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Development and Validation of an Algorithm for the Digitization of ECG Paper Images
- Source :
- Sensors; Volume 22; Issue 19; Pages: 7138
- Publication Year :
- 2022
- Publisher :
- MDPI AG, 2022.
-
Abstract
- The electrocardiogram (ECG) signal describes the heart’s electrical activity, allowing it to detect several health conditions, including cardiac system abnormalities and dysfunctions. Nowadays, most patient medical records are still paper-based, especially those made in past decades. The importance of collecting digitized ECGs is twofold: firstly, all medical applications can be easily implemented with an engineering approach if the ECGs are treated as signals; secondly, paper ECGs can deteriorate over time, therefore a correct evaluation of the patient’s clinical evolution is not always guaranteed. The goal of this paper is the realization of an automatic conversion algorithm from paper-based ECGs (images) to digital ECG signals. The algorithm involves a digitization process tested on an image set of 16 subjects, also with pathologies. The quantitative analysis of the digitization method is carried out by evaluating the repeatability and reproducibility of the algorithm. The digitization accuracy is evaluated both on the entire signal and on six ECG time parameters (R-R peak distance, QRS complex duration, QT interval, PQ interval, P-wave duration, and heart rate). Results demonstrate the algorithm efficiency has an average Pearson correlation coefficient of 0.94 and measurement errors of the ECG time parameters are always less than 1 mm. Due to the promising experimental results, the algorithm could be embedded into a graphical interface, becoming a measurement and collection tool for cardiologists.
- Subjects :
- Digitization
ECG
digitization
electrocardiogram
heart pathologies
Pearson’s coefficient measurement
signals similarity
Reproducibility of Results
Signal Processing, Computer-Assisted
Biochemistry
Atomic and Molecular Physics, and Optics
Analytical Chemistry
Electrocardiography
Computer-Assisted
Algorithms
Heart Rate
Humans
Signal Processing
Electrical and Electronic Engineering
Instrumentation
Subjects
Details
- ISSN :
- 14248220
- Volume :
- 22
- Database :
- OpenAIRE
- Journal :
- Sensors
- Accession number :
- edsair.doi.dedup.....4f901edf904795cceacb0ef562feb02d