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Novel hybrid visual stimuli incorporating periodic motions into conventional flickering or pattern-reversal visual stimuli for steady-state visual evoked potential-based brain-computer interfaces

In this study, we proposed a new type of hybrid visual stimuli for steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs), which incorporate various periodic motions into conventional flickering stimuli (FS) or pattern reversal stimuli (PRS). Furthermore, we investigated...

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Detalles Bibliográficos
Autores principales: Kwon, Jinuk, Hwang, Jihun, Nam, Hyerin, Im, Chang-Hwan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9534124/
https://www.ncbi.nlm.nih.gov/pubmed/36213545
http://dx.doi.org/10.3389/fninf.2022.997068
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author Kwon, Jinuk
Hwang, Jihun
Nam, Hyerin
Im, Chang-Hwan
author_facet Kwon, Jinuk
Hwang, Jihun
Nam, Hyerin
Im, Chang-Hwan
author_sort Kwon, Jinuk
collection PubMed
description In this study, we proposed a new type of hybrid visual stimuli for steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs), which incorporate various periodic motions into conventional flickering stimuli (FS) or pattern reversal stimuli (PRS). Furthermore, we investigated optimal periodic motions for each FS and PRS to enhance the performance of SSVEP-based BCIs. Periodic motions were implemented by changing the size of the stimulus according to four different temporal functions denoted by none, square, triangular, and sine, yielding a total of eight hybrid visual stimuli. Additionally, we developed the extended version of filter bank canonical correlation analysis (FBCCA), which is a state-of-the-art training-free classification algorithm for SSVEP-based BCIs, to enhance the classification accuracy for PRS-based hybrid visual stimuli. Twenty healthy individuals participated in the SSVEP-based BCI experiment to discriminate four visual stimuli with different frequencies. An average classification accuracy and information transfer rate (ITR) were evaluated to compare the performances of SSVEP-based BCIs for different hybrid visual stimuli. Additionally, the user's visual fatigue for each of the hybrid visual stimuli was also evaluated. As the result, for FS, the highest performances were reported when the periodic motion of the sine waveform was incorporated for all window sizes except for 3 s. For PRS, the periodic motion of the square waveform showed the highest classification accuracies for all tested window sizes. A significant statistical difference in the performance between the two best stimuli was not observed. The averaged fatigue scores were reported to be 5.3 ± 2.05 and 4.05 ± 1.28 for FS with sine-wave periodic motion and PRS with square-wave periodic motion, respectively. Consequently, our results demonstrated that FS with sine-wave periodic motion and PRS with square-wave periodic motion could effectively improve the BCI performances compared to conventional FS and PRS. In addition, thanks to its low visual fatigue, PRS with square-wave periodic motion can be regarded as the most appropriate visual stimulus for the long-term use of SSVEP-based BCIs, particularly for window sizes equal to or larger than 2 s.
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spelling pubmed-95341242022-10-06 Novel hybrid visual stimuli incorporating periodic motions into conventional flickering or pattern-reversal visual stimuli for steady-state visual evoked potential-based brain-computer interfaces Kwon, Jinuk Hwang, Jihun Nam, Hyerin Im, Chang-Hwan Front Neuroinform Neuroscience In this study, we proposed a new type of hybrid visual stimuli for steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs), which incorporate various periodic motions into conventional flickering stimuli (FS) or pattern reversal stimuli (PRS). Furthermore, we investigated optimal periodic motions for each FS and PRS to enhance the performance of SSVEP-based BCIs. Periodic motions were implemented by changing the size of the stimulus according to four different temporal functions denoted by none, square, triangular, and sine, yielding a total of eight hybrid visual stimuli. Additionally, we developed the extended version of filter bank canonical correlation analysis (FBCCA), which is a state-of-the-art training-free classification algorithm for SSVEP-based BCIs, to enhance the classification accuracy for PRS-based hybrid visual stimuli. Twenty healthy individuals participated in the SSVEP-based BCI experiment to discriminate four visual stimuli with different frequencies. An average classification accuracy and information transfer rate (ITR) were evaluated to compare the performances of SSVEP-based BCIs for different hybrid visual stimuli. Additionally, the user's visual fatigue for each of the hybrid visual stimuli was also evaluated. As the result, for FS, the highest performances were reported when the periodic motion of the sine waveform was incorporated for all window sizes except for 3 s. For PRS, the periodic motion of the square waveform showed the highest classification accuracies for all tested window sizes. A significant statistical difference in the performance between the two best stimuli was not observed. The averaged fatigue scores were reported to be 5.3 ± 2.05 and 4.05 ± 1.28 for FS with sine-wave periodic motion and PRS with square-wave periodic motion, respectively. Consequently, our results demonstrated that FS with sine-wave periodic motion and PRS with square-wave periodic motion could effectively improve the BCI performances compared to conventional FS and PRS. In addition, thanks to its low visual fatigue, PRS with square-wave periodic motion can be regarded as the most appropriate visual stimulus for the long-term use of SSVEP-based BCIs, particularly for window sizes equal to or larger than 2 s. Frontiers Media S.A. 2022-09-21 /pmc/articles/PMC9534124/ /pubmed/36213545 http://dx.doi.org/10.3389/fninf.2022.997068 Text en Copyright © 2022 Kwon, Hwang, Nam and Im. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Neuroscience
Kwon, Jinuk
Hwang, Jihun
Nam, Hyerin
Im, Chang-Hwan
Novel hybrid visual stimuli incorporating periodic motions into conventional flickering or pattern-reversal visual stimuli for steady-state visual evoked potential-based brain-computer interfaces
title Novel hybrid visual stimuli incorporating periodic motions into conventional flickering or pattern-reversal visual stimuli for steady-state visual evoked potential-based brain-computer interfaces
title_full Novel hybrid visual stimuli incorporating periodic motions into conventional flickering or pattern-reversal visual stimuli for steady-state visual evoked potential-based brain-computer interfaces
title_fullStr Novel hybrid visual stimuli incorporating periodic motions into conventional flickering or pattern-reversal visual stimuli for steady-state visual evoked potential-based brain-computer interfaces
title_full_unstemmed Novel hybrid visual stimuli incorporating periodic motions into conventional flickering or pattern-reversal visual stimuli for steady-state visual evoked potential-based brain-computer interfaces
title_short Novel hybrid visual stimuli incorporating periodic motions into conventional flickering or pattern-reversal visual stimuli for steady-state visual evoked potential-based brain-computer interfaces
title_sort novel hybrid visual stimuli incorporating periodic motions into conventional flickering or pattern-reversal visual stimuli for steady-state visual evoked potential-based brain-computer interfaces
topic Neuroscience
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9534124/
https://www.ncbi.nlm.nih.gov/pubmed/36213545
http://dx.doi.org/10.3389/fninf.2022.997068
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