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dc.contributor.authorKurzynski, M.
dc.contributor.authorWoloszynski, Tomasz
dc.contributor.authorWolczowski, A.
dc.date.accessioned2017-01-30T13:05:20Z
dc.date.available2017-01-30T13:05:20Z
dc.date.created2016-09-12T08:36:40Z
dc.date.issued2010
dc.identifier.citationKurzynski, M. and Woloszynski, T. and Wolczowski, A. 2010. A multiclassifier system with dynamic ensemble selection applied to the recognition of EMG signals for the control of bio-prosthetic hand.
dc.identifier.urihttp://hdl.handle.net/20.500.11937/28489
dc.identifier.doi10.1109/ISABEL.2010.5702931
dc.description.abstract

The paper presents a concept of hand movements recognition on the basis of EMG signal analysis. Signal features are represented by coefficient of autoregressive (AR) model, and as classifier the original multiclassifier systems with dynamic ensemble selection are applied. The performance of the proposed methods was experimentally compared against three classifiers using real datasets. The systems developed achieved the highest overall classification accuracies demonstrating the potential of dynamic classifier selection for recognition of EMG signals. ©2010 IEEE.

dc.titleA multiclassifier system with dynamic ensemble selection applied to the recognition of EMG signals for the control of bio-prosthetic hand
dc.typeConference Paper
dcterms.source.title2010 3rd International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL 2010
dcterms.source.series2010 3rd International Symposium on Applied Sciences in Biomedical and Communication Technologies, ISABEL 2010
dcterms.source.isbn9781424481323
curtin.departmentDepartment of Mechanical Engineering
curtin.accessStatusFulltext not available


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