基于HRV的复杂情绪识别:特征识别和情绪特定指标选择
Da-Yeon Kang1, Chan-Il Kim2, Jong-Ha Lee1
1Department of Biomedical Engineering, School of Engineering, Keimyung University, Daegu 42601, Republic of Korea.
Healthcare (Basel, Switzerland)
|December 11, 2025
概括
心率变化 (HRV) 可以区分复杂的情绪,如积极和消极的惊喜和悲伤. 一个非接触式系统 (DHVS) 显示了通过HRV识别这些情绪的潜力,类似于胸设备.
科学领域:
- 心理生理学 心理生理学
- 情感计算是一种情感计算.
- 生物医学工程 生物医学工程
背景情况:
- 目前的情绪识别系统通常使用离散状态和基于接触的传感器.
- 复杂的情绪是基本情绪的混合,受到价值方向的影响.
- 心率变化 (HRV) 是情绪状态的潜在生理标志物.
研究的目的:
- 使用HRV区分四种复合情绪 (积极的惊喜,消极的惊喜,积极的悲伤,消极的悲伤).
- 评估基于无接触摄像头的系统 (深度健康视觉系统,DHVS) 与参考设备 (极地H10) 相比.
- 探索HRV,主观情感报告 (情感,兴奋,主导) 和情感组成之间的关系.
主要方法:
- 十个健康的成年人观看了引发情感的视频片段.
- HRV是使用极地H10胸和DHVS网络摄像头系统记录的.
- 计算了标准HRV指数,并通过统计分析检查了变化,相关性和设备一致性.
主要成果:
- 主观报告证实了四种复合情绪的不同情感特征.
- HRV变化与价值,兴奋和主导相关,具有对情绪类别 (LF/HF) 和价值 (总功率) 敏感的特定指数.
- DHVS系统与极地H10部分一致,特别是在正值条件下.
结论:
- 人力资源维度捕捉了复杂情绪的独特自主签名,与主观评价相关.
- LF/HF和总功率提供了对情绪类别和价值的互补见解.
- DHVS 证明了作为复杂情绪识别的无接触平台的初步可行性,需要进一步验证.
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