Feature selection and classifier parameters estimation for EEG signals peak detection using particle swarm optimization

• Main Authors: Adam, Asrul, Shapiai, Mohd. Ibrahim, Mohd. Tumari, Mohd. Zaidi, Mohamad, Mohd. Saberi, Mubin, Marizan
• Format: Article
• Language: English
• Published: Hindawi Publishing Corporation 2014
• Subjects: TK Electrical engineering. Electronics Nuclear engineering
• Online Access: http://eprints.utm.my/id/eprint/52873/1/Mohd.IbrahimShapiai2014_Featureselectionandclassifier.pdf; http://eprints.utm.my/id/eprint/52873/; http://dx.doi.org/10.1155/2014/973063

Electroencephalogram (EEG) signal peak detection is widely used in clinical applications. The peak point can be detected using several approaches, including time, frequency, time-frequency, and nonlinear domains depending on various peak features from several models. However, there is no study that...