Noninvasive Human-Computer Interface Methods and Applications for Robotic Control: Past, Current, and Future.

Journal: Computational intelligence and neuroscience
Published Date:

Abstract

The purpose of this study is to explore the noninvasive human-computer interaction methods that have been widely used in various fields, especially in the field of robot control. To have a deep understanding of the development of the methods, this paper employs "Mapping Knowledge Domains" (MKDs) to find research hotspots in the area to show the future potential development. Through the literature review, this paper found that there was a paradigm shift in the research of noninvasive BCI technologies for robotic control, which has occurred from early 2010 since the rapid development of machine learning, deep learning, and sensory technologies. This study further provides a trend analysis that the combination of data-driven methods with optimized algorithms and human-sensory-driven methods will be the key areas for the future noninvasive method development in robotic control. Based on the above findings, the paper provides a potential developing way of noninvasive HCI methods for related areas including health care, robotic system, and media.

Authors

  • Xiaomei Hu
    Center for SCDM, School of Media and Law, NingboTech University, Ningbo 315100, China.
  • Yajuan Liu
    Center for SCDM, School of Media and Law, NingboTech University, Ningbo 315100, China.
  • Hao Lan Zhang
    Center for SCDM, School of Media and Law, NingboTech University, Ningbo 315100, China.
  • Wei Wang
    State Key Laboratory of Quality Research in Chinese Medicine, Institute of Chinese Medical Sciences, University of Macau, Macau 999078, China.
  • Yijie Li
    Accenture, London, United Kingdom.
  • Chao Meng
    Chao Meng, Department of Clinical Laboratory Medicine, Tianjin Second People's Hospital, Tianjin, China.
  • Zhengke Fu
    Center for SCDM, School of Media and Law, NingboTech University, Ningbo 315100, China.