# VibroMAF - Vibrotactile Multi-Method Assessment Fusion
[](https://results.pre-commit.ci/latest/github/hofbi/vibromaf/main)
[](https://github.com/hofbi/vibromaf)
[](https://hofbi.github.io/vibromaf)
[](https://github.com/hofbi/vibromaf)
[](https://github.com/psf/black)
[](https://pypi.org/project/vibromaf/)
[](https://pypi.org/project/vibromaf/)
[](https://pypi.org/project/vibromaf/)
## Vibrotactile Quality Metrics
This package provides implementations of existing vibrotactile quality metrics and machine learning approach that fuses the individual metric scores into a single final quality score.
## Installation
Install `vibromaf` from [PyPI](https://pypi.org/project/vibromaf):
```shell
pip install vibromaf
```
For development versions and alternative installations see the [installation documentation](https://hofbi.github.io/vibromaf/installation/).
## Usage
- [Get Started](https://hofbi.github.io/vibromaf/get-started/)
- [Full Documentation](https://hofbi.github.io/vibromaf/)
## Citation
If you use this work, please cite our paper ([PDF](https://www.researchgate.net/publication/357556145_Automated_Quality_Assessment_for_Compressed_Vibrotactile_Signals_Using_Multi-Method_Assessment_Fusion))
```tex
@inproceedings{noll_vibromaf,
author = {Noll, Andreas and Hofbauer, Markus and Muschter, Evelyn and Li, Shu-Chen and Steinbach, Eckehard},
booktitle = {2022 IEEE Haptics Symposium (HAPTICS)},
title = {Automated Quality Assessment for Compressed Vibrotactile Signals Using Multi-Method Assessment Fusion},
year = {2022},
volume = {},
number = {},
pages = {1-6},
doi = {10.1109/HAPTICS52432.2022.9765599},
address = {Santa Barabara, California, USA}
}
```
## Contribute
See our [CONTRIBUTING.md](CONTRIBUTING.md)
# Changelog
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"description": "# VibroMAF - Vibrotactile Multi-Method Assessment Fusion\n\n[](https://results.pre-commit.ci/latest/github/hofbi/vibromaf/main)\n[](https://github.com/hofbi/vibromaf)\n[](https://hofbi.github.io/vibromaf)\n[](https://github.com/hofbi/vibromaf)\n[](https://github.com/psf/black)\n\n[](https://pypi.org/project/vibromaf/)\n[](https://pypi.org/project/vibromaf/)\n[](https://pypi.org/project/vibromaf/)\n\n## Vibrotactile Quality Metrics\n\nThis package provides implementations of existing vibrotactile quality metrics and machine learning approach that fuses the individual metric scores into a single final quality score.\n\n## Installation\n\nInstall `vibromaf` from [PyPI](https://pypi.org/project/vibromaf):\n\n```shell\npip install vibromaf\n```\n\nFor development versions and alternative installations see the [installation documentation](https://hofbi.github.io/vibromaf/installation/).\n\n## Usage\n\n- [Get Started](https://hofbi.github.io/vibromaf/get-started/)\n- [Full Documentation](https://hofbi.github.io/vibromaf/)\n\n## Citation\n\nIf you use this work, please cite our paper ([PDF](https://www.researchgate.net/publication/357556145_Automated_Quality_Assessment_for_Compressed_Vibrotactile_Signals_Using_Multi-Method_Assessment_Fusion))\n\n```tex\n@inproceedings{noll_vibromaf,\n author = {Noll, Andreas and Hofbauer, Markus and Muschter, Evelyn and Li, Shu-Chen and Steinbach, Eckehard},\n booktitle = {2022 IEEE Haptics Symposium (HAPTICS)},\n title = {Automated Quality Assessment for Compressed Vibrotactile Signals Using Multi-Method Assessment Fusion},\n year = {2022},\n volume = {},\n number = {},\n pages = {1-6},\n doi = {10.1109/HAPTICS52432.2022.9765599},\n address = {Santa Barabara, California, USA}\n}\n```\n\n## Contribute\n\nSee our [CONTRIBUTING.md](CONTRIBUTING.md)\n\n# Changelog\n",
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