five

Kosonogov et al - Data

收藏
DataCite Commons2020-09-01 更新2024-07-25 收录
下载链接:
https://figshare.com/articles/dataset/Kosonogov_et_al_-_Data/5379139
下载链接
链接失效反馈
官方服务:
资源简介:
Functional infrared thermal imaging (fITI) is considered an upcoming method to measure emotional autonomic responses through facial cutaneous thermal variations. However, the facial thermal response to emotion still needs to be investigated in the framework of the dimensional approach to emotions. Hence, the main aim of this study was to assess how the facial thermal variations index the emotional arousal and valence dimensions of visual stimuli. Twenty-four participants were presented with three groups of standardized emotional pictures (unpleasant, neutral and pleasant) from the International Affective Picture System. Facial temperature was recorded at the nose tip, an important region of interest for facial thermal variations, and compared to electrodermal responses, a robust index of emotional arousal. Both types of responses were also compared to subjective ratings of pictures. An emotional arousal effect was found on the amplitude and the latency of thermal responses and on the amplitude and the frequency of electrodermal responses. The participants showed greater thermal and dermal responses to emotional than to neutral pictures with no difference between pleasant and unpleasant ones. The thermal responses correlated and the dermal ones tended to correlate with the subjective ratings. Finally, in the emotional conditions compared to the neutral one, the frequency of simultaneous thermal and dermal responses increased while the isolated responses, thermal or dermal, decreased. Overall, this study brings convergent arguments to consider fITI as a promising method reflecting the arousal dimension of emotional stimulation and, consequently, as a credible alternative to the classical recording of electrodermal activity. The present research provides an original unveiler of autonomic implication in emotional processes and opens new perspectives to measure them in touch-less conditions.
提供机构:
figshare
创建时间:
2017-09-07
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作