{"id":13545764,"url":"https://github.com/scientisst/BioSPPy","last_synced_at":"2025-04-02T17:31:49.167Z","repository":{"id":51614230,"uuid":"520510853","full_name":"scientisst/BioSPPy","owner":"scientisst","description":"Biosignal Processing in Python","archived":false,"fork":true,"pushed_at":"2025-02-21T10:00:07.000Z","size":7155,"stargazers_count":82,"open_issues_count":4,"forks_count":26,"subscribers_count":5,"default_branch":"main","last_synced_at":"2025-03-22T10:18:16.129Z","etag":null,"topics":["biosignals","ecg","eda","eeg","emg","feature-extraction","hrv","pcg","physiological-computing","ppg","python"],"latest_commit_sha":null,"homepage":"https://biosppy.readthedocs.io/","language":"Python","has_issues":true,"has_wiki":null,"has_pages":null,"mirror_url":null,"source_name":"PIA-Group/BioSPPy","license":"other","status":null,"scm":"git","pull_requests_enabled":true,"icon_url":"https://github.com/scientisst.png","metadata":{"files":{"readme":"README.md","changelog":"CHANGELOG.md","contributing":null,"funding":null,"license":"LICENSE","code_of_conduct":null,"threat_model":null,"audit":null,"citation":null,"codeowners":null,"security":null,"support":null,"governance":null}},"created_at":"2022-08-02T13:32:14.000Z","updated_at":"2025-03-16T22:22:18.000Z","dependencies_parsed_at":"2023-02-10T10:46:15.343Z","dependency_job_id":"c5a92c2c-70c2-4345-96b3-6451e7ebcc5d","html_url":"https://github.com/scientisst/BioSPPy","commit_stats":{"total_commits":242,"total_committers":28,"mean_commits":8.642857142857142,"dds":0.6900826446280992,"last_synced_commit":"a6b7560bbb575e57be081f8ae8426ef8cd324b3e"},"previous_names":[],"tags_count":5,"template":false,"template_full_name":null,"repository_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/scientisst%2FBioSPPy","tags_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/scientisst%2FBioSPPy/tags","releases_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/scientisst%2FBioSPPy/releases","manifests_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories/scientisst%2FBioSPPy/manifests","owner_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners/scientisst","download_url":"https://codeload.github.com/scientisst/BioSPPy/tar.gz/refs/heads/main","host":{"name":"GitHub","url":"https://github.com","kind":"github","repositories_count":246860095,"owners_count":20845598,"icon_url":"https://github.com/github.png","version":null,"created_at":"2022-05-30T11:31:42.601Z","updated_at":"2022-07-04T15:15:14.044Z","host_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub","repositories_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repositories","repository_names_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/repository_names","owners_url":"https://repos.ecosyste.ms/api/v1/hosts/GitHub/owners"}},"keywords":["biosignals","ecg","eda","eeg","emg","feature-extraction","hrv","pcg","physiological-computing","ppg","python"],"created_at":"2024-08-01T12:00:16.485Z","updated_at":"2025-04-02T17:31:49.148Z","avatar_url":"https://github.com/scientisst.png","language":"Python","readme":"\u003ca href=\"https://biosppy.readthedocs.org/\"\u003e\n\u003cpicture\u003e\n  \u003csource media=\"(prefers-color-scheme: light)\" srcset=\"docs/logo/logo_400.png\"\u003e\n  \u003csource media=\"(prefers-color-scheme: dark)\" srcset=\"docs/logo/logo_inverted_400.png\"\u003e\n  \u003cimg alt=\"Image\" title=\"I know you're listening! - xkcd.com/525\"\u003e\n\u003c/picture\u003e\n\u003c/a\u003e\n\n*A toolbox for biosignal processing written in Python.*\n\n[![PyPI version](https://badgen.net/pypi/v/biosppy)](https://pypi.org/project/biosppy/)\n[![PyPI downloads](https://badgen.net/pypi/dm/biosppy/?color=blue)](https://pypi.org/project/biosppy/)\n[![License](https://badgen.net/pypi/license/biosppy?color=grey)](https://github.com/scientisst/BioSPPy/blob/main/LICENSE)\n\n[![GitHub stars](https://badgen.net/github/stars/scientisst/BioSPPy?color=yellow)]()\n[![GitHub issues](https://badgen.net/github/open-issues/scientisst/BioSPPy?color=cyan)](https://github.com/scientisst/BioSPPy/issues)\n\n\n### 🎙️ Announcements\n```\n🗒️ BioSPPy can now read EDF files directly! \nWith the biosppy.storage module you can now load your EDF files!\n```\n```\n🌀 New module for signal quality assessment 🌀\nWith the biosppy.quality module you can now evaluate the quality of your signals!\nSo far, the EDA and ECG quality are available, but more could be added soon. \n```\n```\n🫀 New module for heart rate variability (biosppy.signals.hrv)\n🎊 New module for feature extraction (biosppy.features)\n```\n\n\n# BioSPPy - Biosignal Processing in Python\nThe toolbox bundles together various signal processing and pattern recognition\nmethods geared towards the analysis of biosignals.\n\nHighlights:\n\n- Support for various biosignals: ECG, EDA, EEG, EMG, PCG, PPG, Respiration, HRV\n- Signal analysis primitives: filtering, frequency analysis\n- Feature extraction: time, frequency, and non-linear domain\n- Signal quality assessment\n- Signal synthesizers\n- Clustering\n- Biometrics\n\nDocumentation can be found at: \u003chttps://biosppy.readthedocs.org/\u003e\n\n## Installation\n\nInstallation can be easily done with `pip`:\n\n```bash\n$ pip install biosppy\n```\n\nAlternatively, you can install the latest version from the GitHub repository:\n\n```bash\n$ pip install git+https://github.com/scientisst/BioSPPy.git\n```\n\n## Simple Example\n\nThe code below loads an ECG signal from the `examples` folder, filters it,\nperforms R-peak detection, and computes the instantaneous heart rate.\n\n```python\nfrom biosppy import storage\nfrom biosppy.signals import ecg\n\n# load raw ECG signal\nsignal, mdata = storage.load_txt('./examples/ecg.txt')\n\n# process it and plot\nout = ecg.ecg(signal=signal, sampling_rate=1000., show=True)\n```\n\nThis should produce a plot similar to the one below.\n\n![ECG summary example](docs/images/ECG_summary.png)\n\n## Dependencies\n\n- bidict\n- h5py\n- matplotlib\n- numpy\n- scikit-learn\n- scipy\n- shortuuid\n- six\n- joblib\n\n## Citing\nPlease use the following if you need to cite BioSPPy:\n\nP. Bota, R. Silva, C. Carreiras, A. Fred, and H. P. da Silva, \"BioSPPy: A Python toolbox for physiological signal processing,\" SoftwareX, vol. 26, pp. 101712, 2024, doi: 10.1016/j.softx.2024.101712.\n\n```latex\n@article{biosppy,\n    title = {BioSPPy: A Python toolbox for physiological signal processing},\n    author = {Patrícia Bota and Rafael Silva and Carlos Carreiras and Ana Fred and Hugo Plácido {da Silva}},\n    journal = {SoftwareX},\n    volume = {26},\n    pages = {101712},\n    year = {2024},\n    issn = {2352-7110},\n    doi = {https://doi.org/10.1016/j.softx.2024.101712},\n    url = {https://www.sciencedirect.com/science/article/pii/S2352711024000839},\n}\n```\n\nHowever, if you want to cite a specific version of BioSPPy, you can use Zenodo's DOI:\n\n[![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.11048615.svg)](https://doi.org/10.5281/zenodo.11048615)\n\n\n## License\nBioSPPy is released under the BSD 3-clause license. See LICENSE for more details.\n\n## Disclaimer\n\nThis program is distributed in the hope it will be useful and provided\nto you \"as is\", but WITHOUT ANY WARRANTY, without even the implied\nwarranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. This\nprogram is NOT intended for medical diagnosis. We expressly disclaim any\nliability whatsoever for any direct, indirect, consequential, incidental\nor special damages, including, without limitation, lost revenues, lost\nprofits, losses resulting from business interruption or loss of data,\nregardless of the form of action or legal theory under which the\nliability may be asserted, even if advised of the possibility of such\ndamages.\n","funding_links":[],"categories":["Library"],"sub_categories":[],"project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fscientisst%2FBioSPPy","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fscientisst%2FBioSPPy","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fscientisst%2FBioSPPy/lists"}