根据视频中情绪刺激引起的面部暗示来检测抑郁症
Bin Hu1, Yongfeng Tao1, Minqiang Yang1
1Gansu Provincial Key Laboratory of Wearable Computin, Lanzhou University, Lanzhou, 730000, Gansu, China.
Computers in biology and medicine
|September 14, 2023
概括
使用刺激情绪的面部表情分析显示,它有望用于检测抑郁症. 这种非接触方法通过分析面部动作单位 (AU) 和头部运动,实现了76.25%的准确性.
科学领域:
- 精神病学和心理学 精神病学和心理学
- 计算机科学与工程 计算机科学与工程
- 生物医学工程 生物医学工程
背景情况:
- 越来越需要客观和验证的抑郁症检测方法.
- 面部表情分析提供一种非接触式的方法,有可能提供超越自然表情的宝贵见解.
- 刺激的面部表情可能会显示出更有信息的线索来检测抑郁症.
研究的目的:
- 探索健康对照组和抑郁症患者的面部暗示,以应对不同的情绪刺激.
- 提出和验证使用刺激面部表情检测抑郁症的局部面部重组方法.
- 调查不同情绪刺激在引起面部表情变化的有效性.
主要方法:
- 在62名受试者 (健康对照组和抑郁患者) 观看视频刺激时收集了面部表情.
- 提出了局部面部重组方法,提取了局部相位模式,面部动作单元 (AU) 和头部运动特征.
- 利用分类器,根据提取的面部特征区分健康对照组和抑郁症患者.
主要成果:
- 获得了76.25%的分类准确度,80.44%的回忆率和83.21%的特异性.
- 在这两组中,消极的视频刺激在引起面部表情变化方面最有效.
- 从中性和消极刺激中面部特征的融合改善了群体之间的歧视.
- 面部AU变化与负面刺激的相关性更强.
结论:
- 提出的方法证明了使用刺激面部表情来检测抑郁症的可行性.
- 面部表情分析,特别是在负面情绪刺激下,显示出作为辅助诊断工具的潜力.
- 这项研究为计算机辅助抑郁症诊断的未来进展提供了框架.
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