V{u00F5}, T{u00E2}n Quang (Chief Editor)2018-11-222018-11-222012b3088037http://hdl.handle.net/1885/151617Human beings notice differences in their environment and make explicit and implicit differentiations between events and activities. These are very intuitive activities that humans perform on regular basis, studying the cognitive processes behind them will help gain more knowledge on mental tasks, opening up possibilities for better brain-computer interaction (BCI) mechanisms in the future. In this study, these cognitive processes were measured using a non-invasive brain measuring method, Electroencephalography (EEG) as well as a behavioural measure (eye gaze path). Separate experiments were carried out to examine both scenarios of explicit (voluntary) and implicit (involuntary) differentiations. Using a combination of machine learning tools for signal analysis, a high correct rate of classification results in combination with significant statistical figures achieved has shown that one can effectively identify those mental tasks from studying the brainwave and eye gaze measurements. - provided by Candidate.xxii, 106 leaves.en-AUAuthor retains copyrightBF311.V6 2012ElectroencephalographyCognition MeasurementMachine learning201210.25911/5d514ff141b7d2018-11-21