IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on recent advances in biometrics
IEEE Transactions on Information Technology in Biomedicine - Special section on new and emerging technologies in bioinformatics and bioengineering
An emotional model for a guide robot
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans - Special issue on model-based diagnostics
Monitoring user's brain activity for a virtual coach
ICEC'10 Proceedings of the 9th international conference on Entertainment computing
Emotion on the road: necessity, acceptance, and feasibility of affective computing in the car
Advances in Human-Computer Interaction - Special issue on emotion-aware natural interaction
Modeling of operators' emotion and task performance in a virtual driving environment
International Journal of Human-Computer Studies
Affect prediction from physiological measures via visual stimuli
International Journal of Human-Computer Studies
Computer Methods and Programs in Biomedicine
Subject-dependent biosignal features for increased accuracy in psychological stress detection
International Journal of Human-Computer Studies
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In this paper, we present a methodology and a wearable system for the evaluation of the emotional states of car-racing drivers. The proposed approach performs an assessment of the emotional states using facial electromyograms, electrocardiogram, respiration, and electrodermal activity. The system consists of the following: 1) the multisensorial wearable module; 2) the centralized computing module; and 3) the system's interface. The system has been preliminary validated by using data obtained from ten subjects in simulated racing conditions. The emotional classes identified are high stress, low stress, disappointment, and euphoria. Support vector machines (SVMs) and adaptive neuro-fuzzy inference system (ANFIS) have been used for the classification. The overall classification rates achieved by using tenfold cross validation are 79.3% and 76.7% for the SVM and the ANFIS, respectively.