Study on EEG-based mouse system by using brain-computer interface

This paper aimed to design an EEG-based mouse system by using brain-computer interface (BCI) to move a cursor on a computer display. This system to provide an alternative communication or control channel for patients with severe motor disabilities. Such patients might become able to select target on a computer monitor by moving a cursor through mental activity. The user could move the cursor just through imaging his/her hand operation on mouse without any actual action while the movement direction that he/she wanted to choose was lighted in the cue line of four-direction choice circulation. This system used an adaptive algorithm to recognize cursor control patterns in multichannel EEG frequency spectra. The algorithm included preprocessing, feature extraction, and classification. A Fisher ratio was defined to determine the characteristic frequency band. The spectral powering this band was calculated as feature parameter to distinguish the task state of imagination of hand movements (IHM) from free state of non-IHM. Mahalanobis distance classifier was employed to recognize the effective task pattern and produce the trigger signal as cursor controller. Relevant experiment results showed that this system achieved 80% accuracy for IHM task/free pattern classification. This EEG-based mouse system is feasible to drive the cursor's four-direction movement and may provide a new communication and control option for patients with severe motor disabilities.