生物信号,面部表情和语音作为工作场所压力的衡量标准:Workstress3d数据集
Gulin Dogan1, Fatma Patlar Akbulut2, Cagatay Catal3
1Department of Computer Engineering, Istanbul Aydın University, Istanbul, Turkey.
Data in brief
|April 1, 2024
概括
工作压力3D提供多式工作场所压力数据,包括生物信号,面部表情和语音. 这一数据集有助于开发压力检测模型和了解工作环境影响.
科学领域:
- 多模式数据分析数据分析多模式数据分析
- 职业健康心理学 职业健康心理学
- 生物医学工程 生物医学工程
背景情况:
- 工作场所的压力是影响员工幸福感和生产力的重要问题.
- 现有的数据集往往缺乏生态有效性或多模式数据,阻碍了全面的压力研究.
- 多式联络数据融合对精确的压力检测和分析具有前景.
研究的目的:
- 介绍WorkStress3D,这是一个用于工作场所压力研究的新型多式联络数据集.
- 为开发和验证压力检测算法提供丰富的资源.
- 促进在职业环境中对压力的生理和行为指标的调查.
主要方法:
- 在现实工作环境中收集多式联络数据 (生物信号,面部表情,语音).
- 包括电皮活动,血压,皮肤温度,高分辨率视频和语音信号等测量.
- 通过在实际工作环境中收集数据来确保生态有效性,既有无压力和有压力的情况.
主要成果:
- 工作压力3D数据集包括全面的生物信号,面部和语音数据.
- 数据有注释,包括用于深入分析的元数据.
- 数据集代表了无压力和有压力的工作情况的平衡样本.
结论:
- 工作压力3D是压力分析的有价值,生态有效的资源.
- 该数据集支持先进的压力检测模型的开发和评估.
- 它可以研究多式联运数据融合,以更好地了解工作场所的压力.
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