Implementation of a Portable Personal EKG Signal Monitoring System

Tan, Tan-Hsu; Chang, Chia-Wei; Chen, Yung-Fu; Liu, Cheng

doi:10.1007/978-3-540-77413-6_16

Cited by 2 publications

(1 citation statement)

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“…Various method approaches are used to obtain a good end result, such as fuzzy, wavelet, machine learning or statistical methods [8]. There are even those who use tools (CSA) on Linux [9]. In this study, researchers tried to conduct research in terms of literature studies related to electrocardiograms (ECG).…”

Section: Methodsmentioning

confidence: 99%

Use of Wavelets in Electrocardiogram Research: a Literature Review

Darwan¹,

Mustafidah

2021

Jurnal Informatika

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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.

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Section: Methodsmentioning

confidence: 99%