Research Article
ECG Pre-processing and Feature Extraction Tool for Intelligent Simulation Systems
@INPROCEEDINGS{10.1007/978-3-031-57523-5_16, author={Manuel Dom\^{\i}nguez-Morales and Adolfo Mu\`{o}oz-Macho and Jos\^{e} L. Sevillano}, title={ECG Pre-processing and Feature Extraction Tool for Intelligent Simulation Systems}, proceedings={Simulation Tools and Techniques. 15th EAI International Conference, SIMUtools 2023, Seville, Spain, December 14-15, 2023, Proceedings}, proceedings_a={SIMUTOOLS}, year={2024}, month={4}, keywords={ECG Signal processing Feature extraction Report generation Artificial intelligence}, doi={10.1007/978-3-031-57523-5_16} }- Manuel Domínguez-Morales
Adolfo Muñoz-Macho
José L. Sevillano
Year: 2024
ECG Pre-processing and Feature Extraction Tool for Intelligent Simulation Systems
SIMUTOOLS
Springer
DOI: 10.1007/978-3-031-57523-5_16
Abstract
Sudden cardiac death events and fatal cardiac problems are a field of vital importance for physicians working with elite athletes. For this reason, it is common to periodically perform cardiac monitoring with professional ECG devices to detect certain risk markers. As these doctors often work with many athletes (as is the case with professional football teams), an artificial intelligence-based system would help mass screening and allow these exams to be carried out more regularly. Because physicians often evaluate the printed reports generated by ECG devices, few manufacturers provide powerful and configurable software tools. Moreover, for teaching purposes, a simulation tool that would allow working with previously collected ECG files would be very useful. In this paper, we present a software tool to be used with General Electric CardioSoft 12SL electrocardiograph. This tool allows importing the XML files generated by this device, perform a manual or automatic signal filtering process and PQRST peak detection, and finally generate a customisable report as a CSV file containing the features obtained after signal analysis. This pre-processed information can be used as input of ECG simulators and in artificial intelligence systems to develop diagnostic support systems.
