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2 thoughts on “Can Heart Rate Be Detected Remotely?”
Engineers at UC Santa Cruz developed Pulse-Fi, a system using low-cost WiFi chips and machine learning to measure heart rate accurately without wearables. The technology detects subtle changes in WiFi signals caused by heartbeat-induced chest movements, filtering out noise from other motions. Tested on 118 participants in various positions and up to three meters away, Pulse-Fi achieved heart rate accuracy within half a beat per minute after only five seconds, comparable to hospital-grade monitors. This non-intrusive, affordable method could revolutionize health monitoring for elder care, sleep studies, and remote settings, though privacy and commercial use considerations remain.
Published in: 2025 IEEE International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). DOI: 10.1109/DCOSS-IoT65416.2025.00037
From 2017: New AI algorithm monitors sleep with radio waves — Researchers at MIT and Massachusetts General Hospital have developed a non-invasive sleep monitoring system that uses an advanced artificial intelligence algorithm to analyze radio signals reflecting off a sleeping personâs body. This device accurately detects sleep stagesâlight, deep, and REMâwithout needing physical sensors attached to the body, unlike traditional sleep studies that can disrupt sleep with electrodes. Tested on healthy volunteers, the system achieved about 80% accuracy, comparable to expert human analysis of EEG data. This technology promises easier, continuous, and more comfortable sleep monitoring at home, potentially aiding diagnosis and study of sleep disorders like apnea, insomnia, and neurodegenerative diseases.
Engineers at UC Santa Cruz developed Pulse-Fi, a system using low-cost WiFi chips and machine learning to measure heart rate accurately without wearables. The technology detects subtle changes in WiFi signals caused by heartbeat-induced chest movements, filtering out noise from other motions. Tested on 118 participants in various positions and up to three meters away, Pulse-Fi achieved heart rate accuracy within half a beat per minute after only five seconds, comparable to hospital-grade monitors. This non-intrusive, affordable method could revolutionize health monitoring for elder care, sleep studies, and remote settings, though privacy and commercial use considerations remain.
Published in: 2025 IEEE International Conference on Distributed Computing in Smart Systems and the Internet of Things (DCOSS-IoT). DOI: 10.1109/DCOSS-IoT65416.2025.00037
From 2017: New AI algorithm monitors sleep with radio waves — Researchers at MIT and Massachusetts General Hospital have developed a non-invasive sleep monitoring system that uses an advanced artificial intelligence algorithm to analyze radio signals reflecting off a sleeping personâs body. This device accurately detects sleep stagesâlight, deep, and REMâwithout needing physical sensors attached to the body, unlike traditional sleep studies that can disrupt sleep with electrodes. Tested on healthy volunteers, the system achieved about 80% accuracy, comparable to expert human analysis of EEG data. This technology promises easier, continuous, and more comfortable sleep monitoring at home, potentially aiding diagnosis and study of sleep disorders like apnea, insomnia, and neurodegenerative diseases.