Análisis de las anomalías cardíacas basado en procesamiento de señales mediante un sistema de diagnóstico predictivo para estudiantes de biomedicina de la Universidad Politécnica Salesiana

Abstract

The main objective of this project is to develop a predictive diagnostic system that employs signal processing to analyze cardiac anomalies. This system is specifically designed to enhance the education of Biomedical Engineering students at Universidad Politécnica Salesiana by providing a sophisticated and practical tool that integrates machine learning algorithms to deliver real-time predictive readings of electrocardiograms (ECGs). The development of this system is justified by the lack of educational technologies in the field of biomedical engineering, which restricts teaching and familiarization with the proper use of medical devices, such as electrocardiographs. The proposed system will not only help students gain a deeper understanding of cardiac electrical signals, but it will also enable them to practice and improve their ECG interpretation skills, providing immediate feedback on the accuracy of their analyses. The implementation of this system will significantly enhance study methods related to cardiac activities, offering students a richer learning experience and equipping them to meet the challenges of the clinical field with a strong foundation in both practical and theoretical knowledge.