Wearable Sensor-Based Exercise Biofeedback for Supporting Fall Prevention at Physiotherapy

Abstract

Abstract Introduction Exercise interventions focused on strength and balance are effective for falls prevention in older people. Several fall prevention programs were developed with this intent, however there is often a lack of personalization in these solutions. Technological interventions namely biofeedback systems have been shown recently to have the ability to objectively assess therapeutic exercise in real time to improve quality performance. Objectives To describe a technological solution with biofeedback system to be used by physiotherapists at the clinic, to assist the learning process of a personalized and progressive strength and balance exercise program. Methodology The exercises are monitored by two wearable inertial sensors and a pressure platform for mobility, strength and balance measurements. In order to validate the system, a set of five exercises, from the Otago Exercise Program, were tested with a group of 16 older adults during several sessions. Spatial, temporal and balance metrics were extracted during the exercises, providing quantitative biofeedback during the exercise. Results Inertial and pressure sensors are suitable for exercise tracking during fall prevention exercises. Range of motion, weight distribution and shifting, balance and cycle identification were successfully monitored for all exercises. This system successfully automated the process of creating individualized and personalized exercise biofeedback systems to fall prevention programs. Conclusion This study demonstrates this technological solution holds promise in falls prevention. FallSensing Clinic is a feasible monitor and biofeedback tool that can be applied to clinical practice allowing people to better perform the exercise program.