Maximizing Learning Potential: An EEG-based Haptic Feedback BCI Solution for Improving Student Focus

Enhancing Focus with Brain-Computer Interfaces—Real-Time EEG-Based Study Assistance

Developed by Ayraman Bhatia, Grace Lim, Nhu Bui, Ramneek Chahil, Vraj Thakkar

Mentored by Prakhar Sinha, Maitri Khanna, Jordan Ogbu Felix

This BCI was entered into the 2023 NeurotechX competition where it won 3rd place. This BCI project utilizes EEG technology with OpenBCI Cyton, Brainflow, and Arduino to detect loss of focus in students by monitoring brainwave patterns and providing real-time haptic feedback to help maintain concentration.

What it does

This BCI was also a project that was in development to present at the 2023 Neurotech California Conference. Their BCI project utilized EEG technology to detect loss of focus in students during study and learning sessions. By monitoring the presence of common indicators of focus that consist of ratios of alpha, beta, and gamma waves, They were able to alert the user when their focus began to wane.

This BCI has utilized several different platforms/technologies: OpenBCI Cyton, Brainflow and Arduino. They were able to develop a simple yet effective solution to use haptic feedback so the user is alerted that their focus is wavering whether it may be towards the end of the session or during the session with a small vibration.

OpenBCI EEG hardware was used to collect samples of the brain waves which were used to detect focus. The placements of the electrodes consisted of the ground and reference electrodes, prefrontal cortex, frontal cortex, parietal cortex, and occipital cortex which helped aid in the detection of focus.