Impact of Device Placement on Non-Contact Respiratory Monitoring Using Channel State Information

With the rapid development of wireless communication technology, health monitoring using commercial wireless devices has become a research hotspot. This paper proposes a contactless respiratory monitoring technology based on channel state information (CSI), which achieves flexible collection of wireless signals through a software defined radio (SDR) platform. A new respiratory frequency detection algorithm is developed using the differential threshold method (DTM), which reduced the complexity of the algorithm and improved the processing efficiency. This study systematically evaluates the impact of device location on signal quality and breath detection accuracy by changing the location of wireless devices in various experimental environments. Experimental results show that this technology can effectively monitor respiratory frequency and is highly robust to the specific placement of the device.

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Publication Details

Published
2024-09-21
DOI
https://doi.org/10.1109/icicsp62589.2024.10809096
Primary Topic
Bluetooth and Wireless Communication Technologies
Type
article
Field-Weighted Citation Impact
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Impact of Device Placement on Non-Contact Respiratory Monitoring Using Channel State Information

Bintao Hu, Haonan Hu, Yuan Gao, Yanliang Jin et al.
Bluetooth and Wireless Communication Technologies
article

Impact of Device Placement on Non-Contact Respiratory Monitoring Using Channel State Information

Bintao Hu, Haonan Hu, Yuan Gao, Yanliang Jin, Caijun Shao, Yanyi Wang
article en

Abstract

With the rapid development of wireless communication technology, health monitoring using commercial wireless devices has become a research hotspot. This paper proposes a contactless respiratory monitoring technology based on channel state information (CSI), which achieves flexible collection of wireless signals through a software defined radio (SDR) platform. A new respiratory frequency detection algorithm is developed using the differential threshold method (DTM), which reduced the complexity of the algorithm and improved the processing efficiency. This study systematically evaluates the impact of device location on signal quality and breath detection accuracy by changing the location of wireless devices in various experimental environments. Experimental results show that this technology can effectively monitor respiratory frequency and is highly robust to the specific placement of the device.

Shanghai University (CN), Xi’an Jiaotong-Liverpool University (CN), University of Sheffield (GB)
Openalex Percentile: Top 71%
Bluetooth and Wireless Communication Technologies
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