https://github.com/bunyaminergen/heartbeat

Heartbeat is a research project focused on classifying heartbeats using ECG (electrocardiogram) data. Within the scope of this project, both conventional and state-of-the-art models from the literature, as well as experimental deep learning architectures, will be investigated and compared through experimental analyses.
https://github.com/bunyaminergen/heartbeat

ecg ecg-classification ecg-signal healtcare

Last synced: about 1 month ago
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Host: GitHub
URL: https://github.com/bunyaminergen/heartbeat
Owner: bunyaminergen
License: gpl-3.0
Created: 2025-01-25T12:36:22.000Z (4 months ago)
Default Branch: develop
Last Pushed: 2025-03-10T14:35:58.000Z (3 months ago)
Last Synced: 2025-03-29T08:04:11.807Z (about 2 months ago)
Topics: ecg, ecg-classification, ecg-signal, healtcare
Language: Jupyter Notebook
Homepage:
Size: 1.99 MB
Stars: 6
Watchers: 2
Forks: 1
Open Issues: 0
Metadata Files:
- Readme: README.md
- License: LICENSE
- Codeowners: .github/CODEOWNERS

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# Heartbeat

`Heartbeat` is a research project focused on classifying heartbeats using ECG (electrocardiogram) data. Within the scope
of this project, both conventional and state-of-the-art models from the literature, as well as experimental deep
learning architectures, will be investigated and compared through experimental analyses.

**Note**: _This is only a `v0.1.0 Initial` version; many new features will be added, models
will be fine-tuned or trained from scratch, and various optimization efforts will be applied. For more information,
you can check out the [Upcoming](#upcoming) section._

**Note**: _If you would like to contribute to this repository,
please read the [CONTRIBUTING](.docs/documentation/CONTRIBUTING.md) first._

---

### Table of Contents

- [Prerequisites](#prerequisites)
- [Features](#features)
- [Reports](#reports)
- [Installation](#installation)
- [File Structure](#file-structure)
- [Version Control System](#version-control-system)
- [Upcoming](#upcoming)
- [Documentations](#documentations)
- [License](#licence)
- [Links](#links)
- [Team](#team)
- [Contact](#contact)
- [Citation](#citation)

---

### Prerequisites

- `Python 3.12` _(or above)_
- `aws cli` _(for dataset download)_

---

### Features

##### Models

- [x] OneDCNN
- [x] AdvancedOneDCNN
- [x] OneDSelfONN
- [x] AdvancedOneDSelfONN

---

### Reports

##### Metrics

##### OneDSelfONN

![Final Test Confusion Matrix](.docs/report/img/confusion_matrix_test.png)
![Final Train Confusion Matrix](.docs/report/img/confusion_matrix_train.png)
![Final Validation Confusion Matrix](.docs/report/img/confusion_matrix_val.png)
![Training Curves](.docs/report/img/training.png)
![ROC Curve](.docs/report/img/roc_curve.png)

##### Benchmark

| Model | Accuracy | Precision | Recall | F1 Score |
|---------------------|----------|-----------|--------|----------|
| OneDCNN | 0.59 | 0.36 | 0.59 | 0.45 |
| AdvancedOneDCNN | 0.59 | 0.35 | 0.59 | 0.44 |
| OneDSelfONN | 0.60 | 0.44 | 0.58 | 0.45 |
| AdvancedOneDSelfONN | 0.58 | 0.58 | 0.56 | 0.43 |

![Benchmark](.docs/report/img/benchmark.png)

---

### Installation

##### Linux/Ubuntu

```bash
sudo apt update -y && sudo apt upgrade -y
```

```bash
git clone https://github.com/bunyaminergen/Heartbeat
```

```bash
cd Heartbeat
```

```bash
conda env create -f environment.yaml
```

```bash
conda activate Heartbeat
```

##### Dataset Download

```bash
aws s3 sync --no-sign-request s3://physionet-open/challenge-2017/1.0.0/training .data/raw/train
```

```bash
aws s3 sync --no-sign-request s3://physionet-open/challenge-2017/1.0.0/validation .data/raw/validation
```

---

### File Structure

```Text
.
├── config
│ └── config.yaml
├── .data
│ ├── binary
│ │ ├── labels.npy
│ │ └── signals.npy
│ └── raw
│ ├── train
│ │ ├── A00
│ │ │ ├── A00001.hea
│ │ │ ├── A00001.mat
│ │ │ ├── A00002.hea
│ │ │ ├── A00002.mat
│ │ │ ├── ...
│ │ │ ├── A00998.hea
│ │ │ ├── A00998.mat
│ │ │ ├── A00999.hea
│ │ │ └── A00999.mat
│ │ ├── A01
│ │ │ ├── A01000.hea
│ │ │ ├── A01000.mat
│ │ │ ├── A01001.hea
│ │ │ ├── A01001.mat
│ │ │ ├── ...
│ │ │ ├── A01998.hea
│ │ │ ├── A01998.mat
│ │ │ ├── A01999.hea
│ │ │ └── A01999.mat
│ │ ├── A02
│ │ │ ├── A02000.hea
│ │ │ ├── A02000.mat
│ │ │ ├── A02001.hea
│ │ │ ├── A02001.mat
│ │ │ ├── ...
│ │ │ ├── A02998.hea
│ │ │ ├── A02998.mat
│ │ │ ├── A02999.hea
│ │ │ └── A02999.mat
│ │ ├── A03
│ │ │ ├── A03000.hea
│ │ │ ├── A03000.mat
│ │ │ ├── A03001.hea
│ │ │ ├── A03001.mat
│ │ │ ├── ...
│ │ │ ├── A03998.hea
│ │ │ ├── A03998.mat
│ │ │ ├── A03999.hea
│ │ │ └── A03999.mat
│ │ ├── A04
│ │ │ ├── A04000.hea
│ │ │ ├── A04000.mat
│ │ │ ├── A04001.hea
│ │ │ ├── A04001.mat
│ │ │ ├── ...
│ │ │ ├── A04998.hea
│ │ │ ├── A04998.mat
│ │ │ ├── A04999.hea
│ │ │ └── A04999.mat
│ │ ├── A05
│ │ │ ├── A05000.hea
│ │ │ ├── A05000.mat
│ │ │ ├── A05001.hea
│ │ │ ├── A05001.mat
│ │ │ ├── ...
│ │ │ ├── A05998.hea
│ │ │ ├── A05998.mat
│ │ │ ├── A05999.hea
│ │ │ └── A05999.mat
│ │ ├── A06
│ │ │ ├── A06000.hea
│ │ │ ├── A06000.mat
│ │ │ ├── A06001.hea
│ │ │ ├── A06001.mat
│ │ │ ├── ...
│ │ │ ├── A06998.hea
│ │ │ ├── A06998.mat
│ │ │ ├── A06999.hea
│ │ │ └── A06999.mat
│ │ ├── A07
│ │ │ ├── A07000.hea
│ │ │ ├── A07000.mat
│ │ │ ├── A07001.hea
│ │ │ ├── A07001.mat
│ │ │ ├── ...
│ │ │ ├── A07998.hea
│ │ │ ├── A07998.mat
│ │ │ ├── A07999.hea
│ │ │ └── A07999.mat
│ │ ├── A08
│ │ │ ├── A08000.hea
│ │ │ ├── A08000.mat
│ │ │ ├── A08001.hea
│ │ │ ├── A08001.mat
│ │ │ ├── ...
│ │ │ ├── A08527.hea
│ │ │ ├── A08527.mat
│ │ │ ├── A08528.hea
│ │ │ └── A08528.mat
│ │ ├── MD5SUMS
│ │ ├── RECORDS
│ │ ├── RECORDS-af
│ │ ├── RECORDS-noisy
│ │ ├── RECORDS-normal
│ │ ├── RECORDS-other
│ │ ├── REFERENCE.csv
│ │ ├── REFERENCE-v0.csv
│ │ ├── REFERENCE-v1.csv
│ │ ├── REFERENCE-v2.csv
│ │ ├── REFERENCE-v3.csv
│ │ ├── SHA1SUMS
│ │ └── SHA256SUMS
│ └── validation
│ ├── A00001.hea
│ ├── A00001.mat
│ ├── A00002.hea
│ ├── A00002.mat
│ ├── ...
│ ├── A04735.hea
│ ├── A04735.mat
│ ├── A04805.hea
│ ├── A04805.mat
│ ├── MD5SUMS
│ ├── RECORDS
│ ├── RECORDS-af
│ ├── RECORDS-noisy
│ ├── RECORDS-normal
│ ├── RECORDS-other
│ ├── REFERENCE.csv
│ ├── REFERENCE-v0.csv
│ ├── REFERENCE-v1.csv
│ ├── REFERENCE-v2.csv
│ ├── REFERENCE-v3.csv
│ ├── SHA1SUMS
│ └── SHA256SUMS
├── .docs
│ ├── documentation
│ │ ├── CONTRIBUTING.md
│ │ └── RESOURCES.md
│ ├── img
│ │ └── HeartbeatLogo.png
│ └── report
│ └── img
│ ├── confusion_matrix_test.png
│ ├── confusion_matrix_train.png
│ ├── confusion_matrix_val.png
│ ├── roc_curve.png
│ └── training.png
├── environment.yaml
├── .gitignore
├── LICENSE
├── .logs
│ └── heartbeat.log
├── main.py
├── notebook
│ └── eda.ipynb
├── README.md
├── requirements.txt
├── src
│ ├── model
│ │ ├── evaluation.py
│ │ ├── model.py
│ │ └── train.py
│ └── utils
│ ├── data
│ │ └── manager.py
│ ├── log
│ │ └── manager.py
│ └── visualization
│ └── visualize.py

29 directories, 17707 files
```

---

### Version Control System

##### Releases

- [v0.1.0](https://github.com/bunyaminergen/Heartbeat/archive/refs/tags/v1.0.0.zip) _.zip_
- [v0.1.0](https://github.com/bunyaminergen/Heartbeat/archive/refs/tags/v1.0.0.tar.gz) _.tar.gz_

##### Branches

- [main](https://github.com/bunyaminergen/Heartbeat/main/)
- [develop](https://github.com/bunyaminergen/Heartbeat/main/)

---

### Upcoming

- [ ] **Speech Emotion Recognition:** Develop a model to automatically detect emotions from speech data.

##### Considerations

- [ ] Transform the code structure into a pipeline for better modularity and scalability.

---

### Documentations

- [RESOURCES](.docs/documentation/RESOURCES.md)
- [CONTRIBUTING](.docs/documentation/CONTRIBUTING.md)

---

### Licence

- [LICENSE](LICENSE)

---

### Links

- [Github](https://github.com/bunyaminergen/Heartbeat)
- [Website](https://bunyaminergen.com)
- [Linkedin](https://www.linkedin.com/in/bunyaminergen)

---

### Team

- [Bunyamin Ergen](https://www.linkedin.com/in/bunyaminergen)

---

### Contact

- [Mail](mailto:[email protected])

---

### Citation

```bibtex
@software{ Heartbeat,
author = {Bunyamin Ergen},
title = {{Heartbeat}},
year = {2025},
month = {01},
url = {https://github.com/bunyaminergen/Heartbeat},
version = {v0.1.0},
}
```

---

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