Lower Limb Walking Gait Profiling Using Marker-less Motion Capture with GDL and R-GDL methods to Assist Physiotherapy Treatment

Abstract

Physiotherapy includes specialised therapist conducting mechanical force and movement onto human body in order to heal and avoid further physical injuries. Therapists rely on subjective estimation in order to measure the performance improvements after physiotherapy treatments. An automated method to analyse and measure improvement is needed to calculate improvements based on patients' walking gait. This method would require a gait profile database in order to be able to calculate patients' improvement after physiotherapy treatments. The new technologies with low cost sensing devices could provide new opportunities and potential to assist the effectiveness of physiotherapy treatment. This research proposed a framework for walking gait profiling using marker-less motion capture to assist physiotherapy treatment. The framework consists of two major modules which are: Motion Template Module and Motion Evaluation Module. The Motion Template Module includes the motion capturing process where the human body is precisely tracked in order to generate skeleton information, focused target and record the movements before developing a script of motion called GDL scripts (GDLs) as a template. The template will be used for categorisation purposes using Reverse-Gesture Description Language (R-GDL). Evaluations of other respondents' walking gait have been done in Motion Evaluation Module using GDL and the created GDLs. The GDL output is then calculated to generate the walking gait profile. The system can differentiate the similarities between normal and abnormal walking gait. This study shows that the framework can compare the walking gait among normal and abnormal walking, based on the generated template. Using the proposed framework, the effectiveness for walking gait profiling has been proven and can be used to assist the physiotherapy treatment.

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