Brain Computer Interface Design Using Neural Network Classification Of Autoregressive Models Of Mental Task Electroencephalogram Signals.
Autoregressive(AR) feature extraction and neural network(NN) classification techniques are conducted using Electroencephalogram(EEG) signals extracted during mental tasks for Brain Computer Interface (BCI) design. The output of the BCI design could be used with a translation scheme such as Morse Cod...
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| Format: | Thesis |
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2004
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| Online Access: | http://shdl.mmu.edu.my/747/ |
| _version_ | 1848789590538715136 |
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| author | Huan , Nai Jen |
| author_facet | Huan , Nai Jen |
| author_sort | Huan , Nai Jen |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | Autoregressive(AR) feature extraction and neural network(NN) classification techniques are conducted using Electroencephalogram(EEG) signals extracted during mental tasks for Brain Computer Interface (BCI) design. The output of the BCI design could be used with a translation scheme such as Morse Code; to move a cursor around a screen or to control the prosthesis only by using thoughts. This introduces an invaluable means for paralyzed individuals to communicate with their external surroundings. |
| first_indexed | 2025-11-14T17:59:08Z |
| format | Thesis |
| id | mmu-747 |
| institution | Multimedia University |
| institution_category | Local University |
| last_indexed | 2025-11-14T17:59:08Z |
| publishDate | 2004 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-7472010-06-30T07:13:13Z http://shdl.mmu.edu.my/747/ Brain Computer Interface Design Using Neural Network Classification Of Autoregressive Models Of Mental Task Electroencephalogram Signals. Huan , Nai Jen QA76.75-76.765 Computer software Autoregressive(AR) feature extraction and neural network(NN) classification techniques are conducted using Electroencephalogram(EEG) signals extracted during mental tasks for Brain Computer Interface (BCI) design. The output of the BCI design could be used with a translation scheme such as Morse Code; to move a cursor around a screen or to control the prosthesis only by using thoughts. This introduces an invaluable means for paralyzed individuals to communicate with their external surroundings. 2004-06 Thesis NonPeerReviewed Huan , Nai Jen (2004) Brain Computer Interface Design Using Neural Network Classification Of Autoregressive Models Of Mental Task Electroencephalogram Signals. Masters thesis, Multimedia University. http://myto.perpun.net.my/metoalogin/logina.php |
| spellingShingle | QA76.75-76.765 Computer software Huan , Nai Jen Brain Computer Interface Design Using Neural Network Classification Of Autoregressive Models Of Mental Task Electroencephalogram Signals. |
| title | Brain Computer Interface Design Using Neural Network Classification Of Autoregressive Models Of Mental Task Electroencephalogram Signals. |
| title_full | Brain Computer Interface Design Using Neural Network Classification Of Autoregressive Models Of Mental Task Electroencephalogram Signals. |
| title_fullStr | Brain Computer Interface Design Using Neural Network Classification Of Autoregressive Models Of Mental Task Electroencephalogram Signals. |
| title_full_unstemmed | Brain Computer Interface Design Using Neural Network Classification Of Autoregressive Models Of Mental Task Electroencephalogram Signals. |
| title_short | Brain Computer Interface Design Using Neural Network Classification Of Autoregressive Models Of Mental Task Electroencephalogram Signals. |
| title_sort | brain computer interface design using neural network classification of autoregressive models of mental task electroencephalogram signals. |
| topic | QA76.75-76.765 Computer software |
| url | http://shdl.mmu.edu.my/747/ http://shdl.mmu.edu.my/747/ |