Dual-pathway EEG model with channel attention for virtual reality motion sickness detection.

Journal: Journal of neuroscience methods
PMID: 40086600

Abstract

BACKGROUND: Motion sickness has been a key factor affecting user experience in Virtual Reality (VR) and limiting the development of the VR industry. Accurate detection of Virtual Reality Motion Sickness (VRMS) is a prerequisite for solving the problem.

Authors

  • Chengcheng Hua
    * Department of Mechanical Engineering and Automation, Northeastern University, Shenyang 110819, P. R. China.
  • Yuechi Chen
    School of Automation, C-IMER, CICAEET, Nanjing University of Information Science & Technology, Nanjing 210044, China.
  • Jianlong Tao
    School of Automation, C-IMER, CICAEET, Nanjing University of Information Science & Technology, Nanjing 210044, China.
  • Zhian Dai
    School of Automation, C-IMER, CICAEET, Nanjing University of Information Science & Technology, Nanjing 210044, China.
  • Wenqing Yang
    School of Automation, C-IMER, CICAEET, Nanjing University of Information Science & Technology, Nanjing 210044, China.
  • Dapeng Chen
    Dalian Medical University, 116044 Dalian City, Liaoning Province, China.
  • Jia Liu
    Department of Colorectal Oncology, Tianjin Medical University Cancer Institute and Hospital, National Clinical Research Center for Cancer, Tianjin's Clinical Research Center for Cancer, Tianjin Key Laboratory of Digestive Cancer, Tianjin, China.
  • Rongrong Fu
    Measurement Technology and Instrumentation Key Laboratory of Hebei Province, Department of Electrical Engineering, Yanshan University, Qinhuangdao 066000, China. Electronic address: frr1102@aliyun.com.

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