Slow cortical potential signal classification using concave-convex feature.

Journal: Journal of neuroscience methods
Published Date: Jun 8, 2019

Abstract

BACKGROUND: The classification of the slow cortical potential (SCP) signals plays a key role in a variety of research areas, including disease diagnostics, human-machine interaction, and education. The widely used classification methods, which combine multiple kinds of features, can be unsuitable in practical applications due to their low robustness to scenario changes.

Authors

  • Huirang Hou
    Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical and Information Engineering, Tianjin University, Tianjin, China.
  • Biao Sun
    Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical and Information Engineering, Tianjin University, Tianjin, China. Electronic address: sunbiao@tju.edu.cn.
  • Qinghao Meng
    Tianjin Key Laboratory of Process Measurement and Control, Institute of Robotics and Autonomous Systems, School of Electrical and Information Engineering, Tianjin University, Tianjin, China. Electronic address: qh_meng@tju.edu.cn.

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