Open AccessAre ultra‐short heart rate variability features good surrogates of short‐term ones? State‐of‐the‐art review and recommendations
Author(s) -
Pecchia Leandro,
Castaldo Rossana,
Montesinos Luis,
Melillo Paolo
Publication year - 2018
Publication title -
healthcare technology letters
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.45
H-Index - 19
ISSN - 2053-3713
DOI - 10.1049/htl.2017.0090
Subject(s) - heart rate variability , reliability (semiconductor) , computer science , term (time) , protocol (science) , wearable computer , data science , artificial intelligence , medicine , heart rate , alternative medicine , embedded system , pathology , power (physics) , physics , quantum mechanics , blood pressure
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.