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.
<p>As a combination of the three elements of modern information technology, smart sensor network is a brand-new information collection and management technology. The smart sensor network is composed of a large number of smart sensor nodes with low energy consumption. In order to improve the performance of pattern design, this paper proposes an urban sculpture artwork pattern design framework based on intelligent sensor network. It uses intelligent sensor network technology to build design models and design patterns for urban sculptures. Based on the introduction of intelligent sensor network technology, various computer software and pattern texture calculation methods are used to process the urban sculpture pattern in the design process, and the construction of the urban sculpture pattern model is completed through the construction process of the urban sculpture pattern intelligent sensor network mode. Experimental results show that the average design time of urban sculpture patterns based on smart sensor network technology is 0.42 s, the average resolution is 7200 pixels, and the average dot pitch is 0.27mm. Compared with traditional 3D technology pattern design methods, the design performance of urban sculpture patterns based on intelligent sensor network technology is better, and it meets the design requirements of urban sculpture patterns.</p> <p> </p>
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