Accurate wavelet thresholding method for ECG signals
Article Properties
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LanguageEnglish
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DOI (url)
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Publication Date2024/02/01
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Indian UGC (journal)
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Refrences61
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Citations4
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Kaimin Yu ORCID (unauthenticated)
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Lei Feng
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Yunfei Chen ORCID (unauthenticated)
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Minfeng Wu
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Yuanfang Zhang
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Peibin Zhu
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Wen Chen ORCID (unauthenticated)
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Qihui Wu
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Jianzhong Hao ORCID (unauthenticated)
Cite
Yu, Kaimin, et al. “Accurate Wavelet Thresholding Method for ECG Signals”. Computers in Biology and Medicine, vol. 169, 2024, p. 107835, https://doi.org/10.1016/j.compbiomed.2023.107835.
Yu, K., Feng, L., Chen, Y., Wu, M., Zhang, Y., Zhu, P., Chen, W., Wu, Q., & Hao, J. (2024). Accurate wavelet thresholding method for ECG signals. Computers in Biology and Medicine, 169, 107835. https://doi.org/10.1016/j.compbiomed.2023.107835
Yu, Kaimin, Lei Feng, Yunfei Chen, Minfeng Wu, Yuanfang Zhang, Peibin Zhu, Wen Chen, Qihui Wu, and Jianzhong Hao. “Accurate Wavelet Thresholding Method for ECG Signals”. Computers in Biology and Medicine 169 (2024): 107835. https://doi.org/10.1016/j.compbiomed.2023.107835.
1.
Yu K, Feng L, Chen Y, Wu M, Zhang Y, Zhu P, et al. Accurate wavelet thresholding method for ECG signals. Computers in Biology and Medicine. 2024;169:107835.
Journal Categories
Medicine
Medicine (General)
Computer applications to medicine
Medical informatics
Medicine
Medicine (General)
Medical technology
Science
Biology (General)
Science
Mathematics
Instruments and machines
Electronic computers
Computer science
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Refrences
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
A novel automated tower graph based ECG signal classification method with hexadecimal local adaptive binary pattern and deep learning | Journal of Ambient Intelligence and Humanized Computing |
| 29 | 2023 |
| Multilevel hybrid accurate handcrafted model for myocardial infarction classification using ECG signals | International Journal of Machine Learning and Cybernetics |
| 9 | 2023 |
An Iterative Filtering Based ECG Denoising Using Lifting Wavelet Transform Technique | Electronics |
| 5 | 2023 |
| An exhaustive review of machine and deep learning based diagnosis of heart diseases | Multimedia Tools and Applications |
| 8 | 2022 |
| Artificial intelligence methods for analysis of electrocardiogram signals for cardiac abnormalities: state-of-the-art and future challenges | Artificial Intelligence Review |
| 21 | 2022 |
Refrences Analysis
The category
Science: Mathematics: Instruments and machines: Electronic computers. Computer science 19
is the most frequently represented among the references in this article. It primarily includes studies from Sensors and Measurement. The chart below illustrates the number of referenced publications per year.
Refrences used by this article by year
Citations
| Title | Journal | Journal Categories | Citations | Publication Date |
|---|---|---|---|---|
Adaptive Threshold Learning in Frequency Domain for Classification of Breast Cancer Histopathological Images | International Journal of Intelligent Systems |
| 1 | 2024 |
Unraveling Arrhythmias with Graph-Based Analysis: A Survey of the MIT-BIH Database | Computation |
| 1 | 2024 |
Wavelet Decomposition Layer Selection for the φ-OTDR Signal | Photonics |
| 1 | 2024 |
Advancements in Battery Monitoring: Harnessing Fiber Grating Sensors for Enhanced Performance and Reliability | Sensors |
| 2024 |
Citations Analysis
The category
Technology: Chemical technology 2
is the most commonly referenced area in studies that cite this article. The first research to cite this article was titled Advancements in Battery Monitoring: Harnessing Fiber Grating Sensors for Enhanced Performance and Reliability and was published in 2024. The most recent citation comes from a 2024 study titled Advancements in Battery Monitoring: Harnessing Fiber Grating Sensors for Enhanced Performance and Reliability. This article reached its peak citation in 2024, with 4 citations. It has been cited in 4 different journals, 75% of which are open access. Among related journals, the Sensors cited this research the most, with 1 citations. The chart below illustrates the annual citation trends for this article.