tothemoon10080/CHB-MIT-data-preprocessing-and-prediction

This project focuses on data preprocessing and epilepsy seizure prediction using the CHB-MIT EEG dataset. It includes steps like data cleansing, feature extraction, and handling imbalanced datasets, aimed at improving the accuracy of seizure prediction.

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This project helps medical researchers and clinicians analyze EEG brainwave data to predict epileptic seizures. It takes raw CHB-MIT EEG recordings and processes them through cleansing and feature extraction to generate a predictive model. The ultimate goal is to improve the accuracy of anticipating seizure events, aiding in patient care and understanding of epilepsy.

No commits in the last 6 months.

Use this if you are a medical researcher or clinician working with EEG data and need a standardized approach to preprocess and build predictive models for epilepsy seizure forecasting.

Not ideal if you are looking for a ready-to-use clinical diagnostic tool, as this is a research and development project for model building.

epilepsy-research EEG-analysis seizure-prediction neurology biomedical-signal-processing
Stale 6m No Package No Dependents
Maintenance 0 / 25
Adoption 8 / 25
Maturity 16 / 25
Community 14 / 25

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Stars

54

Forks

8

Language

Python

License

MIT

Last pushed

Nov 22, 2023

Commits (30d)

0

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