ECG_PLATFORM is a complete framework designed for testing QRS detectors and ECG delineators on publicly available datasets.
In ECG_PLATFORM there are included the following algorithms for the detection of QRS complexes:
- engzee segmenter - Andr ́e Louren ̧co, Hugo Silva, Paulo Leite, Renato Louren ̧co, and Ana Fred.Real Time Electrocardiogram Segmentation for Finger Based ECG Bio-metrics.
- hamilton segmenter - Hamilton, Tompkins, W. J., "Quantitative investigation of QRS detection rules using the MIT/BIH arrhythmia database", IEEE Trans. Biomed. Eng., BME-33, pp. 1158-1165, 1987.
- WT delineator - Juan Pablo Martínez, Rute Almeida, Salvador Olmos, Member, IEEE, Ana Paula Rocha, and Pablo Laguna, Member, IEEE A Wavelet-Based ECG Delineator: Evaluation on Standard Databases
- ECGPUWAVE - https://www.physionet.org/content/ecgpuwave/1.3.4/
Data sets on which the methods are tested:
- cinc1 - https://physionet.org/pn3/challenge/2014/set-p/
- cinc2 - https://physionet.org/pn3/challenge/2014/set-p2/
- mitdb - https://archive.physionet.org/physiobank/database/mitdb/
- mitdb (pwave annotations) - https://archive.physionet.org/physiobank/database/pwave/
- qtdb - https://physionet.org/content/qtdb/1.0.0/
- ludb - https://physionet.org/content/ludb/1.0.0/
- telehealth - https://dataverse.harvard.edu/dataset.xhtml?persistentId=doi:10.7910/DVN/QTG0EP
- BUT PDB - https://www.physionet.org/content/but-pdb/1.0.0/
Required Python packages: biosppy, wfdb, numpy, pandas, h5py, scipy, matplotlib, scikit-learn