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arXiv · 1407.2227

A Wavelet Based Algorithm for the Identification of Oscillatory Event-Related Potential Components

Arun Kumar A·Ninan Sajeeth Philip·Vincent J Samar·James A Desjardins·Sidney J Segalowitz
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Abstract

Event Related Potentials (ERPs) are very feeble alterations in the ongoing Electroencephalogram (EEG) and their detection is a challenging problem. Based on the unique time-based parameters derived from wavelet coefficients and the asymmetry property of wavelets a novel algorithm to separate ERP components in single-trial EEG data is described. Though illustrated as a specific application to N170 ERP detection, the algorithm is a generalized approach that can be easily adapted to isolate different kinds of ERP components. The algorithm detected the N170 ERP component with a high level of accuracy. We demonstrate that the asymmetry method is more accurate than the matching wavelet algorithm and t-CWT method by 48.67 and 8.03 percent respectively. This paper provides an off-line demonstration of the algorithm and considers issues related to the extension of the algorithm to real-time applications.

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Arun Kumar A, Ninan Sajeeth Philip, Vincent J Samar, James A Desjardins, Sidney J Segalowitz. 2014-06-20. A Wavelet Based Algorithm for the Identification of Oscillatory Event-Related Potential Components. https://doi.org/10.1016/j.jneumeth.2014.06.004

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