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基于EEG的情感大脑计算机接口:最近的进展和未来的挑战

Yuxin Chen1, Yong Peng1,2, Jiajia Tang1

  • 1School of Computer Science and Technology, Hangzhou Dianzi University, Hangzhou 310018, People's Republic of China.

Journal of neural engineering
|June 9, 2025
PubMed
概括
此摘要是机器生成的。

本综述总结了使用脑电图 (EEG) 进行情感识别和调节的情感脑电脑接口 (aBCI) 的进展. 它强调了现实世界 aBCI 应用的挑战和机遇,重点关注心理健康.

关键词:
这是一个EEGEEGEEGEEGEEGEEGEEG.情感大脑 计算机界面情绪的识别和调节情绪的识别和调节.个体间的变异性.

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科学领域:

  • 神经科学是一个神经科学.
  • 计算机科学 计算机科学
  • 生物医学工程 生物医学工程

背景情况:

  • 情感大脑计算机接口 (aBCI) 从神经调节的脑信号解码情绪,特别是对于抑郁和焦虑.
  • 电脑电图 (EEG) 是捕捉与情绪状态相关的神经活动的关键模式.
  • 最近的进展旨在增强基于EEG的闭环aBCI系统,以改善情绪识别和调节.

研究的目的:

  • 系统地审查基于EEG的情绪识别和调节在闭环aBCI系统中的当前进展.
  • 确定关键挑战和未来的研究方向,以弥合实验室研究和实际aBCI应用之间的差距.
  • 为aBCI领域的学术界和行业利益相关者提供全面的概述.

主要方法:

  • 使用Web of Science和相关数据库进行了系统的文献审查,确定了100多项研究.
  • 研究分析基于实验范式,不同情景的情感识别方法,以及在情感障碍诊断和调节中的应用.
  • 该审查还考虑了基于EEG的情绪识别和调节的神经机制和理论基础.

主要成果:

  • 基于EEG的aBCI的进展总结在六个关键领域:情绪诱导,EEG数据探索,多式联络数据融合,跨场景识别,现实场景考虑和情绪障碍应用.
  • 确定了阻碍实际部署aBCI的关键挑战.
  • 概述了aBCI发展的未来机会,重点关注现实世界应用的基本技术.

结论:

  • 该审查巩固了基于EEG的情绪识别和调节的当前做法和表现.
  • 未来的研究应该解决已识别的挑战,以促进实际的aBCI系统部署.
  • 为专注于广泛采用所需的关键aBCI技术提供了指导.