Researchers at the University of California, Santa Cruz have developed a new system called Pulse-Fi that can track heart rates with clinical precision—using nothing more than standard WiFi signals. The breakthrough could pave the way for affordable, non-invasive health monitoring in homes and hospitals.
Instead of relying on wearable devices, Pulse-Fi detects the subtle disruptions in WiFi waves created by a person’s heartbeat. By applying machine learning, the system filters out interference caused by body movement or environmental factors, isolating the heartbeat signal with high accuracy.
In tests involving 118 participants, Pulse-Fi matched the performance of medical-grade monitors. Within just five seconds of measurement, it achieved an average error of only half a beat per minute. Remarkably, it worked across different scenarios—whether subjects were sitting, standing, lying down, or walking—and maintained accuracy at distances of up to 10 feet.
What sets Pulse-Fi apart is its affordability. The prototype was built using $5 ESP32 microchips and a $30 Raspberry Pi, making it vastly cheaper than most existing health-monitoring systems. Researchers believe its low cost and ease of deployment could make it particularly useful in resource-limited settings or for continuous remote monitoring of patients at home.
The team is already working on extending the system’s capabilities beyond heart rate. They hope to enable respiration monitoring, which could assist in detecting conditions such as sleep apnea or respiratory distress—both critical in long-term health management.
By turning something as common as WiFi into a contactless health tool, Pulse-Fi could reduce the need for constant wearable use, while providing clinicians and caregivers with reliable, real-time patient data. If further trials succeed, the technology may soon play a key role in the future of smart healthcare.
