Affective computing
Wearable and automotive systems for affect recognition from physiology
Wearable and automotive systems for affect recognition from physiology
Emotions and heart rate while sitting on a chair
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Recognizing emotions for the audio-visual document indexing
ISCC '04 Proceedings of the Ninth International Symposium on Computers and Communications 2004 Volume 2 (ISCC"04) - Volume 02
Towards an Algebraic Modeling of Emotional States
ICIW '10 Proceedings of the 2010 Fifth International Conference on Internet and Web Applications and Services
EmotionML - an upcoming standard for representing emotions and related states
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part I
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In this study, we propose a new method of recognizing emotional states from physiological signals. Our proposal uses signal processing techniques to analyze physiological signals. It permits to recognize not only the basic emotions (e.g., anger, sadness, fear) but also any kind of complex emotion, including simultaneous superposed or masked emotions. This method consists of two main steps: the training step and the detection step. In the First step, our algorithm extracts the features of emotion from the data to generate an emotion training data base. Then in the second step, we apply the k-nearest-neighbor classifier to assign the predefined classes to instances in the test set. The final result is defined as an eight components vector representing emotion in multidimensional space. Experiments show the efficiency of the proposed method in detecting basic emotion by giving hight recognition rate.