study of isolated cardiac myocytes provide a wealth of basic cellular and molecular information without the complications often associated with heterogeneous multicellular preparations. The overwhelming majority of data presented in myocyte studies, however, are reported in mechanically unloaded conditions. Join us for a practical demonstration of an exciting new technique where mechanical control of the cell reveals the myocyte's force-length relationship by varying pre- and afterload to achieve isometric, isotonic, and, ultimately, work-loop style contractions analogous to the pressure-volume relationship in whole heart studies.
In this exclusive webinar sponsored by IonOptix, Michiel Helmes presents methodology and best-practices that scientists should follow in order to replicate the cardiac cycle in an isolated cardiomyocyte. He discusses how this research method can be used to better address contractile function in cardiovascular disease studies and highlight critical features of the IonOptix MyoStretcher system that are important for this emerging and novel technique.
Interpreting Health Status Of Indian Population Using Phase Angle As Health P...IJRES Journal
Bio Electrical Impedance Analyser is a simple Non-Invasive tool that is used for the Human body composition Analysis. It has been found that the basic principle of Human Body composition Analysis is the measurement of fat vs lean muscle tissue. And it is well known fact that biological tissues the path of least resistance. While Analysing the body composition through Bio Electrical Impedance Analyser body resistance and body reactance are taken into account. Phase Angle is directly calculated from resistance and reactance and Phase Angle is an important indicator of cellular health and integrity. This paper aims at discussing the significance of Phase Angle in Analysis of Human Body Composition and developing and validating prediction equation of Phase Angle at different frequencies.
Quantifying Cardiovascular and Behavioral Correlates of Fear in Mice: Implica...InsideScientific
To learn more and watch the webinar, go to:
https://insidescientific.com/webinar/quantifying-cardiovascular-and-behavioral-correlates-of-fear-in-mice-implications-for-ptsd-and-cardiovascular-disease-risk/
Post-traumatic stress disorder (PTSD) is a prevalent neuropsychological disorder that is in part characterized by exaggerated cardiovascular and autonomic arousal to trauma reminders, which over time may contribute to greater risk for cardiovascular disease (CVD) development (ie., stroke, hypertension). In both humans and rodents, cardiovascular and autonomic responses are strong measures of fear or threat assessment and therefore understanding how these systems go awry in anxiety disorders such as PTSD is critical for improving current PTSD therapies as well as reducing CVD risk in this population.
In this webinar, Dr. Paul Marvar and Benjamin Turley discuss research related to innovative methodology developed in rodent models for pairing real-time multi-modal assessment of behavioral (ie., freezing, startle) and cardiovascular (ie., blood pressure, heart rate) responses to cued fear learning and how these approaches may better inform underlying cardiovascular and autonomic impairments in fear-based disorders, such as PTSD.
Key Topics Include:
- To understand the physiological impact of PTSD on cardiovascular and autonomic homeostasis, CVD risk
- To understand how rodent models of conditioned fear learning can be used to assess real-time cardiovascular and autonomic fear or defensive emotional states in both home-cage and novel environments
- To further understand the benefits for using integrated behavioral and cardiovascular multi-modal methodologies and its translational implications for improved treatments for PTSD and CVD comorbidity
A Comprehensive How-To Demonstration of Higher Throughput Excitation-Contract...InsideScientific
From myocyte isolation to data acquisition, analysis, and post-analysis plotting, join Dr. Michiel Helmes and Dr. Diederik Kuster as they demonstrate best practices and new techniques in high-content, higher throughput investigations of excitation-contraction coupling in isolated cardiomyocytes.
During this 60 minute live webinar, Michiel Helmes and Diederik Kuster will deliver a comprehensive how-to demonstration of higher throughput excitation-contraction coupling investigations with isolated cardiomyocytes.
Characterizing excitation-contraction coupling in isolated cardiac myocytes has been essential to our understanding of heart function. Historically these studies have been constrained by lower throughput data collection and limited sample sizes. Because isolated myocytes display a high degree of functional variability, acquiring data from more myocytes is required for greater accuracy and statistical confidence.
In this webinar, we will demonstrate important aspects of data collection from myocyte isolation to precision data acquisition, data analysis, and post-analysis interpretation. We will focus on how to get the most out of every isolation, how to collect quality data consistently, why statistical power matters, and how to get statistically meaningful data in hours.
Key Topics Include:
Get more from less: learn to maximize data from each animal
Quality and quantity: best practices for data acquisition
Knowledge is power: understand what your data means and how to interpret it
Go beyond numbers: see how to get automated, same-day post-analysis data plotting and processing
Measuring Work in Single Isolated Cardiomyocytes: Replicating the Cardiac CycleInsideScientific
A special webinar for basic cardiovascular researchers interested in a novel technique for measuring work output and replicating the four phases of the cardiac cycle at the single cell level.
The study of isolated cardiac myocytes provide a wealth of basic cellular and molecular information without the complications often associated with heterogeneous multicellular preparations. The overwhelming majority of data presented in myocyte studies, however, are reported in mechanically unloaded conditions. Join us for a practical demonstration of an exciting new technique where mechanical control of the cell reveals the myocyte's force-length relationship by varying pre- and afterload to achieve isometric, isotonic, and, ultimately, work-loop style contractions analogous to the pressure-volume relationship in whole heart studies.
In this exclusive webinar sponsored by IonOptix, Michiel Helmes presents methodology and best-practices that scientists should follow in order to replicate the cardiac cycle in an isolated cardiomyocyte. He discusses how this research method can be used to better address contractile function in cardiovascular disease studies and highlight critical features of the IonOptix MyoStretcher system that are important for this emerging and novel technique.
Interpreting Health Status Of Indian Population Using Phase Angle As Health P...IJRES Journal
Bio Electrical Impedance Analyser is a simple Non-Invasive tool that is used for the Human body composition Analysis. It has been found that the basic principle of Human Body composition Analysis is the measurement of fat vs lean muscle tissue. And it is well known fact that biological tissues the path of least resistance. While Analysing the body composition through Bio Electrical Impedance Analyser body resistance and body reactance are taken into account. Phase Angle is directly calculated from resistance and reactance and Phase Angle is an important indicator of cellular health and integrity. This paper aims at discussing the significance of Phase Angle in Analysis of Human Body Composition and developing and validating prediction equation of Phase Angle at different frequencies.
Quantifying Cardiovascular and Behavioral Correlates of Fear in Mice: Implica...InsideScientific
To learn more and watch the webinar, go to:
https://insidescientific.com/webinar/quantifying-cardiovascular-and-behavioral-correlates-of-fear-in-mice-implications-for-ptsd-and-cardiovascular-disease-risk/
Post-traumatic stress disorder (PTSD) is a prevalent neuropsychological disorder that is in part characterized by exaggerated cardiovascular and autonomic arousal to trauma reminders, which over time may contribute to greater risk for cardiovascular disease (CVD) development (ie., stroke, hypertension). In both humans and rodents, cardiovascular and autonomic responses are strong measures of fear or threat assessment and therefore understanding how these systems go awry in anxiety disorders such as PTSD is critical for improving current PTSD therapies as well as reducing CVD risk in this population.
In this webinar, Dr. Paul Marvar and Benjamin Turley discuss research related to innovative methodology developed in rodent models for pairing real-time multi-modal assessment of behavioral (ie., freezing, startle) and cardiovascular (ie., blood pressure, heart rate) responses to cued fear learning and how these approaches may better inform underlying cardiovascular and autonomic impairments in fear-based disorders, such as PTSD.
Key Topics Include:
- To understand the physiological impact of PTSD on cardiovascular and autonomic homeostasis, CVD risk
- To understand how rodent models of conditioned fear learning can be used to assess real-time cardiovascular and autonomic fear or defensive emotional states in both home-cage and novel environments
- To further understand the benefits for using integrated behavioral and cardiovascular multi-modal methodologies and its translational implications for improved treatments for PTSD and CVD comorbidity
A Comprehensive How-To Demonstration of Higher Throughput Excitation-Contract...InsideScientific
From myocyte isolation to data acquisition, analysis, and post-analysis plotting, join Dr. Michiel Helmes and Dr. Diederik Kuster as they demonstrate best practices and new techniques in high-content, higher throughput investigations of excitation-contraction coupling in isolated cardiomyocytes.
During this 60 minute live webinar, Michiel Helmes and Diederik Kuster will deliver a comprehensive how-to demonstration of higher throughput excitation-contraction coupling investigations with isolated cardiomyocytes.
Characterizing excitation-contraction coupling in isolated cardiac myocytes has been essential to our understanding of heart function. Historically these studies have been constrained by lower throughput data collection and limited sample sizes. Because isolated myocytes display a high degree of functional variability, acquiring data from more myocytes is required for greater accuracy and statistical confidence.
In this webinar, we will demonstrate important aspects of data collection from myocyte isolation to precision data acquisition, data analysis, and post-analysis interpretation. We will focus on how to get the most out of every isolation, how to collect quality data consistently, why statistical power matters, and how to get statistically meaningful data in hours.
Key Topics Include:
Get more from less: learn to maximize data from each animal
Quality and quantity: best practices for data acquisition
Knowledge is power: understand what your data means and how to interpret it
Go beyond numbers: see how to get automated, same-day post-analysis data plotting and processing
Yandex.Trafik "Real-time traffic information for avoiding traffic jam"Yandex.Türkiye
How does Yandex.Trafik gathers information and how does it provide solutions to daily trafic problem.
If you are curious about "How does Yandex.Trafik is so accurate" you will be interested in this presentation
Con el ejemplo de myVIBS el proceso patentar un concepto es explicado. myVIBS es una ayuda para músicos de viento para relajar los músculos que a sido propuesto como patente Europea.
Luxury hotels in Kolkata - The Oberoi Grand, KolkataGaurav Nikalje
Known as the Grand Dame of Kolkata, The Oberoi Grand is situated in a prime location, near the central business district, bustling markets and cultural landmarks. Dating back to the late 1880s, The Oberoi Grand was frequented by the country's leading figures during colonial times and even now, hosts grand functions for Heads of State in the city's largest pillarless Grand Ballroom.
Control of Nonlinear Heartbeat Models under Time- Delay-Switched Feedback Usi...idescitation
In this paper, we adopt the Zeeman nonlinear heart model to discuss its stability
and control its operation using emotional learning control (ELC). We also demonstrate the
control of the heart model under threats of possible time delay introduced in the sensing
loop. We compare the robustness of the ELC with other control methods such as the
classical PID and the model predictive control (MPC) for the heart model under time delay
attack. We have showed that ELC is more robust than the classical PID and the MPC.
The QRS changes during ischemia have historically been more difficult to parameterize
and have not come into clinical practice. This paper presented a new approach to analyze ischemia
by time parameter extraction of RS-Segment of the QRS complex. The proposed methodology
mainly focused on two prominent areas; first: detection of R and S points via Fast Fourier Transform
(FFT) based windowing & thresholding techniques with a sliding edge method. Second: calculating
the RS-Duration. The performances of the detection methods are validated and RS-Duration is
evaluated with the Fantasia database (Fantasia) for 20 healthy subjects & Long-Term ST Database
(LTSTDB) for 80 ischemic patients. The RS-Segment detection sensitivity (Se) and specificity (Sp)
are calculated 100% for Fantasia Database, whereas sensitivity (Se) is 91.6% and specificity (Sp) is
974% for LTSTDB.
Eeg time series data analysis in focal cerebral ischemic rat modelijbesjournal
The mammalian brain exists in a number of attractors. In order to characterize these attractors we have collected the time series data from the EEG recording of rat models. The time series was obtained by recording of the frontoparietal, occipital and temporal regions of the rat brain. Significant changes have
been observed in the dimensionalities of these brain attractors between the normal state, focal ischemic
state and the drug induced state. Thus, these three states were characterized by unique lyapunov exponents,
correlation dimensions and embedding dimensions. The inverse of the lyapunov exponent gave us the long
term coherence of the rat brain and was found to differ for the three states. The autocorrelation function
measured the mean similarity of the EEG signal with itself after a time t. The degree of decay was high indicating that there was maximum correlation in the time series. Thus, the autocorrelation functions clearly indicate the effect of focal cerebral ischemia and drugs induced on the rat brain.
PERFORMANCE EVALUATION OF ARTIFICIAL NEURAL NETWORKS FOR CARDIAC ARRHYTHMIA C...IAEME Publication
In this paper an effective and most reliable method for appropriate classification of cardiac arrhythmia using automatic Artificial Neural Network (ANN) has been proposed. The results are encouraging and are found to have produced a very confident and efficient arrhythmia classification, which is easily applicable in diagnostic decision support system. The authors have employed 3 neural network classifiers to classify three types of beats of ECG signal, namely Normal (N), and two abnormal beats Right Bundle Branch Block (RBBB) and Premature Ventricular Contraction (PVC). The classifiers used in this paper are K-Nearest Neighbor (KNN), Naive Bayes Classifier (NBC) and Multi-Class Support Vector Machine (MSVM). The performance of the classifiers is evaluated using 5 parametric measures namely Sensitivity (Se), Specificity (Sp), Precision (Pr), Bit Error Rate (BER) and Accuracy (A). Hence MSVM classifier using Crammers method is very effective for proper ECG beat classification.
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.
Yandex.Trafik "Real-time traffic information for avoiding traffic jam"Yandex.Türkiye
How does Yandex.Trafik gathers information and how does it provide solutions to daily trafic problem.
If you are curious about "How does Yandex.Trafik is so accurate" you will be interested in this presentation
Con el ejemplo de myVIBS el proceso patentar un concepto es explicado. myVIBS es una ayuda para músicos de viento para relajar los músculos que a sido propuesto como patente Europea.
Luxury hotels in Kolkata - The Oberoi Grand, KolkataGaurav Nikalje
Known as the Grand Dame of Kolkata, The Oberoi Grand is situated in a prime location, near the central business district, bustling markets and cultural landmarks. Dating back to the late 1880s, The Oberoi Grand was frequented by the country's leading figures during colonial times and even now, hosts grand functions for Heads of State in the city's largest pillarless Grand Ballroom.
Control of Nonlinear Heartbeat Models under Time- Delay-Switched Feedback Usi...idescitation
In this paper, we adopt the Zeeman nonlinear heart model to discuss its stability
and control its operation using emotional learning control (ELC). We also demonstrate the
control of the heart model under threats of possible time delay introduced in the sensing
loop. We compare the robustness of the ELC with other control methods such as the
classical PID and the model predictive control (MPC) for the heart model under time delay
attack. We have showed that ELC is more robust than the classical PID and the MPC.
The QRS changes during ischemia have historically been more difficult to parameterize
and have not come into clinical practice. This paper presented a new approach to analyze ischemia
by time parameter extraction of RS-Segment of the QRS complex. The proposed methodology
mainly focused on two prominent areas; first: detection of R and S points via Fast Fourier Transform
(FFT) based windowing & thresholding techniques with a sliding edge method. Second: calculating
the RS-Duration. The performances of the detection methods are validated and RS-Duration is
evaluated with the Fantasia database (Fantasia) for 20 healthy subjects & Long-Term ST Database
(LTSTDB) for 80 ischemic patients. The RS-Segment detection sensitivity (Se) and specificity (Sp)
are calculated 100% for Fantasia Database, whereas sensitivity (Se) is 91.6% and specificity (Sp) is
974% for LTSTDB.
Eeg time series data analysis in focal cerebral ischemic rat modelijbesjournal
The mammalian brain exists in a number of attractors. In order to characterize these attractors we have collected the time series data from the EEG recording of rat models. The time series was obtained by recording of the frontoparietal, occipital and temporal regions of the rat brain. Significant changes have
been observed in the dimensionalities of these brain attractors between the normal state, focal ischemic
state and the drug induced state. Thus, these three states were characterized by unique lyapunov exponents,
correlation dimensions and embedding dimensions. The inverse of the lyapunov exponent gave us the long
term coherence of the rat brain and was found to differ for the three states. The autocorrelation function
measured the mean similarity of the EEG signal with itself after a time t. The degree of decay was high indicating that there was maximum correlation in the time series. Thus, the autocorrelation functions clearly indicate the effect of focal cerebral ischemia and drugs induced on the rat brain.
PERFORMANCE EVALUATION OF ARTIFICIAL NEURAL NETWORKS FOR CARDIAC ARRHYTHMIA C...IAEME Publication
In this paper an effective and most reliable method for appropriate classification of cardiac arrhythmia using automatic Artificial Neural Network (ANN) has been proposed. The results are encouraging and are found to have produced a very confident and efficient arrhythmia classification, which is easily applicable in diagnostic decision support system. The authors have employed 3 neural network classifiers to classify three types of beats of ECG signal, namely Normal (N), and two abnormal beats Right Bundle Branch Block (RBBB) and Premature Ventricular Contraction (PVC). The classifiers used in this paper are K-Nearest Neighbor (KNN), Naive Bayes Classifier (NBC) and Multi-Class Support Vector Machine (MSVM). The performance of the classifiers is evaluated using 5 parametric measures namely Sensitivity (Se), Specificity (Sp), Precision (Pr), Bit Error Rate (BER) and Accuracy (A). Hence MSVM classifier using Crammers method is very effective for proper ECG beat classification.
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.
Introduction: Aging-associated vascular stiffening augments cardiovascular disease risk in the elderly. Research to identify targetable cellular and molecular mechanisms is of key interest as no current therapies are available to specifically target vascular stiffening. In this context, enzymes that mediate remodeling of the vascular matrix and those that promote cellular dysfunction are attractive targets. In pre-clinical models, pulse wave velocity (PWV), the gold standard measure of in vivo vascular stiffness, can be measured longitudinally and non-invasively, to make inroads towards the discovery and validation of potential targets.
A novel target and model: We have identified a central role for tissue transglutaminase (TG2) in vascular stiffening during aging. TG2 is a multifunctional protein of the transglutaminase family, whose primary function is to assist in the formation of a strong and stable matrix by catalyzing crosslinking of matrix proteins. Recent studies have shown that TG2 has putative crosslinking-independent functions in aging-associated vascular stiffening and dysfunction. The crosslinking independent mechanisms of TG2 remain incompletely understood due to the lack of pre-clinical models and specific inhibitors that can selectively inhibit a single function of TG2. Thus, we developed a novel knock-in mouse, the TGM2-C277S mouse, by mutating the active site cysteine of TG2 using the CRISPR-Cas9 gene editing technology to selectively target its crosslinking function.
Results and conclusion: We first validated the TGM2-C277S mouse and confirmed that this mutation removes TG2’s crosslinking function but retains its crosslinking independent functions. We next compared PWV wild type (WT), global TG2 knockout (TG2-/-), and the TGM2-C277S mice, to identify the contributions of the crosslinking-dependent and crosslinking-independent functions of TG2 to vascular aging in vivo. PWV increased significantly with age in WT mice, and to a much lower magnitude in the TGM2-C277S mice. TG2-/- mice were further protected against aging associated increase in PWV. Together, these studies show that TG2 contributes significantly to overall vascular stiffening in aging through both crosslinking dependent and crosslinking independent functions.
The learning objectives are:
To understand changes in pulse wave velocity (PWV) with age in mouse models
To determine the specific role of tissue transglutaminase (TG2) in vascular aging
To evaluate the role of vascular matrix vs. VSMCs to overall in vivo stiffness described by PWV
Machine-Learning Estimation of Body Posture and Physical Activity by Wearable...sipij
We aimed to develop the method for estimating body posture and physical activity by acceleration signals from a Holter electrocardiographic (ECG) recorder with built-in accelerometer. In healthy young subjects, triaxial-acceleration and ECG signal were recorded with the Holter ECG recorder attached on their chest wall. During the recording, they randomly took eight postures, including supine, prone, left and right recumbent, standing, sitting in a reclining chair, sitting in chairs with and without backrest, and performed slow walking and fast walking. Machine learning (Random Forest) was performed on acceleration and ECG variables. The best discrimination model was obtained when the maximum values and standard deviations of accelerations in three axes and mean R-R interval were used as feature values. The overall discrimination accuracy was 79.2% (62.6-90.9%). Supine, prone, left recumbent, and slow and fast walk were discriminated with >80% accuracy, although sitting and standing positions were not discriminated by this method.
MACHINE-LEARNING ESTIMATION OF BODY POSTURE AND PHYSICAL ACTIVITY BY WEARABLE...sipij
We aimed to develop the method for estimating body posture and physical activity by acceleration signals from a Holter electrocardiographic (ECG) recorder with built-in accelerometer. In healthy young subjects, triaxial-acceleration and ECG signal were recorded with the Holter ECG recorder attached on their chest wall. During the recording, they randomly took eight postures, including supine, prone, left and right recumbent, standing, sitting in a reclining chair, sitting in chairs with and without backrest, and performed slow walking and fast walking. Machine learning (Random Forest) was performed on acceleration and ECG variables. The best discrimination model was obtained when the maximum values and standard deviations of accelerations in three axes and mean R-R interval were used as feature values. The overall discrimination accuracy was 79.2% (62.6-90.9%). Supine, prone, left recumbent, and slow and fast walk were discriminated with >80% accuracy, although sitting and standing positions were not discriminated by this method
Analyzing Employee’s Heart rate using Nonlinear Cellular Automata modelIOSR Journals
Non-linear Cellular Automata model is a simulation tool which can be used to diagnosis the intensity of the disease. This paper aims to study the Heart rate behavior between normal respiratory patients and healthy controls/unhealthy controls. We also discuss about Heart Rate Variability (HRV) of employee’s through non-linear Cellular Automata model. Cellular Automata model gives us striking results for further studies
1. Abstract
Measures of electrocardiogram (EKG)-derived complexity could
be used as new vital signs. We propose a new approach for higher,
systems-level interpretation of physiologic complexity via calculation of
multidimensional entropy in vital sign data. Objective: Monitor systems-
level complexity to identify decompensation. Hypothesis: changes in ù
systems-level complexity precede loss of arterial pulsation (LOAP) in
hypoxic cardiac arrest. Methods: Eleven anesthetized, intubated,
paralyzed and mechanically ventilated swine were instrumented. heart
rate (HR), systolic blood pressure (SBP); central venous pressure (CVP);
continuous cardiac output (CCO); pulse oxymetry (SPO2), bispectral
index (BIS) were recorded at baseline, during asphyxiation (endotracheal
loss of aortic pulsation and SBP< 50 mm Hg. All available monitoring
data from any and all sensors available at the bedside was recorded into
this data was loaded into OntoSpace software for determination of
OntoSpace Complexity (OSC), a cumulative measure of system structure
(interconnectedness between devices) and randomness (entropy). OSC
was calculated and timing of the changes in it was compared to the
experimental timeline. Results: see table. At baseline, OSC was low
remained non-indicative of demise until abrupt occurrence of LOAP. At a
mean time of 5 min. 24 sec before LOAP a critical change (rise) in OSC
adjustment for multiple comparisons. Conclusions: Changes in
systems-level complexity precede deterioration in traditional vital signs
during hypoxic cardiac arrest. Prospective studies will be conducted to
evaluate the utility of this approach as a real-time decision-support tool.
Batchinsky AI, MD1, Deshpande BR2, Williams JB3, MD, Baker W, MS1, Walker K III1, Marczyk J, PhD2, White CE1, MD, Salinas J1, PhD, Cancio LC, MD1
1 U.S. Army Institute of Surgical Research, Fort Sam Houston, Texas, 78234,2 Ontonix S.r.l., Como, Italy,
3 Department of General Surgery, University of Texas Health Science Center at San Antonio, TX.,
Changes in Systems-level Complexity Precede Deterioration in Traditional Vital Signs in Hypoxic Cardiac Arrest
Introduction
Current bedside monitoring technology is based on the single-
sensor, single-indicator concept. Each sensor represents a measurable
organs.
We previously showed that assessment of structural complexity (or
randomness) of the R-to-R interval time series of the EKG is useful in
evaluating the amount of regulatory complexity (amount of
hormonal feedback) during hemorrhagic shock and trauma in animal
models and critically ill humans receiving life-saving interventions
(Batchinsky et al. CCM, 2007; J Trauma 2007; Shock, 2009 and Cancio et
al. J Trauma 2008).
In this presentation we explore a new way of interpreting multiple-
sensor data, using a complexity management software system
(OntoSpace by Ontonix S.r.l. Italy). The software computes the structural
complexity of the entire bedside monitoring system. It constructs
cognitive maps of any number of variables by establishing the
interconnectedness among them. The rate of change of complexity is
used as a measure of the instantaneous stability and robustness of the
entire system.
This way of monitoring may provide earlier information about a
patient’s condition because it picks up small but collective changes in
variability of the various signals. Such changes may go unnoticed by
providers until the patient‘crashes’.
The software generates recommendations about system stability
and likelihood of approaching critical states, which may be useful in ICU
decision support.
Results
• It took an average of 30 sec to calculate OSC at each time point using 59 channels of
data.
within normal range.
• After tube clamping, vital signs (except SpO2) did not change for 3-8 min, after which the
shown).
• During LOAP only SBP and SpO2 were indicative of a critical event.
• At an average time of 5 min 40 sec before LOAP (see table ) a critical rise in OSC was
• OSC remained high at LOAP.
Results
Variable/ mepoint
Baseline
Tube clamped,
Data at 5min 40 sec before LOAP LOAP
HR, bpm
119 ± 10 103 ± 13 101 ± 17
SBP, mmHg 88 ± 3 100 ± 10 31 ± 8*†
CVP, mmH2O 5 ± 1 7 ± 1 15 ± 1*†
CCO, l/min 5 4 ± 1 3 ± 1*†
SpO2, % 99 ± 0.5 71 ± 12 19 ± 8*†
BIS, unitless 49 ± 10 59 ± 3 24 ± 7*†
OSC, unitless 10 31 * 27.6 *
Table. Baseline, before start of the experiment animal anesthe zed. Tube clamped, endotracheal tube clamped. LOAP, loss of aor c pulsa on. HR, heart rate in
beats per minute. SBP, arterial blood pressure in mm Hg. CVP, central venous pressure. CCO, con nuous cardiac output in l/minute, SPO2 oxygen satura on in
capillary blood at the tail, %. BIS, bispectral index, unitless. OSC, ontospace complexity, unitless.
Conclusions
References
1. Batchinsky AI, Cooke WH, Kuusela T, et al. Loss of complexity characterizes the heart-rate response to
experimental hemorrhagic shock in swine. Crit Care Med 2007;35:519-525.
2. Batchinsky AI, Salinas J, Kuusela T, et al. Rapid Prediction of Trauma-Patient Survival by Analysis of Heart-Rate
Complexity: Impact of Reducing Dataset Size. Shock 2009;32 565-571.
3. Batchinsky AI, Cancio LC, Salinas J, et al. Prehospital loss of R-to-R interval complexity is associated with
mortality in trauma patients J Trauma 2007;63:512-518.
4. Cancio LC, Batchinsky AI, Salinas J, et al. Heart-rate complexity for prediction of prehospital lifesaving
interventions in trauma patients. J Trauma 2008;65:813-819.
In this experiment OntoSpace Complexity (OSC) increased sharply after tube clamping
and on average at 5 min 40 seconds before LOAP, while common vital signs were
unremarkable (other than SPO2).
Monitoring of systems-level complexity during experimental asphyxia permitted earlier
identification of a critical state in this model.
System-level complexity monitoring may be a useful‘vital sign’which permits crisis
anticipation and can be integrated into future decision support systems at the bedside.
al
“The opinions or assertions contained herein are the private views of the author and are not to be construed as official or as
reflecting the views of the Department of the Army or the Department of Defense.”
“This study has been conducted in compliance with the Animal Welfare Act, the implementing Animal Welfare Regulations and in
accordance with the principles of the Guide for the Care and Use of Laboratory Animals.”
Step 3: Construct systems maps. Analyze all variable
interactions. If the corresponding 2D image of each
paired scatter plot contains structure, create a link in the
map – this corresponds to a relationship between the
two variables plotted on the original x, y plot.
Step 2: Build x,y scatter plots of pairs of data streams
data e.g. HR vs ABP. Next the plot is transformed into a
2D image. The image is analyzed by calculation of image
entropy, a measure of information content.
Step 1: Real-time automatic retrieval of sensor data. Data
from monitors were fed into databases. (Step 1) Data
streams were sampled at 5 second intervals and a moving
window of 500 samples (2500 seconds) was used and
advanced by 10 samples (50 seconds) at each iteration.
Step 6: Understand implicaons for system instability.
Complexity measures (lower bound, current and crical
An abrupt change in current complexity by 30% or more.
Is an indicaon of destabilizaon.
Step 5: Effects of changes in system
maps on complexity history.
Step 4: Visualize running complexity history.
Figure. Example of current prototype of systems level complexity history during an
individual experiment. Note the multude of crical changes in stability which idenfy events in the clini-
cal course. Stability is calculated as the rate of change in OSC. During each change the running contri-
bung signals are ranked in the order of importance poinng to the specific organs and systems that
generate the dominang inputs to current complexity.