Evaluation of Heart Disease Diagnosis Approach using ECG Images

被引：0

作者：

Ferreira Junior, Marcos Aurelio A. ^{[1
]}

Gurgel, Mateus Valentim ^{[1
]}

Marinho, Leandro B. ^{[2
]}

Nascimento, Navar Medeiros M. ^{[2
]}

da Silva, Suane Pires P. ^{[1
]}

Alves, Shara Shami A. ^{[2
]}

Bezerra Ramalho, Gerald Luis ^{[1
]}

Reboucas Filho, Pedro Pedrosa ^{[1
]}

机构：

[1] Inst Fed Ceara, Programa Posgrad Ciencia Comp PPGCC, Fortaleza, Ceara, Brazil

[2] Univ Fed Ceara, Grad Program Teleinfonnat Engn PPGETI, Fortaleza, Ceara, Brazil

来源：

2019 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS (IJCNN) | 2019年

关键词：

MultiLayer Perceptron; Neural Networks; ECG; Heart diseases; ARRHYTHMIA DETECTION; BEAT CLASSIFICATION; FEATURE-EXTRACTION; RECOGNITION; INTEGRATION; FEATURES; TREE;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Among illnesses, heart diseases are accounted for as one of the most responsible for deaths. Precise and fast diagnoses increase the patient's chances to receive treatment time. A non-invasive and low-cost way to diagnose it is by using Electrocardiogram (ECG). In this paper, we propose a way to diagnosis two types of heart arrhythmia, by using the ECG record as an image. To access the performance of our system, five feature extraction methods well-known in literature are used along with five different classifiers are tested. We were able to identify heart disorders with over 96.00% of accuracy, using a vanilla neural-network, Multilayer Perceptron (MLP), and Local Binary Patterns (LBP) from ECG images. This investigation has shown promising results from a medical point-of-view.

引用

页数：7

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