ISSN 0439-755X
CN 11-1911/B
主办:中国心理学会
   中国科学院心理研究所
出版:科学出版社

心理学报 ›› 2010, Vol. 42 ›› Issue (05): 625-632.

• • 上一篇    

交互进化计算对焦虑测量的适用性探析

黄辛隐;张 琰;陈延伟;河林弥志;徐爱兵   

  1. (1 苏州大学教育学院, 苏州) (2 立命馆大学情报理工学部, 日本)
  • 收稿日期:2009-03-11 修回日期:1900-01-01 发布日期:2010-05-30 出版日期:2010-05-30
  • 通讯作者: 黄辛隐

Analysis on Applicability of Interactive Evolutionary Computation to Anxiety Measurement

HUANG Xin-Yin;Yan ZHANG;CHEN Yan-Wei;Hisashi Kawabayashi;XU Ai-Bing   

  1. (1 School of Education, Soochow University, Suzhou, Jiangsu 215123, China)
    (2 College of Information Science and Eng., Ritsumeikan Univ., Shiga, 525-8577, Japan)
  • Received:2009-03-11 Revised:1900-01-01 Online:2010-05-30 Published:2010-05-30
  • Contact: HUANG Xin-Yin

摘要: 大量的研究用stroop色词命名任务和点探测任务等经典的情绪研究方法证明了社交焦虑个体情绪识别的特殊性。该研究采用IEC(交互进化计算)的方法, 研究了焦虑组和对照组(低焦虑组)在情绪感知动态范围上的差异性。实验要求第一组被试利用给出的IEC情绪识别光影系统设计出符合实验维度(高兴、恐惧)的图片, 并让第二组被试对图片进行评估, 得出每幅图片的心理数值范围。实验结果说明IEC可以适用于常规优化系统之外的一个新领域—— 心理健康的测量,同时也表明社交焦虑个体的情绪感知动态范围窄于正常人。

关键词: 交互进化计算, 社交焦虑, 情绪识别, 心理健康测量

Abstract: Previous literatures demonstrate that clinical anxious patients are very sensitive to threatening stimuli, and further, it is easier for them to be engaged in threatening stimuli, including the negative pictures, images and faces. In the present article, we use the faces as the experiment material, which are showed in ways different to the previous researches. This study tries to explore the applicability of this method to anxiety measurement.
In our research, two groups of subjects are involved. The first group includes members that are requested to choose and assess the CG pictures showed on the computer. And the whole process of assessment is carried out based on a new computer technology IEC, (interactive evolutionary computation). IEC is a method for optimizing target systems based on human evaluation criteria, which is broadly used in other fields including facial image generation, speech processing, etc. However, the application of IEC in psychology has not been widely used.
And we have five social anxiety subjects with high scores in IAS and also four ones with low scores in the first group of subjects. IAS is broadly used in measuring the level of social anxiety, which is of good validity and credulity. The social anxiety subjects with high scores in IAS are regarded as experimental subjects and the latter ones are regarded as the control subjects. Other 70 subjects (the second group) in the same university are chosen to be the second group to evaluate the CG images that have been chosen by the first group with Scheff’s method of paired comparison. That is how we have obtained the final psychological scale.
The first step of this experiment has two dimensions: “happy” and “fear”. The subjects of the first group choose and assess the CG images showed on the computer by IEC using five-level rating scale. And then the second group is required to evaluate all the images that have been chosen by the first group. They also used the five-level rating scale to estimate the degree of comparability of all the images. And then we analyze the variance of these estimate data. Statistical tests of the evaluations show: (1) the range of emotional impressions perceived by the five experimental subjects that have high social anxiety between happy-fear is significantly narrower than the control ones (p<0.001). (2) IEC has the potential for the measurement of mental health, especially in the emotional recognition.
It can be concluded that IEC is a new and advanced technology that can be used in the research of psychology. Times’ changing, traditional scales with paper and pen cannot satisfy the need of so many people’s desire for knowing the level of mental health of themselves. This provides an opportunity to apply this computer technology to psychology.

Key words: interactive evolutionary computation, social anxiety, emotional recognition, mental health measurement