Multiclassifiers with competence function applied to the recognition of EMG signals for the control of bio-prosthetic hand

The paper presents a concept of bio-prosthesis control via recognition of user intent on the basis of myopotentials acquired of his body. We assume that in the control process each prosthesis operation consists of specific sequence of elementary actions. The multiclassifier systems with fusion/selec...

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Main Authors: Kurzynski, M., Woloszynski, Tomasz, Wolczowski, A.
Format: Conference Paper
Published: 2009
Online Access:http://hdl.handle.net/20.500.11937/45904
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author Kurzynski, M.
Woloszynski, Tomasz
Wolczowski, A.
author_facet Kurzynski, M.
Woloszynski, Tomasz
Wolczowski, A.
author_sort Kurzynski, M.
building Curtin Institutional Repository
collection Online Access
description The paper presents a concept of bio-prosthesis control via recognition of user intent on the basis of myopotentials acquired of his body. We assume that in the control process each prosthesis operation consists of specific sequence of elementary actions. The multiclassifier systems with fusion/selection strategy based on competence function are applied to the recognition of patient's intent. Experimental investigations of the proposed multiclassifiers for real data are performed and results are discussed. Classification results obtained for three simple fusion methods and one multiclassifier system are used for a comparison. ©2009 IEEE.
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spelling curtin-20.500.11937-459042018-12-14T00:50:57Z Multiclassifiers with competence function applied to the recognition of EMG signals for the control of bio-prosthetic hand Kurzynski, M. Woloszynski, Tomasz Wolczowski, A. The paper presents a concept of bio-prosthesis control via recognition of user intent on the basis of myopotentials acquired of his body. We assume that in the control process each prosthesis operation consists of specific sequence of elementary actions. The multiclassifier systems with fusion/selection strategy based on competence function are applied to the recognition of patient's intent. Experimental investigations of the proposed multiclassifiers for real data are performed and results are discussed. Classification results obtained for three simple fusion methods and one multiclassifier system are used for a comparison. ©2009 IEEE. 2009 Conference Paper http://hdl.handle.net/20.500.11937/45904 10.1109/ITAB.2009.5394318 restricted
spellingShingle Kurzynski, M.
Woloszynski, Tomasz
Wolczowski, A.
Multiclassifiers with competence function applied to the recognition of EMG signals for the control of bio-prosthetic hand
title Multiclassifiers with competence function applied to the recognition of EMG signals for the control of bio-prosthetic hand
title_full Multiclassifiers with competence function applied to the recognition of EMG signals for the control of bio-prosthetic hand
title_fullStr Multiclassifiers with competence function applied to the recognition of EMG signals for the control of bio-prosthetic hand
title_full_unstemmed Multiclassifiers with competence function applied to the recognition of EMG signals for the control of bio-prosthetic hand
title_short Multiclassifiers with competence function applied to the recognition of EMG signals for the control of bio-prosthetic hand
title_sort multiclassifiers with competence function applied to the recognition of emg signals for the control of bio-prosthetic hand
url http://hdl.handle.net/20.500.11937/45904