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Signal Separation and Tracking Algorithm for Multi-Person Vital Signs by Using Doppler Radar
IEEE Transactions on Biomedical Circuits and Systems
|October 8, 2020
Summary
DeepMining, a novel single-antenna radar, accurately tracks multiple people's respiration and heartbeat rates. This Internet-of-Things technology overcomes limitations of existing vital sign monitoring systems.
Area of Science:
- Internet-of-Things (IoT)
- Radio-Frequency (RF) Sensing
- Biomedical Engineering
Background:
- Noninvasive monitoring of vital signs is crucial for healthcare.
- Current radio-frequency (RF) based systems often require complex antenna arrays or limited bandwidth radar.
- These limitations restrict the widespread application of RF vital sign detection.
Purpose of the Study:
- To introduce DeepMining, a novel system for simultaneous, noninvasive vital sign monitoring.
- To demonstrate the capability of a single-antenna, narrowband Doppler radar system for tracking multiple individuals.
- To overcome the size and bandwidth limitations of existing RF detection techniques.
Main Methods:
- Utilizing a single-antenna, narrowband Doppler radar system with a self-injection locking architecture.
- Employing frequency separation algorithms with successive signal cancellation for data extraction.
- Processing time-series signal observations to determine respiration and heartbeat rates.
Main Results:
- DeepMining accurately tracks respiration and heartbeat rates of multiple individuals simultaneously.
- Achieved 90% accuracy for two closely located persons and 85% for three.
- Demonstrated effectiveness even in scenarios with close proximity between subjects.
Conclusions:
- DeepMining offers a highly accurate and accessible solution for multi-person vital sign monitoring.
- The system's single-antenna and narrowband design overcomes key limitations of prior technologies.
- This advancement holds significant potential for Internet-of-Things (IoT) healthcare applications.
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