ISSN 1000-1239 CN 11-1777/TP

计算机研究与发展 ›› 2016, Vol. 53 ›› Issue (3): 716-725.doi: 10.7544/issn1000-1239.2016.20140743

• 其他应用技术 • 上一篇    

5种基本情绪的心肺系统生理反应模式

刘烨,王思睿,傅小兰   

  1. (脑与认知科学国家重点实验室(中国科学院心理研究所) 北京 100101) (中国科学院心理研究所 北京 100101) (liuye@psych.ac.cn)
  • 出版日期: 2016-03-01
  • 基金资助: 
    国家“九七三”重点基础研究发展计划基金项目(2011CB302201);国家自然科学基金项目(61375009)

Patterns of Cardiorespiratory Activity Associated with Five Basic Emotions

LiuYe,WangSirui,FuXiaolan   

  1. (State Key Laboratory of Brain and Cognitive Science (Institute of Psychology, Chinese Academy of Sciences), Beijing 100101) (Institute of Psychology, Chinese Academy of Sciences, Beijing 100101)
  • Online: 2016-03-01

摘要: 情感交互是自然人机交互发展的必然趋势.生理计算为感知和识别用户的生理和情感状态提供了新的途径. 通过阅读文字情境,14名被试分别体验悲伤、喜悦、惊奇、恐惧、愤怒5种基本情绪和中性情绪,并以相应的情绪语调说出与情境有关的特定话语,考察了人们在上述5种基本情绪下的自主神经系统生理反应.使用BIOPAC MP150生理仪和可穿戴式感受器终端记录被试在言语过程中的心电和呼吸数据,并据此分析12项心肺活动指标.结果表明:除悲伤外,其他4种基本情绪下的生理反应与中性情绪存在显著或边缘显著差异;5种情绪所引发的生理反应模式在一定程度上存在差异.该研究表明,基本情绪所引发的心肺系统反应模式存在差异,为基于用户的生理反应模式对用户的情感状态进行识别提供了实验支持证据,通过捕捉心电和呼吸信号可以有效地监测用户的情感状态.

关键词: 情绪, 情感交互, 自主神经反应模式, 心肺活动指标, 生理计算

Abstract: Affective interaction is the inexorable trend of the development of natural interaction. Physiological computing provides a new approach to understand the physiological and emotional states of users. However, there is no scientific consensus on whether there exists a stable relation between emotional states and the physiological responses. The present study review the recent research on physiological responses of autonomic nervous system activity in emotion and addressed to investigate the profile of autonomic nervous responses during the experience of five basic emotions: sadness, happiness, fear, anger, surprise and neutral. ECG and respiratory activity of fourteen healthy volunteers was recorded with BIOPAC SYSTEM MP150 during their reading passages with five basic emotional tones and neutral tone. Twelve indexes computed off-line from ECG and respiratory activities were employed as dependent variables for statistic analysis. The results indicate that significant or marginal differences are detected between the neutral and four basic emotions, except for sadness. The physiological patterns of the five basic emotions are different. Therefore, these results provide the positive evidence for the notion that the distinct patterns of peripheral physiological activity are associated with different emotions. The findings also indicate that it is feasible and effective to recognize users’ affective states based on physiological response patterns of ECG and respiratory activities.

Key words: emotion, affective interaction, autonomic response pattern, cardiorespiratory activity index, physiological computing

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