Independent Component Analysis Applied in Biomedical Signal Processing

Abstract

Abstract. The EEG is composed of electrical potentials arising from several sources. Each source (including separate neural clusters, blink artifact, or pulse artifact) projects a unique topography onto the scalp-'scalp maps'. These maps are mixed according to the principle of linear superposition. Independent component analysis (ICA) attempts to reverse the superposition by separating the EEG into mutually independent scalp maps, or components so that the method used is the study is independent component analysis (ICA). The Polysomnogram (PSG), a complex of more signals recorded over night for the patients with respiratory problems contains also redundant information that can be removed using the ICA.