Improving BCI usability as HCI in ambient assisted living system control

Abstract

Brain Computer Interface (BCI) technology is an alternative/ augmentative communication channel, based on the interpretation of the user’s brain activity, who can then interact with the environment without relying on neuromuscular pathways. Such technologies can act as alternative HCI devices towards AAL (Ambient Assisted Living) systems, thus opening their services to people for whom interacting with conventional interfaces could be troublesome, or even not viable. We present here a complete solution for BCI-enabled home automation. The implemented solution is, nonetheless, more general in the approach, since both the realized hardware module and the software infrastructure can handle general bio-potentials. We demonstrate the effectiveness of the solution by restricting the focus to a SSVEP-based, self-paced BCI, featuring calibration-less operation and a subject-independent, “plug&play” approach. The hardware module will be validated and compared against a commercial EEG device; at the same time, the signal processing chain will be presented, introducing a novel method for improving accuracy and immunity to false positives. The results achieved, especially in terms of false positive rate containment (0.26 min−1) significantly improve over the literature.