title: [Extraction of single-trial event-related potentials by means of ARX modeling and independent component analysis].
abstract: The present paper focused on the extraction of event-related potentials on a single sweep under extremely low S/N ratio. Two methods that can efficiently remove spontaneous EEG, ocular artifacts and power line interference were presented based on ARX modeling and independent component analysis (ICA). The former method applied ARX model to the measured compound signal that extensively contained the three kinds of ordinary noises mentioned above, and used ARX algorithm for parametric identification. The latter decomposed the signal by means of independent component analysis. Besides, some of ICA's important decomposing characters and its intrinsic causality were pointed out definitely. According to the practical situation, some modification on FastICA algorithm was also given, so as to implement auto-adaptive mapping of decomposed results to ERP component. Through simulation, both the two ways are proved to be highly capable of signal extraction and S/N ratio improving.
authors.affiliation: Department of Electronic Science & Engineering, Nanjing University, Nanjing 210093, China.
authors.forename: Rongchang
authors.initials: R
authors.lastname: Wang
authors.forename: Sidan
authors.initials: S
authors.lastname: Du
mesh_terms: D004569:Electroencephalography / Q000379:methods / Q000706:statistics & numerical data*; D018913:Event-Related Potentials, P300 / Q000502:physiology*; D005071:Evoked Potentials / Q000502:physiology*; D006801:Humans; D012815:Signal Processing, Computer-Assisted