A Utility Human Machine Interface Using Low Cost EEG Cap and Eye Tracker

Electroencephalogram (EEG) based Brain Computer Interface (BCI) has a huge market with big potential and wide prospect, however, the acquisition equipment is too expensive to be popular with ordinary users, which makes the majority of applications are still in the laboratory. Inspired by the development of hybrid Human-Computer Interaction (HCI), a utility HCI using low-cost EEG cap and eye tracker are investigated in this paper. The validation experiment indicates that the proposed system is able to detect and classify multiple patterns of EEG signals and translate them into control commands to interact with the environment. Furthermore, an eye tracker enables subjects to freely observe the surrounding environment and select a target object under the naked eye VR technique. Comparing to the HCI only based on eye tracker, EEG signals are used to realize the motor function in this paper to reduce the fatigue caused by long-time fixation in traditional eye tracker application. Furthermore, compared to the BCI system at the same price, the lack of electrodes can be compensated by an eye tracker. In conclusion, the hybrid HCI proposed in this paper achieves superior performance through low-cost equipment, which may promote the development of the interaction between the human and environment based on the physiological signals.