An Overview of Heart Rate Variability Metrics and Norms.
Fred Shaffer,Jay P. Ginsberg +1 more
TLDR
Current perspectives on the mechanisms that generate 24 h, short-term (<5 min), and ultra-short-term HRV are reviewed, and the importance of HRV, and its implications for health and performance are reviewed.Abstract:
Healthy biological systems exhibit complex patterns of variability that can be described by mathematical chaos. Heart rate variability (HRV) consists of changes in the time intervals between consecutive heartbeats called interbeat intervals (IBIs). A healthy heart is not a metronome. The oscillations of a healthy heart are complex and constantly changing, which allow the cardiovascular system to rapidly adjust to sudden physical and psychological challenges to homeostasis. This article briefly reviews current perspectives on the mechanisms that generate 24 h, short-term (~5 min), and ultra-short-term (<5 min) HRV, the importance of HRV, and its implications for health and performance. The authors provide an overview of widely-used HRV time-domain, frequency-domain, and non-linear metrics. Time-domain indices quantify the amount of HRV observed during monitoring periods that may range from ~2 min to 24 h. Frequency-domain values calculate the absolute or relative amount of signal energy within component bands. Non-linear measurements quantify the unpredictability and complexity of a series of IBIs. The authors survey published normative values for clinical, healthy, and optimal performance populations. They stress the importance of measurement context, including recording period length, subject age, and sex, on baseline HRV values. They caution that 24 h, short-term, and ultra-short-term normative values are not interchangeable. They encourage professionals to supplement published norms with findings from their own specialized populations. Finally, the authors provide an overview of HRV assessment strategies for clinical and optimal performance interventions.read more
Citations
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Journal ArticleDOI
Multiscale Information Decomposition Dissects Control Mechanisms of Heart Rate Variability at Rest and During Physiological Stress.
Jana Krohova,Luca Faes,Barbora Czippelova,Zuzana Turianikova,Nikoleta Mazgutova,Riccardo Pernice,Alessandro Busacca,Daniele Marinazzo,Sebastiano Stramaglia,Michal Javorka +9 more
TL;DR: Fast HRV oscillations—respiratory sinus arrhythmia—originate from the coexistence of baroreflex and nonbaroreflex mechanisms at rest, with a stronger barore Flex involvement during HUT, and the barore flex origin is dominant and MA leads to its higher involvement.
Journal ArticleDOI
The Design of CNN Architectures for Optimal Six Basic Emotion Classification Using Multiple Physiological Signals.
TL;DR: A dominant factor influencing the accuracy was found by comparing the relativeness of the parameters, providing a basis for supporting the results of emotion classification.
Proceedings ArticleDOI
Evaluating the accuracy of heart rate sensors based on photoplethysmography for in-the-wild analysis
TL;DR: The study indicates that armband-based devices are more reliable than wrist-based wearables for HRV assessment and shows that PPG is a valid proxy for both HR and standard time- and frequency-domain measurements of HRV.
Journal ArticleDOI
Early Detection of Late Onset Sepsis in Premature Infants Using Visibility Graph Analysis of Heart Rate Variability
TL;DR: Results demonstrate the usefulness of introducing visibility graph indexes in HRV analysis for sepsis prediction in newborns and proposed the possibility of non-invasive, real-time monitoring of risk of LOS in a NICU setting.
Journal ArticleDOI
Heart Rate Variability Analysis on Electrocardiograms, Seismocardiograms and Gyrocardiograms on Healthy Volunteers.
TL;DR: Strong correlation of HRV indices computed on ECG and GCG signals than onECG and SCG signals is confirmed because of greater tolerance to inter-subject variability and disturbances and encourage using SCG or GCG for HRV estimation.
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