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

Healthcare Technology Letters

Luis Montesinos¹  Rossana Castaldo¹  Leandro Pecchia¹  Paolo Melillo² 

[1] School of Engineering, University of Warwick;Surgical and Dental Sciences of the Second University of Naples;

关键词: statistical analysis;    medical signal processing;    electrocardiography;    patient monitoring;    ultrashort heart rate variability features;    short-term heart rate variability features;    HRV;    healthcare applications;    health monitoring;    wearable sensors;    mobile phones;    smart watches;    statistical tests;   

DOI  :  10.1049/htl.2017.0090

来源: DOAJ

【 摘 要 】

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.

【 授权许可】

Unknown