Abstract
Freezing of Gait (FOG) is a symptom in Parkinson's Disease (PD) patients that negatively impacts their productivity and quality of life. There is a need for external cues to aid PD patients to overcome this freezing phenomenon. Integrating biofeedback with monitoring devices will improve their self-efficacy in going about their daily activities. This paper presents a real-time PD monitoring and biofeedback system using low-cost wearable sensors (e.g. accelerometers, gyroscope and magnetic compass). The gait monitoring system that is able to process real-time captured sensory data and detect FOG, then triggering audio and vibration biofeedback to prevent or reduce freezing. The system's FOG detection algorithm uses time frequency analysis and kinematic parameters from gait signals. The system is easy to use, low cost and maximises battery life. Experimental trial runs on PD patients demonstrate the feasibility of the proposed system.
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