Abstract
Recognizing emotional states is becoming a major part of user context for wearable computing applications. The approach presented here starts from the research hypothesis that a wearable system can acquire a user’s emotional state by using physiological sensors. The purpose is to develop a personal emotional states recognition system that is practical, reliable, and can be used for health-care related applications. We use, as book chapter three described, the eHealth platform [1] which is a ready-made, light weight, small and easy to use device. The intension is to recognize emotional states like ‘Sad’, ‘Dislike’, ‘Joy’, ‘Stress’, ‘Normal’, ‘No-Idea’, ‘Positive’ and ‘Negative’ using a decision tree classifier. In this chapter, we present an approach that exhibits this property and provides evidence based on data for eight different emotional states collected from 24 different subjects. Our results indicate that the system has an accuracy rate of approximately 98%.
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Khan, A.M., Lawo, M. (2018). Recognizing Emotional States An Approach Using Physiological Devices. In: Lawo, M., Knackfuß, P. (eds) Clinical Rehabilitation Experience Utilizing Serious Games. Advanced Studies Mobile Research Center Bremen. Springer Vieweg, Wiesbaden. https://doi.org/10.1007/978-3-658-21957-4_9
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DOI: https://doi.org/10.1007/978-3-658-21957-4_9
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