Lower Limb Walking Gait Profiling using Marker-Less Motion Capture to Assist Physiotherapy Treatment

Azrul Amri, Jamal and Engku Fadzli Hasan, Syed Abdullah and Wan Mohd Rizhan, Wan Idris and Fathurrahman, Lananan and Nor Farahana, Zainul Hisham (2017) Lower Limb Walking Gait Profiling using Marker-Less Motion Capture to Assist Physiotherapy Treatment. In: The 5th International Conference on Artificial Intelligence, Computer Science, & Information Technology, 31 July 2017- 1 August 2017, Batu Ferringhi, Pulau Pinang.

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Physiotherapy involves 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 aims of this research are to develop a framework for walking gait profiling using marker-less motion capture and assist physiotherapy evaluation by comparing walking gait to the profile that has been generated. The proposed system consists of four major phases which are: motion capturing; motion profiling; normal gait averaging; and gait profile comparison. The framework that has been developed in this research is shown and discussed in detail in this paper.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Informatics & Computing
Depositing User: Muhammad Akmal Azhar
Date Deposited: 17 Nov 2020 01:51
Last Modified: 17 Nov 2020 01:51
URI: http://eprints.unisza.edu.my/id/eprint/1470

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