Theta-Beta Ratios Are Prominent EEG Features for Visual Tracking Tasks

Abbass H. A. Tang J. Amin R. Ellejmi M. Kirby S. (2014). Augmented cognition using real-time EEG-based adaptive strategies for air traffic control. Paper presented at the Proceedings of the Human Factors and Ergonomics Society Annual Meeting.

Aydemir O. Kayikcioglu T. (2014). Decision tree structure based classification of EEG signals recorded during two dimensional cursor movement imagery. Journal of neuroscience methods, 229, 68-75.

Duan L. Ge H. Ma W. Miao J. (2015). EEG feature selection method based on decision tree. Bio-Medical Materials and Engineering, 26(s1), 1019-1025.

Gayatri N. Nickolas S. Reddy A. V. (2010). Feature selection using decision tree induction in class level metrics dataset for software defect predictions. Paper presented at the Proceedings of the World Congress on Engineering and Computer Science.

Gerhardt G. J. L. Lemke N. Carvalho D. Z. de Santa-Helena E. L. Schönwald S. V. Dellagustin G. Filho J. L. R. (2014). Analysis of EEG Sleep Spindle Parameters from Apnea Patients Using Massive Computing and Decision Tree. Scientia cum Industria, 2(1), 15-18.

Grabczewski K. Jankowski N. (2005). Feature selection with decision tree criterion. Paper presented at the Hybrid Intelligent Systems, 2005. HIS ’05. Fifth International Conference on.

Hall M. Frank E. Holmes G. Pfahringer B. Reutemann P. Witten I. H. (2009). The WEKA data mining software: an update. ACM SIGKDD explorations newsletter, 11(1), 10-18.

Lotte F. Congedo M. Lécuyer A. Lamarche F. (2007). A review of classification algorithms for EEG-based brain–computer interfaces. Journal of neural engineering, 4.

Mihajlovic V. Grundlehner B. Vullers R. Penders J. (2015). Wearable, wireless EEG Solutions in daily life applications: what are we missing? Biomedical and Health Informatics, IEEE Journal of, 19(1), 6-21.

Montgomery D. D. Robb J. Dwyer K. V. Gontkovsky S. T. (1998). Single channel QEEG amplitudes in a bright, normal young adult sample. Journal of Neurotherapy, 2(4), 1-7.

Ratanamahatana C. a. Gunopulos D. (2003). Feature selection for the naive bayesian classifier using decision trees. Applied artificial intelligence, 17(5-6), 475-487.

Stanney K. M. Schmorrow D. D. Johnston M. Fuchs S. Jones D. Hale K. S. . . . Young P. (2009). Augmented cognition: An overview. Reviews of human factors and ergonomics, 5(1), 195-224.

Sugumaran V. Muralidharan V. Ramachandran K. (2007). Feature selection using decision tree and classification through proximal support vector machine for fault diagnostics of roller bearing. Mechanical systems and signal processing, 21(2), 930-942.

Teplan M. (2002). Fundamentals of EEG measurement. Measurement science review, 2(2), 1-11.

Xing S. McCardle R. Xie S. (2012). Reading the mind: The potential of electroencephalography in brain computer interfaces. Paper presented at the Mechatronics and Machine Vision in Practice (M2VIP), 2012 19th International Conference.