Early Detection of Ischemic Heart Disease Using Multi-lead ECG and Heart Sounds
Date Issued
2012
Date
2012
Author(s)
Tseng, Yi-Li
Abstract
Ischemic heart disease has become the first place of ten leading causes of death for many years. According to the statistic results from WHO, up to 16% of mortality is due to ischemic heart disease. The main reason of high death rate is its lack of early symptoms. Patients suffer from sudden death only after a short period of the occurring of acute coronary syndromes. Some even die without any early symptoms. Therefore, early detection of myocardial ischemia has become an important issue recently. In this study, we implemented a non-invasive 12-lead electrocardiogram (ECG) and a phonocardiogram (PCG) monitoring system, and high-accuracy analyzing methods are also proposed for the early detection of ischemic heart diseases. By the detection of the ischemia of cardiac muscles in its early stage, ischemic heart disease can be detected before the occurring of acute symptoms.
Myocardial ischemia commonly manifests as ST- and T-wave changes on the ECG, or the third heart sound (S3) and the fourth heart sound (S4) of the PCG. For the analysis of ECG signals, we proposed two methods, support vector machine (SVM) and sparse representation-based classification (SRC), to detect abnormal ST-T complex. It integrates knowledge-based and novel classifying methods to extract essential information from ECG signals. In comparison with previous methods, the sensitivity for detecting myocardial ischemia is greatly improved using our methods. For the detection of S3 and S4, a time-frequency analysis method, Hilbert-Huang transform (HHT), was used to analyze non-linear and non-stationary PCG signals. This method can decompose the signal adaptively and acquire the instantaneous frequency. Therefore, all the abnormal components of PCG signals correlated to myocardial dysfunction can be detected simultaneously. The design of the monitoring of these non-invasive signals is based on remote home health care concepts. The recording of 12-lead ECG is designed using multiplexing technique suitable for wireless transmission. Moreover, the design of the electronic stethoscope is based on medical concepts with modulated equalizer.
In this investigation, both analyzing methods and monitoring systems for 12-lead ECG and heart sound are proposed. The sensitivity and accuracy of the proposed methods are of better performance compared to previous methods. Furthermore, the whole monitoring system is aimed for remote home health care. With these concepts, detection of myocardial ischemia in its early stage using non-invasive home health care system could be feasible.
Subjects
myocardial ischemia
ischemic heart disease
12-lead ECG
heart sound
support vector machine
sparse representation-based classification
Hilbert-Huang transform
Type
thesis
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