Abstract
Emotional abnormality may be brought out by physiological fatigue. In order to solve the problem, an emotion detection method based on deep learning in medical and health data is proposed in this paper. First of all, the related content of emotional fatigue is studied. The concept and the classification of emotional fatigue are introduced. Then, a multi-modal data emotional fatigue detection system is designed. In the system, multi-channel convolutional aotoencoder neural network is used to extract electrocardiograms (ECG) data features and emotional text features for emotional fatigue detection. Secondly, the network structure of learning ECG features by multi-channel convolutional aotoencoder model is introduced in detail. And the network structure of learning emotional text features by convolutional aotoencoder model is also described in detail. Finally, multi-modal data features are combined for emotional detection. It is shown by the experimental results that the proposed model has an average accuracy of more than 85% in predicting emotional fatigue.
Highlights
In today’s society, the pace of people’s life is speeding up
Xu et al.: Intelligent Emotion Detection Method Based on Deep Learning in Medical and Health Data data quickly and accurately, how to use high-speed network to transmit medical and health data reliably and efficiently, and how to mine useful information from big data of health care with machine learning and deep learning related to artificial intelligence and further develop intelligent applications for medical staff and ordinary people
In order to avoid the limitations of artificial design features, a multi-channel convolutional aotoencoder neural network structure is proposed
Summary
In today’s society, the pace of people’s life is speeding up. With the stress on entering school, employment, work, and family, people may suffer from strong mental pressure for a long time. When people’s emotions are in a state of fluctuation, over tension, depression or pessimism for a long time, psychological diseases may occur. J. Xu et al.: Intelligent Emotion Detection Method Based on Deep Learning in Medical and Health Data data quickly and accurately, how to use high-speed network to transmit medical and health data reliably and efficiently, and how to mine useful information from big data of health care with machine learning and deep learning related to artificial intelligence and further develop intelligent applications for medical staff and ordinary people. Aiming at the problems related to the analysis of health care data and the development of intelligent application, the risk assessment of chronic diseases that have great impact on people’s health is studied in this paper. It is proposed to establish a multimodal emotional fatigue detection system in this paper. The importance of each word in the sentence is expressed effectively, and more hidden information is obtained
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