Armstrong, Kai, Wen, Yan, Zhang, Lei , Ye, Xujiong and Lee, Paul (2022) Novel Clinical Applications of Marker-less Motion Capture as a Low-cost Human Motion Analysis Method in the Detection and Treatment of Knee Osteoarthritis. Journal of Arthritis, 11 (1). 001-005. ISSN 2167-7921
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| Item Type: | Article |
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| Item Status: | Live Archive |
Abstract
Marker-less motion capture is a rapidly advancing field that can take simple RGB image sequences, or more advanced Red Green Blue Depth (RGB-D) image sequences obtained using depth sensors, and outputs an estimated human pose. This method of human pose estimation allows for the extraction of biomechanical features which can then be analysed by clinicians to give more insights into a patient’s movement capabilities. When compared to other, more clinically proven technologies such as the Knee Kinesiography (KneeKG), biomechanics presented have the advantage of being more representative of natural movement without the obstructive markers placed on the body. This Significant difference of up to 10 degrees in a range of motion for the knee could be the key to better identifying a person’s gait or tracking their natural walking pattern over time, while also being more robust and better suited to a smaller clinical environment.
| Keywords: | Human motion analysis, artificial intelligence, Computer-Aided Diagnosis (CAD) |
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| Subjects: | G Mathematical and Computer Sciences > G700 Artificial Intelligence G Mathematical and Computer Sciences > G760 Machine Learning G Mathematical and Computer Sciences > G740 Computer Vision |
| Divisions: | College of Science > School of Computer Science |
| Related URLs: | |
| ID Code: | 53608 |
| Deposited On: | 06 Mar 2023 16:12 |
Available Versions of this Item
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Novel Clinical Applications of Marker-less Motion Capture as a Low-cost Human Motion Analysis Method in the Detection and Treatment of Knee Osteoarthritis. (deposited 09 Feb 2022 16:54)
- Novel Clinical Applications of Marker-less Motion Capture as a Low-cost Human Motion Analysis Method in the Detection and Treatment of Knee Osteoarthritis. (deposited 06 Mar 2023 16:12) [Currently Displayed]
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