Rough set algorithms in classification problem
Rough set methods and applications
Regularity analysis and its applications in data mining
Rough set methods and applications
IEEE Transactions on Pattern Analysis and Machine Intelligence
Toward Machine Emotional Intelligence: Analysis of Affective Physiological State
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
The production and recognition of emotions in speech: features and algorithms
International Journal of Human-Computer Studies - Application of affective computing in humanComputer interaction
Categorical imperative NOT: facial affect is perceived continuously
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Emotion recognition from physiological signals using wireless sensors for presence technologies
Cognition, Technology and Work
Neural Networks - Special issue: Emotion and brain
RIONA: A New Classification System Combining Rule Induction and Instance-Based Learning
Fundamenta Informaticae
International Journal of Human-Computer Studies
Using noninvasive wearable computers to recognize human emotions from physiological signals
EURASIP Journal on Applied Signal Processing
International Journal of Human-Computer Studies
International Journal of Human-Computer Studies
A Survey of Affect Recognition Methods: Audio, Visual, and Spontaneous Expressions
IEEE Transactions on Pattern Analysis and Machine Intelligence
Fundamentals of physiological computing
Interacting with Computers
Short-term emotion assessment in a recall paradigm
International Journal of Human-Computer Studies
A GMM based 2-stage architecture for multi-subject emotion recognition using physiological responses
Proceedings of the 1st Augmented Human International Conference
IEEE Transactions on Information Technology in Biomedicine - Special section on affective and pervasive computing for healthcare
Toward Emotion Recognition in Car-Racing Drivers: A Biosignal Processing Approach
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Subject-dependent biosignal features for increased accuracy in psychological stress detection
International Journal of Human-Computer Studies
Computer Methods and Programs in Biomedicine
Emoções na interação humano-computador: um estudo considerando sensores
Proceedings of the 12th Brazilian Symposium on Human Factors in Computing Systems
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This study aims to predict different affective states via physiological measures with three types of computational models. An experiment was designed to elicit affective states with standardized affective pictures when multiple physiological signals were measured. Three data mining methods (i.e., decision rules, k-nearest neighbours, and decomposition tree) based on the rough set technique were then applied to construct prediction models from the extracted physiological features. We created three types of prediction models, i.e., gender-specific (male vs. female), culture-specific (Chinese vs. Indian vs. Western), and general models (participants with different genders and cultures as samples), and direct comparisons were made among these models. The best average prediction accuracies in terms of the F"1 measures (the harmonic mean of precision and recall) were 60.2%, 64.9%, 63.5% for the general models with 14, 21, and 42 samples, 78.0% for the female models, 75.1% for the male models, 72.0% for the Chinese models, 73.0% for the Indian models, and 76.5% for the Western models, respectively. These results suggested that the specific models performed better than did the general models.