scholarly journals Opening the Schrödinger Box: Short- and Long-Range Mammalian Heart Rate Variability

2021 ◽  
Vol 12 ◽  
Author(s):  
Ido Weiser-Bitoun ◽  
Moran Davoodi ◽  
Aviv A. Rosenberg ◽  
Alexandra Alexandrovich ◽  
Yael Yaniv
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Long Range ◽  
Short Range ◽  
Target Species ◽  
Relative Contribution ◽  
Novel Approach ◽  
Before And After ◽  
Ecg Data ◽  
General Method

BackgroundThe interactions between the autonomic nervous system (ANS), intrinsic systems (e.g., endocrine), and internal pacemaker mechanisms govern short (milliseconds–seconds)- and long (seconds–minutes)-range heart rate variability (HRV). However, there is a debate regarding the identity of the mechanism underlying HRV on each time scale. We aim to design a general method that accurately differentiates between the relative contribution of the ANS and pacemaker mechanisms to HRV in various mammals, without the need for drug perturbations or organ isolation. Additionally, we aim to explore the universality of the relative contribution of the ANS and pacemaker system of different mammals.MethodsThis work explored short- and long-range HRVs using published ECG data from dogs, rabbits, and mice. To isolate the effects of ANS on HRV, ECG segments recorded before and after ANS-blockade were compared.ResultsDifferentiation of the ANS from extrinsic and intrinsic pacemaker mechanisms was successfully achieved. In dogs, the internal pacemaker mechanisms were the main contributors to long-range and the ANS to short-range HRV. In rabbits and mice, the ANS and the internal pacemaker mechanisms affected both time scales, and anesthesia changed the relative contribution of the pacemaker mechanism to short- and long-range HRVs. In mice, the extrinsic mechanisms affected long-range HRV, while their effect was negligible in rabbits.ConclusionWe offer a novel approach to determine the relative contributions of ANS and extrinsic and intrinsic pacemaker mechanisms to HRV and highlight the importance of selecting mammalian research models with HRV mechanisms representative of the target species of interest.

840 – Heart rate variability in panic disorder patients before and after the therapy

2013 ◽  
Vol 28 ◽  
pp. 1 ◽  
Author(s):  
T. Diveky ◽  
J. Prasko ◽  
M. Cerna ◽  
D. Kamaradova ◽  
A. Grambal ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Panic Disorder ◽  
Before And After

scholarly journals Heart rate variability: Analysis of time-domain indices in patients with chronic Chagas disease before and after an exercise program

2013 ◽  
Vol 32 (3) ◽  
pp. 219-227 ◽  
Author(s):  
Marcus Vinicius Amaral da Silva Souza ◽  
Carla Cristiane Santos Soares ◽  
Juliana Rega de Oliveira ◽  
Cláudia Rosa de Oliveira ◽  
Paloma Hargreaves Fialho ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Chagas Disease ◽  
Time Domain ◽  
Exercise Program ◽  
Heart Rate Variability Analysis ◽  
Variability Analysis ◽  
Before And After ◽  
Chronic Chagas Disease

Comparative study on effect of neutral spinal bath and neutral spinal spray on blood pressure, heart rate and heart rate variability in healthy volunteers

2018 ◽  
Vol 16 (2) ◽  
Author(s):  
Arundhati Goley ◽  
A. Mooventhan ◽  
NK. Manjunath
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Healthy Volunteers ◽  
Group Analysis ◽  
Low Frequency ◽  
Single Session ◽  
Arterial Blood ◽  
Before And After ◽  
Instantaneous Heart Rate

Abstract Background Hydrotherapeutic applications to the head and spine have shown to improve cardiovascular and autonomic functions. There is lack of study reporting the effect of either neutral spinal bath (NSB) or neutral spinal spray (NSS). Hence, the present study was conducted to evaluate and compare the effects of both NSB and NSS in healthy volunteers. Methods Thirty healthy subjects were recruited and randomized into either neutral spinal bath group (NSBG) or neutral spinal spray group (NSSG). A single session of NSB, NSS was given for 15 min to the NSBG and NSSG, respectively. Assessments were taken before and after the interventions. Results Results of this study showed a significant reduction in low-frequency (LF) to high-frequency (HF) (LF/HF) ratio of heart rate variability (HRV) spectrum in NSBG compared with NSSG (p=0.026). Within-group analysis of both NSBG and NSSG showed a significant increase in the mean of the intervals between adjacent QRS complexes or the instantaneous heart rate (HR) (RRI) (p=0.002; p=0.009, respectively), along with a significant reduction in HR (p=0.002; p=0.004, respectively). But, a significant reduction in systolic blood pressure (SBP) (p=0.037) and pulse pressure (PP) (p=0.017) was observed in NSSG, while a significant reduction in diastolic blood pressure (DBP) (p=0.008), mean arterial blood pressure (MAP) (p=0.008) and LF/HF ratio (p=0.041) was observed in NSBG. Conclusion Results of the study suggest that 15 min of both NSB and NSS might be effective in reducing HR and improving HRV. However, NSS is particularly effective in reducing SBP and PP, while NSB is particularly effective in reducing DBP and MAP along with improving sympathovagal balance in healthy volunteers.

scholarly journals Quantitative assessment of the relationship between behavioral and autonomic dynamics during propofol-induced unconsciousness

2020 ◽  
Author(s):  
Sandya Subramanian ◽  
Patrick L. Purdon ◽  
Riccardo Barbieri ◽  
Emery N. Brown
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Prediction Models ◽  
Electrodermal Activity ◽  
Strong Relationship ◽  
Pulse Amplitude ◽  
Physiological Data ◽  
Statistical Tool ◽  
Autonomic Changes ◽  
Before And After

ABSTRACTDuring general anesthesia, both behavioral and autonomic changes are caused by the administration of anesthetics such as propofol. Propofol produces unconsciousness by creating highly structured oscillations in brain circuits. The anesthetic also has autonomic effects due to its actions as a vasodilator and myocardial depressant. Understanding how autonomic dynamics change in relation to propofol-induced unconsciousness is an important scientific and clinical question since anesthesiologists often infer changes in level of unconsciousness from changes in autonomic dynamics. Therefore, we present a framework combining physiology-based statistical models that have been developed specifically for heart rate variability and electrodermal activity with a robust statistical tool to compare behavioral and multimodal autonomic changes before, during, and after propofol-induced unconsciousness. We tested this framework on physiological data recorded from nine healthy volunteers during computer-controlled administration of propofol. We studied how autonomic dynamics related to behavioral markers of unconsciousness: 1) overall, 2) during the transitions of loss and recovery of consciousness, and 3) before and after anesthesia as a whole. Our results show a strong relationship between behavioral state of consciousness and autonomic dynamics. All of our prediction models showed areas under the curve greater than 0.75 despite the presence of non-monotonic relationships among the variables during the transition periods. Our analysis highlighted the specific roles played by fast versus slow changes, parasympathetic vs sympathetic activity, heart rate variability vs electrodermal activity, and even pulse rate vs pulse amplitude information within electrodermal activity. Further advancement upon this work can quantify the complex and subject-specific relationship between behavioral changes and autonomic dynamics before, during, and after anesthesia. However, this work demonstrates the potential of a multimodal, physiologically-informed, statistical approach to characterize autonomic dynamics.

Effect of sleep restriction on orthostatic cardiovascular control in humans

2000 ◽  
Vol 88 (3) ◽  
pp. 966-972 ◽  
Author(s):  
N. K. Muenter ◽  
D. E. Watenpaugh ◽  
W. L. Wasmund ◽  
S. L. Wasmund ◽  
S. A. Maxwell ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Lower Body Negative Pressure ◽  
Systolic Pressure ◽  
Cardiovascular Responses ◽  
Sleep Restriction ◽  
Orthostatic Tolerance ◽  
Arterial Baroreflex ◽  
Finger Arterial Pressure ◽  
Before And After

We hypothesized that sleep restriction (4 consecutive nights, 4 h sleep/night) attenuates orthostatic tolerance. The effect of sleep restriction on cardiovascular responses to simulated orthostasis, arterial baroreflex gain, and heart rate variability was evaluated in 10 healthy volunteers. Arterial baroreflex gain was determined from heart rate responses to nitroprusside-phenylephrine injections, and orthostatic tolerance was tested via lower body negative pressure (LBNP). A Finapres device measured finger arterial pressure. No difference in baroreflex function, heart rate variability, or LBNP tolerance was observed with sleep restriction ( P > 0.3). Systolic pressure was greater at −60 mmHg LBNP after sleep restriction than before sleep restriction (110 ± 6 and 124 ± 3 mmHg before and after sleep restriction, respectively, P = 0.038), whereas heart rate decreased (108 ± 8 and 99 ± 8 beats/min before and after sleep restriction, respectively, P = 0.028). These data demonstrate that sleep restriction produces subtle changes in cardiovascular responses to simulated orthostasis, but these changes do not compromise orthostatic tolerance.

scholarly journals Direct application of an ECG-based sleep staging algorithm on reflective photoplethysmography data decreases performance

2020 ◽  
Vol 13 (1) ◽  
Author(s):  
M. M. van Gilst ◽  
B. M. Wulterkens ◽  
P. Fonseca ◽  
M. Radha ◽  
M. Ross ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Direct Application ◽  
Alternative Methods ◽  
Sleep Staging ◽  
Practical Application ◽  
Sleep Monitoring ◽  
Data Source ◽  
Variability Data ◽  
Ecg Data

Abstract Objective The maturation of neural network-based techniques in combination with the availability of large sleep datasets has increased the interest in alternative methods of sleep monitoring. For unobtrusive sleep staging, the most promising algorithms are based on heart rate variability computed from inter-beat intervals (IBIs) derived from ECG-data. The practical application of these algorithms is even more promising when alternative ways of obtaining IBIs, such as wrist-worn photoplethysmography (PPG) can be used. However, studies validating sleep staging algorithms directly on PPG-based data are limited. Results We applied an automatic sleep staging algorithm trained and validated on ECG-data directly on inter-beat intervals derived from a wrist-worn PPG sensor, in 389 polysomnographic recordings of patients with a variety of sleep disorders. While the algorithm reached moderate agreement with gold standard polysomnography, the performance was significantly lower when applied on PPG- versus ECG-derived heart rate variability data (kappa 0.56 versus 0.60, p < 0.001; accuracy 73.0% versus 75.9% p < 0.001). These results show that direct application of an algorithm on a different source of data may negatively affect performance. Algorithms need to be validated using each data source and re-training should be considered whenever possible.

scholarly journals Experimental Study for Determining the Parameters Required for Detecting ECG and EEG Related Diseases during the Timed-Up and Go Test

Computers ◽  
2020 ◽  
Vol 9 (3) ◽  
pp. 67
Author(s):  
Vasco Ponciano ◽  
Ivan Miguel Pires ◽  
Fernando Reinaldo Ribeiro ◽  
María Vanessa Villasana ◽  
Maria Canavarro Teixeira ◽  
...  
Keyword(s):  
Heart Rate ◽  
Experimental Study ◽  
Heart Rate Variability ◽  
Mobile Devices ◽  
Brain Activity ◽  
Health Conditions ◽  
Qrs Complex ◽  
Timed Up And Go ◽  
Eeg Data ◽  
Ecg Data

The use of smartphones, coupled with different sensors, makes it an attractive solution for measuring different physical and physiological features, allowing for the monitoring of various parameters and even identifying some diseases. The BITalino device allows the use of different sensors, including Electroencephalography (EEG) and Electrocardiography (ECG) sensors, to study different health parameters. With these devices, the acquisition of signals is straightforward, and it is possible to connect them using a Bluetooth connection. With the acquired data, it is possible to measure parameters such as calculating the QRS complex and its variation with ECG data to control the individual’s heartbeat. Similarly, by using the EEG sensor, one could analyze the individual’s brain activity and frequency. The purpose of this paper is to present a method for recognition of the diseases related to ECG and EEG data, with sensors available in off-the-shelf mobile devices and sensors connected to a BITalino device. The data were collected during the elderly’s experiences, performing the Timed-Up and Go test, and the different diseases found in the sample in the study. The data were analyzed, and the following features were extracted from the ECG, including heart rate, linear heart rate variability, the average QRS interval, the average R-R interval, and the average R-S interval, and the EEG, including frequency and variability. Finally, the diseases are correlated with different parameters, proving that there are relations between the individuals and the different health conditions.

Heart Rate Variability before and after Knee Surgery in Amateur Soccer Players

2007 ◽  
Vol 16 (4) ◽  
pp. 336-342
Author(s):  
Nicolas Olivier ◽  
Renaud Legrand ◽  
Jacques Rogez ◽  
FX Gamelin ◽  
Serge Berthoin ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Knee Surgery ◽  
Soccer Players ◽  
Total Power ◽  
Autonomic Nervous ◽  
Hospitalization Period ◽  
Before And After

Objective:To analyze the consequences on heart rate variability (HRV) of a hospitalization period due to surgery of the knee in sportsmen.Patients:Ten soccer players who had undergone knee surgery took part in this study.Design:HRV was measured before and after hospitalization within a 7-day interval.Results:After the hospitalization phase, heart rate at rest increased significantly (3 beats/minute). A significant decrease of 7% in the cardiac inter beat interval (R-R interval), P < 0.05 and a 66% decrease in total power spectral density: −66%, P < 0.05 were observed. The disturbance of the autonomic nervous system could be due to a variation in cardiac vagal activity resulting in a 64% decrease in the high frequencies (P < 0.05). This variation was not associated with a modification in normalized markers (LFn.u., HFn.u.) and LF/HF ratio (P > 0.05).Conclusion:In sportsmen, a hospitalization period led to an increase in resting heart rate and was associated with a disturbance of the autonomic nervous system.

Sign in / Sign up

Export Citation Format

Share Document