People identification with RMS-Based spatial pattern of EEG signal

Authors:
Salahiddin Altahat;Xu Huang;Dat Tran;Dharmendra Sharma
Affiliations:
Faculty of Information Sciences and Engineering, University of Canberra, ACT, Australia;Faculty of Information Sciences and Engineering, University of Canberra, ACT, Australia;Faculty of Information Sciences and Engineering, University of Canberra, ACT, Australia;Faculty of Information Sciences and Engineering, University of Canberra, ACT, Australia
Venue:
ICA3PP'12 Proceedings of the 12th international conference on Algorithms and Architectures for Parallel Processing - Volume Part II
Year:
2012

Citing 3
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Abstract

Recently, there are increasing interests in proposing novel people identification methods. In this work we propose to use root mean square (rms) to create a spatial pattern of the Electroencephalogram (EEG), and use this pattern in people identification. The proposed method is straight forward and has low cost of computation comparing to recent published methods such as auto regression (AR), independent component analysis (ICA) or wavelet. More importantly, the proposed method gives very promising results.