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Multi-Person Respiration Rate Estimation With Single Pair Of Transmit And Receive Antenna

Abstract

Human respiration rate (RR) estimation is essential for various health care applications, such as sleep apnea detection and chronic obstructive pulmonary disease early diagnose. Recently, radio frequency based RR estimation has achieved high accuracy for single-person RR detection. However, multi-person RR estimation is still the obstacle blocking the wide commercialization of RF sensing based RR solution. In this paper, a novel multi-person RR estimation algorithm that can overcome the frequency resolution limit is present. The proposed algorithm is not only analytically justified but also verified in a real test-bed involving commercial off-the-shelf WiFi devices. Extensive experiment results show a 98% accuracy in people-counting and a root mean square error (RMSE) of 0.13 breath per minute (bpm) on RR detection. To the best of our knowledge, this is the first WiFi sensing work that can detect different people who share the same RR by only using a single pair of transmit and receive antenna.

Author: Hao-Hsuan Chang, Vishnu Ratnam, Hao Chen, Junsu Choi, Charlie Jianzhong Zhang

Published: ICASSP 2024 - 2024 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

Date: Apr 14, 2024