Guiding deep brain stimulation contact selection using local field potentials sensed by a chronically implanted device in Parkinson's disease patients

Allison T. Connolly, William F. Kaemmerer, Siddharth Dani, Scott R. Stanslaski, Eric Panken, Matthew D Johnson, Timothy Denison

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

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.

Original languageEnglish (US)
Title of host publication2015 7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
PublisherIEEE Computer Society
Pages840-843
Number of pages4
ISBN (Electronic)9781467363891
DOIs
StatePublished - Jul 1 2015
Event7th International IEEE/EMBS Conference on Neural Engineering, NER 2015 - Montpellier, France
Duration: Apr 22 2015Apr 24 2015

Publication series

NameInternational IEEE/EMBS Conference on Neural Engineering, NER
Volume2015-July
ISSN (Print)1948-3546
ISSN (Electronic)1948-3554

Other

Other7th International IEEE/EMBS Conference on Neural Engineering, NER 2015
CountryFrance
CityMontpellier
Period4/22/154/24/15

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