Abstract:We designed a healthcare system that focuses on emotional aspects to cope with negative emotions in daily life. Our emotional healthcare system integrates emotion recognition based on facial expressions and ECG signals to identify user emotions to provide appropriate services. Recognizing emotions from facial expressions is sometimes difficult to correctly recognize them when users hide their emotions from their appearance. To solve this, emotion recognition using ECG signals is applied because they cannot be controlled by humans, since they are directly affected by mental states including emotions. This paper focuses on emotion recognition using ECG signals. To recognize emotions from them, we adapted the local binary pattern (LBP) and local ternary pattern (LTP) which are favorable local pattern description methods for emotion recognition by facial expressions. We evaluated the LBP and LTP performances. Our results indicate that they effectively extracted ECG features with high accuracy. In real-time evaluation, we experimentally evaluated its efficiency and effectiveness for recognizing negative emotions. Our results show that the real-time emotion recognition from ECG signal is beneficial and efficient enough for emotional healthcare system to analyze negative emotions to provide assistance.
Our emotional healthcare system is designed to cope with users' negative emotions in daily life. To make the system more intelligent, we integrated emotion recognition by facial expression to provide appropriate services based on user's current emotional state. Our emotion recognition by facial expression has confusion issue to recognize some positive, neutral and negative emotions that make the emotional healthcare system provide a relaxation service even though users don't have negative emotions. Therefore, to increase the effectiveness of the system to provide the relaxation service, we integrate stress detection from ECG signal. The stress detection might be able to address the confusion issue of emotion recognition by facial expression to provide the service. Indeed, our results show that integration of stress detection increases the effectiveness and efficiency of the emotional healthcare system to provide services.
In recent years, several systems have been proposed to emphasize the support of physical aspects at the expense of emotional aspects. However, emotional health is as important as physical health and negative emotional health can lead to social or mental health problems. To cope with negative emotional health, we propose a new healthcare system that focuses on emotional aspects. Our healthcare system integrates augmented reality to display virtual objects in real environments and Kinect, which allows users to freely interact with them. We also employ biological sensors to measure and detect user emotions, and provide three services based on their expected emotions: relaxation, amusement and excitement services. This paper focuses on the implementation of a breathing control application in the relaxation service that applied deep breathing techniques of stress management to supports users when they experience stress and other negative emotions. This application displays a virtual music box to assist them perform deep breathing. Virtual objects and music can increase user relaxation and decrease stress.
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