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An Approach to Analysis of Physiological Responses to Stimulus From Electrodermal Activity to Combined Physiological Responses

机译:一种分析生理反应对电台活性的生理反应与综合生理反应

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Recent advances in wearable devices capable of measuring physiological signals such as Electrodermal Activity (EDA) support affective computing and related applications. We present an algorithm that uses EDA signals to detect highlights of a stimulus. To test the accuracy of our method, two different mediums, a scene from a movie, as our ground truth, and a scene from a video game, for testing the algorithm, were selected. We conducted a user study with 20 participants, analyzed the differences between mediums and validated the accuracy of our method for detecting the highlights of the stimulus using only EDA signals. Our approach uses commonalities among users based on their phasic responses for detecting highlights. The result of the study shows a Fl score of 0.93 and 0.89 for movie and video game respectively. We are in a process of conducting a user study with several sensory devices to explore combined physiological responses using IAPS data set as a stimulus.
机译:可穿戴设备的最新进展能够测量电台活性(EDA)等生理信号支持情感计算和相关应用。我们介绍了一种使用EDA信号来检测刺激的亮点的算法。为了测试我们方法的准确性,选择了两种不同的媒介,从电影中的场景,作为我们的地面真理以及用于测试算法的视频游戏的场景。我们用20名参与者进行了用户学习,分析了培养基之间的差异,并验证了我们仅使用EDA信号检测刺激的亮点的方法的准确性。我们的方法基于对检测亮点的相位响应来使用用户之间的共性。该研究的结果分别显示了电影和视频游戏的0.93和0.89的FL得分。我们正在进行具有多个感官设备的用户学习,以探索使用IAPS数据作为刺激的组合生理反应。

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