Automatic Eyeblink Artifact Removal from Single Channel EEG Signals Using One-Dimensional Convolutional Denoising Autoencoder
Eyeblink artifacts are common and significant disruption that occurs when the subject blinks during the recording of the Electroencephalogram (EEG) signals. Removing this artifact is essential to ensure the precision and reliability of the recorded brain activity. Compared to multichannel EEG system...
Uloženo v:
| Vydáno v: | International Conference on Computer, Electrical & Communication Engineering (Online) s. 1 - 7 |
|---|---|
| Hlavní autoři: | , |
| Médium: | Konferenční příspěvek |
| Jazyk: | angličtina |
| Vydáno: |
IEEE
02.02.2024
|
| Témata: | |
| ISSN: | 2768-0576 |
| On-line přístup: | Získat plný text |
| Tagy: |
Přidat tag
Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!
|
| Abstract | Eyeblink artifacts are common and significant disruption that occurs when the subject blinks during the recording of the Electroencephalogram (EEG) signals. Removing this artifact is essential to ensure the precision and reliability of the recorded brain activity. Compared to multichannel EEG systems, the limited spatial resolution of single channel EEG makes it more challenging to identify and eliminate eyeblink artifacts. In this work, we proposed a one-dimensional Convolutional Denoising Autoencoder (CDAE) architecture to efficiently remove the eyeblink artifacts from the single channel EEG signals. The publicly available "EEGdenoiseNet" dataset was used to synthetically generate the eyeblink-contaminated noisy EEG signals which were fed to the encoder to generate a compressed representation and capture essential features. From there, the decoder reconstructed the clean EEG signal. We calculated the Relative Root Mean Square Error (RRMSE) and Correlation Coefficient (CC) to assess the effectiveness of our proposed method and achieved an RRMSE of 35.4% and CC of 0.92. Our proposed method efficiently removes eyeblink artifacts from the single channel EEG signal and performs better in terms of CC compared to any other state-of-the-art method. |
|---|---|
| AbstractList | Eyeblink artifacts are common and significant disruption that occurs when the subject blinks during the recording of the Electroencephalogram (EEG) signals. Removing this artifact is essential to ensure the precision and reliability of the recorded brain activity. Compared to multichannel EEG systems, the limited spatial resolution of single channel EEG makes it more challenging to identify and eliminate eyeblink artifacts. In this work, we proposed a one-dimensional Convolutional Denoising Autoencoder (CDAE) architecture to efficiently remove the eyeblink artifacts from the single channel EEG signals. The publicly available "EEGdenoiseNet" dataset was used to synthetically generate the eyeblink-contaminated noisy EEG signals which were fed to the encoder to generate a compressed representation and capture essential features. From there, the decoder reconstructed the clean EEG signal. We calculated the Relative Root Mean Square Error (RRMSE) and Correlation Coefficient (CC) to assess the effectiveness of our proposed method and achieved an RRMSE of 35.4% and CC of 0.92. Our proposed method efficiently removes eyeblink artifacts from the single channel EEG signal and performs better in terms of CC compared to any other state-of-the-art method. |
| Author | Acharjee, Raktim Ahamed, Shaik Rafi |
| Author_xml | – sequence: 1 givenname: Raktim surname: Acharjee fullname: Acharjee, Raktim email: a.raktim@iitg.ac.in organization: Indian Institute of Technology Guwahati,Dept. of Electronics and Electrical Engineering,Guwahati,Assam,India – sequence: 2 givenname: Shaik Rafi surname: Ahamed fullname: Ahamed, Shaik Rafi email: rafiahamed@iitg.ac.in organization: Indian Institute of Technology Guwahati,Dept. of Electronics and Electrical Engineering,Guwahati,Assam,India |
| BookMark | eNo1UN1KwzAYjaLgnHsDL-IDdH5Jmja5HF2dg8FA3fVIui8z2ibSdsIufHer06vD-eEcONfkIsSAhNwxmDIG-n5ZFGVRSpWlcsqBp1MGqc65hjMy0blWQoIYzFyfkxHPM5WAzLMrMum6NwAQHFKmxYh8zQ59bEzvK1oe0dY-vNNZ23tnqp4-YRM_TU1dGxv67MO-Rlq8mhCwpmW5GKR9MHVHN93g0XXAZO4bDJ2Pg0yLGD5jfehPbI4h-t_czyKGKu6wvSGXbijAyR-OyeahfCkek9V6sSxmq8Qzpvuk0nmFiu2EQaesZJJb4IrBjjshUVpWKeWkUMoKhEykJrPo3A455hYzsGJMbk-9HhG3H61vTHvc_j8mvgENH2T_ |
| ContentType | Conference Proceeding |
| DBID | 6IE 6IL CBEJK RIE RIL |
| DOI | 10.1109/ICCECE58645.2024.10497290 |
| DatabaseName | IEEE Electronic Library (IEL) Conference Proceedings IEEE Proceedings Order Plan All Online (POP All Online) 1998-present by volume IEEE Xplore All Conference Proceedings IEEE Electronic Library (IEL) IEEE Proceedings Order Plans (POP All) 1998-Present |
| DatabaseTitleList | |
| Database_xml | – sequence: 1 dbid: RIE name: IEEE Electronic Library (IEL) url: https://ieeexplore.ieee.org/ sourceTypes: Publisher |
| DeliveryMethod | fulltext_linktorsrc |
| EISBN | 9798350386479 |
| EISSN | 2768-0576 |
| EndPage | 7 |
| ExternalDocumentID | 10497290 |
| Genre | orig-research |
| GroupedDBID | 6IE 6IF 6IL 6IN AAWTH ABLEC ADZIZ ALMA_UNASSIGNED_HOLDINGS BEFXN BFFAM BGNUA BKEBE BPEOZ CBEJK CHZPO IEGSK OCL RIE RIL |
| ID | FETCH-LOGICAL-i119t-c97ce81d3aef8b5152b02810d2f35e5b1c88f5388b3e0634a6beffde2e7be60b3 |
| IEDL.DBID | RIE |
| IngestDate | Wed Aug 27 02:09:32 EDT 2025 |
| IsPeerReviewed | false |
| IsScholarly | false |
| Language | English |
| LinkModel | DirectLink |
| MergedId | FETCHMERGED-LOGICAL-i119t-c97ce81d3aef8b5152b02810d2f35e5b1c88f5388b3e0634a6beffde2e7be60b3 |
| PageCount | 7 |
| ParticipantIDs | ieee_primary_10497290 |
| PublicationCentury | 2000 |
| PublicationDate | 2024-Feb.-2 |
| PublicationDateYYYYMMDD | 2024-02-02 |
| PublicationDate_xml | – month: 02 year: 2024 text: 2024-Feb.-2 day: 02 |
| PublicationDecade | 2020 |
| PublicationTitle | International Conference on Computer, Electrical & Communication Engineering (Online) |
| PublicationTitleAbbrev | ICCECE |
| PublicationYear | 2024 |
| Publisher | IEEE |
| Publisher_xml | – name: IEEE |
| SSID | ssj0003204193 |
| Score | 1.8596944 |
| Snippet | Eyeblink artifacts are common and significant disruption that occurs when the subject blinks during the recording of the Electroencephalogram (EEG) signals.... |
| SourceID | ieee |
| SourceType | Publisher |
| StartPage | 1 |
| SubjectTerms | Automatic Artifact Removal Brain modeling Brain-Computer Interface (BCI) Convolution Convolutional Denoising Autoencoder Correlation coefficient Decoding Electroencephalogram (EEG) Electroencephalography Eyeblink Artifact Noise reduction Single Channel EEG Training |
| Title | Automatic Eyeblink Artifact Removal from Single Channel EEG Signals Using One-Dimensional Convolutional Denoising Autoencoder |
| URI | https://ieeexplore.ieee.org/document/10497290 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV07T8MwELagQogJEEW8ZSTWlCTOwxmrNAWWUvGQulWxfUEVJUElrcTAf-fOTYsYGNgcKydb9tl3tu_7jrErpYUOpZEUNkiQHK0dGYbagTwRnlFEGGNssol4MJCjUTJswOoWCwMANvgMOlS0b_mm0nO6KsMVHqBsgif0zTiOl2Ct9YWK8N0AvZFtdtnwaF7fpWmWZqGMghAPgn7QWcn_yqRiDUl_959d2GPtH0geH66NzT7bgPKAfXXndWU5V3n2SeHe5SvvoioQWoE_wFuFasQJQMIfUWgKnLAEJUx5lt1g1QtxJ3MbNMDvS3B6xPS_ZOng2Oyi0Ur86kFZTex_1CJxXxqYtdlzP3tKb50mn4Iz8bykdnQSa0D_VORQSIWOjK_Qu_Bc4xcihFB5WsoCN0CpBKDnEuSRgqIw4EOsIHKVOGStsirhiHG0dyqSUaJAQoDLOJc-GCwEkTEicYtj1qaxG78vKTPGq2E7-aP-lO3QDNlwaP-MterZHM7Zll7Uk4_ZhZ3obz-kq0Q |
| linkProvider | IEEE |
| linkToHtml | http://cvtisr.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwlV3PT8IwFG6MGvWkRoy_rYnX4bZ2ozuSMYSISBQTboS2b4aIm8FB4sH_3dcyMB48eOuadV3a172v3fu-R8i1VEwFQgsTNmgoOUo5IgiUA6OIeVoawRhtk03Uul0xGES9kqxuuTAAYIPPoGqK9l--ztXMHJXhCufYNsId-kbAue8t6FqrIxXmuxzxyBa5KpU0b9pxnMRJIEIe4FbQ59XlE37lUrGupLn7z5fYI5UfUh7trdzNPlmD7IB81WdFblVXafJpAr6zV1pHYzB8BfoIbzkaEjUUEvqEjSZADZsggwlNklusejHqydSGDdCHDJyG0fpf6HRQ7HZe2iVeNSDLx_Y-06NRv9QwrZDnZtKPW06ZUcEZe15UOCqqKUCEykaQColQxpeILzxX-ykLIJCeEiLFT6CQDBC78FEoIU01-FCTELqSHZL1LM_giFD0eDIUYSRBAMeFPBI-aCzwUGsWuekxqZixG74vRDOGy2E7-aP-kmy3-vedYafdvTslO2a2bHC0f0bWi-kMzsmmmhfjj-mFnfRvU66uiw |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=proceeding&rft.title=International+Conference+on+Computer%2C+Electrical+%26+Communication+Engineering+%28Online%29&rft.atitle=Automatic+Eyeblink+Artifact+Removal+from+Single+Channel+EEG+Signals+Using+One-Dimensional+Convolutional+Denoising+Autoencoder&rft.au=Acharjee%2C+Raktim&rft.au=Ahamed%2C+Shaik+Rafi&rft.date=2024-02-02&rft.pub=IEEE&rft.eissn=2768-0576&rft.spage=1&rft.epage=7&rft_id=info:doi/10.1109%2FICCECE58645.2024.10497290&rft.externalDocID=10497290 |