Link to paper:
10.1109/BMEiCON60347.2023.10322025
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Mind to Motion: EEG-Based Classification of Motor Imagery and Actual Hand Movements Using LSTM Models
Project Timeline
Jun 2022 - Jan-2023
OVERVIEW
Developed an EEG-based LSTM classification model to differentiate motor imagery from real hand movements, achieving 62.5% accuracy in imagery vs. action and 72.5% accuracy in rest vs. action, advancing applications in BCI and motor rehabilitation.
HighlightS
- The project received an honorable mention in the Research, Invention, and Creative Work Award for the academic year 2022 by Rangsit University, Thailand.
- Presented the paper at '2023 15th Biomedical Engineering International Conference (BMEiCON'23)' held by IEEE in Tokyo, Japan.
SKILLS
EEG Signal Processing & AcquisitionData preprocessing techniquesDeep Learning Machine Learning Workflow
SUPPORTING MATERIALS
Additional Details
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