On ordered weighted averaging aggregation operators in multicriteria decisionmaking
IEEE Transactions on Systems, Man and Cybernetics
On the issue of obtaining OWA operator weights
Fuzzy Sets and Systems
Toward Machine Emotional Intelligence: Analysis of Affective Physiological State
IEEE Transactions on Pattern Analysis and Machine Intelligence - Graph Algorithms and Computer Vision
Wearable and automotive systems for affect recognition from physiology
Wearable and automotive systems for affect recognition from physiology
Active and Dynamic Information Fusion for Facial Expression Understanding from Image Sequences
IEEE Transactions on Pattern Analysis and Machine Intelligence
Generating optimal adaptive fuzzy-neural models of dynamicalsystems with applications to control
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
A hybrid clustering and gradient descent approach for fuzzymodeling
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
OWA aggregation over a continuous interval argument with applications to decision making
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Modeling prioritized multicriteria decision making
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Active affective State detection and user assistance with dynamic bayesian networks
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A probabilistic framework for modeling and real-time monitoring human fatigue
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
A fuzzy classifier with ellipsoidal regions
IEEE Transactions on Fuzzy Systems
An online self-constructing neural fuzzy inference network and its applications
IEEE Transactions on Fuzzy Systems
Quantitative weights and aggregation
IEEE Transactions on Fuzzy Systems
International Journal of Human-Computer Studies
Driving profile modeling and recognition based on soft computing approach
IEEE Transactions on Neural Networks
A driver fatigue recognition model based on information fusion and dynamic Bayesian network
Information Sciences: an International Journal
Review article: Human scalp EEG processing: Various soft computing approaches
Applied Soft Computing
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To achieve an effective and safe operation on the machine system where the human interacts with the machine mutually, there is a need for the machine to understand the human state, especially cognitive state, when the human's operation task demands an intensive cognitive activity. Due to a well-known fact with the human being, a highly uncertain cognitive state and behavior as well as expressions or cues, the recent trend to infer the human state is to consider multimodality features of the human operator. In this paper, we present a method for multimodality inferring of human cognitive states by integrating neuro-fuzzy network and information fusion techniques. To demonstrate the effectiveness of this method, we take the driver fatigue detection as an example. The proposed method has, in particular, the following new features. First, human expressions are classified into four categories: (i) casual or contextual feature, (ii) contact feature, (iii) contactless feature, and (iv) performance feature. Second, the fuzzy neural network technique, in particular Takagi-Sugeno-Kang (TSK) model, is employed to cope with uncertain behaviors. Third, the sensor fusion technique, in particular ordered weighted aggregation (OWA), is integrated with the TSK model in such a way that cues are taken as inputs to the TSK model, and then the outputs of the TSK are fused by the OWA which gives outputs corresponding to particular cognitive states under interest (e.g., fatigue). We call this method TSK-OWA. Validation of the TSK-OWA, performed in the Northeastern University vehicle drive simulator, has shown that the proposed method is promising to be a general tool for human cognitive state inferring and a special tool for the driver fatigue detection.