khushwant18/Grasp-and-Lift-EEG-detection
Deep learning techniques for detecting 6 types of hand movements from labeled dataset procured from Kaggle, Grasp-and-Lift EEG Detection.
This project helps researchers and engineers working on Brain-Computer Interfaces (BCI) interpret electroencephalography (EEG) signals. It takes raw, multi-channel EEG recordings of a person performing grasp-and-lift hand movements as input. The output is a classification of six specific hand actions (e.g., "Hand Start," "Lift Off") happening within short timeframes. It's intended for those developing systems to understand or predict human motor intent from brain activity.
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Use this if you need to detect and classify specific hand movement intentions from complex EEG data for BCI applications or motor neuroprosthetics.
Not ideal if you are looking for a real-time, production-ready system, as this focuses on evaluating different deep learning models and preprocessing techniques.
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Feb 28, 2021
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