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Noncontact assessment for fatigue based on heart rate variability using IR-UWB radar

Physical fatigue can be assessed using heart rate variability (HRV). We measured HRV at rest and in a fatigued state using impulse-radio ultra wideband (IR-UWB) radar in a noncontact fashion and compared the measurements with those obtained using electrocardiography (ECG) to assess the reliability a...

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Autores principales: Ahmed, Sarfaraz, Lee, Yonggu, Lim, Young-Hyo, Cho, Seok-Hyun, Park, Hyun-Kyung, Cho, Sung Ho
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392064/
https://www.ncbi.nlm.nih.gov/pubmed/35987815
http://dx.doi.org/10.1038/s41598-022-18498-w
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author Ahmed, Sarfaraz
Lee, Yonggu
Lim, Young-Hyo
Cho, Seok-Hyun
Park, Hyun-Kyung
Cho, Sung Ho
author_facet Ahmed, Sarfaraz
Lee, Yonggu
Lim, Young-Hyo
Cho, Seok-Hyun
Park, Hyun-Kyung
Cho, Sung Ho
author_sort Ahmed, Sarfaraz
collection PubMed
description Physical fatigue can be assessed using heart rate variability (HRV). We measured HRV at rest and in a fatigued state using impulse-radio ultra wideband (IR-UWB) radar in a noncontact fashion and compared the measurements with those obtained using electrocardiography (ECG) to assess the reliability and validity of the radar measurements. HRV was measured in 15 subjects using radar and ECG simultaneously before (rest for 10 min before exercise) and after a 20-min exercise session (fatigue level 1 for 0–9 min; fatigue level 2 for 10–19 min; recovery for ≥ 20 min after exercise). HRV was analysed in the frequency domain, including the low-frequency component (LF), high-frequency component (HF) and LF/HF ratio. The LF/HF ratio measured using radar highly agreed with that measured using ECG during rest (ICC = 0.807), fatigue-1 (ICC = 0.712), fatigue-2 (ICC = 0.741) and recovery (ICC = 0.764) in analyses using intraclass correlation coefficients (ICCs). The change pattern in the LH/HF ratios during the experiment was similar between radar and ECG. The subject’s body fat percentage was linearly associated with the time to recovery from physical fatigue (R(2) = 0.96, p < 0.001). Our results demonstrated that fatigue and rest states can be distinguished accurately based on HRV measurements using IR-UWB radar in a noncontact fashion.
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spelling pubmed-93920642022-08-22 Noncontact assessment for fatigue based on heart rate variability using IR-UWB radar Ahmed, Sarfaraz Lee, Yonggu Lim, Young-Hyo Cho, Seok-Hyun Park, Hyun-Kyung Cho, Sung Ho Sci Rep Article Physical fatigue can be assessed using heart rate variability (HRV). We measured HRV at rest and in a fatigued state using impulse-radio ultra wideband (IR-UWB) radar in a noncontact fashion and compared the measurements with those obtained using electrocardiography (ECG) to assess the reliability and validity of the radar measurements. HRV was measured in 15 subjects using radar and ECG simultaneously before (rest for 10 min before exercise) and after a 20-min exercise session (fatigue level 1 for 0–9 min; fatigue level 2 for 10–19 min; recovery for ≥ 20 min after exercise). HRV was analysed in the frequency domain, including the low-frequency component (LF), high-frequency component (HF) and LF/HF ratio. The LF/HF ratio measured using radar highly agreed with that measured using ECG during rest (ICC = 0.807), fatigue-1 (ICC = 0.712), fatigue-2 (ICC = 0.741) and recovery (ICC = 0.764) in analyses using intraclass correlation coefficients (ICCs). The change pattern in the LH/HF ratios during the experiment was similar between radar and ECG. The subject’s body fat percentage was linearly associated with the time to recovery from physical fatigue (R(2) = 0.96, p < 0.001). Our results demonstrated that fatigue and rest states can be distinguished accurately based on HRV measurements using IR-UWB radar in a noncontact fashion. Nature Publishing Group UK 2022-08-20 /pmc/articles/PMC9392064/ /pubmed/35987815 http://dx.doi.org/10.1038/s41598-022-18498-w Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) .
spellingShingle Article
Ahmed, Sarfaraz
Lee, Yonggu
Lim, Young-Hyo
Cho, Seok-Hyun
Park, Hyun-Kyung
Cho, Sung Ho
Noncontact assessment for fatigue based on heart rate variability using IR-UWB radar
title Noncontact assessment for fatigue based on heart rate variability using IR-UWB radar
title_full Noncontact assessment for fatigue based on heart rate variability using IR-UWB radar
title_fullStr Noncontact assessment for fatigue based on heart rate variability using IR-UWB radar
title_full_unstemmed Noncontact assessment for fatigue based on heart rate variability using IR-UWB radar
title_short Noncontact assessment for fatigue based on heart rate variability using IR-UWB radar
title_sort noncontact assessment for fatigue based on heart rate variability using ir-uwb radar
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9392064/
https://www.ncbi.nlm.nih.gov/pubmed/35987815
http://dx.doi.org/10.1038/s41598-022-18498-w
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