title: An algorithm for source signal extraction from the peripheral nerve.
abstract: Extracting physiological signals to control external devices such as prosthetics is a field of research that offers great hope for patients suffering from disabilities. In this paper, a novel source signal extraction algorithm, based on the source localization method Champagne, is presented. The algorithm constructs spatial filters that not only maximizes the signal to noise ratio (SNR > 13 dB) of the source activities but also minimizes the cross-talk interference between the sources 10log((P(source of interest)/P(interference sources)) > 14 dB.
authors.affiliation: Department of Biomedical Engineering, Case Western Reserve University, Cleveland, OH 44106, USA. dyt1@ case.edu
authors.forename: Yuang
authors.initials: Y
authors.lastname: Tang
authors.forename: Brian
authors.initials: B
authors.lastname: Wodlinger
authors.forename: Dominique M
authors.initials: DM
authors.lastname: Durand
mesh_terms: D000465:Algorithms; D000818:Animals; D006801:Humans; D010525:Peripheral Nerves; D011817:Rabbits; D059629:Signal-To-Noise Ratio