https://github.com/johanneskasser/hdsemg-select
A graphical user interface (GUI) application for selecting and analyzing HDsEMG channels from .mat files. This tool helps identify and exclude faulty channels (e.g., due to electrode misplacement or corrosion) from HDsEMG recordings, enabling more accurate and efficient analysis.
https://github.com/johanneskasser/hdsemg-select
data-cleaning data-preparation data-preprocessing data-presentation emg-data emg-signal high-density-emg pyqt5
Last synced: 3 months ago
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A graphical user interface (GUI) application for selecting and analyzing HDsEMG channels from .mat files. This tool helps identify and exclude faulty channels (e.g., due to electrode misplacement or corrosion) from HDsEMG recordings, enabling more accurate and efficient analysis.
- Host: GitHub
- URL: https://github.com/johanneskasser/hdsemg-select
- Owner: johanneskasser
- Created: 2025-03-27T17:01:12.000Z (about 1 year ago)
- Default Branch: main
- Last Pushed: 2026-01-26T11:49:59.000Z (4 months ago)
- Last Synced: 2026-01-27T01:13:13.498Z (4 months ago)
- Topics: data-cleaning, data-preparation, data-preprocessing, data-presentation, emg-data, emg-signal, high-density-emg, pyqt5
- Language: Python
- Homepage: https://johanneskasser.github.io/hdsemg-select/
- Size: 5.76 MB
- Stars: 0
- Watchers: 1
- Forks: 0
- Open Issues: 4
-
Metadata Files:
- Readme: README.md
- Contributing: docs/contributing.md
Awesome Lists containing this project
README
🧼 hdsemg-select 🧼
HDsEMG data cleaning tool
A graphical user interface (GUI) application for selecting and analyzing HDsEMG channels from `.mat` files. This tool
helps identify and exclude faulty channels and automatically flag potential artifacts like ECG contamination, power line noise (50/60Hz), or general signal anomalies.
📚 **[View the full documentation](https://johanneskasser.github.io/hdsemg-select/)**
## Key Features
- ✅ Support for multiple file formats (`.mat`, `.otb+`, `.otb4`)
- 🧠 Intelligent grid detection and configuration
- 🖼 Comprehensive visualization tools
- ⚡️ Advanced artifact detection
- 💾 Structured data export
- 🔍 Detailed signal analysis capabilities
## Quick Start
1. **Clone the repository:**
```bash
git clone https://github.com/johanneskasser/hdsemg-select.git
cd hdsemg_select
```
2. **Create virtual environment (as admin):**
```bash
python -m venv venv
source venv/bin/activate # On Windows use venv\Scripts\activate
pip install -r requirements.txt
```
3. **Run the application:**
```bash
python src/main.py
```
📖 For detailed instructions, visit our [Installation Guide](https://johanneskasser.github.io/hdsemg-select/installation).
## Documentation
- 📥 [Installation Guide](https://johanneskasser.github.io/hdsemg-select/installation)
- 📖 [Usage Guide](https://johanneskasser.github.io/hdsemg-select/usage)
- 🛠 [Developer Guide](https://johanneskasser.github.io/hdsemg-select/developer)
## Screenshots
## Requirements
- Python 3.8+
- See `requirements.txt` for dependencies
- Tested on Linux and Windows 11
## Related Tools
- [hdsemg-pipe App 🧼](https://github.com/johanneskasser/hdsemg-pipe.git)
- [openhdemg 🧬](https://github.com/GiacomoValliPhD/openhdemg)
## Contributing
Contributions are welcome! Please feel free to submit a Pull Request. For major changes, please open an issue first to discuss what you would like to change.
## License
This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.