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.
journal_name
J Neurosci Methodsjournal_title
Journal of neuroscience methodsauthors
Aniyan AK,Philip NS,Samar VJ,Desjardins JA,Segalowitz SJdoi
10.1016/j.jneumeth.2014.06.004subject
Has Abstractpub_date
2014-08-15 00:00:00pages
63-72eissn
0165-0270issn
1872-678Xpii
S0165-0270(14)00210-6journal_volume
233pub_type
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