Electrophysiological signal processing for intraoperative localization of subthalamic nucleus during deep brain stimulation surgery

Mahsa Khosravi, Seyed Farokh Atashzar, Greydon Gilmore, Mandar S. Jog, Rajni V. Patel

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

Abstract

In this paper, a novel technique is proposed for localization of Subthalamic Nucleus (STN) during deep brain stimulation (DBS) Surgery. DBS surgery is performed on individuals living with Parkinson's disease (PD) to permanently implant stimulation electrodes for managing some motor symptoms of PD. The most challenging part of this surgery is to accurately place the electrodes inside the STN. Commonly, microelectrode recordings (MERs) are interpreted by the surgical team intraoperatively to estimate the location of electrodes and detect the borders of the STN. In this work, we aim to automate the process of localizing the STN using a machine learning technique (trained based on the electrophysiological signals that we have collected during 20 surgeries). The proposed approach is capable of detecting the dorsal borders of the STN during the procedure with high accuracy (85%), and outperforms the current state-of-the-art approach for this application.

Original languageEnglish (US)
Title of host publication2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages424-428
Number of pages5
ISBN (Electronic)9781728112954
DOIs
StatePublished - Jul 2 2018
Event2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Anaheim, United States
Duration: Nov 26 2018Nov 29 2018

Publication series

Name2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018 - Proceedings

Conference

Conference2018 IEEE Global Conference on Signal and Information Processing, GlobalSIP 2018
Country/TerritoryUnited States
CityAnaheim
Period11/26/1811/29/18

Keywords

  • DBS surgery
  • Electrophysiological Signal Processing
  • Parkinson's disease.
  • STN localization
  • Supervised machine learning

ASJC Scopus subject areas

  • Information Systems
  • Signal Processing

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