Artificial Bee Colony Algorithm for Single-Trial Electroencephalogram Analysis

• Published in: Clinical EEG and neuroscience Vol. 46; no. 2; pp. 119 - 125
• Main Authors: Hsu, Wei-Yen, Hu, Ya-Ping
• Format: Journal Article
• Language: English
• Published: Los Angeles, CA SAGE Publications 01.04.2015; SAGE PUBLICATIONS, INC
• Subjects: Algorithms; Animals; Bees; Biomimetics - methods; Brain; Brain - physiology; Brain Mapping - methods; Brain-Computer Interfaces; Electroencephalography; Electroencephalography - methods; Evoked Potentials - physiology; Female; Humans; Male; Neurosciences; Pattern Recognition, Automated - methods; Reproducibility of Results; Sensitivity and Specificity; Statistics as Topic; artificial bee colony (ABC); brain–computer interface (BCI); independent component analysis (ICA); support vector machine (SVM); autoregressive (AR) model; phase-locking value; electroencephalogram (EEG)

In this study, we propose an analysis system combined with feature selection to further improve the classification accuracy of single-trial electroencephalogram (EEG) data. Acquiring event-related brain potential data from the sensorimotor cortices, the system comprises artifact and background noise...