Diagnosis of Left Ventricular Hypertrophy Based on Electrocardiogram Signal and Fuzzy Logic

Abstract

Sokolow – Lyon index in detection of left ventricular hypertrophy is a hard limited index, so the clinical manifestation of the disease can be ignored when the measured index is near the threshold. Several proposed studies incorporate multiple index to improve diagnostic quality. However, the process of examination and diagnosis will be longer due to the need to collect more data. To solve this problem, the paper proposes a method of classifying left ventricular hypertrophy using fuzzy logic combining with digital signal processing techniques. The proposed method mainly uses the Sokolov-Lyon index (SV₁+RV₅/V₆ ≥ 35 mm) for major changes in ECG signal but with four soft thresholds corresponding to the different clinical manifestations of the disease. In addition, a program is written in C++ language with QT Creator compiler also is developed to implement the algorithm. From there, the doctors can refer and propose to the patient's treatment regimen.

Keywords

ECG, left ventricular hypertrophy, signal processing, fuzzy logic.

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