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

机译:一种分析从皮肤电活动到综合生理反应的刺激生理反应的方法

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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:能够测量生理信号(例如皮肤电活动(EDA))的可穿戴设备的最新进展支持情感计算和相关应用。我们提出了一种使用EDA信号来检测刺激亮点的算法。为了测试我们方法的准确性,选择了两种不同的媒介,一种是​​电影中的场景作为我们的地面真理,另一种是视频游戏中的场景,用于测试算法。我们与20名参与者进行了一项用户研究,分析了培养基之间的差异,并验证了仅使用EDA信号检测刺激亮点的方法的准确性。我们的方法基于用户的阶段性响应,利用用户之间的共通性来检测亮点。研究结果显示电影和视频游戏的F1得分分别为0.93和0.89。我们正在使用几种感官设备进行用户研究,以使用IAPS数据集作为刺激来探索综合的生理反应。

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