Browse Code
EEG Data Processor is a desktop application built with Python and PyQt6 for processing raw EEG recordings from the Muse 2/S Athena headband.
It provides three main tools in a tabbed interface:
EEG Processor — Cleans a raw CSV by removing noise, bad signal quality rows, and all-zero brainwave entries. Supports optional user ID tagging, timestamp range filtering, session section labeling (manual or imported from a .txt report), and three output sampling modes: original rate (~256 records/s), reduced to 1 record/second, or reduced to 1 record/minute.
Data Combiner — Concatenates multiple preprocessed EEG CSV files from different participants into a single unified dataset, sorted by user and timestamp.
Data Integration — Merges the EEG dataset with secondary sources such as Embrace Plus wearable data or survey responses, using configurable join keys, join types (inner, left, outer), and automatic timestamp format normalization.
Project Samples
