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Technology Assisted  Upper Extremities Movement Measurement System for     
​Research Programmes Connected Rehabilitation Platform​
​Clinical PI: Mr KUAH Wee Keong, Christopher​
Principal Occupational Therapist, Centre for Advanced Rehabilitation Therapeutics, Tan Tock Seng Hospital
​Technical PI:​ Prof ANG Wei Tech
Executive Director, Rehabilitation Research Institute of Singapore
A/Professor, School of Mechanical & Aerospace Engineering
LKC School of Medicine, Nanyang Technological University

Current physical rehabilitation exercises at home do not receive enough insightful feedback from a therapist due to the lack of healthcare manpower to monitor all those daily-generated exercises. 

This project aims to build a movement monitoring system that record the movement and flag anomalous parts in the exercise that should be reviewed by a therapist which will reduce the therapist’s time spent on the feedback generation task. The project is composed of two main parts. 

First, a home-based upper-limb sensing system is built on a combination of a depth camera, a pair of IMU wristbands, and a suite of sensorized household items to capture the full degree-of-freedom of upper-extremity movements. Second, the kinematic data from the sensing system will be automatically analysed to flag anomalies using some statistical and machine-learning techniques. These techniques will generate the norm model for each exercise by learning from exercise demonstration from a group of healthy subjects.

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