Social Risk and Depression: Evidence from Manual and Automatic Facial Expression Analysis.

Jeffrey M Girard, Jeffrey F Cohn, Mohammad H Mahoor, Seyedmohammad Mavadati, Dean P Rosenwald
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Abstract

Investigated the relationship between change over time in severity of depression symptoms and facial expression. Depressed participants were followed over the course of treatment and video recorded during a series of clinical interviews. Facial expressions were analyzed from the video using both manual and automatic systems. Automatic and manual coding were highly consistent for FACS action units, and showed similar effects for change over time in depression severity. For both systems, when symptom severity was high, participants made more facial expressions associated with contempt, smiled less, and those smiles that occurred were more likely to be accompanied by facial actions associated with contempt. These results are consistent with the "social risk hypothesis" of depression. According to this hypothesis, when symptoms are severe, depressed participants withdraw from other people in order to protect themselves from anticipated rejection, scorn, and social exclusion. As their symptoms fade, participants send more signals indicating a willingness to affiliate. The finding that automatic facial expression analysis was both consistent with manual coding and produced the same pattern of depression effects suggests that automatic facial expression analysis may be ready for use in behavioral and clinical science.

社会风险与抑郁:手动和自动面部表情分析的证据
研究抑郁症状严重程度随时间的变化与面部表情之间的关系。在一系列临床访谈过程中,对抑郁症患者进行了全程跟踪和录像。通过手动和自动系统对视频中的面部表情进行分析。对于 FACS 动作单元,自动编码和手动编码高度一致,并对抑郁症严重程度随时间的变化表现出相似的效果。在这两种系统中,当症状严重程度较高时,参与者会做出更多与蔑视相关的面部表情,微笑较少,而且在微笑时更有可能伴有与蔑视相关的面部动作。这些结果符合抑郁症的 "社会风险假说"。根据这一假说,当症状严重时,抑郁参与者会从其他人那里退缩,以保护自己免受预期的拒绝、蔑视和社会排斥。随着症状的消退,参与者会发出更多表示愿意与他人交往的信号。自动面部表情分析与人工编码一致,并产生了相同的抑郁效应模式,这一发现表明自动面部表情分析可以用于行为和临床科学。
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