NDLI: Are ultra-short heart rate variability features good surrogates of short-term ones? State-of-the-art review and recommendations

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Are ultra-short heart rate variability features good surrogates of short-term ones? State-of-the-art review and recommendations

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Are ultra-short heart rate variability features good surrogates of short-term ones? State-of-the-art review and recommendations

Content Provider	IET Digital Library
Author	Pecchia, Leandro Castaldo, Rossana Montesinos, Luis Melillo, Paolo
Abstract	Ultra-short heart rate variability (HRV) analysis refers to the study of HRV features in excerpts of length <5 min. Ultra-short HRV is widely growing in many healthcare applications for monitoring individual's health and well-being status, especially in combination with wearable sensors, mobile phones, and smart-watches. Long-term (nominally 24 h) and short-term (nominally 5 min) HRV features have been widely investigated, physiologically justified and clear guidelines for analysing HRV in 5 min or 24 h are available. Conversely, the reliability of ultra-short HRV features remains unclear and many investigations have adopted ultra-short HRV analysis without questioning its validity. This is partially due to the lack of accepted algorithms guiding investigators to systematically assess ultra-short HRV reliability. This Letter critically reviewed the existing literature, aiming to identify the most suitable algorithms, and harmonise them to suggest a standard protocol that scholars may use as a reference in future studies. The results of the literature review were surprising, because, among the 29 reviewed papers, only one paper used a rigorous method, whereas the others employed methods that were partially or completely unreliable due to the incorrect use of statistical tests. This Letter provides recommendations on how to assess ultra-short HRV features reliably and proposes an inclusive algorithm that summarises the state-of-the-art knowledge in this area.
Starting Page	94
Ending Page	100
Page Count	7
Volume Number	5
e-ISSN	20533713
Issue Number	Issue 3, Jun (2018)
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/htl/5/3
Alternate Webpage(s)	https://digital-library.theiet.org/content/journals/10.1049/htl.2017.0090
Journal	Healthcare Technology Letters
Publisher	The Institution of Engineering and Technology
Publisher Date	2018-03-14
Access Restriction	Open
Rights License	Creative Commons Attribution License (http://creativecommons.org/licenses/by/3.0/)
Subject Keyword	Bioelectric Signal Biology And Medical Computing Digital Signal Processing Electrical Activity in Neurophysiological Processes Electrocardiography Electrodiagnostics And Other Electrical Measurement Technique Health Monitoring Healthcare Application HRV Medical Signal Processing Mobile Phones Patient Monitoring Probability Theory Short-term Heart Rate Variability Feature Signal Processing And Detection Smart Watches Statistical Analysis Statistical Tests Statistics Stochastic Linearised SCUC Ultrashort Heart Rate Variability Feature Wearable Sonsor
Content Type	Text
Resource Type	Article

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