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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Altered heart rate variability during sleep in mild cognitive impairment
Shawn D.X. Kong,Camilla M. Hoyos,Craig L. Phillips,Andrew C. McKinnon,Pinghsiu Lin,Shantel L. Duffy,Loren Mowszowski,Haley M LaMonica,Haley M LaMonica,Ronald R. Grunstein,Sharon L. Naismith,Christopher J. Gordon,Christopher J. Gordon,Christopher J. Gordon +13 more
TL;DR: Amnestic MCI participants had greater reductions in HF-HRV during NREM sleep, relative to those with SCI, suggesting potential vulnerability to sleep-related parasympathetic dysfunction.
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Enhancing the Robustness of Smartphone Photoplethysmography: A Signal Quality Index Approach
TL;DR: This study aimed to bridge the gap in the literature by developing a novel smartphone PPG quality index (SPQI) that can filter corrupted data and support not only the proposed approach but also the general value of using smartphones PPG in HRV analysis.
Journal ArticleDOI
RR-APET - Heart rate variability analysis software.
TL;DR: The aim of this work is to provide a comprehensive open-source package that offers considerable graphical signal editing features, flexibility within the algorithms used for R-peak detection and HRV quantification, and includes graphical functionality for batch processing, providing a platform suited to either physician or researcher.
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Automated Affective Computing Based on Bio-Signals Analysis and Deep Learning Approach
Chiara Filippini,Adolfo Di Crosta,Rocco Palumbo,David Perpetuini,Daniela Cardone,Irene Ceccato,Alberto Di Domenico,Arcangelo Merla +7 more
TL;DR: The developed DL model is able to classify the emotional state into four classes, derived from the linear combination of valence and arousal, with an overall accuracy of 70% outperforming the 66% accuracy reached by the RF model.
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Color-dependent changes in humans during a verbal fluency task under colored light exposure assessed by SPA-fNIRS.
TL;DR: In this article, the authors investigated how colored light exposure (CLE) and a verbal fluency task (VFT) interact and affect cerebral hemodynamics, oxygenation, and systemic physiology as determined by systemic physiology augmented functional near-infrared spectroscopy (SPA-fNIRS).
References
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