Online identification of functional regions in deep brain stimulation based on an unsupervised random forest with feature selection.

Journal: Journal of neural engineering
PMID: 31266003

Abstract

OBJECTIVE: The identification of functional regions, in particular the subthalamic nucleus, through microelectrode recording (MER) is the key step in deep brain stimulation (DBS). To eliminate variability in a neurosurgeon's judgment, this study presents an online identification method for identifying functional regions along the electrode trajectory.

Authors

  • Lei Cao
    State Key Laboratory of Robotics, Shenyang Institute of Automation, Chinese Academy of Sciences, Shenyang, Liaoning, People's Republic of China. Institutes for Robotics and Intelligent Manufacturing, Chinese Academy of Sciences, Shenyang, Liaoning, People's Republic of China. University of Chinese Academy of Sciences, Beijing, People's Republic of China.
  • Jie Li
    Guangdong-Hong Kong-Macao Greater Bay Area Artificial Intelligence Application Technology Research Institute, Shenzhen Polytechnic University, Shenzhen, China.
  • Yuanyuan Zhou
    Shanghai Key Laboratory of Forensic Medicine, Shanghai Forensic Service Platform, Academy of Forensic Science, Ministry of Justice, Shanghai, 200063, China; Department of Forensic Medicine, Inner Mongolia Medical University, Huhhot, Inner Mongolia, 010110, China.
  • Yunhui Liu
  • Yiwen Zhao
  • Hao Liu
    Key Laboratory of Development and Maternal and Child Diseases of Sichuan Province, Department of Pediatrics, Sichuan University, Chengdu, China.

Keywords

External Resources

Popular Topics
Recent Journals