EchoHealth: Non-Contact Rehabilitation Exercises via Active Acoustic Sensing
Chao Liu, Hao Chen, Jingyang Hu, Qibo Zhang, Siyu Chen, Hongbo Jiang, Penghao Wang · 2025
With the aging population, there is an increasing demand for rehabilitation services for people with chronic diseases. However, limitations such as medical resources, geographic barriers, and cost make home rehabilitation an option for more patients. Existing wearable devices and vision methods are effective but face problems with portability, cost, and privacy concerns. As for existing wireless sensing methods, they can only extract coarse features for activity recognition. Therefore, we present EchoHealth, which utilizes a smart speaker for rehabilitation exercise detection and assessment. We upgrade the smart speaker into an active sonar system without hardware modification to generate acoustic micro-distance images with motion information. Then, time-domain motion detection and distance-domain feature extraction are utilized to filter out the effects of non-motion time and distance to extract patient motion features for motion recognition. We further assess the patient's rehabilitation exercises from five aspects, based on which EchoHealth provides rehabilitation guidance. Extensive experiments with 15 participants performing 12 rehabilitation motions confirmed that EchoHealth can achieve 97.4% average accuracy in recognition of rehabilitation motion and provide accurate rehabilitation indicators in various environments.