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Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring
Wrist-based respiratory rate (RR) measurement during sleep faces accuracy limitations. This study aimed to assess the accuracy of the RR estimation function during sleep based on the severity of obstructive sleep apnea (OSA) using the Samsung Galaxy Watch (GW) series. These watches are equipped with...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2023
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536355/ https://www.ncbi.nlm.nih.gov/pubmed/37766031 http://dx.doi.org/10.3390/s23187976 |
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author | Jung, Hyunjun Kim, Dongyeop Choi, Jongmin Joo, Eun Yeon |
author_facet | Jung, Hyunjun Kim, Dongyeop Choi, Jongmin Joo, Eun Yeon |
author_sort | Jung, Hyunjun |
collection | PubMed |
description | Wrist-based respiratory rate (RR) measurement during sleep faces accuracy limitations. This study aimed to assess the accuracy of the RR estimation function during sleep based on the severity of obstructive sleep apnea (OSA) using the Samsung Galaxy Watch (GW) series. These watches are equipped with accelerometers and photoplethysmography sensors for RR estimation. A total of 195 participants visiting our sleep clinic underwent overnight polysomnography while wearing the GW, and the RR estimated by the GW was compared with the reference RR obtained from the nasal thermocouple. For all participants, the root mean squared error (RMSE) of the average overnight RR and continuous RR measurements were 1.13 bpm and 1.62 bpm, respectively, showing a small bias of 0.39 bpm and 0.37 bpm, respectively. The Bland–Altman plots indicated good agreement in the RR measurements for the normal, mild, and moderate OSA groups. In participants with normal-to-moderate OSA, both average overnight RR and continuous RR measurements achieved accuracy rates exceeding 90%. However, for patients with severe OSA, these accuracy rates decreased to 79.45% and 75.8%, respectively. The study demonstrates the GW’s ability to accurately estimate RR during sleep, even though accuracy may be compromised in patients with severe OSA. |
format | Online Article Text |
id | pubmed-10536355 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-105363552023-09-29 Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring Jung, Hyunjun Kim, Dongyeop Choi, Jongmin Joo, Eun Yeon Sensors (Basel) Article Wrist-based respiratory rate (RR) measurement during sleep faces accuracy limitations. This study aimed to assess the accuracy of the RR estimation function during sleep based on the severity of obstructive sleep apnea (OSA) using the Samsung Galaxy Watch (GW) series. These watches are equipped with accelerometers and photoplethysmography sensors for RR estimation. A total of 195 participants visiting our sleep clinic underwent overnight polysomnography while wearing the GW, and the RR estimated by the GW was compared with the reference RR obtained from the nasal thermocouple. For all participants, the root mean squared error (RMSE) of the average overnight RR and continuous RR measurements were 1.13 bpm and 1.62 bpm, respectively, showing a small bias of 0.39 bpm and 0.37 bpm, respectively. The Bland–Altman plots indicated good agreement in the RR measurements for the normal, mild, and moderate OSA groups. In participants with normal-to-moderate OSA, both average overnight RR and continuous RR measurements achieved accuracy rates exceeding 90%. However, for patients with severe OSA, these accuracy rates decreased to 79.45% and 75.8%, respectively. The study demonstrates the GW’s ability to accurately estimate RR during sleep, even though accuracy may be compromised in patients with severe OSA. MDPI 2023-09-19 /pmc/articles/PMC10536355/ /pubmed/37766031 http://dx.doi.org/10.3390/s23187976 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Jung, Hyunjun Kim, Dongyeop Choi, Jongmin Joo, Eun Yeon Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring |
title | Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring |
title_full | Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring |
title_fullStr | Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring |
title_full_unstemmed | Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring |
title_short | Validating a Consumer Smartwatch for Nocturnal Respiratory Rate Measurements in Sleep Monitoring |
title_sort | validating a consumer smartwatch for nocturnal respiratory rate measurements in sleep monitoring |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10536355/ https://www.ncbi.nlm.nih.gov/pubmed/37766031 http://dx.doi.org/10.3390/s23187976 |
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