面部表情识别在一般性焦虑症查中的可靠性和有效性
Xueqing Ren1, Shanshan Su1, Wenhui Jiang1
1Shanghai Mental Health Center, Shanghai Jiao Tong University School of Medicine, Shanghai, China.
Journal of affective disorders
|October 10, 2024
概括
面部表情识别显示出作为客观工具的承诺,以帮助诊断泛性焦虑障碍 (GAD). 这种方法可以通过补充主观评估来提高准确性,为心理健康查提供一种新的方法.
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 (面部识别)
- 生物医学工程 生物医学工程
背景情况:
- 泛性焦虑障碍 (GAD) 是中国普遍存在的精神健康状况.
- 目前的GAD评估依赖于主观措施,增加了诊断错误的风险.
- 需要客观的生物指标来提高GAD识别的准确性.
研究的目的:
- 验证面部表情识别作为一般性焦虑障碍的查工具.
- 开发一个客观的,自动化的方法来协助诊断GAD.
主要方法:
- 基于国际情感图像系统的实验范式被用来记录面部表情.
- 在60名GAD患者和60名对照人群中,使用GAD-7和HAMA尺度评估了与标准相关的有效性.
- 使用MINI作为评估选性能的黄金标准进行了接收器操作特征 (ROC) 分析.
主要成果:
- 面部表情分析显示,中性情绪,愤怒情绪和恐惧情绪 (p < 0.001) 有显著的群间影响.
- GAD尺度和面部表情之间的皮尔森相关性在 -0.35 到 0.34 (p < 0.01) 之间.
- 在ROC分析中,曲线下的面积 (AUC) 值为中立的0.723,愤怒的0.792,恐惧的面部表情为0.727.
结论:
- 面部表情识别是GAD患者辅助查的一个可行的工具.
- 这项研究提供了一个客观的,自动化的方法来支持焦虑症的心理诊断.
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