Emotion recognition using heart rate data from a smart bracelet and a 'neutral + target' video pair paradigm was effective using Adaboost and GBDT classifiers on a 25-subject dataset.
Can heart rate data from a wearable smart bracelet be used to effectively recognize emotions?
Heart rate data from a smart bracelet can effectively recognize emotions using a 'neutral + target' stimulation paradigm and machine learning classifiers.
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.
Shu et al. (Tue,) conducted a other in Emotion recognition (n=25). Emotion recognition using heart rate data from a smart bracelet was evaluated on Emotion recognition effectiveness. Emotion recognition using heart rate data from a smart bracelet and a 'neutral + target' video pair paradigm was effective using Adaboost and GBDT classifiers on a 25-subject dataset.
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