A hybrid BCI web browser based on EEG and EOG signals.

Area of Science:

• Neuroscience
• Human-Computer Interaction
• Biomedical Engineering

Background:

• Traditional web browsing relies on physical input devices.
• Brain-computer interfaces (BCIs) offer alternative control methods for individuals with motor impairments.
• Hybrid BCIs integrating multiple signal types can enhance control accuracy and robustness.

Purpose of the Study:

• To develop and evaluate a novel web browser utilizing a hybrid BCI.
• To enable users to navigate and interact with web content using a combination of EEG and EOG signals.
• To assess the feasibility and effectiveness of the proposed BCI-controlled web browser.

Main Methods:

• A hybrid BCI system was developed, integrating electroencephalography (EEG) for imagined hand movements and electrooculography (EOG) for eye blinks.
• Users controlled mouse cursor movement (horizontal via EEG, vertical via EOG), target selection, and text input through synchronized blinking with GUI elements.
• An online experiment was conducted with five healthy subjects to evaluate the system's performance.

Main Results:

• The hybrid BCI system allowed users to control mouse movement, select targets, and input text within the web browser.
• Experimental results demonstrated the effectiveness of the proposed method in enabling web browsing functionalities.
• Subjects were able to open web pages, select targets, and read content using the BCI.

Conclusions:

• The proposed hybrid BCI approach is effective for web browsing.
• Combining EEG and EOG signals provides a viable method for intuitive human-computer interaction.
• This technology holds potential for improving web accessibility and user experience.