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Full Respiration Rate Monitoring Exploiting Doppler Information with Commodity Wi-Fi Devices

Respiration rate is an essential indicator of vital signs, which can demonstrate the physiological condition of the human body and provide clues to some diseases. Commercial Wi-Fi devices can provide a non-invasive, cost-effective and long-term respiration rate-monitoring scheme for home scenarios....

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Autores principales: Dou, Chendan, Huan, Hao
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157398/
https://www.ncbi.nlm.nih.gov/pubmed/34069847
http://dx.doi.org/10.3390/s21103505
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author Dou, Chendan
Huan, Hao
author_facet Dou, Chendan
Huan, Hao
author_sort Dou, Chendan
collection PubMed
description Respiration rate is an essential indicator of vital signs, which can demonstrate the physiological condition of the human body and provide clues to some diseases. Commercial Wi-Fi devices can provide a non-invasive, cost-effective and long-term respiration rate-monitoring scheme for home scenarios. However, previous studies show that the breathing depth and location may affect the detectability of respiratory signals. In this study, we leverage the variation of the Doppler spectral energy extracted from the channel state information (CSI) collected by Wi-Fi devices to track the chest displacement induced by respiration. First, the random phase is eliminated by phase-fitting method to obtain the complex CSI containing the Doppler shift. Then, the multipath decomposition of CSI is carried out to obtain the channel impulse response, which eliminates the interference phase of the time delay and retains the Doppler shift. The dynamic path units are also separate from the multipath, which overcomes the indoor multipath effect. Finally, we conduct a time–frequency analysis to dynamic units to accumulate Doppler spectral energy. Based on these ideas, we design a complete respiration rate-monitoring system to obtain the respiration rate by using the consistency between the Doppler energy change period and the respiratory cycle. We evaluate our system through extensive experiments in several typical home environments filled with multipath. Experimental results show that the errors of the three scenarios are approximate, the maximum error is less than 0.7 bpm, and the average errors are approximately 0.15 bpm. This result indicates that our scheme can achieve high precision respiration monitoring and has good anti-multipath ability compared with existing methods.
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spelling pubmed-81573982021-05-28 Full Respiration Rate Monitoring Exploiting Doppler Information with Commodity Wi-Fi Devices Dou, Chendan Huan, Hao Sensors (Basel) Article Respiration rate is an essential indicator of vital signs, which can demonstrate the physiological condition of the human body and provide clues to some diseases. Commercial Wi-Fi devices can provide a non-invasive, cost-effective and long-term respiration rate-monitoring scheme for home scenarios. However, previous studies show that the breathing depth and location may affect the detectability of respiratory signals. In this study, we leverage the variation of the Doppler spectral energy extracted from the channel state information (CSI) collected by Wi-Fi devices to track the chest displacement induced by respiration. First, the random phase is eliminated by phase-fitting method to obtain the complex CSI containing the Doppler shift. Then, the multipath decomposition of CSI is carried out to obtain the channel impulse response, which eliminates the interference phase of the time delay and retains the Doppler shift. The dynamic path units are also separate from the multipath, which overcomes the indoor multipath effect. Finally, we conduct a time–frequency analysis to dynamic units to accumulate Doppler spectral energy. Based on these ideas, we design a complete respiration rate-monitoring system to obtain the respiration rate by using the consistency between the Doppler energy change period and the respiratory cycle. We evaluate our system through extensive experiments in several typical home environments filled with multipath. Experimental results show that the errors of the three scenarios are approximate, the maximum error is less than 0.7 bpm, and the average errors are approximately 0.15 bpm. This result indicates that our scheme can achieve high precision respiration monitoring and has good anti-multipath ability compared with existing methods. MDPI 2021-05-18 /pmc/articles/PMC8157398/ /pubmed/34069847 http://dx.doi.org/10.3390/s21103505 Text en © 2021 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
Dou, Chendan
Huan, Hao
Full Respiration Rate Monitoring Exploiting Doppler Information with Commodity Wi-Fi Devices
title Full Respiration Rate Monitoring Exploiting Doppler Information with Commodity Wi-Fi Devices
title_full Full Respiration Rate Monitoring Exploiting Doppler Information with Commodity Wi-Fi Devices
title_fullStr Full Respiration Rate Monitoring Exploiting Doppler Information with Commodity Wi-Fi Devices
title_full_unstemmed Full Respiration Rate Monitoring Exploiting Doppler Information with Commodity Wi-Fi Devices
title_short Full Respiration Rate Monitoring Exploiting Doppler Information with Commodity Wi-Fi Devices
title_sort full respiration rate monitoring exploiting doppler information with commodity wi-fi devices
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8157398/
https://www.ncbi.nlm.nih.gov/pubmed/34069847
http://dx.doi.org/10.3390/s21103505
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