title: A wavelet based algorithm for the identification of oscillatory event-related potential components.
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.
authors.affiliation: St. Thomas College, Kozhencherry 689641, Kerala, India. Electronic address: aka.bhagya@gmail.com.
authors.forename: Arun Kumar
authors.initials: AK
authors.lastname: Aniyan
authors.affiliation: St. Thomas College, Kozhencherry 689641, Kerala, India. Electronic address: nspp@iucaa.ernet.in.
authors.forename: Ninan Sajeeth
authors.initials: NS
authors.lastname: Philip
authors.affiliation: Rochester Institute of Technology, 52 Lomb Memorial Drive, Rochester, NY 14623, USA. Electronic address: vjsncr@rit.edu.
authors.forename: Vincent J
authors.initials: VJ
authors.lastname: Samar
authors.affiliation: Brock University, 500 Glenridge Avenue, St. Catharines, ON L2S 3A1, Canada. Electronic address: jdesjardins@brocku.ca.
authors.forename: James A
authors.initials: JA
authors.lastname: Desjardins
authors.affiliation: Brock University, 500 Glenridge Avenue, St. Catharines, ON L2S 3A1, Canada. Electronic address: ssegalowitz@brocku.ca.
authors.forename: Sidney J
authors.initials: SJ
authors.lastname: Segalowitz
mesh_terms: D000328:Adult; D000465:Algorithms; D001921:Brain / Q000502:physiology*; D004569:Electroencephalography / Q000379:methods*; D005071:Evoked Potentials; D005260:Female; D006801:Humans; D008297:Male; D010363:Pattern Recognition, Automated; D012146:Rest; D058067:Wavelet Analysis; D055815:Young Adult
keywords: N170 ERP detection; Single-trial EEG; Wavelet asymmetry