EEG signal classification for real-time brain-computer interface applications: a review
Brain-computer interface (BCI) is linking the brain activity to computer, which allows a person to control devices directly with his brain waves and without any use of his muscles. Recent advances in real-time signal processing have made BCI a feasible alternative for controlling robot and for commu...
| Main Authors: | , |
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| Format: | Proceeding Paper |
| Language: | English |
| Published: |
2011
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| Subjects: | |
| Online Access: | http://irep.iium.edu.my/1820/1/EEG.pdf |
| _version_ | 1796874830311587840 |
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| author | Khorshidtalab, A. Salami, Momoh Jimoh Emiyoka |
| author_facet | Khorshidtalab, A. Salami, Momoh Jimoh Emiyoka |
| author_sort | Khorshidtalab, A. |
| collection | IIUM |
| description | Brain-computer interface (BCI) is linking the brain activity to computer, which allows a person to control devices directly with his brain waves and without any use of his muscles. Recent advances in real-time signal processing have made BCI a feasible alternative for controlling robot and for communication as well. Controlling devices using BCI is a crucial aid for people suffering from severe disabilities and more than that, BCIs can replace human to control robots working in dangerous or uncongenial situations. Effective BCIs demand for accurate and real-time EEG signals processing. This paper is to review the current state of research and to compare the performance of different algorithms for real-time classification of BCIbased electroencephalogram signals. |
| first_indexed | 2024-03-05T22:30:04Z |
| format | Proceeding Paper |
| id | oai:generic.eprints.org:1820 |
| institution | International Islamic University Malaysia |
| language | English |
| last_indexed | 2024-03-05T22:30:04Z |
| publishDate | 2011 |
| record_format | dspace |
| spelling | oai:generic.eprints.org:18202012-02-28T02:48:18Z http://irep.iium.edu.my/1820/ EEG signal classification for real-time brain-computer interface applications: a review Khorshidtalab, A. Salami, Momoh Jimoh Emiyoka T175 Industrial research. Research and development Brain-computer interface (BCI) is linking the brain activity to computer, which allows a person to control devices directly with his brain waves and without any use of his muscles. Recent advances in real-time signal processing have made BCI a feasible alternative for controlling robot and for communication as well. Controlling devices using BCI is a crucial aid for people suffering from severe disabilities and more than that, BCIs can replace human to control robots working in dangerous or uncongenial situations. Effective BCIs demand for accurate and real-time EEG signals processing. This paper is to review the current state of research and to compare the performance of different algorithms for real-time classification of BCIbased electroencephalogram signals. 2011 Proceeding Paper PeerReviewed application/pdf en http://irep.iium.edu.my/1820/1/EEG.pdf Khorshidtalab, A. and Salami, Momoh Jimoh Emiyoka (2011) EEG signal classification for real-time brain-computer interface applications: a review. In: ICOM 2011, 17-19 May, 2011, Kuala Lumpur, Malaysia. http://www.iium.edu.my/ICOM/2011/ |
| spellingShingle | T175 Industrial research. Research and development Khorshidtalab, A. Salami, Momoh Jimoh Emiyoka EEG signal classification for real-time brain-computer interface applications: a review |
| title | EEG signal classification for real-time brain-computer interface applications: a review |
| title_full | EEG signal classification for real-time brain-computer interface applications: a review |
| title_fullStr | EEG signal classification for real-time brain-computer interface applications: a review |
| title_full_unstemmed | EEG signal classification for real-time brain-computer interface applications: a review |
| title_short | EEG signal classification for real-time brain-computer interface applications: a review |
| title_sort | eeg signal classification for real time brain computer interface applications a review |
| topic | T175 Industrial research. Research and development |
| url | http://irep.iium.edu.my/1820/1/EEG.pdf |
| work_keys_str_mv | AT khorshidtalaba eegsignalclassificationforrealtimebraincomputerinterfaceapplicationsareview AT salamimomohjimohemiyoka eegsignalclassificationforrealtimebraincomputerinterfaceapplicationsareview |