Are ultra-short heart rate variability features good surrogates of short-term ones? State-of-the-art review and recommendations
- Author(s): Leandro Pecchia 1 ; Rossana Castaldo 1 ; Luis Montesinos 1 ; Paolo Melillo 2
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View affiliations
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Affiliations:
1:
School of Engineering, University of Warwick , Coventry, CV4 7AL , UK ;
2: The Multidisciplinary Department of Medical , Surgical and Dental Sciences of the Second University of Naples , Naples, 80131 , Italy
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Affiliations:
1:
School of Engineering, University of Warwick , Coventry, CV4 7AL , UK ;
- Source:
Volume 5, Issue 3,
June
2018,
p.
94 – 100
DOI: 10.1049/htl.2017.0090 , Online ISSN 2053-3713
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.
Inspec keywords: medical signal processing; electrocardiography; patient monitoring; statistical analysis
Other keywords: statistical tests; ultrashort heart rate variability features; healthcare applications; smart watches; short-term heart rate variability features; HRV; health monitoring; mobile phones; wearable sensors
Subjects: Probability theory, stochastic processes, and statistics; Digital signal processing; Electrodiagnostics and other electrical measurement techniques; Biology and medical computing; Other topics in statistics; Electrical activity in neurophysiological processes; Other topics in statistics; Bioelectric signals; Signal processing and detection
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