MindsApplied/Minds_AI_EEG_Filter
MindsApplied EEG Signal Filter for Real-time or Offline Analysis
This tool helps neuroscientists and researchers clean up raw EEG data, whether it's streaming in real-time from a headset or collected offline. It takes noisy EEG signals and outputs a much clearer signal by reducing artifacts like eye blinks or motion, sharpening brain rhythms, and reconstructing data from malfunctioning electrodes. The primary user is anyone analyzing EEG data who needs to improve its quality for better interpretation or downstream AI processing.
Use this if you need to reliably remove artifacts and noise from EEG signals while preserving crucial neural activity, without requiring extensive pre-training or perfectly clean input data.
Not ideal if you are looking for a deep learning-based filter or if your data is not time-series electrophysiological data.
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17
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Language
Python
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Last pushed
Feb 25, 2026
Commits (30d)
0
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