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ECGMiner: A flexible software for accurately digitizing ECG.
Santamónica, Adolfo F; Carratalá-Sáez, Rocío; Larriba, Yolanda; Pérez-Castellanos, Alberto; Rueda, Cristina.
Affiliation
  • Santamónica AF; Depto. de Estadística e Investigación Operativa de la Universidad de Valladolid, Paseo de Belén 7, Valladolid, 47011, Castilla y León, Spain. Electronic address: adolfo.fernandez.santamonica@estudiantes.uva.es.
  • Carratalá-Sáez R; Depto. Informática de la Universidad de Valladolid, Paseo de Belén 5, Valladolid, 47011, Castilla y León, Spain. Electronic address: rocio@infor.uva.es.
  • Larriba Y; Depto. de Estadística e Investigación Operativa de la Universidad de Valladolid, Paseo de Belén 7, Valladolid, 47011, Castilla y León, Spain. Electronic address: yolanda.larriba@uva.es.
  • Pérez-Castellanos A; Servicio de Cardiología, Hospital Universitario Son Espases, Instituto de Investigación Sanitaria de Baleares (IdISBa), Carretera de Valldemossa, 79, Palma, Illes Balears, Palma, 07120, Illes Balears, Spain. Electronic address: alberto.perezcastellanos@ssib.es.
  • Rueda C; Depto. de Estadística e Investigación Operativa de la Universidad de Valladolid, Paseo de Belén 7, Valladolid, 47011, Castilla y León, Spain. Electronic address: cristina.rueda@uva.es.
Comput Methods Programs Biomed ; 246: 108053, 2024 Apr.
Article in En | MEDLINE | ID: mdl-38340566
ABSTRACT
BACKGROUND AND

OBJECTIVE:

The electrocardiogram (ECG) is the most important non-invasive method for elucidating information about heart and cardiovascular disease diagnosis. Typically, the ECG system manufacturing companies provide ECG images, but store the numerical data in a proprietary format that is not interpretable and is not therefore useful for automatic diagnosis. There have been many efforts to digitize paper-based ECGs. The main limitations of previous works in ECG digitization are that they require manual selection of the regions of interest, only partly provide signal digitization, and offer limited accuracy.

METHODS:

We have developed the ECGMiner, an open-source software to digitize ECG images. It is precise, fast, and simple to use. This software digitizes ECGs in four

steps:

1) recognizing the image composition; 2) removing the gridline; 3) extracting the signals; 4) post-processing and storing the data.

RESULTS:

We have evaluated the ECGMiner digitization capabilities using the Pearson Correlation Coefficient (PCC) and the Root Mean Square Error (RMSE) measures, and we consider ECG from two large, public, and widely used databases, LUDB and PTB-XL. The actual and digitized values of signals in both databases have been compared. The software's ability to correctly identify the location of characteristic waves has also been validated. Specifically, the PCC values are between 0.971 and 0.995, and the RMSE values are between 0.011 and 0.031 mV.

CONCLUSIONS:

The ECGMiner software presented in this paper is open access, easy to install, easy to use, and capable of precisely recovering the paper-based/digital ECG signal data, regardless of the input format and signal complexity. ECGMiner outperforms existing digitization algorithms in terms of PCC and RMSE values.
Subject(s)
Key words

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Signal Processing, Computer-Assisted / Software Type of study: Guideline / Prognostic_studies Language: En Journal: Comput Methods Programs Biomed Journal subject: INFORMATICA MEDICA Year: 2024 Document type: Article

Full text: 1 Collection: 01-internacional Database: MEDLINE Main subject: Signal Processing, Computer-Assisted / Software Type of study: Guideline / Prognostic_studies Language: En Journal: Comput Methods Programs Biomed Journal subject: INFORMATICA MEDICA Year: 2024 Document type: Article
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