Sensing-Fi: Wi-Fi CSI and accelerometer fusion system for fall detection

Abstract

Falling is a major cause of death among elders. To detect falls, numerous approaches have been proposed in the past decade, including computer-vision based image processing, wearable sensors, and acoustic signal processing, etc. Though the recent advancement in infra-red LED, depth camera, MEMS (Micro-Electro-Mechanical Systems) sensors and machine learning algorithms may have enlarged the application scope, the privacy intrusion and lack of convenience still remain to be open issues which prevent these systems from large deployment. A novel Sensing-Fi system described in this paper aims to overcome such deficiencies. The system design is comprised of harnessing Wi-Fi Channel State Information (CSI) coupled with ground-mounted accelerometer to detect floor vibration, hence the system is completely passive and non-invasive, i.e., the user is not required to wear the technology contrary to wearable accelerometers. In addition, contrary to the existing standalone Wi-Fi CSI fall detection systems, it overcomes the constraint by which only one user can be present in the room. The system has shown promising results with 95% accuracy.