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.
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© 2012 Springer-Verlag Berlin Heidelberg
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Altahat, S., Huang, X., Tran, D., Sharma, D. (2012). People Identification with RMS-Based Spatial Pattern of EEG Signal. In: Xiang, Y., Stojmenovic, I., Apduhan, B.O., Wang, G., Nakano, K., Zomaya, A. (eds) Algorithms and Architectures for Parallel Processing. ICA3PP 2012. Lecture Notes in Computer Science, vol 7440. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33065-0_33
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DOI: https://doi.org/10.1007/978-3-642-33065-0_33
Publisher Name: Springer, Berlin, Heidelberg
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