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CHB-MIT-data-preprocessing-and-prediction

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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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# CHB-MIT Data Preprocessing and Prediction
<details open>
<summary>English Description</summary>
 
## Project Introduction
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.

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

## Dataset
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](https://physionet.org/content/chbmit/1.0.0/)

## File Descriptions
- `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.

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

## License
[MIT License](LICENSE)

</details>

## 项目简介
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。

## 环境设置
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。

## 数据集
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](https://physionet.org/content/chbmit/1.0.0/)

## 文件说明
- `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。

## 使用方法
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。

## 贡献
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。

## 许可证
[MIT License](LICENSE)

</details>

CHB-MIT-data-preprocessing-and-prediction

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