ANESTHESIA
Assumptions:
- The EEG data is stored in EDF files (European Data Format).
- You have access to Python libraries like MNE, scipy, pandas, numpy, sklearn, and pycatch22.
- Your dataset contains the necessary metadata, such as mentation categories and EEG features.
Functions:
- Load and preprocess EEG data.
- Extract features (PSD, Catch22, etc.) from the EEG.
- Train classifiers (e.g., Random Forest, SVM) to predict mentation states (active/inactive).
- Generate automated anesthesia scores and perform analyses on the relationship between anesthesia depth and mentation states.