Comparison of static and dynamic neural network classifiers for brain-machine interfaces / Hema C.R. ...[et al.]
Neural network classifiers are one among the popular modes in the design of brain machine interface (BMI). In this study two novel dynamic neural network classifier designs for a four-state BMI are presented. Dynamic neural network based design for a four-state BMI to drive a wheelchair is analyzed....
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | en |
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UiTM Press
2010
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| Online Access: | https://ir.uitm.edu.my/id/eprint/61879/1/61879.pdf https://ir.uitm.edu.my/id/eprint/61879/ https://jeesr.uitm.edu.my/v1/ |
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| _version_ | 1839753491008978944 |
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| author | C.R., Hema M.P., Paulraj Yaacob, S. Adom, A.H. Nagarajan, R. |
| author_facet | C.R., Hema M.P., Paulraj Yaacob, S. Adom, A.H. Nagarajan, R. |
| author_sort | C.R., Hema |
| building | Tun Abdul Razak Library |
| collection | Institutional Repository |
| content_provider | Universiti Teknologi Mara |
| content_source | UiTM Institutional Repository |
| continent | Asia |
| country | Malaysia |
| description | Neural network classifiers are one among the popular modes in the design of brain machine interface (BMI). In this study two novel dynamic neural network classifier designs for a four-state BMI are presented. Dynamic neural network based design for a four-state BMI to drive a wheelchair is analyzed. Motor imagery signals recorded noninvasively at the sensorimotor cortex region using two bipolar electrodes is used in the study. The performances of the proposed algorithms are compared with a static feed forward neural classifier. Average classification performance of 97.7% was achievable. Experiment results show that the distributed time delay neural network model out performs the layered recurrent and feed forward neural classifiers for a four-state BMI design. |
| format | Article |
| id | my.uitm.ir-61879 |
| institution | Universiti Teknologi Mara |
| language | en |
| publishDate | 2010 |
| publisher | UiTM Press |
| record_format | eprints |
| spelling | my.uitm.ir-618792025-07-31T03:40:25Z https://ir.uitm.edu.my/id/eprint/61879/ Comparison of static and dynamic neural network classifiers for brain-machine interfaces / Hema C.R. ...[et al.] jeesr C.R., Hema M.P., Paulraj Yaacob, S. Adom, A.H. Nagarajan, R. Neural networks (Computer science) Neural network classifiers are one among the popular modes in the design of brain machine interface (BMI). In this study two novel dynamic neural network classifier designs for a four-state BMI are presented. Dynamic neural network based design for a four-state BMI to drive a wheelchair is analyzed. Motor imagery signals recorded noninvasively at the sensorimotor cortex region using two bipolar electrodes is used in the study. The performances of the proposed algorithms are compared with a static feed forward neural classifier. Average classification performance of 97.7% was achievable. Experiment results show that the distributed time delay neural network model out performs the layered recurrent and feed forward neural classifiers for a four-state BMI design. UiTM Press 2010-06 Article PeerReviewed text en https://ir.uitm.edu.my/id/eprint/61879/1/61879.pdf C.R., Hema and M.P., Paulraj and Yaacob, S. and Adom, A.H. and Nagarajan, R. (2010) Comparison of static and dynamic neural network classifiers for brain-machine interfaces / Hema C.R. ...[et al.]. (2010) Journal of Electrical and Electronic Systems Research (JEESR) <https://ir.uitm.edu.my/view/publication/Journal_of_Electrical_and_Electronic_Systems_Research_=28JEESR=29.html>, 3 (1): 6. pp. 49-57. ISSN 1985-5389 https://jeesr.uitm.edu.my/v1/ |
| spellingShingle | Neural networks (Computer science) C.R., Hema M.P., Paulraj Yaacob, S. Adom, A.H. Nagarajan, R. Comparison of static and dynamic neural network classifiers for brain-machine interfaces / Hema C.R. ...[et al.] |
| title | Comparison of static and dynamic neural network classifiers for brain-machine interfaces / Hema C.R. ...[et al.] |
| title_full | Comparison of static and dynamic neural network classifiers for brain-machine interfaces / Hema C.R. ...[et al.] |
| title_fullStr | Comparison of static and dynamic neural network classifiers for brain-machine interfaces / Hema C.R. ...[et al.] |
| title_full_unstemmed | Comparison of static and dynamic neural network classifiers for brain-machine interfaces / Hema C.R. ...[et al.] |
| title_short | Comparison of static and dynamic neural network classifiers for brain-machine interfaces / Hema C.R. ...[et al.] |
| title_sort | comparison of static and dynamic neural network classifiers for brain-machine interfaces / hema c.r. ...[et al.] |
| topic | Neural networks (Computer science) |
| url | https://ir.uitm.edu.my/id/eprint/61879/1/61879.pdf https://ir.uitm.edu.my/id/eprint/61879/ https://jeesr.uitm.edu.my/v1/ |
| url_provider | http://ir.uitm.edu.my/ |