Computer Interface and Electric Wheelchair

The investigation of steady-state visual evoked potential (SSVEP) for brain-computer interface (BCI) and the study of electric wheelchair control present an exciting field of research that aims to enhance the lives of individuals with motor disabilities. SSVEP is a neurophysiological response generated by the brain when exposed to repetitive visual stimuli. It has gained significant attention as a reliable signal for BCI systems, allowing users to control external devices using their brain activity.

This research explores the potential of SSVEP as a means to develop a robust and efficient BCI system for electric wheelchair control. By leveraging the brain’s response to visual stimuli, users can select directional commands, enabling them to navigate and control electric wheelchairs with ease and precision.

The study involves investigating the characteristics and parameters of SSVEP signals, such as frequency, amplitude, and latency, to optimize the performance of the BCI system. Advanced signal processing techniques, including filtering, feature extraction, and classification algorithms, are employed to accurately detect and interpret SSVEP patterns.

Furthermore, the research delves into the design and implementation of user-friendly interfaces and control strategies for electric wheelchair operation. Human factors, ergonomics, and user experience play a vital role in developing intuitive and efficient control interfaces that align with the needs and capabilities of the intended users.

The ultimate goal of this investigation is to create a seamless and reliable BCI system that enables individuals with motor disabilities to regain mobility and independence through intuitive control of electric wheelchairs. Such advancements have the potential to significantly improve the quality of life for individuals facing mobility challenges, granting them greater autonomy and freedom of movement.