title: A new approach in the BCI research based on fractal dimension as feature and Adaboost as classifier.
abstract: High rate classification of imagery tasks is still one of the hot topics among the brain computer interface (BCI) groups. In order to improve this rate, a new approach based on fractal dimension as feature and Adaboost as classifier is presented for five subjects in this paper. To have a comparison, features such as band power, Hjorth parameters along with LDA classifier have been taken into account. Fractal dimension as a feature with Adaboost and LDA can be considered as alternative combinations for BCI applications.
authors.affiliation: Amir Kabir University of Technology, Faculty of Biomedical Engineering, Tehran, Iran.
authors.forename: Reza
authors.initials: R
authors.lastname: Boostani
authors.forename: Mohammad Hassan
authors.initials: MH
authors.lastname: Moradi
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D003143:Communication Devices for People with Disabilities; D003936:Diagnosis, Computer-Assisted / Q000379:methods; D004569:Electroencephalography / Q000379:methods*; D005071:Evoked Potentials / Q000502:physiology*; D017709:Fractals; D006801:Humans; D007092:Imagination / Q000502:physiology; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D014584:User-Computer Interface