EOG Blink-to-Click Brain-Computer Interface

Project Overview

The Blink-to-Click BCI project enables hands-free computer interaction through voluntary eye blinks. It uses electrooculography (EOG) signals captured from the frontal region of the brain (Fp1 and Fp2 electrode positions) to detect intentional blinks and translate them into mouse clicks, providing an accessible input method for individuals with limited mobility or those seeking alternative control interfaces. Prolonged eye closure can be programmed to trigger various customizable actions based on personal preference, such as opening specific applications, navigating to websites, or executing user-defined commands.

This project was made possible by the OpenBCI open-source biosensing platform and the GREENTEK GT Cap BCI. The OpenBCI Cyton board provides the foundation for accessible neurotechnology development, enabling researchers and developers worldwide to explore brain-computer interface applications. Special thanks to OpenBCI for their open-source approach to neurotechnology.

Project Budget: €1.750.

99% Detection Accuracy
250Hz Sampling Rate
0.5s Response Time
30 Feature Vectors

Video Demonstration

Blink detection BCI in action

Watch as I type hands-free using computer vision eye-tracking, an EEG cap, and machine learning trained to register blinks as letter selections.

The machine learning model was trained on extensive datasets containing 8 recordings of 45 seconds each for every action type (eyes open, blink, and closed eyes) resulting in 24 total CSV datasets that ensure robust sample diversity.

Real Life Applications

Diverse real-world applications demonstrating the versatility of brain-computer interface technology

Assistive Technology

Hands-free computer control for users with motor disabilities, enabling mouse clicking and navigation through intentional blink patterns.

Gaming & Entertainment

Immersive gaming experiences where bioelectric signals become natural input methods for virtual reality and interactive entertainment.

Smart Home Automation

EOG-controlled living space where eye blinks toggle lights, adjust temperature, or control entertainment systems.

Future BCI Research Projects

Exploring the frontiers of brain-computer interface technology and next-generation neural applications

Thought-to-Speech Interface

Advanced BCI system using trained machine learning models to recognize the neural patterns associated with different words or phrases. Users can generate speech output simply by thinking about specific words, creating an intuitive and seamless communication experience.

Speech Decoding Neural Networks NLP Processing

Biometric Authentication

Security system that leverages the uniqueness of individual brainwave patterns for authentication. By analyzing specific neural signatures and EEG characteristics, this BCI creates an unbreakable biometric password that's impossible to replicate or steal.

EEG Patterns Biometric Security Identity Verification

Motor Imagery Control

BCI system that interprets imagined movements for controlling robotic prosthetics. Uses advanced signal processing for movement intention classification.

Motor Imagery Robotics Prosthetics

Neural Feedback Training

Neurofeedback system for cognitive enhancement and brain training. Real-time visualization of neural activity to improve focus, meditation, and cognitive performance.

Neurofeedback Cognitive Training Meditation

Technology Used

OpenBCI Cyton Board Ag/AgCl Electrodes BrainFlow Random Forest Scikit-learn NumPy SciPy Pandas PyAutoGUI OpenBCI GUI

Interested in BCI Technology?

Feel free to reach out with any questions about the project.

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