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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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Pecchia, Leandro, Castaldo, Rossana, Montesinos-Silva, Luis and Melillo, Paolo (2018) Are ultra-short heart rate variability features good surrogates of short-term ones? State-of-the-art review and recommendations. Healthcare Technology Letters, 5 (3). pp. 94-100. doi:10.1049/htl.2017.0090 ISSN 2053-3713 .
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Official URL: https://doi.org/10.1049/htl.2017.0090
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.
Item Type: | Journal Article | ||||||
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Subjects: | Q Science > QP Physiology | ||||||
Divisions: | Faculty of Science, Engineering and Medicine > Engineering > Engineering | ||||||
Library of Congress Subject Headings (LCSH): | Heart rate monitoring, Patient monitoring, Algorithms | ||||||
Journal or Publication Title: | Healthcare Technology Letters | ||||||
Publisher: | The Institution of Engineering and Technology | ||||||
ISSN: | 2053-3713 | ||||||
Official Date: | June 2018 | ||||||
Dates: |
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Volume: | 5 | ||||||
Number: | 3 | ||||||
Page Range: | pp. 94-100 | ||||||
DOI: | 10.1049/htl.2017.0090 | ||||||
Status: | Peer Reviewed | ||||||
Publication Status: | Published | ||||||
Access rights to Published version: | Restricted or Subscription Access | ||||||
Date of first compliant deposit: | 2 August 2018 | ||||||
Date of first compliant Open Access: | 2 August 2018 | ||||||
Open Access Version: |
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