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In this paper we explore the use of electrical biosignals measured on scalpand corresponding to mental relaxation and concentration tasks in order tocontrol an object in a video game. To evaluate the requirements of such asystem in terms of sensors and signal processing we compare two designs. Thefirst one uses only one scalp electroencephalographic (EEG) electrode and thepower in the alpha frequency band. The second one uses sixteen scalp EEGelectrodes and machine learning methods. The role of muscular activity is alsoevaluated using five electrodes positioned on the face and the neck. Resultsshow that the first design enabled 70% of the participants to successfullycontrol the game, whereas 100% of the participants managed to do it with thesecond design based on machine learning. Subjective questionnaires confirmthese results: users globally felt to have control in both designs, with anincreased feeling of control in the second one. Offline analysis of face andneck muscle activity shows that this activity could also be used to distinguishbetween relaxation and concentration tasks. Results suggest that thecombination of muscular and brain activity could improve performance of thiskind of system. They also suggest that muscular activity has probably beenrecorded by EEG electrodes.

Using Scalp Electrical Biosignals to Control an Object by Concentration and Relaxation Tasks: Design and Evaluation