scholarly journals The Use of Nonlinear Parameters of Heart Rate Variability for Stress Detection

2021 ◽  
pp. 265-274
Author(s):  
Dmitriy Dimitriev ◽  
◽  
Elena Saperova ◽  
Aleksey Dimitriev ◽  
El’dar Salimov ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Sensitivity And Specificity ◽  
Recurrence Plot ◽  
Line Length ◽  
Detection Algorithm ◽  
Stress Detection ◽  
Linear Discriminant ◽  
Rr Interval ◽  
Diagonal Line

This paper presents a stress detection algorithm using heart rate variability (HRV) parameters. Five-minute electrocardiograms were recorded at rest and under exam stress (252 students were involved). The determined HRV parameters were applied to detect stress by means of several classification algorithms. We analysed linear indices in the time (standard deviation of NN intervals (SDNN) and root mean square of successive RR interval differences (RMSSD)) and frequency domains (low frequency (LF) and high frequency (HF) power as well as LF/HF ratio). To study nonlinear HRV indices, we evaluated approximate entropy (ApEn), sample entropy (SampEn), α1 (DFA1) and α2 (DFA2) scaling exponents, correlation dimension D2, and recurrence plot quantification measures (recurrence rate (REC), mean diagonal line length (Lmean), maximum diagonal line length (Lmax), determinism (DET), and Shannon entropy (ShanEn)). Receiver operating characteristic (ROC) was used to test the performance of the classifiers derived from HRV. The highest area under the ROC curve (AUC), sensitivity, and specificity were found for mean RR-interval, DFA1, DFA2, RMSSD, and Lmax. These parameters were used for stress/rest classification with the help of algorithms that are common in clinical and physiological applications, i.e. logistic regression (LR) and linear discriminant analysis (LDA). Classification performance for stress was quantified using accuracy, sensitivity and specificity measures. The LR achieved an accuracy of 68.25 % at an optimal cutoff value of 0.57. LDA determined stress with 67.46 % accuracy. Thus, HRV parameters can serve as an objective tool for stress detection.

scholarly journals Smart Devices and Wearable Technologies to Detect and Monitor Mental Health Conditions and Stress: A Systematic Review

Sensors ◽  
2021 ◽  
Vol 21 (10) ◽  
pp. 3461
Author(s):  
Blake Anthony Hickey ◽  
Taryn Chalmers ◽  
Phillip Newton ◽  
Chin-Teng Lin ◽  
David Sibbritt ◽  
...  
Keyword(s):  
Mental Health ◽  
Systematic Review ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Electrodermal Activity ◽  
Smart Devices ◽  
Stress Detection ◽  
Wearable Technologies ◽  
Detection Of Stress ◽  
Anxiety Depression

Recently, there has been an increase in the production of devices to monitor mental health and stress as means for expediting detection, and subsequent management of these conditions. The objective of this review is to identify and critically appraise the most recent smart devices and wearable technologies used to identify depression, anxiety, and stress, and the physiological process(es) linked to their detection. The MEDLINE, CINAHL, Cochrane Central, and PsycINFO databases were used to identify studies which utilised smart devices and wearable technologies to detect or monitor anxiety, depression, or stress. The included articles that assessed stress and anxiety unanimously used heart rate variability (HRV) parameters for detection of anxiety and stress, with the latter better detected by HRV and electroencephalogram (EGG) together. Electrodermal activity was used in recent studies, with high accuracy for stress detection; however, with questionable reliability. Depression was found to be largely detected using specific EEG signatures; however, devices detecting depression using EEG are not currently available on the market. This systematic review highlights that average heart rate used by many commercially available smart devices is not as accurate in the detection of stress and anxiety compared with heart rate variability, electrodermal activity, and possibly respiratory rate.

DIAGNOSTICS OF THE ISCHEMIC HEART DISEASE WITH THE USE OF HEART RATE VARIABILITY AND DISPERSION MAPPING OF THE MYOCARDIUM DURING STRESS-ECHOCARDIOGRAPHY

2021 ◽  
Vol 55 (5) ◽  
pp. 53-58
Author(s):  
S.V. Zhuravlev ◽  
◽  
V.N. Ardashev ◽  
E.M. Novikov ◽  
O.M. Maslennikova ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Heart Disease ◽  
Ischemic Heart Disease ◽  
Sensitivity And Specificity ◽  
Stress Echocardiography ◽  
Ischemic Heart ◽  
Diagnostic Tools ◽  
Heart Rate Variability Analysis ◽  
Variability Analysis

The authors present a stress-echocardiography (stress-echoECG) technique enhanced with dispersion mapping and heart rate variability analysis. This combination of diagnostic tools increases IHD diagnostics sensitivity and specificity to 96 and 89 % respectively.

scholarly journals Analysis of heart rate variability in corn snakes (Pantherophis guttatus)

2021 ◽  
Vol 10 (11) ◽  
pp. e294101119781
Author(s):  
Antonio Gomes da Silva Neto ◽  
Daniel Souza Ferreira Magalhães ◽  
Raduan Hage ◽  
Laurita dos Santos ◽  
José Carlos Cogo
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Nervous System ◽  
Autonomic Nervous System ◽  
Low Frequency ◽  
Autonomic Nervous ◽  
Rr Interval ◽  
Diagnosis And Prognosis ◽  
Frequency Domains ◽  
The Time Domain

The assessment of heart rate variability (HRV) by linear methods in conjunction with Poincaré plots can be useful for evaluating cardiac regulation by the autonomic nervous system and for the diagnosis and prognosis of heart disease in snakes. In this report, we describe an analysis of HRV in conscious adult corn snakes Pantherophis guttatus (P. guttatus).  The electrocardiogram (ECG) parameters were determined in adult corn snakes (8 females, 13 males) and used for HRV analysis, and the RR interval was analyzed by linear methods in the time and frequency domains. There was no sex-related difference in heart rate. However, significant differences were seen in the duration of the P, PR, and T waves and QRS complex; there was no difference in the QT interval. The values for the RR interval varied by 15.3% and 18.8% in male and female snakes, respectively, and there was considerable variation in the values for the high and low frequency domains. The changes in the time domain were attributed to regulation by the parasympathetic branch of the autonomic nervous system, in agreement with variations in the high and low frequency domains. The values for standard deviations 1 and 2 in Poincaré plots, as well as the values of the frequency domain, provide useful parameters for future studies of cardiac function in P. guttatus.

Effect of fingolimod on cardiac autonomic regulation in patients with multiple sclerosis

2015 ◽  
Vol 22 (8) ◽  
pp. 1080-1085 ◽  
Author(s):  
Sakari Simula ◽  
Tomi Laitinen ◽  
Tiina M Laitinen ◽  
Tuula Tarkiainen ◽  
Päivi Hartikainen ◽  
...  
Keyword(s):  
Multiple Sclerosis ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
High Frequency ◽  
Frequency Ratio ◽  
Low Frequency ◽  
Autonomic Regulation ◽  
Rr Interval ◽  
Cardiac Autonomic Regulation ◽  
Multiple Sclerosis Patients

Background: Fingolimod modulates sphingosine-1-phosphate receptors that are also found in cardiovascular tissue. Objective: To investigate the effects of fingolimod on cardiac autonomic regulation prospectively. Methods: Twenty-seven relapsing–remitting multiple sclerosis patients underwent 24-hour electrocardiogram recording before, at the first day of fingolimod treatment (1d) and after three months of continuous dosing (3mo). The time interval between two consecutive R-peaks (RR-interval) was measured. Cardiac autonomic regulation was assessed by the various parameters of heart rate variability. Parasympathetic stimulation prolongs the RR-interval and increases heart rate variability while the effects of sympathetic stimulation are mainly the opposite. The low frequency/high frequency ratio reflects sympathovagal balance. Results: From baseline to 1d, a prolongation of the RR-interval ( P<0.001), an increase in the values of various heart rate variability parameters ( P<0.05 to P<0.001) and a decrease in the low frequency/high frequency ratio ( P<0.05) were demonstrated. At 3mo, although the RR-interval remained longer ( P<0.01), the values of various heart rate variability parameters were lower ( P<0.01 to P<0.001) as compared to baseline. At 3mo, the low frequency/high frequency ratio ( P<0.05) was higher in men than in women although no such difference was found at baseline or at 1d. Conclusions: After an initial increase in parasympathetic regulation, continuous fingolimod dosing shifts cardiac autonomic regulation towards sympathetic predominance, especially in men. Careful follow-up of fingolimod-treated relapsing–remitting multiple sclerosis patients is warranted as sympathetic predominance associates generally with impaired outcome. ClinicalTrials.cov: NCT01704183

scholarly journals Binary symbolic dynamics analysis to detect stress-associated changes of nonstationary heart rate variability

2020 ◽  
Vol 10 (1) ◽  
Author(s):  
Conrad Spellenberg ◽  
Peter Heusser ◽  
Arndt Büssing ◽  
Andreas Savelsbergh ◽  
Dirk Cysarz
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Psychological Stress ◽  
Symbolic Dynamics ◽  
Acute Stress ◽  
Stress Test ◽  
Autonomic Regulation ◽  
Rr Interval ◽  
Cardiac Autonomic Regulation ◽  
Acute Psychological Stress

Abstract Psychological stress may have harmful physiological effects and result in deteriorating health. Acute psychological stress acts also on cardiac autonomic regulation and may lead to nonstationarities in the interbeat interval series. We address the requirement of stationary RR interval series to calculate frequency domain parameters of heart rate variability (HRV) and use binary symbolic dynamics derived from RR interval differences to overcome this obstacle. 24 healthy subjects (12 female, 20–35 years) completed the following procedure: waiting period, Trier Social Stress Test to induce acute psychological stress, recovery period. An electrocardiogram was recorded throughout the procedure and HRV parameters were calculated for nine 5-min periods. Nonstationarities in RR interval series were present in all periods. During acute stress the average RR interval and SDNN decreased compared to rest before and after the stress test. Neither low frequency oscillations (LF), high frequency oscillations (HF) nor LF/HF could unambiguously reflect changes during acute stress in comparison to rest. Pattern categories derived from binary symbolic dynamics clearly identified acute stress and accompanying alterations of cardiac autonomic regulation. Methods based on RR interval differences like binary symbolic dynamics should be preferred to overcome issues related to nonstationarities.

scholarly journals The Use of Percent Change in RR Interval for Data Exclusion in Analyzing 24-h Time Domain Heart Rate Variability in Rodents

2019 ◽  
Vol 10 ◽  
Author(s):  
Emma Karey ◽  
Shiyue Pan ◽  
Amber N. Morris ◽  
Donald A. Bruun ◽  
Pamela J. Lein ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Time Domain ◽  
Rr Interval ◽  
Percent Change
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