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Abstract
An approach to the knowledge representation extraction from biomedical signals analysis concerning motor activity of Parkinson disease patients is proposed in this paper. This is done utilizing accelerometers attached to their body as well as exploiting video image of their hand movements. Experiments are carried out employing artificial neural networks and support vector machine to the recognition of characteristic motor activity disorders in patients. Obtained results indicate that it is possible to interpret some selected patient’s body movements with a sufficiently high effectiveness.
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- DOI:
- Digital Object Identifier (open in new tab) 10.1007/s11047-014-9475-0
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- Category:
- Articles
- Type:
- artykuł w czasopiśmie wyróżnionym w JCR
- Published in:
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Natural Computing
no. 14,
edition 4,
pages 579 - 591,
ISSN: 1567-7818 - Language:
- English
- Publication year:
- 2015
- Bibliographic description:
- Kostek B., Kupryjanow A., Czyżewski A.: Knowledge representation of motor activity of patients with Parkinson’s disease // Natural Computing. -Vol. 14, iss. 4 (2015), s.579-591
- DOI:
- Digital Object Identifier (open in new tab) 10.1007/s11047-014-9475-0
- Verified by:
- Gdańsk University of Technology
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