Fatigue factors and fatigue indices in SSVEP-based brain-computer interfaces: a systematic review and meta-analysis
BackgroundFatigue is a serious challenge when applying a steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) in the real world. Many researchers have used quantitative indices to study the effect of visual stimuli on fatigue. According to a wide range of studies in fa...
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| Format: | Article |
| Language: | English |
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Frontiers Media S.A.
2023-11-01
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| Series: | Frontiers in Human Neuroscience |
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| Online Access: | https://www.frontiersin.org/articles/10.3389/fnhum.2023.1248474/full |
| _version_ | 1827759614140088320 |
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| author | Maedeh Azadi Moghadam Ali Maleki |
| author_facet | Maedeh Azadi Moghadam Ali Maleki |
| author_sort | Maedeh Azadi Moghadam |
| collection | DOAJ |
| description | BackgroundFatigue is a serious challenge when applying a steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) in the real world. Many researchers have used quantitative indices to study the effect of visual stimuli on fatigue. According to a wide range of studies in fatigue analysis, there are contradictions and inconsistencies in the behavior of fatigue indicators.New methodIn this study, for the first time, a systematic review and meta-analysis were performed on fatigue indices and fatigue caused by stimulation paradigm. We queried three scientific search engines for studies published between 2000 and 2022. The inclusion criteria were papers investigating mental and visual fatigue from performing a visual task using electroencephalogram (EEG) signals.ResultsAttractiveness and variation are the most effective ways to reduce BCI fatigue. Therefore, zoom motion, Newton’s ring motion, and cue patterns reduce fatigue. While the color of the cue could effectively reduce fatigue, its shape and background had no effect on fatigue. Additionally, the questionnaire and quantitative indicators such as frequency indices, signal-to-noise ratio (SNR), SSVEP amplitude, and multiscale entropy were utilized to assess fatigue. Meta-analysis indicated that when a person is fatigued, the spectrum amplitude of alpha, theta, and α+θ/β increase significantly, while SNR and SSVEP amplitude decrease significantly.ConclusionThe outcomes of this study can be used to design more optimal stimulation protocols that cause less fatigue. Moreover, the level of fatigue can be quantitatively assessed with indicators without the participant’s self-reports. |
| first_indexed | 2024-03-11T09:28:10Z |
| format | Article |
| id | doaj.art-35c13736a35049efab9d46000a983c2b |
| institution | Directory Open Access Journal |
| issn | 1662-5161 |
| language | English |
| last_indexed | 2024-03-11T09:28:10Z |
| publishDate | 2023-11-01 |
| publisher | Frontiers Media S.A. |
| record_format | Article |
| series | Frontiers in Human Neuroscience |
| spelling | doaj.art-35c13736a35049efab9d46000a983c2b2023-11-16T17:51:08ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612023-11-011710.3389/fnhum.2023.12484741248474Fatigue factors and fatigue indices in SSVEP-based brain-computer interfaces: a systematic review and meta-analysisMaedeh Azadi Moghadam0Ali Maleki1Department of Biotechnology, Faculty of New Sciences and Technologies, Semnan University, Semnan, IranDepartment of Biomedical Engineering, Semnan University, Semnan, IranBackgroundFatigue is a serious challenge when applying a steady-state visual evoked potential (SSVEP)-based brain-computer interfaces (BCIs) in the real world. Many researchers have used quantitative indices to study the effect of visual stimuli on fatigue. According to a wide range of studies in fatigue analysis, there are contradictions and inconsistencies in the behavior of fatigue indicators.New methodIn this study, for the first time, a systematic review and meta-analysis were performed on fatigue indices and fatigue caused by stimulation paradigm. We queried three scientific search engines for studies published between 2000 and 2022. The inclusion criteria were papers investigating mental and visual fatigue from performing a visual task using electroencephalogram (EEG) signals.ResultsAttractiveness and variation are the most effective ways to reduce BCI fatigue. Therefore, zoom motion, Newton’s ring motion, and cue patterns reduce fatigue. While the color of the cue could effectively reduce fatigue, its shape and background had no effect on fatigue. Additionally, the questionnaire and quantitative indicators such as frequency indices, signal-to-noise ratio (SNR), SSVEP amplitude, and multiscale entropy were utilized to assess fatigue. Meta-analysis indicated that when a person is fatigued, the spectrum amplitude of alpha, theta, and α+θ/β increase significantly, while SNR and SSVEP amplitude decrease significantly.ConclusionThe outcomes of this study can be used to design more optimal stimulation protocols that cause less fatigue. Moreover, the level of fatigue can be quantitatively assessed with indicators without the participant’s self-reports.https://www.frontiersin.org/articles/10.3389/fnhum.2023.1248474/fullbrain-computer interface (BCI)steady-state visual evoked potential (SSVEP)fatiguevisual stimulation paradigmquantitative indices |
| spellingShingle | Maedeh Azadi Moghadam Ali Maleki Fatigue factors and fatigue indices in SSVEP-based brain-computer interfaces: a systematic review and meta-analysis Frontiers in Human Neuroscience brain-computer interface (BCI) steady-state visual evoked potential (SSVEP) fatigue visual stimulation paradigm quantitative indices |
| title | Fatigue factors and fatigue indices in SSVEP-based brain-computer interfaces: a systematic review and meta-analysis |
| title_full | Fatigue factors and fatigue indices in SSVEP-based brain-computer interfaces: a systematic review and meta-analysis |
| title_fullStr | Fatigue factors and fatigue indices in SSVEP-based brain-computer interfaces: a systematic review and meta-analysis |
| title_full_unstemmed | Fatigue factors and fatigue indices in SSVEP-based brain-computer interfaces: a systematic review and meta-analysis |
| title_short | Fatigue factors and fatigue indices in SSVEP-based brain-computer interfaces: a systematic review and meta-analysis |
| title_sort | fatigue factors and fatigue indices in ssvep based brain computer interfaces a systematic review and meta analysis |
| topic | brain-computer interface (BCI) steady-state visual evoked potential (SSVEP) fatigue visual stimulation paradigm quantitative indices |
| url | https://www.frontiersin.org/articles/10.3389/fnhum.2023.1248474/full |
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