Metadata-Version: 2.1
Name: ecg_qc
Version: 1.0b6
Summary: a package to compute if ECG signal quality is optimal or noisy
Home-page: https://github.com/Aura-healthcare/ecg_qc
Author: Alexandre CHIROUZE, Alexis COMTE, Laura DUMONT
Author-email: alexandre@chirouze.tech, alexis.g.comte@gmail.com, laura.dt.dumont@gmail.com
License: GPLv3
Description: # ECG_QC (Quality Classification)
        
        
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        ![alt text](sphinx-docs/source/images/ecg_signal_classification.png)
        
        **Full Documentation** : https://aura-healthcare.github.io/ecg_qc/
        
        **Website** : https://www.aura.healthcare
        
        **Github** : https://github.com/Aura-healthcare
        
        **Version** : 1.0b6
        
        ecg_qc is a python library that classifies ECG signal into good/bad quality thanks to Machine Learning.
        
        There are currently 4 trained models:
        | Name | Type of model | (training) ECG time window | (training) ECG segments individual standardization |
        | ------ | ----------- | ----------- | ----------- | 
        | dfc_2s.pkl | Decision Tree Classifier | 2 seconds | No |
        | rfc_2s.pkl | Random Forest Classifier | 2 seconds | No |
        | rfc_2s_norm.pkl | Random Forest Classifier | 2 seconds | Yes |
        | xgb_9s.joblib | XGboost Classifier | 9 seconds | No |
        
        
        ## Installation / Prerequisites
        
        #### Dependencies
        
        ecg_qc requires:
        
        - Python (>= 3.6)
        - biosppy>=0.6.1
        - dill>=0.3.4
        - pathtools>=0.1.2
        - py-ecg-detectors>=1.0.2
        - scikit-learn>=0.23.2
        - wfdb>=3.1.1
        - xgboost>=1.3.1
        
        #### User installation
        
        The easiest way to install hrv-analysis is using ``pip`` :
        
            $ pip install ecg-qc
        
        you can also clone the repository:
        
            $ git clone https://github.com/Aura-healthcare/ecg_qc.git
            $ python setup.py install
        
        
        ## Getting started
        
        ### Usage
        
        Import:
        
        ```python
        from ecg_qc import EcgQc
        ```
        
        Class initialization:
        
        ```python
        ecg_qc = EcgQc()
        ```
        
        Default parameters:
        
        ```python
        ecg_qc = EcgQc(model='rfc_norm_2s.pkl',
                       sampling_frequency=256,
                       normalized=True)
        ```
        
        Predicting the quality of the signal:
        
        ```python
        ecg_data = [1905.72, ... -150.75995323, -134.14559104] # ECG values with same sampling frequency as class declaration
        
        signal_quality = ecg_qc.get_signal_quality(ecg_data)
        ```
        
        Computing SQIs before making prediction:
        
        ```python
        ecg_data = [1905.72, ... -150.75995323, -134.14559104] # ECG values with same sampling frequency as class declaration
        
        sqi_scores = ecg_qc.compute_sqi_score(ecg_data)
        signal_quality = ecg_qc.predict_quality(sqi_scores)
        ```
        
        
        ## Authors
        
        **Alexandre CHIROUZE** - (https://github.com/achirouze)
        
        **Alexis COMTE** - (https://github.com/alexisgcomte)
        
        **Laura DUMONT** - (https://github.com/laudmt)
        
        ## License
        
        This project is licensed under the *GNU GENERAL PUBLIC License* - see the [LICENSE.md](https://github.com/Aura-healthcare/ecg_qc/blob/main/LICENSE) file for details
        
        
        References
        ==========
        Nemcova, A., Smisek, R., Opravilová, K., Vitek, M., Smital, L., & Maršánová, L. (2020). Brno University of Technology ECG Quality Database (BUT QDB) (version 1.0.0). PhysioNet. https://doi.org/10.13026/kah4-0w24.
Platform: UNKNOWN
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Education
Classifier: Intended Audience :: Science/Research
Classifier: Intended Audience :: Healthcare Industry
Classifier: Natural Language :: English
Classifier: Programming Language :: Python :: 3
Classifier: Operating System :: OS Independent
Classifier: Development Status :: 4 - Beta
Classifier: License :: OSI Approved :: GNU General Public License v3 (GPLv3)
Classifier: Programming Language :: Python :: 3.6
Classifier: Programming Language :: Python :: 3.7
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: Implementation :: PyPy
Requires-Python: >=3.6
Description-Content-Type: text/markdown
