A review on microelectrode recording selection of features for machine learning in deep brain stimulation surgery for Parkinson's disease.

Journal: Clinical neurophysiology : official journal of the International Federation of Clinical Neurophysiology
PMID: 30293864

Abstract

OBJECTIVE: This study seeks to systematically review the selection of features and algorithms for machine learning and automation in deep brain stimulation surgery (DBS) for Parkinson's disease. This will assist in consolidating current knowledge and accuracy levels to allow greater understanding and research to be performed in automating this process, which could lead to improved clinical outcomes.

Authors

  • Kai Rui Wan
    Department of Neurosurgery, National Neuroscience Institute, Singapore; Department of Neurosurgery, Singapore General Hospital, Singapore.
  • Tomasz Maszczyk
    School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore.
  • Angela An Qi See
    Department of Neurosurgery, National Neuroscience Institute, Singapore; Department of Neurosurgery, Singapore General Hospital, Singapore.
  • Justin Dauwels
    School of Electrical and Electronic Engineering, Nanyang Technological University, Singapore, Singapore.
  • Nicolas Kon Kam King
    National Neuroscience Institute, Singapore.

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