Inferring the stability of LIFE through Brain Machine Interfaces

Author

DiGiovanna, Jack ; Citi, Luca ; Yoshida, Ken ; Carpaneto, Jacopo ; Principe, Jose C. ; Sanchez, Justin C. ; Micera, Silvestro

Author_Institution

Dept. of Biomedical Engineering, University of Florida, 106 BME Bldg. Gainesville, 32611 USA

fYear

2008

fDate

20-25 Aug. 2008

Firstpage

2008

Lastpage

2011

Abstract

We examine neural signals from Longitudinally implanted Intra-Fascicular Electrodes (LIFE) in a chronic, rabbit model. Translation-invariant wavelet de-noising methods are used to improve S%R. Then traditional template-based spike sorting is applied to discriminate single units. We investigate the effect of discriminating between identified units on Brain Machine Interface (BMI) decoding performance. We infer the stability of LIFE based on decoding performance with and without current BMI methods to counter-act electrode neural signal degradation.

Keywords

Biomedical engineering; Decoding; Degradation; Electrodes; Neurons; Rabbits; Signal restoration; Sorting; Stability; Student members; Action Potentials; Algorithms; Animals; Electrodes, Implanted; Electrophysiology; Female; Models, Neurological; Muscle, Skeletal; Rabbits; Signal Processing, Computer-Assisted; User-Computer Interface;

fLanguage

English

Publisher

ieee

Conference_Titel

Engineering in Medicine and Biology Society, 2008. EMBS 2008. 30th Annual International Conference of the IEEE

Conference_Location

Vancouver, BC

ISSN

1557-170X

Print_ISBN

978-1-4244-1814-5

Electronic_ISBN

1557-170X

Type

conf

DOI

10.1109/IEMBS.2008.4649584

Filename

4649584