Use of Wavelets in Electrocardiogram Research: a Literature Review

Abstract

Currently the introduction and detection of heart abnormalities using electrocardiogram (ECG) is very much. ECG conducted many research approaches in various methods, one of which is wavelet. This article aims to explain the trends of ECG research using wavelet approach in the last ten years. We reviewed journals with the keyword title "ecg wavelet" and published from 2011 to 2020. Articles classified by the most frequently discussed topics include: datasets, case studies, pre-processing, feature extraction and classification/identification methods. The increase in the number of ECG-related articles in recent years is still growing in new ways and methods. This study is very interesting because only a few researchers focus on researching about it. Several approaches from many researchers are used to obtain the best results, both by using machine learning and deep learning. This article will provide further explanation of the most widely used algorithms against ECG research with wavelet approaches. At the end of this article it is also shown that the critical aspect of ECG research can be done in the future is the use of datasets, as well as the extraction of characteristics and classifications by looking at the level of accuracy.

Literature Review of the Use of Deep Learning Methods in Identification of Heart Defects Based on ECG

“…Several studies related to ECG have been published a lot in the past few decades. Based on searches obtained by researchers and also conducted by [14], ECG-related research has previously been conducted by [15]. While the use of Deep Learning in identifying heart abnormalities using ECG obtained by researchers was first carried out by [16].…”

“…In addition to the selection of methods, at this stage will also usually look for performance from the research being developed. Researchers in terms of performance search that are often used include accuracy, sensitivity and specificity [14]. Confusion Matrix is used to find the level of accuracy, sensitivity and specificity, some even use precision [42].…”

Application of Artificial Neural Networks in the Identification of Heart Abnormalities Based on Ecg: Literature Review

“…The classification and identification stages are some researchers looking for performance. Performance that is often used by researchers includes accuracy, sensitivity and specificity [45]. In finding the level of accuracy, sensitivity and specificity using the Confusion Matrix [46].…”