| dc.contributor.author | Hema, Chengalvarayan Radhakrishnamurthy | |
| dc.contributor.author | Murugesa Pandiyan, Paulraj, Assoc. Prof. Dr. | |
| dc.date.accessioned | 2011-10-05T15:52:08Z | |
| dc.date.available | 2011-10-05T15:52:08Z | |
| dc.date.issued | 2011-06-20 | |
| dc.identifier.citation | IFMBE Proceedings, vol. 35 (9), 2011, pages 287-291 | en_US |
| dc.identifier.isbn | 978-364221728-9 | |
| dc.identifier.issn | 1680-0737 | |
| dc.identifier.uri | http://www.springerlink.com/content/h443052035k7511n/ | |
| dc.identifier.uri | http://dspace.unimap.edu.my/123456789/14037 | |
| dc.description | Link to publisher's homepage at http://www.springerlink.com/ | en_US |
| dc.description.abstract | Controlling a power wheelchair using a brain machine interface (BMI) requires sufficient subject training. A neural network based BMI design using motor imagery of four states is used to control the navigation of a power wheelchair. The online experiment results are presented for two indoor navigation protocols. Twotrained subjects participated in the study. Performance of the real-time experiments is assessed based on the targets reached, time taken to reach the targets and on completion of a given navigation protocol. A performance rate of 85.7% is achievable by both subjects for the real-time experiments. | en_US |
| dc.language.iso | en | en_US |
| dc.publisher | Springer-Verlag | en_US |
| dc.relation.ispartofseries | Proceedings of the 5th Kuala Lumpur International Conference on Biomedical Engineering (BIOMED 2011) | en_US |
| dc.subject | Brain machine interface (BMI) | en_US |
| dc.subject | EEG signal processing | en_US |
| dc.subject | Neural networks | en_US |
| dc.title | Control brain machine interface for a power wheelchair | en_US |
| dc.type | Working Paper | en_US |
| dc.contributor.url | paul@unimap.edu.my | en_US |
