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面部反馈在微表情识别过程中的作用 被引量:2

Facial Feedback and Micro-Expression Recognition
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摘要 采用JACBART范式,通过考察增强面部反馈对高强度微表情识别的影响(实验1)和增强面部反馈对低强度微表情识别的影响(实验2)来探究面部反馈在微表情识别过程中的作用。结果发现:(1)增强面部反馈不能提高被试对高强度微表情识别的准确率;(2)增强面部反馈降低了低强度微表情的识别准确率。研究提示面部反馈参与了微表情的识别过程,但它是一种对微表情识别"有害"的抑制性线索,且这一线索的作用受微表情强度的调节。。 In situations in which individuals are motivated to conceal or repress their true emotions, their facial expressions may leak despite their efforts to conceal them. Many of these leakages are manifested in the form of micro-expressions, and these leakages can be very useful for detection of deception and dangerous demeanor. However, it is difficult for humans to accurately detect and recognize these micro-expressions. Previous studies have shown that facial feedback signals are effective cues in macro-expression recognition. Can facial feedback also be an effective signal in micro-expression recognition? In the present study, we investigated the effects of facial feedback on micro-expression recognition by conducting two behavioral experiments. In these two behavioral experiments, a gel composed ofpolyvinyl alcohol and polyvinylpyrrolidone was applied to participants' full face in order to enhance the facial feedback signals, whereas participants in the control condition had to apply the gel to their non-dominate inner arm. Results of a pilot study showed that the gel manipulation could amplify facial feedback signals by preserving the initiation of muscular movements but increasing the skin resistance to these movements. In experiment 1, we investigated the effects of amplifying facial feedback on the recognition of intense micro- expressions. In this experiment, participants had to finish two behavioral tasks: the micro-expression recognition task and the working memory task. In the micro-expression recognition task, the micro-expressions were presented by employing the JACBART paradigm, in which micro-expressions (lasted for 50ms, 150ms, or 333ms) were sandwiched between the first two presentations of the same expresser's neutral faces. Those facial expressions were selected from the NimStim facial expression database. Those facial expressions were also shown to be high in the intensity level of facial expressions in another pilot study. The recognition accuracy was recorded in the micro-expressio
出处 《心理科学》 CSSCI CSCD 北大核心 2016年第6期1353-1358,共6页 Journal of Psychological Science
基金 国家自然科学基金项目(31300870) 湖南师范大学青年科学基金项目(13XQN01) 湖南师范大学青年优秀人才培养计划项目(社科类,2015yx08)的资助
关键词 面部反馈 微表情 微表情识别 facial feedback, micro-expresssion, micro-expression recognition
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