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Related Experiment Video

Updated: Aug 18, 2025

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Effective Analysis of Human Exposure Conditions with Body-worn Dosimeters in the 2.4 GHz Band

Published on: May 2, 2018

Multi-Person Breathing Detection With Switching Antenna Array Based on WiFi Signal.

Lei Guan¹, Zhiya Zhang², Xiaodong Yang¹

¹Key Laboratory of High Speed Circuit Design and EMC, Ministry of Education, School of Electronic EngineeringXidian University Xi'an Shaanxi 710071 China.

IEEE Journal of Translational Engineering in Health and Medicine

|December 8, 2022

Summary

This study introduces a novel WiFi sensing system for multi-person respiration monitoring. The technology accurately detects respiratory rates and positions, enabling remote health surveillance.

Keywords:

Beamforming Wi-Fi sensing multi-person respiration sensing

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Last Updated: Aug 18, 2025

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Area of Science:

Wireless communication
Biomedical engineering
Signal processing

Background:

WiFi sensing is a growing technology for vital sign monitoring.
Existing respiration monitoring systems primarily focus on single individuals.
There is a need for non-contact, multi-person respiratory monitoring solutions.

Purpose of the Study:

To develop a WiFi-based system for simultaneous multi-person breathing sensing.
To enable accurate estimation of respiratory frequency and location for multiple individuals.
To provide a low-cost, non-contact solution for long-term health monitoring.

Main Methods:

Utilized a switching antenna array and a reference channel to eliminate phase offsets.
Employed beamforming for two-dimensional scene scanning.
Combined Angle of Arrival (AOA) and frequency domain analysis to create an AOA-FREQ spectrogram.
Applied clustering techniques to identify individual respiratory frequencies and positions.

Main Results:

Successfully estimated the direction and respiration rate of multiple individuals.
Demonstrated the capability to monitor abnormal respiration patterns in multi-person scenarios.
Validated the system's effectiveness in non-contact, multi-person respiratory detection.

Conclusions:

The proposed WiFi sensing system offers a low-cost, non-contact method for multi-person respiratory monitoring.
This technology can be applied to long-term home health monitoring, including the detection of abnormal breathing.
The system effectively addresses the limitations of single-person focused respiration monitoring.