Multi-Person Breathing Detection With Switching Antenna Array Based on WiFi Signal
WiFi sensing, an emerging sensing technology, has been widely used in vital sign monitoring. However, most respiration monitoring studies have focused on single-person tasks. In this paper, we propose a multi-person breathing sensing system based on WiFi signals. Specifically, we use radio frequency (RF) switch to extend the antennas to form switching antenna array. A reference channel is introduced in the receiver, which is connected to the transmitter by cable and attenuator. The phase offset introduced by asynchronous transceiver devices can be eliminated by using the ratio of the channel frequency response (CFR) between the antenna array and the reference channel. In order to realize multi-person breathing perception, we use beamforming technology to conduct two-dimensional scanning of the whole scene. After eliminating static clutter, we combine frequency domain and angle of arrival (AOA) domain analysis to construct the AOA and frequency (AOA-FREQ) spectrogram. Finally, the respiratory frequency and position of each target are obtained by clustering. Experimental results show that the proposed system can not only estimate the direction and respiration rate of multi-person, but also monitor abnormal respiration in multi-person scenarios. The proposed low-cost, non-contact, rapid multi-person respiratory detection technology can meet the requirements of long-term home health monitoring..
| Medienart: |
E-Artikel |
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| Erscheinungsjahr: |
2023 |
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| Erschienen: |
2023 |
| Enthalten in: |
Zur Gesamtaufnahme - volume:11 |
|---|---|
| Enthalten in: |
IEEE Journal of Translational Engineering in Health and Medicine - 11(2023), Seite 23-31 |
| Sprache: |
Englisch |
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| Beteiligte Personen: |
Lei Guan [VerfasserIn] |
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| Links: |
doi.org [kostenfrei] |
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| Themen: |
Beamforming |
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| doi: |
10.1109/JTEHM.2022.3218638 |
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| funding: |
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| Förderinstitution / Projekttitel: |
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| PPN (Katalog-ID): |
DOAJ025694138 |
|---|
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| 520 | |a WiFi sensing, an emerging sensing technology, has been widely used in vital sign monitoring. However, most respiration monitoring studies have focused on single-person tasks. In this paper, we propose a multi-person breathing sensing system based on WiFi signals. Specifically, we use radio frequency (RF) switch to extend the antennas to form switching antenna array. A reference channel is introduced in the receiver, which is connected to the transmitter by cable and attenuator. The phase offset introduced by asynchronous transceiver devices can be eliminated by using the ratio of the channel frequency response (CFR) between the antenna array and the reference channel. In order to realize multi-person breathing perception, we use beamforming technology to conduct two-dimensional scanning of the whole scene. After eliminating static clutter, we combine frequency domain and angle of arrival (AOA) domain analysis to construct the AOA and frequency (AOA-FREQ) spectrogram. Finally, the respiratory frequency and position of each target are obtained by clustering. Experimental results show that the proposed system can not only estimate the direction and respiration rate of multi-person, but also monitor abnormal respiration in multi-person scenarios. The proposed low-cost, non-contact, rapid multi-person respiratory detection technology can meet the requirements of long-term home health monitoring. | ||
| 650 | 4 | |a Beamforming | |
| 650 | 4 | |a multi-person respiration sensing | |
| 650 | 4 | |a Wi-Fi sensing | |
| 653 | 0 | |a Computer applications to medicine. Medical informatics | |
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| 700 | 0 | |a Zhiya Zhang |e verfasserin |4 aut | |
| 700 | 0 | |a Xiaodong Yang |e verfasserin |4 aut | |
| 700 | 0 | |a Nan Zhao |e verfasserin |4 aut | |
| 700 | 0 | |a Dou Fan |e verfasserin |4 aut | |
| 700 | 0 | |a Muhammad Ali Imran |e verfasserin |4 aut | |
| 700 | 0 | |a Qammer H. Abbasi |e verfasserin |4 aut | |
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