EEG Eye Blink Artifacts Removal with Wavelet Denoising and Bandpass Filtering
Many data sources can be analyzed using Wavelet Transforms (WT), a mathematical technique frequently used for extracting information from them. Although WT was effective at Blind Source Separation (BSS), it had some limitations, such as signal loss. The problem has been addressed with the introduct...
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| Format: | Article |
| Language: | English |
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University of Baghdad, College of Science for Women
2024-11-01
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| Series: | مجلة بغداد للعلوم |
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| Online Access: | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/8947 |
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| author | Ebtesam N. AlShemmary Bushra K. Hilal Azmi Sh. Abdulbaqi Mohammed A. Ahmed Zhentai Lu |
| author_facet | Ebtesam N. AlShemmary Bushra K. Hilal Azmi Sh. Abdulbaqi Mohammed A. Ahmed Zhentai Lu |
| author_sort | Ebtesam N. AlShemmary |
| collection | DOAJ |
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Many data sources can be analyzed using Wavelet Transforms (WT), a mathematical technique frequently used for extracting information from them. Although WT was effective at Blind Source Separation (BSS), it had some limitations, such as signal loss. The problem has been addressed with the introduction of a joint algorithm that combines WT with Frequency Domain Filtering (BPF). Wavelet Denoising Technique (WDT) and Band-Pass Filtering (BPF) are employed in this research to propose an innovative algorithm for combining advanced wavelet transform methods. Combining these two techniques helps reduce eye flutter in electroencephalograms (EEGs).FP1 signals produced by eye movement are filtered out by this novel algorithm. EEG signals should be captured dependably. Combined WTs perform better than traditional WTs, according to evidence. Based on Signal-to-Noise-Ration (SNR) and Power Spectral Density (PSD) measurements, the removal process has been demonstrated to be more efficient than a standard WT.
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| format | Article |
| id | doaj-art-c8e78a82f3ba4d218d0723a1f1d18f01 |
| institution | Kabale University |
| issn | 2078-8665 2411-7986 |
| language | English |
| publishDate | 2024-11-01 |
| publisher | University of Baghdad, College of Science for Women |
| record_format | Article |
| series | مجلة بغداد للعلوم |
| spelling | doaj-art-c8e78a82f3ba4d218d0723a1f1d18f012025-08-20T03:57:43ZengUniversity of Baghdad, College of Science for Womenمجلة بغداد للعلوم2078-86652411-79862024-11-01211110.21123/bsj.2024.8947EEG Eye Blink Artifacts Removal with Wavelet Denoising and Bandpass FilteringEbtesam N. AlShemmary 0https://orcid.org/0000-0001-7500-9702Bushra K. Hilal 1Azmi Sh. Abdulbaqi 2Mohammed A. Ahmed 3Zhentai Lu4IT Research and Development Center, University of Kufa, Najaf, Iraq.Department of Computer Information Systems, College of Computer Science and Information Technology, University of Qadisiyah, Al-Qadisiyah, Iraq.Renewable Energy Research Center, University of Anbar, Ramadi, Iraq.College of Computer Software, South China University of Technology, Guangzhou, China.Biomedical Engineering School, Southern Medical University, Guangzhou, China. Many data sources can be analyzed using Wavelet Transforms (WT), a mathematical technique frequently used for extracting information from them. Although WT was effective at Blind Source Separation (BSS), it had some limitations, such as signal loss. The problem has been addressed with the introduction of a joint algorithm that combines WT with Frequency Domain Filtering (BPF). Wavelet Denoising Technique (WDT) and Band-Pass Filtering (BPF) are employed in this research to propose an innovative algorithm for combining advanced wavelet transform methods. Combining these two techniques helps reduce eye flutter in electroencephalograms (EEGs).FP1 signals produced by eye movement are filtered out by this novel algorithm. EEG signals should be captured dependably. Combined WTs perform better than traditional WTs, according to evidence. Based on Signal-to-Noise-Ration (SNR) and Power Spectral Density (PSD) measurements, the removal process has been demonstrated to be more efficient than a standard WT. https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/8947Analyzing of Signal, Blinking of Eye, Electroencephalogram (EEG), Processing of Bandpass Filtering (BPF), Wavelet Transformation (WT). |
| spellingShingle | Ebtesam N. AlShemmary Bushra K. Hilal Azmi Sh. Abdulbaqi Mohammed A. Ahmed Zhentai Lu EEG Eye Blink Artifacts Removal with Wavelet Denoising and Bandpass Filtering مجلة بغداد للعلوم Analyzing of Signal, Blinking of Eye, Electroencephalogram (EEG), Processing of Bandpass Filtering (BPF), Wavelet Transformation (WT). |
| title | EEG Eye Blink Artifacts Removal with Wavelet Denoising and Bandpass Filtering |
| title_full | EEG Eye Blink Artifacts Removal with Wavelet Denoising and Bandpass Filtering |
| title_fullStr | EEG Eye Blink Artifacts Removal with Wavelet Denoising and Bandpass Filtering |
| title_full_unstemmed | EEG Eye Blink Artifacts Removal with Wavelet Denoising and Bandpass Filtering |
| title_short | EEG Eye Blink Artifacts Removal with Wavelet Denoising and Bandpass Filtering |
| title_sort | eeg eye blink artifacts removal with wavelet denoising and bandpass filtering |
| topic | Analyzing of Signal, Blinking of Eye, Electroencephalogram (EEG), Processing of Bandpass Filtering (BPF), Wavelet Transformation (WT). |
| url | https://bsj.uobaghdad.edu.iq/index.php/BSJ/article/view/8947 |
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