Use of Wavelets in Electrocardiogram Research: a Literature Review
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 rev...
| Main Authors: | , |
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| Format: | Article |
| Language: | Indonesian |
| Published: |
Universitas Muhammadiyah Purwokerto
2021-05-01
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| Series: | Jurnal Informatika |
| Subjects: | |
| Online Access: | http://jurnalnasional.ump.ac.id/index.php/JUITA/article/view/10202 |
| _version_ | 1818937846302507008 |
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| author | Darwan Darwan Hindayati Mustafidah |
| author_facet | Darwan Darwan Hindayati Mustafidah |
| author_sort | Darwan Darwan |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-12-20T05:58:27Z |
| format | Article |
| id | doaj.art-2a8fb8a629c04745934b48f13e4b7e93 |
| institution | Directory Open Access Journal |
| issn | 2086-9398 2579-8901 |
| language | Indonesian |
| last_indexed | 2024-12-20T05:58:27Z |
| publishDate | 2021-05-01 |
| publisher | Universitas Muhammadiyah Purwokerto |
| record_format | Article |
| series | Jurnal Informatika |
| spelling | doaj.art-2a8fb8a629c04745934b48f13e4b7e932022-12-21T19:50:58ZindUniversitas Muhammadiyah PurwokertoJurnal Informatika2086-93982579-89012021-05-0191495610.30595/juita.v9i1.102023736Use of Wavelets in Electrocardiogram Research: a Literature ReviewDarwan Darwan0Hindayati Mustafidah1IAIN Syekh Nurjati CirebonUniversitas Muhammadiyah PurwokertoCurrently 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.http://jurnalnasional.ump.ac.id/index.php/JUITA/article/view/10202ecg, wavelet, dataset, pre-rocesssing, feature extraction |
| spellingShingle | Darwan Darwan Hindayati Mustafidah Use of Wavelets in Electrocardiogram Research: a Literature Review Jurnal Informatika ecg, wavelet, dataset, pre-rocesssing, feature extraction |
| title | Use of Wavelets in Electrocardiogram Research: a Literature Review |
| title_full | Use of Wavelets in Electrocardiogram Research: a Literature Review |
| title_fullStr | Use of Wavelets in Electrocardiogram Research: a Literature Review |
| title_full_unstemmed | Use of Wavelets in Electrocardiogram Research: a Literature Review |
| title_short | Use of Wavelets in Electrocardiogram Research: a Literature Review |
| title_sort | use of wavelets in electrocardiogram research a literature review |
| topic | ecg, wavelet, dataset, pre-rocesssing, feature extraction |
| url | http://jurnalnasional.ump.ac.id/index.php/JUITA/article/view/10202 |
| work_keys_str_mv | AT darwandarwan useofwaveletsinelectrocardiogramresearchaliteraturereview AT hindayatimustafidah useofwaveletsinelectrocardiogramresearchaliteraturereview |