A Feasibility Study on Enhanced Mobility and Comfort: Wheelchairs Empowered by SSVEP BCI for Instant Noise Cancellation and Signal Processing in Assistive Technology

Abstract

Steady-state visual evoked potential (SSVEP)-based brain-computer interface (BCI) technology offers a promising solution for wheelchair control by translating neural signals into navigation commands. A major challenge-signal noise caused by eye blinks-is addressed in this feasibility study through real-time blink detection and correction. The proposed design utilizes sensors to capture both SSVEP and blink signals, enabling the isolation and compensation of interference, which improves control accuracy by 14.68%. Real-time correction during blinks significantly enhances system reliability and responsiveness. Furthermore, user data and global positioning system (GPS) trajectories are uploaded to the cloud via Wi-Fi 6E for continuous safety monitoring. This approach not only restores mobility for users with physical disabilities but also promotes independence and spatial autonomy.