Proceedings of the 9th international conference on Multimodal interfaces
Computer aided diagnosis of ECG data on the least square support vector machine
Digital Signal Processing
Fuzzy relation based modeling for medical diagnostic decision support: Case studies
International Journal of Knowledge-based and Intelligent Engineering Systems
Automatic EEG signal classification for epilepsy diagnosis with Relevance Vector Machines
Expert Systems with Applications: An International Journal
Evaluating of traumatic brain injuries using artificial neural networks
Expert Systems with Applications: An International Journal
Classification of EEG signals using relative wavelet energy and artificial neural networks
Proceedings of the first ACM/SIGEVO Summit on Genetic and Evolutionary Computation
Statistics over features: EEG signals analysis
Computers in Biology and Medicine
Expert Systems with Applications: An International Journal
Epileptic seizure detection in EEGs using time-frequency analysis
IEEE Transactions on Information Technology in Biomedicine - Special section on computational intelligence in medical systems
Heartbeat time series classification with support vector machines
IEEE Transactions on Information Technology in Biomedicine - Special section on biomedical informatics
Automatic recognition of epileptic seizure in EEG via support vector machine and dimension fractal
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
Computers in Biology and Medicine
Computers in Biology and Medicine
Combination of EEG complexity and spectral analysis for epilepsy diagnosis and seizure detection
EURASIP Journal on Advances in Signal Processing
International Journal of Innovative Computing and Applications
Kernel machines for epilepsy diagnosis via EEG signal classification: A comparative study
Artificial Intelligence in Medicine
Review article: Human scalp EEG processing: Various soft computing approaches
Applied Soft Computing
Clustering technique-based least square support vector machine for EEG signal classification
Computer Methods and Programs in Biomedicine
A tunable support vector machine assembly classifier for epileptic seizure detection
Expert Systems with Applications: An International Journal
Evaluation of Fuzzy Relation Method for Medical Decision Support
Journal of Medical Systems
Time-frequency distributions in the classification of epilepsy from EEG signals
Expert Systems with Applications: An International Journal
A systematic approach to embedded biomedical decision making
Computer Methods and Programs in Biomedicine
International Journal of Knowledge Discovery in Bioinformatics
Detection of artifacts from high energy bursts in neonatal EEG
Computers in Biology and Medicine
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In this paper, we proposed the multiclass support vector machine (SVM) with the error-correcting output codes for the multiclass electroencephalogram (EEG) signals classification problem. The probabilistic neural network (PNN) and multilayer perceptron neural network were also tested and benchmarked for their performance on the classification of the EEG signals. Decision making was performed in two stages: feature extraction by computing the wavelet coefficients and the Lyapunov exponents and classification using the classifiers trained on the extracted features. The purpose was to determine an optimum classification scheme for this problem and also to infer clues about the extracted features. Our research demonstrated that the wavelet coefficients and the Lyapunov exponents are the features which well represent the EEG signals and the multiclass SVM and PNN trained on these features achieved high classification accuracies