| _version_ |
1860799574816325632
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| building |
INTELEK Repository
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| collection |
Online Access
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| collectionurl |
https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072
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| date |
2017-07-28 09:52:16
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| eventvenue |
Batu Ferringhi, Pulau Pinang
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| format |
Restricted Document
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| id |
6533
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| institution |
UniSZA
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| originalfilename |
1470-01-FH03-FIK-17-10498.pdf
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| person |
User™
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| recordtype |
oai_dc
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| resourceurl |
https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6533
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| spelling |
6533 https://intelek.unisza.edu.my/intelek/pages/view.php?ref=6533 https://intelek.unisza.edu.my/intelek/pages/search.php?search=!collection407072 Restricted Document Conference Conference Paper application/pdf 8 1.6 Adobe Acrobat Pro DC 20 Paper Capture Plug-in User™ 2017-07-28 09:52:16 1470-01-FH03-FIK-17-10498.pdf UniSZA Private Access Lower Limb Walking Gait Profiling using Marker-Less Motion Capture to Assist Physiotherapy Treatment 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. The 5th International Conference on Artificial Intelligence, Computer Science, & Information Technology Batu Ferringhi, Pulau Pinang
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| spellingShingle |
Lower Limb Walking Gait Profiling using Marker-Less Motion Capture to Assist Physiotherapy Treatment
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| summary |
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.
|
| title |
Lower Limb Walking Gait Profiling using Marker-Less Motion Capture to Assist Physiotherapy Treatment
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| title_full |
Lower Limb Walking Gait Profiling using Marker-Less Motion Capture to Assist Physiotherapy Treatment
|
| title_fullStr |
Lower Limb Walking Gait Profiling using Marker-Less Motion Capture to Assist Physiotherapy Treatment
|
| title_full_unstemmed |
Lower Limb Walking Gait Profiling using Marker-Less Motion Capture to Assist Physiotherapy Treatment
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| title_short |
Lower Limb Walking Gait Profiling using Marker-Less Motion Capture to Assist Physiotherapy Treatment
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| title_sort |
lower limb walking gait profiling using marker-less motion capture to assist physiotherapy treatment
|