WiFi-Based Heart Rate Monitoring Achieves Clinical-Grade Accuracy with Low-Cost Hardware

Researchers at UC Santa Cruz have developed Pulse-Fi, a system using inexpensive WiFi devices and machine learning to accurately measure heart rate. This non-wearable technology achieves clinical-grade accuracy by analyzing subtle variations in WiFi signals caused by heartbeats. Testing with ESP32 chips (costing only $5-10) demonstrated accurate readings even from three meters away and across various body positions. Pulse-Fi promises a cost-effective solution for health monitoring, particularly in low-resource settings.