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Channel selection and classification of electroencephalogram signals: an artificial neural network and genetic algorithm-based approach.
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Yang, Jianhua, Singh, Harsimrat, Hines, Evor, Schlaghecken, Friederike, Iliescu, Daciana, Leeson, Mark S. and Stocks, Nigel G. (2012) Channel selection and classification of electroencephalogram signals: an artificial neural network and genetic algorithm-based approach. Artificial Intelligence In Medicine, Volume 55 (Number 2). pp. 117-126. doi:10.1016/j.artmed.2012.02.001
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Official URL: http://dx.doi.org/10.1016/j.artmed.2012.02.001
Abstract
We demonstrate that GNMM is able to perform effective channel selections/reductions, which not only reduces the difficulty of data collection, but also greatly improves the generalization of the classifier. An important step that affects the effectiveness of GNMM is the pre-processing method. In this paper, we also highlight the importance of choosing an appropriate time window position.
| Item Type: | Journal Article | ||||||||
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| Subjects: | R Medicine > R Medicine (General) R Medicine > RC Internal medicine > RC0321 Neuroscience. Biological psychiatry. Neuropsychiatry T Technology > TA Engineering (General). Civil engineering (General) |
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| Divisions: | Faculty of Science > Engineering Faculty of Science > Psychology |
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| Journal or Publication Title: | Artificial Intelligence In Medicine | ||||||||
| Publisher: | Elsevier BV | ||||||||
| ISSN: | 1873-2860 | ||||||||
| Official Date: | June 2012 | ||||||||
| Dates: |
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| Volume: | Volume 55 | ||||||||
| Number: | Number 2 | ||||||||
| Number of Pages: | 10 | ||||||||
| Page Range: | pp. 117-126 | ||||||||
| DOI: | 10.1016/j.artmed.2012.02.001 | ||||||||
| Status: | Peer Reviewed | ||||||||
| Publication Status: | Published | ||||||||
| Access rights to Published version: | Open Access | ||||||||
| Funder: | Economic and Social Research Council (Great Britain) (ESRC), Warwick Postgraduate Research Fellowship (WPRF), UK Overseas Research Students Awards Scheme (ORSAS), Warwick Institute of Advanced Study (IAS) | ||||||||
| Grant number: | RES-000-22-1841 (ESRC) |
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