@article{(Open Science Index):https://publications.waset.org/pdf/1768, title = {Analysis of the EEG Signal for a Practical Biometric System}, author = {Muhammad Kamil Abdullah and Khazaimatol S Subari and Justin Leo Cheang Loong and Nurul Nadia Ahmad}, country = {}, institution = {}, abstract = {This paper discusses the effectiveness of the EEG signal for human identification using four or less of channels of two different types of EEG recordings. Studies have shown that the EEG signal has biometric potential because signal varies from person to person and impossible to replicate and steal. Data were collected from 10 male subjects while resting with eyes open and eyes closed in 5 separate sessions conducted over a course of two weeks. Features were extracted using the wavelet packet decomposition and analyzed to obtain the feature vectors. Subsequently, the neural networks algorithm was used to classify the feature vectors. Results show that, whether or not the subjects- eyes were open are insignificant for a 4– channel biometrics system with a classification rate of 81%. However, for a 2–channel system, the P4 channel should not be included if data is acquired with the subjects- eyes open. It was observed that for 2– channel system using only the C3 and C4 channels, a classification rate of 71% was achieved.}, journal = {International Journal of Biomedical and Biological Engineering}, volume = {4}, number = {8}, year = {2010}, pages = {364 - 368}, ee = {https://publications.waset.org/pdf/1768}, url = {https://publications.waset.org/vol/44}, bibsource = {https://publications.waset.org/}, issn = {eISSN: 1307-6892}, publisher = {World Academy of Science, Engineering and Technology}, index = {Open Science Index 44, 2010}, }