An algorithm for source signal extraction from the peripheral nerve

Author

Tang, Yuang ; Wodlinger, Brian ; Durand, Dominique M.

Author_Institution

Dept. of Biomed. Eng., Case Western Reserve Univ., Cleveland, OH, USA

fYear

2011

fDate

Aug. 30 2011-Sept. 3 2011

Firstpage

4251

Lastpage

4254

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 >; 13dB) of the source activities but also minimizes the cross-talk interference between the sources 10 log(P (source of interest)/P (interference sources) >; 14 dB.

Keywords

medical signal processing; neurophysiology; prosthetics; spatial filters; cross-talk interference; external devices; peripheral nerve; prosthetics; signal-noise ratio; source activities; source localization method champagne; source signal extraction algorithm; spatial filters; Algorithm design and analysis; Approximation methods; Filtering algorithms; Interference; Signal to noise ratio; Spatial filters; Algorithms; Animals; Humans; Peripheral Nerves; Rabbits; Signal-To-Noise Ratio;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, EMBC, 2011 Annual International Conference of the IEEE

Conference_Location

Boston, MA

ISSN

1557-170X

Print_ISBN

978-1-4244-4121-1

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2011.6091055

Filename

6091055