A high-performance general computer cursor control scheme based on a hybrid BCI combining motor imagery and...

Area of Science:

• Neuroscience
• Biomedical Engineering
• Human-Computer Interaction

Background:

• Neuromuscular disabilities present significant challenges to digital interaction.
• Existing assistive technologies often lack sufficient accuracy and ease of use.
• Brain-computer interfaces (BCIs) offer a promising avenue for restoring digital capabilities.

Purpose of the Study:

• To develop and evaluate a novel hybrid BCI system for virtual cursor control.
• To enhance cursor control accuracy, simplicity, and usability for individuals with neuromuscular impairments.
• To facilitate fundamental computing tasks and online community integration for users.

Main Methods:

• Integration of eye-tracking technology with motor imagery (MI) based BCI.
• Real-time classification algorithms for cursor control.
• System implementation within common operating systems for practical application.
• Evaluation of cursor control accuracy, stability, and text input rate.

Main Results:

• Achieved real-time classification accuracy of 87.92% (peak 93.33%).
• Demonstrated high cursor stability in the gazing state at 96.1%.
• Enabled practical tasks including text entry (53.2 CPM), chatting, email, web browsing, and file manipulation.

Conclusions:

• The hybrid eye-tracking and MI-BCI system significantly improves virtual cursor control for users with neuromuscular disabilities.
• The technology enhances digital accessibility, enabling participation in online activities.
• This research paves the way for advanced BCI applications and improved quality of life.