EEG Signal Preprocessing for AI Enhancement

I'm seeking a professional with extensive experience in EEG data preprocessing to assist with cleaning a large dataset of EEG signals. The ultimate goal is to improve the performance of AI models by enhancing the quality of the data.

Key Responsibilities:
- Remove all artifacts from the data, including eye movement artifacts, electrode drift noise, and muscle movement noise.
- Utilize various EEG preprocessing techniques to clean the data, including Filtering, Independent Component Analysis (ICA), and Artifact Subspace Reconstruction (ASR) or other helpful techniques.

Data Format:
- The EEG data is currently in EDF format.

Ideal Skills and Experience:
- Extensive experience with EEG data preprocessing techniques.
- Proficiency in working with EDF formatted data.
- Familiarity with AI model requirements.
- Able to implement various EEG preprocessing techniques.

If you have the expertise to enhance the quality of this data for analysis and improve AI model performance, please get in touch!

Dataset link: https://github.com/tsyoshihara/Alzheimer-s-Classification-EEG/tree/master