Development of an Online Home Appliance Control System Using Augmented Reality and an SSVEP-Based Brain-Computer Interface
Seonghun Park, Ho‐Seung Cha, Jinuk Kwon, Hodam Kim, Chang‐Hwan Im
Abstract
In this study, we implemented a new home appliance control system by combining a steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI), augmented reality (AR), and internet of things (IoT) technologies. The visual stimuli were presented on a see-through head-mounted display (HMD), while the recorded brain activity was analyzed to classify the control command, and the home appliances were controlled through IoT. The average classification accuracy of the SSVEP-BCI-based control system was 92.8%, with an information transfer rate (ITR) of 37.4 bits/min. The proposed system exhibited an excellent performance, surpassing the best results reported in previous studies regarding external device control based on BCI using an HMD as rendering device.