Automatic target localization using microelectrode recordings

R. A. Santiago, J. McNames, H. Falkenberg, K. Burchiel

Research output: Contribution to journalConference articlepeer-review

1 Scopus citations

Abstract

We describe an algorithm that objectively and automatically identifies target regions in the brain for ablation or stimulation during neurosurgery for Parkinson's disease and other movement disorders. The algorithm uses microelectrode recordings to distinguish between the target and adjacent anatomic structures during stereotactic neurosurgery. This algorithm uses a novel method of signal feature extraction that enables standard classification algorithms such as support vector machines to perform well. The algorithm was validated on microelectrode recordings acquired near the globus pallidus internus and labeled by the neurosurgeon.

Keywords

  • Deep brain stimulation
  • Microelectrode recording
  • Movement disorders
  • Parkinson's disease
  • Spike source identification
  • Support vector machines

ASJC Scopus subject areas

  • Signal Processing
  • Biomedical Engineering
  • Computer Vision and Pattern Recognition
  • Health Informatics

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