Method of identifying individuals using VEP signals and neural network
A method of identifying individuals using visual-evoked-potential (VEP) signals and neural network (NN) is proposed. In the approach, a backpropagation (BP) NN is trained to identify individuals using gamma-band (30-50 Hz) spectral power ratio of VEP signals extracted from 61 electrodes located on t...
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| Format: | Article |
| Language: | English |
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2004
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| Online Access: | http://shdl.mmu.edu.my/2509/ http://shdl.mmu.edu.my/2509/1/1773.pdf |
| _version_ | 1848790074287718400 |
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| author | Palaniappan, R. |
| author_facet | Palaniappan, R. |
| author_sort | Palaniappan, R. |
| building | MMU Institutional Repository |
| collection | Online Access |
| description | A method of identifying individuals using visual-evoked-potential (VEP) signals and neural network (NN) is proposed. In the approach, a backpropagation (BP) NN is trained to identify individuals using gamma-band (30-50 Hz) spectral power ratio of VEP signals extracted from 61 electrodes located on the scalp of the brain. The gamma-band spectral-power ratio is computed using a zero-phase Butterworth digital filter and Parseval's time-frequency equivalence theorem. NN classification gives an average of 99.06% across 400 test VEP patterns from 20 individuals using 10-fold cross-validation scheme. This shows promise for the approach to be developed further as a biometric identification system. |
| first_indexed | 2025-11-14T18:06:50Z |
| format | Article |
| id | mmu-2509 |
| institution | Multimedia University |
| institution_category | Local University |
| language | English |
| last_indexed | 2025-11-14T18:06:50Z |
| publishDate | 2004 |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | mmu-25092011-08-22T07:04:48Z http://shdl.mmu.edu.my/2509/ Method of identifying individuals using VEP signals and neural network Palaniappan, R. TA Engineering (General). Civil engineering (General) A method of identifying individuals using visual-evoked-potential (VEP) signals and neural network (NN) is proposed. In the approach, a backpropagation (BP) NN is trained to identify individuals using gamma-band (30-50 Hz) spectral power ratio of VEP signals extracted from 61 electrodes located on the scalp of the brain. The gamma-band spectral-power ratio is computed using a zero-phase Butterworth digital filter and Parseval's time-frequency equivalence theorem. NN classification gives an average of 99.06% across 400 test VEP patterns from 20 individuals using 10-fold cross-validation scheme. This shows promise for the approach to be developed further as a biometric identification system. 2004-01 Article NonPeerReviewed application/pdf en http://shdl.mmu.edu.my/2509/1/1773.pdf Palaniappan, R. (2004) Method of identifying individuals using VEP signals and neural network. IEE Proceedings - Science, Measurement and Technology, 151 (1). pp. 16-20. ISSN 13502344 http://dx.doi.org/10.1049/ip-smt:20040003 doi:10.1049/ip-smt:20040003 doi:10.1049/ip-smt:20040003 |
| spellingShingle | TA Engineering (General). Civil engineering (General) Palaniappan, R. Method of identifying individuals using VEP signals and neural network |
| title | Method of identifying individuals using VEP signals and neural network |
| title_full | Method of identifying individuals using VEP signals and neural network |
| title_fullStr | Method of identifying individuals using VEP signals and neural network |
| title_full_unstemmed | Method of identifying individuals using VEP signals and neural network |
| title_short | Method of identifying individuals using VEP signals and neural network |
| title_sort | method of identifying individuals using vep signals and neural network |
| topic | TA Engineering (General). Civil engineering (General) |
| url | http://shdl.mmu.edu.my/2509/ http://shdl.mmu.edu.my/2509/ http://shdl.mmu.edu.my/2509/ http://shdl.mmu.edu.my/2509/1/1773.pdf |