Assessment of knee joint motor disability improvement rate using kinect sensor
This study enhances disability recovery detection in knee osteoarthritis patients by evaluating a fuzzy system for diagnosing knee pain severity and tracking recovery. A kinect sensor analysed three-dimensional gait data from 48 patients, with 24 for training and 24 for testing. Based on expert-defined rules, the system categorised mobility impairments and aligned closely with clinical assessments. It provided real-time feedback, improved treatment personalisation, and reduced evaluation subjectivity. The results demonstrate its reliability for clinical integration, offering accurate diagnosis and recovery monitoring. This approach could enhance treatment outcomes and aid in managing knee joint disorders and motor disabilities.
Authors
- Masoume Gholizade (ORCID: https://orcid.org/0000-0002-5221-8197)
- Mohammad Zahraei (ORCID: https://orcid.org/0000-0002-3778-5425)
- Hadi Soltanizadeh (ORCID: https://orcid.org/0000-0002-2210-675X)
- Farhad Azadi (ORCID: https://orcid.org/0000-0003-1754-2730)
- Shib Sankar Sana (ORCID: https://orcid.org/0000-0002-7834-8969)
- Esmaeil Khaleghi
Institutions
- Visva-Bharati University (IN)
- Sina Hospital (IR)
- University of Social Welfare and Rehabilitation Sciences (IR)
- Semnan University (IR)
Publication Details
- Journal
- International Journal of Biomedical Engineering and Technology
- Published
- 2025-01-01
- DOI
- https://doi.org/10.1504/ijbet.2025.149325
- Primary Topic
- Hand Gesture Recognition Systems
- Type
- article
- Field-Weighted Citation Impact
- 0.00