Separation of multi-channel spinal cord recordings using unsupervised adaptive filtering

Author

Tie, Yanmei ; Sahin, Mesut

Author_Institution

Dept. of Biomed. Eng., Louisiana Tech Univ., Ruston, LA, USA

Volume

3

fYear

2002

fDate

23-26 Oct. 2002

Firstpage

2014

Abstract

In anesthetized animals, evoked motor signals descending through the corticospinal tract were recorded from the spinal cord with selectivity using multi-contact surface electrodes. However, the spatial selectivity needs to be improved for this approach to be used as a multi-channel neural interface. In this study, we applied the blind source separation (BBS) technique to improve the separation between the neural channels. The BSS algorithm improved the selectivity from an initial value of less than 1% to 91% although the signal-to-noise ratio of the signals was as low as 0.46 on average.

Keywords

adaptive filters; adaptive signal processing; biological techniques; electromyography; neurophysiology; anesthetized animals; blind source separation technique; corticospinal tract; evoked motor signals; multichannel neural interface; multichannel spinal cord recordings; multicontact surface electrodes; neuroscience method; selectivity; spatial selectivity; unsupervised adaptive filtering; Adaptive filters; Animals; Biomedical electrodes; Biomedical engineering; Blind source separation; Independent component analysis; Neural networks; Signal to noise ratio; Source separation; Spinal cord;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology, 2002. 24th Annual Conference and the Annual Fall Meeting of the Biomedical Engineering Society EMBS/BMES Conference, 2002. Proceedings of the Second Joint

ISSN

1094-687X

Print_ISBN

0-7803-7612-9

Type

conf

DOI

10.1109/IEMBS.2002.1053143

Filename

1053143