title: A non-orthogonal SVD-based decomposition for phase invariant error-related potential estimation.
abstract: The estimation of the Error Related Potential from a set of trials is a challenging problem. Indeed, the Error Related Potential is of low amplitude compared to the ongoing electroencephalographic activity. In addition, simple summing over the different trials is prone to errors, since the waveform does not appear at an exact latency with respect to the trigger. In this work, we propose a method to cope with the discrepancy of these latencies of the Error Related Potential waveform and offer a framework in which the estimation of the Error Related Potential waveform reduces to a simple Singular Value Decomposition of an analytic waveform representation of the observed signal. The followed approach is promising, since we are able to explain a higher portion of the variance of the observed signal with fewer components in the expansion.
authors.affiliation: Vision and Brain Signal Processing Research Group at GIPSA-lab, Universities of Grenoble/CNRS UMR 5216, Grenoble, France.
authors.forename: Ronald
authors.initials: R
authors.lastname: Phlypo
authors.forename: Nisrine
authors.initials: N
authors.lastname: Jrad
authors.forename: Sandra
authors.initials: S
authors.lastname: Rousseau
authors.forename: Marco
authors.initials: M
authors.lastname: Congedo
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D004569:Electroencephalography / Q000379:methods; D005071:Evoked Potentials; D005583:Fourier Analysis; D006801:Humans; D015233:Models, Statistical; D025341:Principal Component Analysis; D015203:Reproducibility of Results; D012815:Signal Processing, Computer-Assisted; D059629:Signal-To-Noise Ratio; D012984:Software; D013997:Time Factors