NextMind lightweight Python reader and shielding utilities

This small toolkit provides a defensive reader for NextMind .raw and .inf files and a set of simple "shielding" functions (filters and artifact rejection).

Files added:

• nextmind_reader.py — helper functions to discover recordings and load .raw/.inf files.
• shielding.py — bandpass/notch filters and a simple threshold-based artifact rejection.
• run_example.py — example script to load a recording, apply shielding, and save cleaned data.
• requirements.txt — numpy and scipy required.

Quickstart

1. Create a virtualenv and install requirements:

python -m venv .venv; .\.venv\Scripts\Activate.ps1; pip install -r requirements.txt

2. Run the example on recording/0 (from the .nextmind folder):

python run_example.py recording\0

Notes and assumptions

• The reader uses heuristics to infer data dtype and channel count when metadata isn't available.
• "Shielding" here means simple preprocessing (bandpass + notch + threshold-based artifact removal).
• If you have richer metadata (sample rate, channel names, units), pass those to the functions or extend read_inf.

Next steps

• If you want fully-featured EEG processing, I can adapt this to use mne and add channel montages, ICA-based artifact removal, and better event parsing.