Computer Navigation and Control Using BCI

The project introduces a novel approach to computer navigation and control using Brain-Computer Interfaces (BCI). BCI enables individuals to interact with computers using their brainwaves, offering a new way of smartly interacting with technology. The work presents a new concept that is designed to help individuals with physical disabilities use computers more easily. The Electroencephalogram (EEG) technology is utilized to record the brainwave patterns and detect signals associated with movement. This allows the user to operate their computer using their eye movements. Eye movement is a crucial real-time input medium for human-computer communication, especially for people with physical disabilities. The Emotive EEG headset, which consists of five electrodes, records electrical signals from different regions of the brain. These signals are processed using EEGLAB to preprocess and extract events, and then classified using a Multilayer Perceptron (MLP) network, trained using Scaled Conjugate Gradient (SCG) optimization. The project also includes a motor imagery experiment, which involves the user imagining the movement of their limbs while their EEG signals are recorded. The signals are then processed and classified using the aforementioned methods to provide control commands to the computer. The EEG technology's portability and ease of use make it a promising option for researchers and individuals interested in exploring the potential of BCI technology. The proposed approach has the potential to provide a more accessible and efficient way of computer navigation and control for individuals with physical disabilities. In summary, this project introduces a new concept for computer navigation and control using BCI and EEG technology. The inclusion of a motor imagery experiment and the use of machine learning techniques to classify EEG signals make this project an exciting contribution to the field of BCI research.