Identifying Stable EEG Patterns in Manipulation Task for Negative Emotion Recognition

Negative emotion recognition during manipulation task plays crucial role in human-machine interaction, where diverse cognitive variables coexist and influence each other. However, traditional emotion experiments often overemphasize emotion induction while overlooking other practical cognitive tasks, which leads participants to suffer from simplistic emotional experiences and ultimately compromises the real-world applicability of the emotional data collected. To incorporate critical cognitive variables into emotion elicitation, we utilize joystick-based real-time emotion annotation to encourage subjects to continuously feel emotional intensity, to advisedly decide when to manipulate the joystick, and to…

• NN
  National Natural Science Foundation of China

  Awards: 62406338, 62332019
• BN
  Beijing Nova Program

  Award: 20240484513