BEETL AI Challenge
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About
The BEETL AI Challenge focuses on developing innovative algorithmic solutions for electroencephalography (EEG) data analysis, posing two main tasks: one on automatic sleep stage annotation for medical diagnostics, and another on motor imagery decoding for Brain-Computer Interfaces (BCI). By addressing the challenges of transfer learning across different EEG setups and minimal training data, this initiative seeks to enhance the decoding of brain states, facilitating advancements in healthcare technologies driven by biosignal data.
Platform
Task
Features
• automatic sleep stage annotation
• motor imagery decoding
• focus on transfer learning and meta-learning
• eeg data analysis
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