Enhancing Performance of Single-Channel SSVEP-Based Visual Acuity Assessment via Mode Decomposition
This study aimed to improve the performance of single-channel steady-state visual evoked potential (SSVEP)-based visual acuity assessment by mode decomposition methods. Using the SSVEP dataset induced by the vertical sinusoidal gratings at six spatial frequency steps from 11 subjects, 3-40-Hz band-p...
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Published in | IEEE transactions on neural systems and rehabilitation engineering Vol. 31; pp. 4203 - 4210 |
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Main Authors | , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
ISSN | 1534-4320 1558-0210 1558-0210 |
DOI | 10.1109/TNSRE.2023.3323000 |
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Abstract | This study aimed to improve the performance of single-channel steady-state visual evoked potential (SSVEP)-based visual acuity assessment by mode decomposition methods. Using the SSVEP dataset induced by the vertical sinusoidal gratings at six spatial frequency steps from 11 subjects, 3-40-Hz band-pass filtering and other four mode decomposition methods, i.e., empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), and variational mode decomposition (VMD), were used to preprocess the single-channel SSVEP signals from Oz electrode. After comparing the SSVEP signal characteristics corresponding to each mode decomposition method, the visual acuity threshold estimation criterion was used to obtain the final visual acuity results. The agreement between subjective Freiburg Visual Acuity and Contrast Test (FrACT) and SSVEP visual acuity for band-pass filtering (−0.095 logMAR), EMD (−0.112 logMAR), EEMD (−0.098 logMAR), ICEEMDAN (−0.093 logMAR), and VMD (−0.090 logMAR) was all pretty good, with an acceptable difference between FrACT and SSVEP acuity for band-pass filtering (0.129 logMAR), EMD (0.083 logMAR), EEMD (0.120 logMAR), ICEEMDAN (0.103 logMAR), and VMD (0.108 logMAR), finding that the visual acuity obtained by these four mode decompositions had a lower limit of agreement and a lower or close difference compared to the traditional band-pass filtering method. This study proved that the mode decomposition methods can enhance the performance of single-channel SSVEP-based visual acuity assessment, and also recommended ICEEEMDAN as the mode decomposition method for single-channel electroencephalography (EEG) signal denoising in the SSVEP visual acuity assessment. |
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AbstractList | This study aimed to improve the performance of single-channel steady-state visual evoked potential (SSVEP)-based visual acuity assessment by mode decomposition methods. Using the SSVEP dataset induced by the vertical sinusoidal gratings at six spatial frequency steps from 11 subjects, 3-40-Hz band-pass filtering and other four mode decomposition methods, i.e., empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), and variational mode decomposition (VMD), were used to preprocess the single-channel SSVEP signals from Oz electrode. After comparing the SSVEP signal characteristics corresponding to each mode decomposition method, the visual acuity threshold estimation criterion was used to obtain the final visual acuity results. The agreement between subjective Freiburg Visual Acuity and Contrast Test (FrACT) and SSVEP visual acuity for band-pass filtering (-0.095 logMAR), EMD (-0.112 logMAR), EEMD (-0.098 logMAR), ICEEMDAN (-0.093 logMAR), and VMD (-0.090 logMAR) was all pretty good, with an acceptable difference between FrACT and SSVEP acuity for band-pass filtering (0.129 logMAR), EMD (0.083 logMAR), EEMD (0.120 logMAR), ICEEMDAN (0.103 logMAR), and VMD (0.108 logMAR), finding that the visual acuity obtained by these four mode decompositions had a lower limit of agreement and a lower or close difference compared to the traditional band-pass filtering method. This study proved that the mode decomposition methods can enhance the performance of single-channel SSVEP-based visual acuity assessment, and also recommended ICEEEMDAN as the mode decomposition method for single-channel electroencephalography (EEG) signal denoising in the SSVEP visual acuity assessment. This study aimed to improve the performance of single-channel steady-state visual evoked potential (SSVEP)-based visual acuity assessment by mode decomposition methods. Using the SSVEP dataset induced by the vertical sinusoidal gratings at six spatial frequency steps from 11 subjects, 3-40-Hz band-pass filtering and other four mode decomposition methods, i.e., empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), and variational mode decomposition (VMD), were used to preprocess the single-channel SSVEP signals from Oz electrode. After comparing the SSVEP signal characteristics corresponding to each mode decomposition method, the visual acuity threshold estimation criterion was used to obtain the final visual acuity results. The agreement between subjective Freiburg Visual Acuity and Contrast Test (FrACT) and SSVEP visual acuity for band-pass filtering (-0.095 logMAR), EMD (-0.112 logMAR), EEMD (-0.098 logMAR), ICEEMDAN (-0.093 logMAR), and VMD (-0.090 logMAR) was all pretty good, with an acceptable difference between FrACT and SSVEP acuity for band-pass filtering (0.129 logMAR), EMD (0.083 logMAR), EEMD (0.120 logMAR), ICEEMDAN (0.103 logMAR), and VMD (0.108 logMAR), finding that the visual acuity obtained by these four mode decompositions had a lower limit of agreement and a lower or close difference compared to the traditional band-pass filtering method. This study proved that the mode decomposition methods can enhance the performance of single-channel SSVEP-based visual acuity assessment, and also recommended ICEEEMDAN as the mode decomposition method for single-channel electroencephalography (EEG) signal denoising in the SSVEP visual acuity assessment.This study aimed to improve the performance of single-channel steady-state visual evoked potential (SSVEP)-based visual acuity assessment by mode decomposition methods. Using the SSVEP dataset induced by the vertical sinusoidal gratings at six spatial frequency steps from 11 subjects, 3-40-Hz band-pass filtering and other four mode decomposition methods, i.e., empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), and variational mode decomposition (VMD), were used to preprocess the single-channel SSVEP signals from Oz electrode. After comparing the SSVEP signal characteristics corresponding to each mode decomposition method, the visual acuity threshold estimation criterion was used to obtain the final visual acuity results. The agreement between subjective Freiburg Visual Acuity and Contrast Test (FrACT) and SSVEP visual acuity for band-pass filtering (-0.095 logMAR), EMD (-0.112 logMAR), EEMD (-0.098 logMAR), ICEEMDAN (-0.093 logMAR), and VMD (-0.090 logMAR) was all pretty good, with an acceptable difference between FrACT and SSVEP acuity for band-pass filtering (0.129 logMAR), EMD (0.083 logMAR), EEMD (0.120 logMAR), ICEEMDAN (0.103 logMAR), and VMD (0.108 logMAR), finding that the visual acuity obtained by these four mode decompositions had a lower limit of agreement and a lower or close difference compared to the traditional band-pass filtering method. This study proved that the mode decomposition methods can enhance the performance of single-channel SSVEP-based visual acuity assessment, and also recommended ICEEEMDAN as the mode decomposition method for single-channel electroencephalography (EEG) signal denoising in the SSVEP visual acuity assessment. This study aimed to improve the performance of single-channel steady-state visual evoked potential (SSVEP)-based visual acuity assessment by mode decomposition methods. Using the SSVEP dataset induced by the vertical sinusoidal gratings at six spatial frequency steps from 11 subjects, 3-40-Hz band-pass filtering and other four mode decomposition methods, i.e., empirical mode decomposition (EMD), ensemble empirical mode decomposition (EEMD), improved complete ensemble empirical mode decomposition with adaptive noise (ICEEMDAN), and variational mode decomposition (VMD), were used to preprocess the single-channel SSVEP signals from Oz electrode. After comparing the SSVEP signal characteristics corresponding to each mode decomposition method, the visual acuity threshold estimation criterion was used to obtain the final visual acuity results. The agreement between subjective Freiburg Visual Acuity and Contrast Test (FrACT) and SSVEP visual acuity for band-pass filtering (−0.095 logMAR), EMD (−0.112 logMAR), EEMD (−0.098 logMAR), ICEEMDAN (−0.093 logMAR), and VMD (−0.090 logMAR) was all pretty good, with an acceptable difference between FrACT and SSVEP acuity for band-pass filtering (0.129 logMAR), EMD (0.083 logMAR), EEMD (0.120 logMAR), ICEEMDAN (0.103 logMAR), and VMD (0.108 logMAR), finding that the visual acuity obtained by these four mode decompositions had a lower limit of agreement and a lower or close difference compared to the traditional band-pass filtering method. This study proved that the mode decomposition methods can enhance the performance of single-channel SSVEP-based visual acuity assessment, and also recommended ICEEEMDAN as the mode decomposition method for single-channel electroencephalography (EEG) signal denoising in the SSVEP visual acuity assessment. |
Author | Zheng, Xiaowei Zhang, Rui Zhang, Xun Xu, Guanghua |
Author_xml | – sequence: 1 givenname: Xiaowei orcidid: 0000-0002-8653-7129 surname: Zheng fullname: Zheng, Xiaowei organization: Medical Big Data Research Center and the School of Mathematics, Northwest University, Xi'an, China – sequence: 2 givenname: Xun orcidid: 0000-0002-2165-7525 surname: Zhang fullname: Zhang, Xun organization: School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China – sequence: 3 givenname: Guanghua orcidid: 0000-0002-7409-4068 surname: Xu fullname: Xu, Guanghua organization: State Key Laboratory for Manufacturing Systems Engineering and the School of Mechanical Engineering, Xi'an Jiaotong University, Xi'an, China – sequence: 4 givenname: Rui orcidid: 0000-0001-9547-2585 surname: Zhang fullname: Zhang, Rui email: rzhang@nwu.edu.cn organization: Medical Big Data Research Center and the School of Mathematics, Northwest University, Xi'an, China |
BackLink | https://www.ncbi.nlm.nih.gov/pubmed/37812551$$D View this record in MEDLINE/PubMed |
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SubjectTerms | Acuity Algorithms Band-pass filters Bandpass filters Decomposition EEG Electrodes Electroencephalography Electroencephalography - methods empirical mode decomposition Evoked Potentials, Visual Filtering Frequency dependence Humans Performance enhancement signal denoising Steady-state steady-state visual evoked potential Visual Acuity Visual evoked potentials Visual Perception Visual signals Visual thresholds Visualization White noise |
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Title | Enhancing Performance of Single-Channel SSVEP-Based Visual Acuity Assessment via Mode Decomposition |
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