DocumentCode
2743922
Title
An artificial neural network approach to predicting arm movements from ECoG
Author
Cornwell, A.S. ; Kirsch, R.F. ; Burgess, R.C.
Author_Institution
Dept. of Biomedical Eng., Case Western Reserve Univ., Cleveland, OH, USA
Volume
2
fYear
2004
fDate
1-5 Sept. 2004
Firstpage
4241
Lastpage
4243
Abstract
There are three specific aims. First, demonstrate the practicality of using an artificial neural network based approach to correlate these cortical signals with actual and imagined arm movements. Second, to identify areas of the cortical surface that provide the most useful command information. Third, quantify the information content and information transfer rate of the signals obtained from the subdural grids relative to a set of relevant arm movements. This work presents progress toward these aims.
Keywords
bioelectric phenomena; biomechanics; neural nets; neurophysiology; arm movement prediction; artificial neural network; cortical signals; electrocorticogram; information content; information transfer rate; Artificial neural networks; Biological neural networks; Biomedical engineering; Electrical stimulation; Electrodes; Nervous system; Neural prosthesis; Neuromuscular stimulation; Signal processing; Sternum; Artificial Neural Networks; Brain Machine Interface; Funtional Electrical Stimulation;
fLanguage
English
Publisher
ieee
Conference_Titel
Engineering in Medicine and Biology Society, 2004. IEMBS '04. 26th Annual International Conference of the IEEE
Conference_Location
San Francisco, CA
Print_ISBN
0-7803-8439-3
Type
conf
DOI
10.1109/IEMBS.2004.1404182
Filename
1404182
Link To Document