Development of rehabilitation devices with artificial intelligence for Gait Disorder symptom of Parkinson's Disease

Abstract

Parkinson’s Disease(PD) is one of neurodegenerative disease. Perfect cure methods have still not been found yet. Medication and rehabilitation methods are utilized to control severity. Cueing and feedback training, are utilized to improve a patient’s quality of life and prevent rapid degradation speed. Devices that detect and classifies a user’s gait based on several factors is required to use those rehabilitation methods. Therefore, in this research, I developed gait detection and classification devices. After, I also developed adaptive control algorithm for inertial measurement unit devices. At first, the simple and mechanical gait detection and classification system showed that they could detect a user’s gait based on a metal bead and a microswitch. Secondly, the advanced Gait Detection and Classification (GDC) devices and GDC algorithm using acceleration and angular velocity from IMU were designed. Finally, the adaptive Gait Detection and Classification Rate (GDCR) control algorithm was developed after statistically analyzing results. In this research, I could observe the designed devices could detect and classify users’ gait based on various factors. I am looking forward to using this device in the future to use effective rehabilitation methods.