Pulse-Fi technology enables heart rate measurement using only Wi-Fi signals without a wearable device
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Pulse-Fi: A Low-Cost System for Accurate Heart Rate Monitoring Using Wi-Fi Channel State Information | IEEE Conference Publication | IEEE Xplore
https://ieeexplore.ieee.org/abstract/document/11096342
WiFi signals can measure heart rate—no wearables needed - News
https://news.ucsc.edu/2025/09/pulse-fi-wifi-heart-rate/
Heart rate is one of the most basic and important indicators of health, providing clues about physical activity, stress, anxiety, dehydration, etc. Until now, measuring heart rate required some kind of wearable device, such as a smartwatch or hospital-grade equipment.
Now, a research team led by UC Santa Cruz computer science and engineering professor Katia Obraczka , doctoral student Nayan Bhatia , and high school student Pranay Kocheta, who joined the team through a science internship program, has developed a way to monitor heart rate using signals from home Wi-Fi devices without the need for a wearable device.
The technology, which the researchers call 'Pulse-Fi,' combines low-cost Wi-Fi devices with machine learning algorithms. Wi-Fi devices emit radio-frequency signals into the surrounding air, which are then transmitted to receiving devices like computers and smartphones. When the signals pass through objects in the air, some of the signals are absorbed by the objects, causing changes that can be mathematically detected.
Pulse-Fi uses Wi-Fi transmitters and receivers to perform signal processing and machine learning algorithms on the radio waves arriving at the receiver. The research team trained the machine learning algorithm to filter out all signal variations caused by environmental factors, movement, etc., allowing it to identify even the slightest signal fluctuations caused by a human heartbeat. 'Signals are very sensitive to the environment, so we need to choose the right filter to remove all the unwanted noise,' Bhatia said.
In the photo below, Professor Obraczka is on the left and doctoral student Bhatia is on the right.
The research team conducted experiments on 118 subjects and confirmed that processing signals from just five seconds was enough to measure heart rate with clinical-level accuracy. The five-second monitoring period showed an error of just 0.5 beats per minute, and the accuracy improved with longer monitoring times.
Pulse-Fi also measured heart rate regardless of the position of the device or the subject's posture, and the system worked whether the subject was sitting, standing, lying down, or walking.
These results were confirmed with both
The study also found that Pulse-Fi performed accurately even when subjects were 3 meters away from the hardware. Further experiments, in addition to those published in the study, showed promising results even at distances greater than 3 meters. 'Thanks to our machine learning model, we found that distance had almost no effect on performance, which was a major challenge with previous models,' Kocheta said.
The research team is working on further research to develop a technology that can detect not only heart rate but also breathing rate, which could potentially help detect conditions such as sleep apnea.
