Pulse‑Fi Turns Home Wi‑Fi into Contactless Heart Monitors — Could Your Router Track Your Pulse?
Researchers at UC Santa Cruz developed Pulse‑Fi, a system that turns everyday Wi‑Fi into a contactless heart‑rate monitor, detecting tiny chest movements via radio signals to measure pulse without wearables from about 10 feet away.
Key takeaways
- Pulse‑Fi from UC Santa Cruz uses consumer Wi‑Fi hardware to detect heartbeat‑caused changes in radio waves at distances up to about 10 feet (3 meters).
- Clinical‑level accuracy: the method can reach roughly 0.5 beats per minute error after five seconds of monitoring and improves with longer windows or higher‑quality hardware — reported by UC Santa Cruz and Tom’s Hardware.
- Low‑cost implementation: Pulse‑Fi works with inexpensive chips such as the ESP32 or a Raspberry Pi for higher fidelity captures using signal processing and machine learning.
How Pulse‑Fi reads a heartbeat from radio waves
Pulse‑Fi leverages the same radio waves sent by a home Wi‑Fi router. A beating heart produces tiny chest movements that subtly alter how radio waves reflect, scatter or pass around the body. Pulse‑Fi measures minute changes in signal strength and timing and applies mathematical models to extract a repeating heartbeat pattern from noisy data.
The research team says this can be performed with off‑the‑shelf Wi‑Fi chips and simple hardware placed within roughly 10 feet (3 meters) of a person, making the approach feasible for home use. See the UC Santa Cruz release at UC Santa Cruz Pulse‑Fi news release.
Technical building blocks
Two main components make Pulse‑Fi possible:
- Signal processing and machine learning: advanced filters and trained models remove household noise — fans, footsteps, pets — and isolate the heartbeat signature from other motion. The team trains models to recognize the repeating pattern produced by a pulse.
- Channel State Information (CSI): detailed Wi‑Fi amplitude and phase data across many subcarriers can be used to refine readings and improve robustness in cluttered home environments. Earlier peer‑reviewed work on CSI supports these methods (CSI study).
“Signal processing plus CSI enables the system to pick the best frequencies and channels to watch for heartbeat motion,” researchers write, highlighting how the methods combine.
Accuracy, cost and practical setup
Accuracy: The team reports clinical‑level performance — about 0.5 beats per minute error after five seconds of monitoring, with improvements for longer monitoring windows and higher‑quality receivers.
Cost and hardware: Demonstrations used low‑cost parts such as the ESP32 (≈$5–$10) and a Raspberry Pi (≈$30) for higher fidelity captures, which could make deployments inexpensive compared with many medical devices.
Who is behind the work
Pulse‑Fi was developed at the University of California, Santa Cruz, led by Professor Katia Obraczka and graduate researcher Nayan Bhatia. Related research groups include teams at ShanghaiTech University and the Chinese Academy of Sciences; the field builds on multiple CSI and machine‑learning studies (see the CSI study).
Potential uses and benefits
Researchers and advocates point to several promising applications:
- Passive monitoring for older adults who may not wear sensors or forget to charge wearables.
- Remote patient monitoring where frequent in‑person checks are difficult.
- Smart‑home integration: automatic alerts to caregivers if a resident’s heart rate becomes abnormal.
- Low‑cost public health deployments in communities with limited resources.
Investigative questions: privacy, regulation and reliability
Privacy concerns: If ordinary Wi‑Fi can read a heartbeat, key questions arise — who controls that data, how is consent obtained for passive monitoring, and are there surveillance risks? Experts emphasize the need for clear policies and technical safeguards before wide deployment (Environmental News Network report).
Technical limits: Performance can degrade with large movements, multiple people present, or complex home layouts. Pulse‑Fi is not a certified medical device; regulators will need to decide classification and approval if used for diagnosis or treatment.
Where the work stands in science
Wi‑Fi heart‑rate monitoring is part of a growing body of contactless sensing research presented at conferences and in peer‑reviewed journals. Pulse‑Fi and related projects were discussed at events such as the 2025 IEEE International Conference on Distributed Computing in Smart Systems and the Internet of Things. Researchers cite earlier CSI studies to support clinical‑grade measurements and are working to improve robustness in real homes (CSI study).
Implications for the Inland Empire, California
The Inland Empire (Riverside and San Bernardino counties) could see concrete effects from contactless Wi‑Fi health sensing:
- Economic impact: Low‑cost hardware and open research could lower barriers for local clinics, community health programs and startups to pilot remote monitoring projects using the Pulse‑Fi approach.
- Political and regulatory consequences: Local agencies should demand clear consent rules, HIPAA compliance, and transparent data controls if pilots proceed (ENN report).
- Social effects: Contactless monitoring could help homebound older adults or those who avoid wearables, but residents may worry about unannounced monitoring; community education and opt‑in programs will be essential.
- Cultural relevance: Multi‑generational households and essential workers in the region could benefit, but adoption requires culturally sensitive outreach and simple setups that respect privacy.
Practical applications include pilots by home health agencies, assisted living centers and telemedicine providers to track resting heart‑rate trends, flag concerning changes, or support virtual check‑ins without distributing wearables.
Local next steps
Community health leaders and county tech teams should consider small, well‑designed pilots that include privacy safeguards, clear consent, and technical validation across diverse home layouts. Partnerships with nearby universities, makerspaces and community clinics can help test the technology in real homes and build trust before broader use.
