ArticleJournal of medical systems2019
A New Algorithm to Reduce and Individualize HRV Recording Time.
Article in Journal of medical systems, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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Who cites it
4 citing papers in PubMed.
- The short-term effect of a myofascial protocol versus light touch applied to the cervical spine towards the prevention of balance disorders in the elderly: protocol of a randomised controlled trial.Chiropractic & manual therapies · 2022Article
- RMSSD Is More Sensitive to Artifacts Than Frequency-Domain Parameters: Implication in Athletes' Monitoring.Journal of sports science & medicine · 2022Article
- Better forbearance, lower depression: Evidence based on heart rate variability.Frontiers in psychology · 2022Article
- Applying Heart Rate Variability to Monitor Health and Performance in Tactical Personnel: A Narrative Review.International journal of environmental research and public health · 2021Review
Corrections and comments
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Authors and funding
2 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
The aim of the present work was to propose a Smartphone algorithm to analyze, in real time, the evolution of Heart Rate Variability (HRV) in order to individualize and reduce the recording time according to the specificities of each user. During HRV recording, a new RMSSD value is calculated each time a new RR is captured. The recording process stops once an acceptable stability of HRV is reached. This new method was tested on 3 groups of 15 subjects (cardiac patients, sedentary employees and national-level athletes) and compared with the gold standard method (5 min HRV recording time). The RMSSD indices provided by the short method and by the gold standard method (respectively 62.1 ± 43.7 ms vs. 62.7 ± 44.1 ms) showed no significant differences. In addition, a very strong correlation was observed between RMSSD values obtained by the 2 methods (n = 45; R = 0.998; p < 0.001). Routine duration of the new method was significantly shorter with a time-savings of 2 min (178 ± 51 s vs. 300 s; p < 0.05). This new algorithm seems to adapt perfectly to each subject, and it can detect the stability phase for HRV measurements during the recording process. Algorithm provides an adapted and personal routine duration that can evolve each day depending on parameters such as fatigue or stress level that are known to influence HRV. This solution can be easily implemented in a smartphone application and seems particularly suitable for performing daily HRV monitoring in field conditions.
Indexed as
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.