Clarity-Digital-Twin/brain-go-brr-v2
TCN + Bi-Mamba/FLA + GNN + Dynamic LPE for Clinical EEG Seizure Detection
This project offers an advanced system for automatically detecting seizures from continuous EEG recordings in clinical settings. It takes raw EEG data as input and identifies seizure events, aiming to reduce the number of false alarms that can lead to staff fatigue. Neurologists, intensivists, and other critical care professionals would use this to improve patient monitoring and care.
Use this if you need to accurately identify seizure activity in continuous EEG data with a low rate of false alarms, which is crucial for effective patient care in ICUs.
Not ideal if you require a system that has already achieved the clinical gold standard of less than 1 false alarm per day, as this project is still in active research and development.
Stars
18
Forks
6
Language
Python
License
Apache-2.0
Category
Last pushed
Dec 29, 2025
Commits (30d)
0
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