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Presenter: Eman Al-bilali , MSc Student, Project supervised by Prof Hatim Aboalsamh and Dr. Areej Alwabil.
Abstract:  Brain computer interfaces (BCIs) have become one of the growing areas for human computer interaction research studies. Initially, brain computer interface research was focused on finding new solutions for paralyzed people to improve their quality of life. Increasingly, alternative applications were proposed and investigated on healthy subjects either for entertainment technologies or usability testing. Various researches were conducted to control graphical user interfaces using brain computer interface methods. Furthermore, eye tracking was another approach used by people to control cursor movements. In this approach, the point of gaze determines x, y screen coordinates facilitating cursor movements. Problem of selecting a target object arises since the point of gaze cannot simulate mouse clicking. Dwell time was suggested as a cursor selection, when a subject's gaze at specific objects for the duration of a specific dwell time results in selecting it. Using this method was a trade-off between accuracy and speed. Some researchers suggest to combine both eye tracking and brain computer interface so each method will cover the other's cons. Eye tracking enable fast intuitive ways of controlling cursor movement while brain computer interface facilitates object selection. In this project we developed an application to investigate object selection using P300 brain signals, eye tracking combined with brain signal and finally using the eye tracker. A consistently designed graphical user interface through the three approaches was developed to test the three input modalities. We conducted several experiments on the three approaches on able-bodied subjects. The aim of these experiments was to evaluate accuracy, time to complete the task and subjective satisfaction. Experimental results show that eye tracking achieves the highest accuracy among the other interaction modalities. P300 was found to produce the lowest accuracy and efficiency results compared to the other input modalities. System usability scales reported by subjects' showed high scores for the eye tracking approach and the combined eye tracking and brain signal approach. P300 achieved moderate scores as reported by subjects.
Eman is a Computer Science MSc student at King Saud University's College of Computer and Information Sciences. She is a Teaching Assistant in the Computer Science Department in King Saud University. Her MSc project "Interpretation of human brain signals to develop a screen GUI", will be completed in Jun 2013 under the supervision of Prof. Hatim abo Alsamh and Dr Areej Al-Wabil.
 Date:  May 27, 2013
Time: 12:00 - 12:30 pm
  Location: Research Center Auditorium, Building 2, Malaz Campus