Scientists at the University of California, Santa Cruz, have developed a revolutionary method for monitoring heart rates. They refer to it as Pulse-Fi. Creating this pioneering technology is under the direction of Professor Katia Obraczka. By estimating heart rates using Wi-Fi signals, it offers numerous advantages compared to traditional methods. Pulse-Fi uses ESP32 microcontrollers to locate heartbeats with precision. By making touch-free monitoring possible, this technology has the potential to transform how we detect vital signs.
In a recent study, seven volunteers participated by simply sitting in a chair. They stood positioned at 1, 2, and 3 meters from two ESP32 microcontrollers operating with Pulse-Fi. The heart rate data collected from these devices was matched to heart rate measurements obtained with a pulse oximeter. Despite the considerable challenges, Pulse-Fi maintained an impressive 97% accuracy. This held true regardless of posture in the seated, walking, or upright conditions. The system even performed well at distances up to 10 feet from the recording device.
Pulse-Fi employs a sophisticated filtering technology. This proprietary technology greatly reduces background noise and allows detection of fluctuations in signal amplitude from beat to beat. With this unique combination of approaches, we enable the development of robust heart rate monitoring for virtually any environment and situation. Professor Obraczka emphasized the effectiveness of the technology, stating, “Pulse-Fi uses ordinary Wi-Fi signals to monitor your heartbeat without touching you. It records minor changes in the Wi-Fi signals waves, which are made by heart beats.
The technology’s versatility goes well beyond simple heart rate tracking. Today, Obraczka and her team are continuing to expand Pulse-Fi’s healthcare and wellness applications. They are perhaps most excited by its potential to keep tabs on sleep apnea and breathing rate. The system has proven in practice that it can succeed under different conditions. That’s a remarkable success, despite the fact that its underlying AI model wasn’t explicitly trained on such edge cases.
In a subsequent experiment, researchers deployed Pulse-Fi on Raspberry Pi devices. They randomly assigned heart rate targets to more than 100 participants and tracked their heart rates. These people completed a range of activities, including treadmill walking, running in place, more prolonged sitting, and prolonged standing. This multi-functionality creates amazing opportunities for Pulse-Fi. When utilized effectively, it can be an excellent resource for both self-management of health and within the clinical workflow.
The technology is incredibly cost-effective. Pulse-Fi uses readily available ESP32 chips, which typically go for $5 to $10 USD. In comparison, Raspberry Pis have an order of magnitude greater cost ($30 USD). This affordability can improve access and adoption among people who are looking for less invasive ways to monitor and improve their health.
That said, the existing use cases of Pulse-Fi have mostly targeted single-user settings. As the research continues, Obraczka noted that the team is working on expanding its capabilities to accommodate multiple users simultaneously. “In addition to working on multi-user environments, we are exploring other wellness and healthcare applications for Pulse-Fi,” she stated.
Although these recent innovations show a lot of potential, wearable devices still struggle with user comfort and adherence due to the intrusive nature of traditional heart rate monitoring. Obraczka highlighted this issue, saying, “Using wearables to monitor vitals can be uncomfortable, have weak adherence, and have limited accessibility due to cost.” Pulse-Fi’s non-contact approach is a major benefit.