Automated Marker-based Abnormal Gait Pattern Detection Using Novel 6-dimensional Skeleton
Conference paper
Wickramarachchi, W., Brown, R., Ghavami, M., Berthaume, M. and Dudley-Mcevoy, S. (2024). Automated Marker-based Abnormal Gait Pattern Detection Using Novel 6-dimensional Skeleton. ISMICT 2024. London, UK 15 - 17 May 2024 Institute of Electrical and Electronics Engineers (IEEE).
Authors | Wickramarachchi, W., Brown, R., Ghavami, M., Berthaume, M. and Dudley-Mcevoy, S. |
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Type | Conference paper |
Abstract | Marker-based motion-capturing technologies are widely used in clinics to diagnose motor-related pathologies due to their high resolution and accuracy. However, it often requires manual intervention to process the raw marker data. Although previous research has proposed algorithms to automate these processes, they do not address different marker placement models, abnormal gait patterns, or variations in the anthropometric measurements which limits their scalability. Therefore, this research proposes a novel automated algorithm to process the raw marker data and generate a novel 6D skeleton representation. It is used in machine learning classifiers to identify abnormal gait patterns. The proposed algorithm was tested with marker-based gait analysis data and achieved 99.7% accuracy in classifying normal and abnormal gait patterns using multilayer perceptron classifiers. |
Keywords | Wearable technologies; Marker-based motion capturing; 6D Skeleton; Gait analysis; Abnormal gait |
Year | 2024 |
Publisher | Institute of Electrical and Electronics Engineers (IEEE) |
Web address (URL) | https://www.ismict-2024.com/ |
Accepted author manuscript | License File Access Level Open |
Publication dates | |
15 May 2024 | |
Publication process dates | |
Accepted | 15 Apr 2024 |
Deposited | 10 Jul 2024 |
Web address (URL) of conference proceedings | https://www.ismict-2024.com/ |
https://openresearch.lsbu.ac.uk/item/979y5
Restricted files
Accepted author manuscript
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