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Wearable Emotion Recognition Using Heart Rate Data from a Smart Bracelet

机译:使用来自智能手环的心率数据进行可穿戴情绪识别

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摘要

Emotion recognition and monitoring based on commonly used wearable devices can play an important role in psychological health monitoring and human-computer interaction. However, the existing methods cannot rely on the common smart bracelets or watches for emotion monitoring in daily life. To address this issue, our study proposes a method for emotional recognition using heart rate data from a wearable smart bracelet. A ‘neutral + target’ pair emotion stimulation experimental paradigm was presented, and a dataset of heart rate from 25 subjects was established, where neutral plus target emotion (neutral, happy, and sad) stimulation video pairs from China’s standard Emotional Video Stimuli materials (CEVS) were applied to the recruited subjects. Normalized features from the data of target emotions normalized by the baseline data of neutral mood were adopted. Emotion recognition experiment results approved the effectiveness of ‘neutral + target’ video pair simulation experimental paradigm, the baseline setting using neutral mood data, and the normalized features, as well as the classifiers of Adaboost and GBDT on this dataset. This method will promote the development of wearable consumer electronic devices for monitoring human emotional moods.
机译:基于常用可穿戴设备的情绪识别和监视在心理健康监视和人机交互中可以发挥重要作用。但是,现有的方法不能依靠普通的智能手镯或手表进行日常生活中的情绪监测。为了解决这个问题,我们的研究提出了一种使用可穿戴智能手环的心率数据进行情绪识别的方法。提出了“中性+目标”对情绪刺激实验范例,并建立了来自25个受试者的心率数据集,其中来自中国标准“情绪视频刺激”材料的中性与目标情绪(中性,快乐和悲伤)刺激视频对( CEVS)应用于招募的受试者。采用通过中性情绪基线数据归一化的目标情绪数据归一化特征。情绪识别实验结果证实了“中性+目标”视频对模拟实验范式的有效性,使用中性情绪数据的基线设置,归一化特征以及该数据集上Adaboost和GBDT的分类器。这种方法将促进可穿戴式消费电子设备的发展,以监测人类的情绪。

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