Comparisons of three BCIs which do not rely on the visual modality

Qiu, Zhaoyang; Jin, Jing; Yu, Zhang; Sun, Hongyan; Wang, Xingyu

doi:10.1109/icsai.2016.7810934

Cited by 4 publications

(5 citation statements)

References 23 publications

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“…Our search approach returned 37 journal articles, 39 conference/workshop papers, and 3 book chapters eligible for our inclusion criteria [ 1 , 3 , 4 , 8 , 9 , 24 , 30 – 43 , 47 – 105 ]. These papers were published from 2006 to 2021.…”

Section: Resultsmentioning

confidence: 99%

“…It effectively eliminates the data out of the interesting bandwidth. The 0.1–30 Hz bandpass filtering drew the greatest attention in EVE-BCI [ 4 , 34 , 55 , 58 , 78 , 87 , 96 ]. Followed by the bandpass filter, down-sampling was the second prior option, which may be due to the high sample rate of EEG collection devices.…”

Section: Resultsmentioning

confidence: 99%

“…Despite its simplicity, LDA often brought out robust and acceptable classification results for previous EVE-BCIs. Depending on various parameter settings, other deformed DAs such as Bayesian Linear Discriminant Analysis (BLDA) [ 1 , 4 , 36 , 75 ], Shrinkage LDA [ 30 , 31 , 38 , 55 , 86 ], Regularized Discriminant Analysis (RDA)) [ 24 , 33 , 42 , 43 , 51 , 62 , 99 ], and step-wise Linear Discriminant Analysis (SWLDA) [ 74 , 88 , 91 , 92 , 98 ] were also used. In terms of popularity, followed by the DA, another robust supervised learning model, linear Support Vector Machine (linear SVM), was also implemented in [ 32 , 33 , 73 , 82 , 84 , 89 , 95 ].…”

Section: Resultsmentioning

confidence: 99%

“…Nevertheless, only healthy subjects were included in the remaining 80% of articles. An emphasis that, EVE-BCI aims to provide an external communication channel for patients with motor ability impairment, is made in several of these studies [ 4 , 33 , 51 ]. However, neither training nor evaluation of their EVE-BCIs was implemented using patients’ data.…”

Section: Discussionmentioning

confidence: 99%

“…BCI’s primary goal is to enable human and external world interactions by only using brain signals without relying on the brain’s normal output pathways, including peripheral nerves and muscles [ 2 ]. Many BCI systems have been proposed to offer feasible approaches to interact with the environment for healthy people [ 1 , 3 , 4 ] and patients who partially or entirely lose their motor functions [ 5 – 9 ]. BCI has a promising future for valuable applications with more research focus and the latest innovation.…”

Section: Introductionmentioning

confidence: 99%

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EEG-based vibrotactile evoked brain-computer interfaces system: A systematic review

Huang

Liang

et al. 2022

PLoS ONE

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Recently, a novel electroencephalogram-based brain-computer interface (EVE-BCI) using the vibrotactile stimulus shows great potential for an alternative to other typical motor imagery and visual-based ones. (i) Objective: in this review, crucial aspects of EVE-BCI are extracted from the literature to summarize its key factors, investigate the synthetic evidence of feasibility, and generate recommendations for further studies. (ii) Method: five major databases were searched for relevant publications. Multiple key concepts of EVE-BCI, including data collection, stimulation paradigm, vibrotactile control, EEG signal processing, and reported performance, were derived from each eligible article. We then analyzed these concepts to reach our objective. (iii) Results: (a) seventy-nine studies are eligible for inclusion; (b) EEG data are mostly collected among healthy people with an embodiment of EEG cap in EVE-BCI development; (c) P300 and Steady-State Somatosensory Evoked Potential are the two most popular paradigms; (d) only locations of vibration are heavily explored by previous researchers, while other vibrating factors draw little interest. (e) temporal features of EEG signal are usually extracted and used as the input to linear predictive models for EVE-BCI setup; (f) subject-dependent and offline evaluations remain popular assessments of EVE-BCI performance; (g) accuracies of EVE-BCI are significantly higher than chance levels among different populations. (iv) Significance: we summarize trends and gaps in the current EVE-BCI by identifying influential factors. A comprehensive overview of EVE-BCI can be quickly gained by reading this review. We also provide recommendations for the EVE-BCI design and formulate a checklist for a clear presentation of the research work. They are useful references for researchers to develop a more sophisticated and practical EVE-BCI in future studies.

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