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.

To run this project, you need to install related dependencies. The dependencies are detailed in the requirements.txt file.

This project uses the publicly available CHB-MIT EEG dataset. Detailed information about the dataset and how to obtain it can be found at the following link: CHB-MIT EEG Dataset

• data: Contains a part of the dataset.
• src/data: Contains code related to data preprocessing and feature extraction.
• train.py: Code for model training and evaluation.

1. Clone the repository to your local machine.

pip clone https://github.com/tothemoon10080/CHB-MIT-data-preprocessing-and-prediction.git

2. Ensure all dependencies are installed.

In the project folder:

pip install -r requirements.txt

3. Run the train.py script to perform data preprocessing, feature extraction, and model training.

Contributions of any kind are welcome. You can contribute by submitting issues or pull requests.

MIT License

本项目专注于使用 CHB-MIT EEG 数据集进行数据预处理和癫痫发作预测。项目包括数据清洗、特征提取、处理不平衡数据集等步骤，旨在提高对癫痫发作的预测准确性。

要运行此项目，您需要安装相关的依赖包。依赖详见 requirements.txt 文件。

此项目使用的是公开的 CHB-MIT EEG 数据集。数据集详细信息和获取方式可在以下链接找到： CHB-MIT EEG 数据集

• data: 包含部分数据集。
• scr/data: 包含数据预处理与特征提取的相关代码。
• train.py: 模型训练和评估的代码。

1. 克隆仓库到本地。

pip clone https://github.com/tothemoon10080/CHB-MIT-data-preprocessing-and-prediction.git

2. 确保安装所有依赖。

在此项目文件夹下

pip install -r requirements.txt

3. 运行 train.py 脚本这会进行数据预处理、特征提取和模型训练。

欢迎任何形式的贡献。您可以通过提交问题或拉取请求来贡献。

MIT License