Designing a BMI-based robotic arm using EEG and motor articulation control
In this project, we will use EEG recordings to control robotic arm by extracting left and right side motor imagery movement patterns. We will develop and use feature extraction methods to extract the required features from the pre-processed signal data. As a precursor in addition to detailed biophysical modelling, we have also started modifying feature extraction methods to appropriately recognize the mental tasks or motor tasks based on EEG signals.Features that can be significantly employed to distinguish different classes are extracted to make classifiers of BCI systems with a good performance. The project aims to develop and deploy a potential method for low-cost neuroprosthetic arms that could be controlled using EEG-based signal.