scholarly journals Decrease of heart rate variability during exercise: an index of cardiorespiratory fitness

2021 ◽  
Author(s):  
Denis Mongin ◽  
Clovis Chabert ◽  
Manuel Gomez Extremera ◽  
Olivier Hue ◽  
Delphine Sophie Courvoisier ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Cardiorespiratory Fitness ◽  
Equation Model ◽  
Time Interval ◽  
Portable Devices ◽  
Promising Tool ◽  
Exponential Decrease ◽  
Exponential Trend ◽  
Fitness Measures

The present study proposes to measure and quantify the heart rate variability (HRV) changes during effort and to test the capacity of the produced indices to predict cardiorespiratory fitness measures. Therefore, the beat-to-beat cardiac time interval series of 18 adolescent athletes (15.2 +- 2.0 years) measured during maximal graded effort test were detrended using a dynamical first-order differential equation model. Heart rate variability was then calculated as the standard deviation of the detrended RR intervals within successive windows of one minute. The variation of this measure of HRV during exercise is properly adjusted by an exponential decrease of the heart rate. The amplitude and the decay rate of this exponential trend are strongly associated with maximum oxygen consumption, maximal aerobic power, and ventilatory thresholds. It indicates that among athletes with better fitness, HRV has higher values at low heart rate and decreases faster when the heart rate increases during exercise. This analysis, based only on cardiac measurements, provides a promising tool for the study of cardiac measurements generated by portable devices.

The Accuracy of Acquiring Heart Rate Variability from Portable Devices: A Systematic Review and Meta-Analysis

2019 ◽  
Vol 49 (3) ◽  
pp. 417-435 ◽  
Author(s):  
Ward C. Dobbs ◽  
Michael V. Fedewa ◽  
Hayley V. MacDonald ◽  
Clifton J. Holmes ◽  
Zackary S. Cicone ◽  
...  
Keyword(s):  
Systematic Review ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Meta Analysis ◽  
Portable Devices

scholarly journals Behavioral Modification Enhances the Benefits from Structured Aerobic and Resistance Training

2019 ◽  
Vol 03 (02) ◽  
pp. E48-E57 ◽  
Author(s):  
Brett A. Dolezal ◽  
David M. Boland ◽  
Eric V. Neufeld ◽  
Jennifer L. Martin ◽  
Christopher B. Cooper
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Body Composition ◽  
Resistance Training ◽  
Aerobic Performance ◽  
Behavioral Modification ◽  
Lower Body ◽  
Fitness Measures ◽  
Lower Body Power

AbstractBehavioral modification (BM) is a strategy designed to sustain or restore well-being through effects such as enhanced relaxation, reduced stress, and improved sleep. Few studies have explored the role of BM delivered in the context of fitness programs for healthy adults. Thus, the purpose of this investigation was to examine whether BM combined with aerobic and resistance training programs would improve health and fitness measures more than the exercise training alone. Thirty-two healthy fitness club members (19 men) were randomized to receive a BM program (n=15) or an equal-attention (EA) control (n=17). BM consisted of twelve, 10-min education sessions between a trained fitness professional and the participant, coupled with weekly, individualized relaxation, stress reduction, and sleep improvement assignments. All participants engaged in 1 h of coached resistance training and remotely guided aerobic exercise thrice weekly for 12 weeks. Fitness measures (aerobic performance, body composition, muscle strength and endurance, lower-body power), sleep characteristics, and heart rate variability (HRV) were obtained at baseline and after the 12-week program. BM resulted in greater improvements in aerobic performance (increased maximum oxygen uptake, metabolic (lactate) threshold, and percent of maximum oxygen uptake at which metabolic threshold occurred), peak and average lower-body power, and body composition (decreased body fat percentage and fat mass) compared to EA. BM also positively influenced parasympathetic tone through increased High-frequency HRV. BM resulted in greater improvements in fitness measures, body composition, and heart rate variability compared with EA. These findings have intriguing implications regarding the role of BM in augmenting health and physical performance.

scholarly journals Heart rate variability: Measurement and emerging use in critical care medicine

2019 ◽  
Vol 21 (2) ◽  
pp. 148-157 ◽  
Author(s):  
Brian W Johnston ◽  
Richard Barrett-Jolley ◽  
Anton Krige ◽  
Ingeborg D Welters
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Intensive Care ◽  
Sinus Node ◽  
Heart Rate Variability Analysis ◽  
Time Interval ◽  
Physiological Basis ◽  
Disease States ◽  
Organ Systems ◽  
Heart Rate Variability Measurement

Variation in the time interval between consecutive R wave peaks of the QRS complex has long been recognised. Measurement of this RR interval is used to derive heart rate variability. Heart rate variability is thought to reflect modulation of automaticity of the sinus node by the sympathetic and parasympathetic components of the autonomic nervous system. The clinical application of heart rate variability in determining prognosis post myocardial infarction and the risk of sudden cardiac death is well recognised. More recently, analysis of heart rate variability has found utility in predicting foetal deterioration, deterioration due to sepsis and impending multiorgan dysfunction syndrome in critically unwell adults. Moreover, reductions in heart rate variability have been associated with increased mortality in patients admitted to the intensive care unit. It is hypothesised that heart rate variability reflects and quantifies the neural regulation of organ systems such as the cardiovascular and respiratory systems. In disease states, it is thought that there is an ‘uncoupling’ of organ systems, leading to alterations in ‘inter-organ communication’ and a clinically detectable reduction in heart rate variability. Despite the increasing evidence of the utility of measuring heart rate variability, there remains debate as to the methodology that best represents clinically relevant outcomes. With continuing advances in technology, our understanding of the physiology responsible for heart rate variability evolves. In this article, we review the current understanding of the physiological basis of heart rate variability and the methods available for its measurement. Finally, we review the emerging use of heart rate variability analysis in intensive care medicine and conditions in which heart rate variability has shown promise as a potential physiomarker of disease.

scholarly journals Heart Rate Is a Better Predictor of Cardiorespiratory Fitness Than Heart Rate Variability in Overweight/Obese Children: The ActiveBrains Project

2019 ◽  
Vol 10 ◽  
Author(s):  
Abel Plaza-Florido ◽  
Jairo H. Migueles ◽  
Jose Mora-Gonzalez ◽  
Pablo Molina-Garcia ◽  
Maria Rodriguez-Ayllon ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Cardiorespiratory Fitness ◽  
Obese Children

scholarly journals Persistent homology as a new method of the assessment of heart rate variability

PLoS ONE ◽  
2021 ◽  
Vol 16 (7) ◽  
pp. e0253851
Author(s):  
Grzegorz Graff ◽  
Beata Graff ◽  
Paweł Pilarczyk ◽  
Grzegorz Jabłoński ◽  
Dariusz Gąsecki ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Data Analysis ◽  
Persistent Homology ◽  
Assessment Tools ◽  
Topological Data Analysis ◽  
Topological Descriptors ◽  
Time Interval ◽  
Analysis Tool ◽  
Frequency Domain Methods

Heart rate variability (hrv) is a physiological phenomenon of the variation in the length of the time interval between consecutive heartbeats. In many cases it could be an indicator of the development of pathological states. The classical approach to the analysis of hrv includes time domain methods and frequency domain methods. However, attempts are still being made to define new and more effective hrv assessment tools. Persistent homology is a novel data analysis tool developed in the recent decades that is rooted at algebraic topology. The Topological Data Analysis (TDA) approach focuses on examining the shape of the data in terms of connectedness and holes, and has recently proved to be very effective in various fields of research. In this paper we propose the use of persistent homology to the hrv analysis. We recall selected topological descriptors used in the literature and we introduce some new topological descriptors that reflect the specificity of hrv, and we discuss their relation to the standard hrv measures. In particular, we show that this novel approach provides a collection of indices that might be at least as useful as the classical parameters in differentiating between series of beat-to-beat intervals (RR-intervals) in healthy subjects and patients suffering from a stroke episode.

scholarly journals VARIABILITY OF ARTERIAL PRESSURE AT SHORT-TERM TIME INTERVALS

2019 ◽  
pp. 72-77
Author(s):  
S. M. Zakharov
Keyword(s):  
Blood Pressure ◽  
Heart Rate ◽  
Heart Rate Variability ◽  
Spectral Analysis ◽  
Arterial Pressure ◽  
Real Time ◽  
Time Interval ◽  
Short Term ◽  
Time Intervals ◽  
Short Time

The time and spectral analysis of blood pressure signals (BP of systolic, diastolic, pulse) obtained in real time and reflecting the work of the heart at short time intervals is presented. As a time interval, a sequence of one hundred cardiac cycles was chosen. The main parameters of variability are determined. The proposed method of analysis is an analogue of heart rate variability (HRV), based on the study of RR cardiointervals. Spectral analysis of blood pressure signals shows differences in the degree of orderliness or disorder of individual frequencies or the spectrum as a whole. The presented methodology will allow to reveal further features for use in the diagnosis of various pathologies.

scholarly journals Effects of Coexistence Hypertension and Type II Diabetes on Heart Rate Variability and Cardiorespiratory Fitness

2018 ◽  
Author(s):  
Daniela Bassi ◽  
Ramona Cabiddu ◽  
Renata G. Mendes ◽  
Natália Tossini ◽  
Vivian M. Arakelian ◽  
...  
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Cardiorespiratory Fitness ◽  
Type Ii Diabetes ◽  
Type Ii

Heart Rate Variability During a Simulated Assembly Task; Influence of Age and Gender

2017 ◽  
Vol 61 (1) ◽  
pp. 1853-1857 ◽  
Author(s):  
Angel M. Nardolillo ◽  
Amir Baghdadi ◽  
Lora A. Cavuoto
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Assembly Line ◽  
Age Groups ◽  
Time Interval ◽  
Prolonged Fatigue ◽  
And Gender ◽  
Assembly Tasks ◽  
The Relationship ◽  
Efficiency And Productivity

Attention has been concentrated on productivity in manufacturing settings with assembly line tasks being a common area of focus. Prolonged fatigue can occur during various assembly tasks both cognitively and physically. This can place a damper on efficiency and productivity for workers in manufacturing. Intercession can subsequently take place centered on reducing excessive workload tasks to assure a worker’s mental and physical thresholds are not contravened. Fatigue can be better understood by a person’s physiologic measures specifically their heart rate. Heart rate variability (HRV) which consists of calculations taken from each heartbeat can objectively quantify human capacity levels and the onset of fatigue. This study considers HRV during an assembly line task and compares differences in cardiac parameters between younger and older participants. The results obtained from this study were used to better understand the pattern of fatigue during the task at each segmented time interval. The HRV outcomes exhibited an index for each interval which gave the ability to make improved task demand decisions within the assembly line task. Statistical differences between age groups were also prominent which gave notion that workplace tasks should consider age classification when designing work structures for employees. This study assessed the potential function of HRV during a simulated task by examining the autonomic responses of the heart. The relationship between the autonomic nervous system to HRV was examined.

scholarly journals Efficient methods for acute stress detection using heart rate variability data from Ambient Assisted Living sensors

2021 ◽  
Vol 20 (1) ◽  
Author(s):  
Benedek Szakonyi ◽  
István Vassányi ◽  
Edit Schumacher ◽  
István Kósa
Keyword(s):  
Heart Rate ◽  
Heart Rate Variability ◽  
Time Domain ◽  
Assisted Living ◽  
Acute Stress ◽  
Ambient Assisted Living ◽  
Portable Devices ◽  
Stress Detection ◽  
Non Linear ◽  
Variability Data

Abstract Background Using Ambient Assisted Living sensors to detect acute stress could help people mitigate the harmful effects of everyday stressful situations. This would help both the healthy and those affected more by sudden stressors, e.g., people with diabetes or heart conditions. The study aimed to develop a method for providing reliable stress detection based on heart rate variability features extracted from portable devices. Methods Features extracted from portable electrocardiogram sensor recordings were used for training various classification algorithms for stress detection purposes. Data were recorded in a clinical trial with 7 participants and two stressors, the Trier Social Stress Test and the Stroop colour word test, both validated by standardised questionnaires. Different heart rate variability feature sets (all, time-domain and non-linear only, frequency-domain only) were tested to investigate how classification performance is affected, in addition to various time window length setups and participant-wise training sessions. The accuracy and F1 score of the trained models were compared and analysed. Results The best results were achieved with models using time-domain and non-linear heart rate variability features with 5-min-long overlapping time windows, yielding 96.31% accuracy and 96.26% F1 score. Shorter overlapping windows had slightly lower performance, with 91.62–94.55% accuracy and 91.77–94.55% F1 score ranges. Non-overlapping window configurations were less effective, with both accuracy and F1 score below 88%. For participant-wise learning, average F1 scores of 99.47%, 98.93% and 96.1% were achieved for feature sets using all, time-domain and non-linear, and frequency-domain features, respectively. Conclusion The tested stress detector models based on heart rate variability data recorded by a single electrocardiogram sensor performed just as well as those published in the literature working with multiple sensors, or even better. This suggests that once portable devices such as smartwatches provide reliable hear rate variability recordings, efficient stress detection can be achieved without the need for additional physiological measurements.

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