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Heart Rate Variability Duration: Expanding the Ability of Wearable Technology to Improve Outpatient Monitoring?
Heart rate variability (HRV) evaluates beat-to-beat interval (BBI) differences and is a suggested marker of the autonomic nervous system with diagnostic/monitoring capabilities in mental health; especially parasympathetic measures. The standard duration for short-term HRV analysis ranges from 24 h d...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2021
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8239131/ https://www.ncbi.nlm.nih.gov/pubmed/34211411 http://dx.doi.org/10.3389/fpsyt.2021.682553 |
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author | Sheridan, David C. Domingo, Karyssa N. Dehart, Ryan Baker, Steven D. |
author_facet | Sheridan, David C. Domingo, Karyssa N. Dehart, Ryan Baker, Steven D. |
author_sort | Sheridan, David C. |
collection | PubMed |
description | Heart rate variability (HRV) evaluates beat-to-beat interval (BBI) differences and is a suggested marker of the autonomic nervous system with diagnostic/monitoring capabilities in mental health; especially parasympathetic measures. The standard duration for short-term HRV analysis ranges from 24 h down to 5-min. However, wearable technology, mainly wrist devices, have large amounts of motion at times resulting in need for shorter duration of monitoring. The objective of this study was to evaluate the correlation between 1 and 5 min segments of continuous HRV data collected simultaneously on the same patient. Subjects wore a patch electrocardiograph (Cardea Solo, Inc.) over a 1–7 day period. For every consecutive hour the patch was worn, we selected a 5-min, artifact-free electrocardiogram segment. HRV metric calculation was performed to the entire 5-min segment and the first 1-min from this same 5-min segment. There were 492 h of electrocardiogram data collected allowing calculation of 492 5 min and 1 min segments. 1 min segments of data showed good correlation to 5 min segments in both time and frequency domains: root mean square of successive difference (RMSSD) (R = 0.92), high frequency component (HF) (R = 0.90), low frequency component (LF) (R = 0.71), and standard deviation of NN intervals (SDNN) (R = 0.63). Mental health research focused on parasympathetic HRV metrics, HF and RMSSD, may be accomplished through smaller time windows of recording, making wearable technology possible for monitoring. |
format | Online Article Text |
id | pubmed-8239131 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2021 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-82391312021-06-30 Heart Rate Variability Duration: Expanding the Ability of Wearable Technology to Improve Outpatient Monitoring? Sheridan, David C. Domingo, Karyssa N. Dehart, Ryan Baker, Steven D. Front Psychiatry Psychiatry Heart rate variability (HRV) evaluates beat-to-beat interval (BBI) differences and is a suggested marker of the autonomic nervous system with diagnostic/monitoring capabilities in mental health; especially parasympathetic measures. The standard duration for short-term HRV analysis ranges from 24 h down to 5-min. However, wearable technology, mainly wrist devices, have large amounts of motion at times resulting in need for shorter duration of monitoring. The objective of this study was to evaluate the correlation between 1 and 5 min segments of continuous HRV data collected simultaneously on the same patient. Subjects wore a patch electrocardiograph (Cardea Solo, Inc.) over a 1–7 day period. For every consecutive hour the patch was worn, we selected a 5-min, artifact-free electrocardiogram segment. HRV metric calculation was performed to the entire 5-min segment and the first 1-min from this same 5-min segment. There were 492 h of electrocardiogram data collected allowing calculation of 492 5 min and 1 min segments. 1 min segments of data showed good correlation to 5 min segments in both time and frequency domains: root mean square of successive difference (RMSSD) (R = 0.92), high frequency component (HF) (R = 0.90), low frequency component (LF) (R = 0.71), and standard deviation of NN intervals (SDNN) (R = 0.63). Mental health research focused on parasympathetic HRV metrics, HF and RMSSD, may be accomplished through smaller time windows of recording, making wearable technology possible for monitoring. Frontiers Media S.A. 2021-06-15 /pmc/articles/PMC8239131/ /pubmed/34211411 http://dx.doi.org/10.3389/fpsyt.2021.682553 Text en Copyright © 2021 Sheridan, Domingo, Dehart and Baker. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Psychiatry Sheridan, David C. Domingo, Karyssa N. Dehart, Ryan Baker, Steven D. Heart Rate Variability Duration: Expanding the Ability of Wearable Technology to Improve Outpatient Monitoring? |
title | Heart Rate Variability Duration: Expanding the Ability of Wearable Technology to Improve Outpatient Monitoring? |
title_full | Heart Rate Variability Duration: Expanding the Ability of Wearable Technology to Improve Outpatient Monitoring? |
title_fullStr | Heart Rate Variability Duration: Expanding the Ability of Wearable Technology to Improve Outpatient Monitoring? |
title_full_unstemmed | Heart Rate Variability Duration: Expanding the Ability of Wearable Technology to Improve Outpatient Monitoring? |
title_short | Heart Rate Variability Duration: Expanding the Ability of Wearable Technology to Improve Outpatient Monitoring? |
title_sort | heart rate variability duration: expanding the ability of wearable technology to improve outpatient monitoring? |
topic | Psychiatry |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8239131/ https://www.ncbi.nlm.nih.gov/pubmed/34211411 http://dx.doi.org/10.3389/fpsyt.2021.682553 |
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