DocumentCode :
718358
Title :
Guiding deep brain stimulation contact selection using local field potentials sensed by a chronically implanted device in Parkinson´s disease patients
Author :
Connolly, Allison T. ; Kaemmerer, William F. ; Dani, Siddharth ; Stanslaski, Scott R. ; Panken, Eric ; Johnson, Matthew D. ; Denison, Timothy
Author_Institution :
Univ. of Minnesota, Minneapolis, MN, USA
fYear :
2015
fDate :
22-24 April 2015
Firstpage :
840
Lastpage :
843
Abstract :
We have found that a set of support vector machines operating upon local field potentials sensed from an implanted DBS lead can identify the contact chosen by the physician for the patient´s STN DBS therapy with 91% accuracy. The finding is based on a small data set and thus subject to change with further data collection and cross-validation. Nevertheless, the results suggest that an algorithm for selecting an effective contact for STN DBS based on the signals sensed from the DBS lead may be feasible.
Keywords :
bioelectric potentials; brain; diseases; medical signal processing; neurophysiology; patient treatment; support vector machines; Parkinson´s disease patients; STN DBS therapy; chronically implanted device; deep brain stimulation contact selection; local field potentials; support vector machines; Diseases; Electrodes; Medical treatment; Programming; Satellite broadcasting; Support vector machines;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Engineering (NER), 2015 7th International IEEE/EMBS Conference on
Conference_Location :
Montpellier
Type :
conf
DOI :
10.1109/NER.2015.7146754
Filename :
7146754
Link To Document :
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