scholarly journals Validation of a Wireless Bluetooth Photoplethysmography Sensor Used on the Earlobe for Monitoring Heart Rate Variability Features during a Stress-Inducing Mental Task in Healthy Individuals

Sensors ◽  
2020 ◽  
Vol 20 (14) ◽  
pp. 3905
Author(s):  
Bruno Correia ◽  
Nuno Dias ◽  
Patrício Costa ◽  
José Miguel Pêgo
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Analysis Data ◽  
Mental Task ◽  
Non Invasive ◽  
Stressful Task ◽  
Response Alternatives ◽  
The Mean ◽  
Hrv Analysis ◽  
Good Agreement

Heart rate variability (HRV), using electrocardiography (ECG), has gained popularity as a biomarker of the stress response. Alternatives to HRV monitoring, like photoplethysmography (PPG), are being explored as cheaper and unobtrusive non-invasive technologies. We report a new wireless PPG sensor that was tested in detecting changes in HRV, elicited by a mentally stressful task, and to determine if its signal can be used as a surrogate of ECG for HRV analysis. Data were collected simultaneously from volunteers using a PPG and ECG sensor, during a resting and a mentally stressful task. HRV metrics were extracted from these signals and compared to determine the agreement between them and to determine if any changes occurred in the metrics due to the stressful task. For both tasks, a moderate/good agreement was found in the mean interbeat intervals, SDNN, LF, and SD2, and a poor agreement for the pNN50, RMSSD|SD1, and HF metrics. The majority of the tested HRV metrics obtained from the PPG signal showed a significant decrease caused by the mental task. The disagreement found between specific HRV features imposes caution when comparing metrics from different technologies. Nevertheless, the tested sensor was successful at detecting changes in the HRV caused by a mental stressor.

scholarly journals Remote monitoring can predict lethal arrhythmic events through time-domain analysis of heart rate variability in patients with implantable cardioverter defibrillator

2020 ◽  
Vol 41 (Supplement_2) ◽  
Author(s):  
Y Shirakawa ◽  
S Niwano ◽  
J Oikawa ◽  
D Saito ◽  
T Sato ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Implantable Cardioverter Defibrillator ◽  
Time Domain ◽  
Remote Monitoring ◽  
Time Domain Analysis ◽  
Domain Analysis ◽  
Cardioverter Defibrillator ◽  
The Mean ◽  
Hrv Analysis

Abstract Background We prospectively collected device and heart rate data, i.e. heart rate variability (HRV), through remote monitoring (RM) of patients with implantable cardioverter defibrillator (ICD). Several studies have demonstrated usefulness of RM in implanted device patients, however, reports concerning the predictors of lethal ventricular arrhythmias are limited. Purpose The objective was to identify the predictors of lethal arrhythmic events (VT/VF). Methods Thirty-three patients (mean age: 50 years) with ICDs [with functionality of HRV analysis] were divided into 2 groups [VT/VF(+), VT/VF(−)]. Clinical, device (ventricular lead impedance; amplitude of ventricular electrogram), and HRV data were compared between the 2 groups. As the index of time-domain HRV analysis, NN intervals-index (SDNNi) was calculated for every 5 minutes, and the mean, maximum, and minimum SDNNi during the 24-hour period were used. Results During the observation period (median 12 months), 10 patients experienced VT/VF events. In HRV data, the mean, max, and min SDNNi were higher in VT/VF(+) than VT/VF(−) group (132.9±9.3 v.s. 93.5±6.1, p=0.0013; 214.6±10.6 v.s. 167.0±7.0, p=0.0007; 71.2±7.5 v.s. 43.9±4.9, p=0.0047). The other parameters did not exhibit significant difference. On logistic regression analysis, the mean SDNNi of 100.1, max SDNNi of 185.0 and min SDNNi of 52.0 as cut-off values for prediction of VT/VF event demonstrated significant receiver operating characteristics (ROC) curves (AUC=0.86, p=0.0007; AUC=0.84, p=0.0005; AUC=0.78, p=0.0030). Furthermore, in cases of VT/VF(+) group, the max ΔSDNNi, i.e., difference from baseline SDNNi, and min ΔSDNNi in 7 and 28 days preceding VT/VF events exhibited time course changes in comparison with baseline values. They were significant predictors of VT/VF events (max ΔSDNNi cut-off: 46.8, AUC=0.91, p=0.0002; min ΔSDNNi cut-off: −42.4, AUC=0.88, p=0.0014). Conclusion Time-domain analysis of HRV through RM may help identify patients at high risk of lethal arrhythmic events, and predict occurrence of such arrhythmic events. Funding Acknowledgement Type of funding source: None

scholarly journals Effect of Motion Artifact on Variation in Heart Rate Variability Parameters

2020 ◽  
Vol 8 (6) ◽  
pp. 4611-4616
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Complete Removal ◽  
Motion Artifact ◽  
Time Shift ◽  
Short Term ◽  
Dynamic Activity ◽  
The Mean ◽  
Hrv Analysis ◽  
Sudden Motion

The heart rate variability (HRV) is a noninvasive way properly for investigating the activity of the autonomic nervous system (ANS) as well as to predict cardiovascular diseases. To guarantee an accurate HRV analysis, a motion artifact-free HRV recording must be obtained. However, complete removal of a motion artifact is impossible when measuring heartbeats for 5 min, and the motion artifact due to sudden ANS activity must be taken into consideration for the HRV parameters. And, the ANS balance has thus far been evaluated by each individual HRV parameter calculated for a single 5 min HRV segment, leading to the dynamic activity of the ANS within the same period being ignored. Therefore, to resolve this problem, HRV parameters for ultra-short-term segments that are short enough to reflect a sudden motion artifact must be analyzed. The aim of the present study was to evaluate the effects of a motion artifact on the variation in HRV parameters to provide detailed information on ANS activity. The 121 ultra-short-term HRV segments were created by moving a 1-min window forward by a time shift interval of 2 s for the entire 5 min HRV segment. The ratios of Ln LF to Ln HF in these ultra-short-term segments and a single 5 min segment with a motion artifact were 0.89 and 1.06, respectively, while those in a motion artifact-free HRV segment were 0.75 and 0.93, respectively. This variation test for a short-term motion artifact and motion artifact-free HRV dataset was found to affect the SDNN (7.73 and 2.68), SD2 (11.44 and 4.42), TINN (40.33 and 9.92), and Ln HF (0.37 and 0.13) the most in terms of the standard deviation, respectively. Taken together, the mean HRV parameters of many ultra-short-term segments might play an important role in evaluating dynamic ANS activities within a short-term segment, avoiding the false conclusions made by the traditional HRV analysis.

scholarly journals Heart rate variability as an autonomic biomarker in ischemic stroke

2020 ◽  
Vol 78 (11) ◽  
pp. 724-732
Author(s):  
Natalia Buitrago-Ricaurte ◽  
Fátima Cintra ◽  
Gisele Sampaio Silva
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Ischemic Stroke ◽  
Cardiac Complications ◽  
Invasive Approach ◽  
Non Invasive ◽  
Cardiac Autonomic Regulation ◽  
Causes Of Mortality ◽  
Hrv Analysis ◽  
The Brain

ABSTRACT Stroke is one of the leading causes of mortality and disability worldwide. Autonomic dysfunction after ischemic stroke is frequently associated with cardiac complications and high mortality. The brain-heart axis is a good model for understanding autonomic interaction between the autonomic central network and the cardiovascular system. Heart rate variability (HRV) analysis is a non-invasive approach for understanding cardiac autonomic regulation. In stroke patients, HRV parameters are altered in the acute and chronic stages of the disease, having a prognostic value. In this literature review we summarize the main concepts about the autonomic nervous system and HRV as autonomic biomarkers in ischemic stroke.

scholarly journals Comparing Ictal Cardiac Autonomic Changes in Patients with Frontal Lobe Epilepsy and Temporal Lobe Epilepsy by Ultra-Short-Term Heart Rate Variability Analysis

Medicina ◽  
2021 ◽  
Vol 57 (7) ◽  
pp. 666
Author(s):  
Sungmin You ◽  
Hyunjin Jo ◽  
Baekhwan Cho ◽  
Jooyeon Song ◽  
Dongyeop Kim ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Temporal Lobe Epilepsy ◽  
Frontal Lobe ◽  
Repeated Measures ◽  
Sympathetic Activity ◽  
Frontal Lobe Epilepsy ◽  
Short Term ◽  
The Mean ◽  
Hrv Analysis

Background and Objectives: Abnormal epileptic discharges in the brain can affect the central brain regions that regulate autonomic activity and produce cardiac symptoms, either at onset or during propagation of a seizure. These autonomic alterations are related to cardiorespiratory disturbances, such as sudden unexpected death in epilepsy. This study aims to investigate the differences in cardiac autonomic function between patients with temporal lobe epilepsy (TLE) and frontal lobe epilepsy (FLE) using ultra-short-term heart rate variability (HRV) analysis around seizures. Materials and Methods: We analyzed electrocardiogram (ECG) data recorded during 309 seizures in 58 patients with epilepsy. Twelve patients with FLE and 46 patients with TLE were included in this study. We extracted the HRV parameters from the ECG signal before, during and after the ictal interval with ultra-short-term HRV analysis. We statistically compared the HRV parameters using an independent t-test in each interval to compare the differences between groups, and repeated measures analysis of variance was used to test the group differences in longitudinal changes in the HRV parameters. We performed the Tukey–Kramer multiple comparisons procedure as the post hoc test. Results: Among the HRV parameters, the mean interval between heartbeats (RRi), normalized low-frequency band power (LF) and LF/HF ratio were statistically different between the interval and epilepsy types in the t-test. Repeated measures ANOVA showed that the mean RRi and RMSSD were significantly different by epilepsy type, and the normalized LF and LF/HF ratio significantly interacted with the epilepsy type and interval. Conclusions: During the pre-ictal interval, TLE patients showed an elevation in sympathetic activity, while the FLE patients showed an apparent increase and decrease in sympathetic activity when entering and ending the ictal period, respectively. The TLE patients showed a maintained elevation of sympathetic and vagal activity in the pos-ictal interval. These differences in autonomic cardiac characteristics between FLE and TLE might be relevant to the ictal symptoms which eventually result in SUDEP.

Acute and Chronic Effects of Exercise on Heart Rate Variability in Adults and Children: A Review

2002 ◽  
Vol 14 (4) ◽  
pp. 328-344 ◽  
Author(s):  
Richard Winsley
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Oxygen Uptake ◽  
Peak Oxygen Uptake ◽  
Non Invasive ◽  
Cardiac Autonomic Regulation ◽  
Sympathetic Modulation ◽  
Adults And Children ◽  
Hrv Analysis ◽  
Acute And Chronic Effects

Adults’ cardiac autonomic regulation during exercise and in relation to peak oxygen uptake is well understood, however the situation in children is sparsely documented. Heart rate variability (HRV) analysis provides a non-invasive tool to research sympathovagal balance. A predominance of parasympathetic mediated modulation is characterized by a greater degree of HRV and vice versa. The available data indicate the child’s response to be similar to that observed in adults; heart rate increase arises through withdrawal of parasympathetic modulation with ensuing increase in sympathetic modulation; aerobic training increases HRV and a positive correlation between peak oxygen uptake and a parasympathetic preponderance.

scholarly journals Differential effects of the blood pressure state on pulse rate variability and heart rate variability in critically ill patients

2021 ◽  
Vol 4 (1) ◽  
Author(s):  
Elisa Mejía-Mejía ◽  
James M. May ◽  
Mohamed Elgendi ◽  
Panayiotis A. Kyriacou
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Pulse Rate ◽  
Pulse Transit Time ◽  
Pulse Rate Variability ◽  
Physiological Factors ◽  
Ecg Signals ◽  
Non Invasive ◽  
Electrocardiogram Ecg

AbstractHeart rate variability (HRV) utilizes the electrocardiogram (ECG) and has been widely studied as a non-invasive indicator of cardiac autonomic activity. Pulse rate variability (PRV) utilizes photoplethysmography (PPG) and recently has been used as a surrogate for HRV. Several studies have found that PRV is not entirely valid as an estimation of HRV and that several physiological factors, including the pulse transit time (PTT) and blood pressure (BP) changes, may affect PRV differently than HRV. This study aimed to assess the relationship between PRV and HRV under different BP states: hypotension, normotension, and hypertension. Using the MIMIC III database, 5 min segments of PPG and ECG signals were used to extract PRV and HRV, respectively. Several time-domain, frequency-domain, and nonlinear indices were obtained from these signals. Bland–Altman analysis, correlation analysis, and Friedman rank sum tests were used to compare HRV and PRV in each state, and PRV and HRV indices were compared among BP states using Kruskal–Wallis tests. The findings indicated that there were differences between PRV and HRV, especially in short-term and nonlinear indices, and although PRV and HRV were altered in a similar manner when there was a change in BP, PRV seemed to be more sensitive to these changes.

scholarly journals Field Monitoring the Effects of Overnight Shift Work on Specialist Tactical Police Training with Heart Rate Variability Analysis

2021 ◽  
Vol 13 (14) ◽  
pp. 7895
Author(s):  
Colin Tomes ◽  
Ben Schram ◽  
Robin Orr
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Shift Work ◽  
Emergency Response ◽  
Police Training ◽  
Heart Rate Variability Analysis ◽  
Response Team ◽  
Hrv Analysis ◽  
And Performance ◽  
Personnel Allocation

Police work exposes officers to high levels of stress. Special emergency response team (SERT) service exposes personnel to additional demands. Specifically, the circadian cycles of SERT operators are subject to disruption, resulting in decreased capacity to compensate in response to changing demands. Adaptive regulation loss can be measured through heart rate variability (HRV) analysis. While HRV Trends with health and performance indicators, few studies have assessed the effect of overnight shift work on HRV in specialist police. Therefore, this study aimed to determine the effects overnight shift work on HRV in specialist police. HRV was analysed in 11 SERT officers and a significant (p = 0.037) difference was found in pRR50 levels across the training day (percentage of R-R intervals varying by >50 ms) between those who were off-duty and those who were on duty the night prior. HRV may be a valuable metric for quantifying load holistically and can be incorporated into health and fitness monitoring and personnel allocation decision making.

Trends in Heart Rate and Heart Rate Variability during Pregnancy and Three Months Postpartum: Continuous Monitoring in a Free-Living Context (Preprint)

2021 ◽  
Author(s):  
Fatemeh Sarhaddi ◽  
Iman Azimi ◽  
Anna Axelin ◽  
Hannakaisa Niela-Vilen ◽  
Pasi Liljeberg ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Pregnant Women ◽  
Time Domain ◽  
Second Trimester ◽  
Third Trimester ◽  
Non Invasive ◽  
The Third ◽  
Invasive Method ◽  
Frequency Power

BACKGROUND Heart rate variability (HRV) is a non-invasive method reflecting autonomic nervous system (ANS) regulations. Altered HRV is associated with adverse mental or physical health complications. ANS also has a central role in physiological adaption during pregnancy causing normal changes in HRV. OBJECTIVE Assessing trends in heart rate (HR) and HRV parameters as a non-invasive method for remote maternal health monitoring during pregnancy and three months postpartum. METHODS Fifty-eight pregnant women were monitored using an Internet-of-Things (IoT)-based remote monitoring system during pregnancy and 3-months postpartum. Pregnant women were asked to continuously wear Gear sport smartwatch to monitor their HR and HRV. In addition, a cross-platform mobile application was utilized for collecting pregnancy-related information. The trends of HR and HRV parameters were extracted using reliable data. We also analyzed the trends of normalized HRV parameters based on HR to remove the effect of HR changes on HRV trends. Finally, we exploited hierarchical linear mixed models to analyze the trends of HR, HRV, and normalized HRV parameters. RESULTS HR increased significantly during the second trimester (P<.001) and decreased significantly during the third trimester (P<.01). Time-domain HRV parameters, average normal interbeat intervals (AVNN), standard deviation of normal interbeat intervals (SDNN), root mean square of the successive difference of normal interbeat intervals (RMSSD), normalized SDNN (nSDNN), and normalized RMSSD (nRMSSD) decreased significantly during the second trimester (P<.001) then increased significantly during the third trimester (P<.01). Some of the frequency domain parameters, low-frequency power (LF), high-frequency power (HF), and normalized HF (nHF) decreased significantly during the second trimester (P<.01), and HF increased significantly during the third trimester (P<.01). In the postpartum period, nRMSSD decreased (P<.05), and the LF to HF ratio (LF/HF) increased significantly (P<.01). CONCLUSIONS Our study showed that HR increased and HRV parameters decreased as the pregnancy proceeded, and the values returned to normal after the delivery. Moreover, our results show that HR started to decrease while time-domain HRV parameters and HF started to increase during the third trimester. Our results also demonstrate the possibility of continuous HRV monitoring in everyday life settings.

HEART RATE VARIABILITY RELATED TO N95 RESPIRATOR USE IN INTERNS DURING COVID-19 PANDEMIC

2021 ◽  
pp. 69-70
Author(s):  
Pakanati Sujana ◽  
Venkata Mahesh Gandhavalla ◽  
K. Prabhakara Rao
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Low Frequency ◽  
Protective Equipment ◽  
Short Term ◽  
Non Invasive ◽  
Critical Components ◽  
The Individual ◽  
N95 Respirators ◽  
Respiratory Droplets

Introduction: COVID19 is caused by SARS-CoV-2 which is primarily transmitted through respiratory droplets and contact routes. WHO recommended the use of personal protective equipment (PPE) for prevention and N95 respirators are critical components of PPE. Breathing through N95 respirator will impart stress in the individual and that can be assessed by heart rate variability (HRV). HRV measures the variation in time between each heartbeat controlled by autonomic nervous system (ANS), which is a non invasive reliable index to identify the ANS imbalances. Aims And Objectives: This study is aimed at assessing the HRV of Interns working in COVID19 wards using N95 respirators. Methodology: This study included 100 interns in whom short term HRV was recorded using the standard protocol. Lead II of ECG was recorded using AD instruments (ADI) 8channel polygraph and HRV was analysed using Labchart 8pro software. The recordings were taken before and 1hour after wearing N95 respirator. Results: Overall HRV (SDRR) was found to decrease signicantly after wearing N95 respirator for 1hr (p=0.000). Similarly, indices representing the parasympathetic component ( RMSSD and HF ) were also found to decrease signicantly with the use of N95 respirator. Low frequency (LF) power and LF/HF ratio increased signicantly with N95 respirator use (p=0.000). Conclusion: We conclude that using N95 respirator increased sympathetic activity reecting decreased HRV in our subjects Hence we recommend that it is better to change the duty pattern for interns.

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