Affective computing
Toward Machine Emotional Intelligence: Analysis of Affective Physiological State
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
SmartCar: Detecting Driver Stress
ICPR '00 Proceedings of the International Conference on Pattern Recognition - Volume 4
Interaction Reproducing Model: A Model for Giving Supports Appropriate to User State
PCM '08 Proceedings of the 9th Pacific Rim Conference on Multimedia: Advances in Multimedia Information Processing
ACM Transactions on Accessible Computing (TACCESS)
Smart cooking support system based on interaction reproducing model
CEA '09 Proceedings of the ACM multimedia 2009 workshop on Multimedia for cooking and eating activities
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A real-time user-independent emotion detection system using physiological signals has been developed. The system has the ability to classify affective states into 2-dimensions using valence and arousal. Each dimension ranges from 1 to 5 giving a total of 25 possible affective regions. Physiological signals were measured using 3 biometric sensors for Blood Volume Pulse (BVP), Skin Conductance (SC) and Respiration (RESP). Two emotion inducing experiments were conducted to acquire physiological data from 13 subjects. The data from 10 of these subjects were used to train the system, while the remaining 3 datasets were used to test the performance of the system. A recognition rate of 62% for valence and 67% for arousal was achieved within +/- 1 units of the valence and arousal rating.