Rapid Detection of Cardiac Pathologies by Neural Networks Using ECG Signals (1D) and sECG Images (3D)

Abstract

Usually, cardiac pathologies are detected using one-dimensional electrocardiogram signals or two-dimensional images. When working with electrocardiogram signals, they can be represented in the time and frequency domains (one-dimensional signals). However, this technique can present difficulties, such as the high cost of private health services or the time the public health system takes to refer the patient to a cardiologist. In addition, the variety of cardiac pathologies (more than 20 types) is a problem in diagnosing the disease. On the other hand, surface electrocardiography (sECG) is a little-explored technique for this diagnosis. sECGs are three-dimensional images (two dimensions in space and one in time). In this way, the signals were taken in one-dimensional format and analyzed using neural networks. Following the transformation of the one-dimensional signals to three-dimensional signals, they were analyzed in the same sense. For this research, two models based on LSTM and ResNet34 neural networks were developed, which showed high accuracy, 98.71% and 93.64%, respectively. This study aims to propose the basis for developing Decision Support Software (DSS) based on machine learning models.

Biomechanical Study of the Eye with Keratoconus-Type Corneal Ectasia Using a 3D Geometric Model

“…The strategy for this study was to create a realistic customized 3D model, as it provides accuracy in how certain geometric aspects of the cornea influence the biomechanics and progression of the disease. With these aspects, it was possible to build an investigation using the data of the examination of patients from an authorized database in the form of point clouds exported by Pentacam ® ; Rhinoceros ® processed these points to build the 3D models.The model was executed in ABAQUS ® , in which a finite element analysis was performed [12]. The objective was to simulate the behavior and deformation of corneas under a defined load for comparison with a healthy cornea model.…”