Pulse‑Fi Turns Home Wi‑Fi into a Contactless Heart Rate Monitor, UCSC Researchers Say
UCSC researchers have created Pulse‑Fi, a low‑cost system that uses ordinary Wi‑Fi and machine learning to detect heartbeats without contact or wearables, delivering clinical‑level accuracy and promising scalable, affordable home and remote monitoring in trials for care.
- Pulse‑Fi uses ordinary Wi‑Fi hardware and low‑cost boards like ESP32 or Raspberry Pi to sense heartbeat‑induced RF changes (UCSC News).
- Machine learning filters noise to isolate faint heartbeat signatures and reaches clinical‑level accuracy in controlled tests (UCSC News; ZME Science).
- Low cost and scalable — core hardware can cost as little as $5–$30, enabling broad home and clinic deployment (Tom’s Hardware).
- Privacy, regulation, and further trials required before commercial use; deployments must address consent, data security, and accuracy across environments (UCSC News).
Overview
Researchers at the University of California, Santa Cruz’s Baskin School of Engineering developed Pulse‑Fi, a contactless heart‑rate monitoring system that interprets tiny variations in Wi‑Fi radio frequency (RF) waves caused by cardiac motion. The team presented their proof of concept at the 2025 IEEE DCOSS‑IoT conference and documented results showing clinical‑level accuracy in initial tests (UCSC News).
How Pulse‑Fi works
Pulse‑Fi senses the subtle changes in Wi‑Fi wave patterns that occur when radio waves pass through or reflect off the human body. The heartbeat produces minute motion that modulates those waves. Using off‑the‑shelf components — such as ESP32 chips and Raspberry Pi devices — the system collects RF data and pairs it with ground truth pulse oximeter readings to train machine learning models to recognize heartbeat signatures.
“The key innovation is smarter signal processing: ML models learn to find very faint heartbeat signatures in real home environments,” the team reports (UCSC News).
Training and noise filtering
To teach Pulse‑Fi what a heartbeat looks like in Wi‑Fi data, researchers recorded Wi‑Fi signals while simultaneously measuring heart rates with a pulse oximeter. They then trained models to:
– Isolate periodic heartbeat signatures
– Suppress noncardiac motion and room noise
– Maintain performance when subjects shift position
Performance and accuracy
Controlled tests indicate Pulse‑Fi reports heart rate within about 0.5 beats per minute after ~5 seconds of tracking, with accuracy improving over longer windows. The system remained robust with subject movement within a roughly 10‑foot radius — a notable improvement over earlier wireless monitoring attempts (Tom’s Hardware; UCSC News).
Cost and scalability
One major advantage is affordability. Core hardware can cost as little as $5–$10 for ESP32 boards and about $30 for a Raspberry Pi, far below many commercial wearables and clinical room sensors. Because Pulse‑Fi uses common Wi‑Fi components, it could be deployed widely in homes, clinics, and community centers at low cost (Tom’s Hardware).
Scientific and medical implications
Pulse‑Fi could expand contactless monitoring where wearables are impractical — for older adults, people with sensitive skin, or patients receiving home hospice care. The approach may also be extendable to other vitals such as respiratory rate and sleep‑related breathing events, though those applications are early and require additional validation (UCSC News; Earth.com).
Technical innovation
The innovation lies mainly in signal processing and machine learning. Rather than requiring specialized radios, Pulse‑Fi uses ordinary Wi‑Fi hardware and trains models to find heartbeat patterns amid household noise. That moves the method beyond lab demos that required immobility toward real‑world feasibility.
Limitations and open questions
Pulse‑Fi is a research prototype. The team notes several caveats:
- Results may vary with building materials, multi‑person rooms, and RF interference from other devices.
- Larger clinical trials are needed to verify accuracy across ages, body types, and health conditions.
- Performance in diverse real‑world home layouts remains under study (UCSC News).
Commercialization and deployment
The UCSC team is exploring software packaging, regulatory pathways, and partnerships to scale Pulse‑Fi beyond the lab. As of October 2025, Pulse‑Fi remains a research project and is not yet a commercial product (UCSC News).
Privacy and security concerns
Contactless heart tracking raises privacy and legal issues. If ordinary Wi‑Fi can measure heart rate without contact, deployments must consider consent, data use, and potential surveillance risks. Health data protections like HIPAA apply to covered entities, but many home devices and networks fall into gray areas. Real‑world use will require strong safeguards, transparent consent, and secure handling of sensitive data (UCSC News; ZME Science).
Who built Pulse‑Fi
The project was led by Professor Katia Obraczka with Ph.D. student Nayan Bhatia and visiting high school researcher Pranay Kocheta at UCSC’s Baskin School of Engineering. Their paper was presented at the 2025 IEEE DCOSS‑IoT conference (UCSC News).
Implications for Los Angeles, California
Pulse‑Fi could have multiple regional effects in Los Angeles:
- Economic impact: LA’s health‑tech and maker community could adopt low‑cost kits and services integrating Pulse‑Fi ideas into telehealth platforms.
- Health services: Hospitals and outpatient clinics might use contactless monitoring to support home‑based care and reduce readmissions.
- Vulnerable populations: Senior centers, shelters, and community clinics could benefit from non‑wearable screening options, but deployments must emphasize consent and privacy.
- Practical constraints: Dense apartment RF interference, varied construction, and multi‑person rooms could affect accuracy, making local pilot studies essential.
Sources and further reading
Full sources and reporting:
