By
Chethan P.J.,
Aishwarya B.R.,
Amitha G.S.,
Ananya V.K.,
Anjali C.R.,
- Assistant Professor Department of Computer Science and Engineering, People’s Education Society Institute of Technology and Management, Shivamogga, Virupina Koppa Karnataka India
- Student Department of Computer Science and Engineering, People’s Education Society Institute of Technology and Management, Shivamogga, Virupina Koppa Karnataka India
- Student Department of Computer Science and Engineering, People’s Education Society Institute of Technology and Management, Shivamogga, Virupina Koppa Karnataka India
- Student Department of Computer Science and Engineering, People’s Education Society Institute of Technology and Management, Shivamogga, Virupina Koppa Karnataka India
- Student Department of Computer Science and Engineering, People’s Education Society Institute of Technology and Management, Shivamogga, Virupina Koppa Karnataka India
Abstract
Stroke is a major health concern worldwide, often resulting in impaired motor functions and affecting the quality of life for affected individuals. This research introduces an innovative approach for predicting stroke recovery rates by leveraging movement analysis during computer interaction. The proposed system aims to provide a non-invasive and automated solution to assess the rehabilitation progress of stroke survivors. The system utilizes advanced motion tracking technologies to capture and analyze the fine-grained movements exhibited during computer-based tasks. Machine learning algorithms are employed to correlate these movement patterns with established indicators of stroke recovery, allowing for personalized predictions tailored to individual patients. This approach offers a more dynamic and responsive assessment compared to traditional methods.
Keywords: AIML, computer vision, CNN, rehabilitation, movement analysis
[This article belongs to Journal of Computer Technology & Applications(jocta)]
How to cite this article: Chethan P.J., Aishwarya B.R., Amitha G.S., Ananya V.K., Anjali C.R.. Automatic Stroke Recovery Rate Prediction System Based on Movement Analysis During Computer Interaction. Journal of Computer Technology & Applications. 2024; 15(02):76-82.
How to cite this URL: Chethan P.J., Aishwarya B.R., Amitha G.S., Ananya V.K., Anjali C.R.. Automatic Stroke Recovery Rate Prediction System Based on Movement Analysis During Computer Interaction. Journal of Computer Technology & Applications. 2024; 15(02):76-82. Available from: https://journals.stmjournals.com/jocta/article=2024/view=160433
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Regular Issue Subscription Review Article
Journal of Computer Technology & Applications
ISSN: 2229-6964
| Volume | 15 |
| Issue | 02 |
| Received | May 3, 2024 |
| Accepted | July 22, 2024 |
| Published | August 1, 2024 |