Neurogaming With Motion-Onset Visual Evoked Potentials (mVEPs): Adults Versus Teenagers

Beveridge, Ryan; Wilson, Shane; Callaghan, Michael; Coyle, Damien

doi:10.1109/tnsre.2019.2904260

Cited by 22 publications

(33 citation statements)

References 46 publications

(60 reference statements)

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“…We observed some features in the ERP responses to both conditions which may be related to motion-onset visual evoked potentials (mVEP). Such mVEPs occur when users percieve the beginning of movement of an object or symbol on a screen (Kuba et al, 2007;Guo et al, 2008;Marshall et al, 2013;Beveridge et al, 2019). Three main peaks have been identified in mVEP: a positive peak (P1), followed by a negative deflection (N2), then another positive peak with a latency of 240-500 ms (Kuba et al, 2007;Guo et al, 2008;Marshall et al, 2013;Beveridge et al, 2019), which has been described as a P2 (Kuba et al, 2007;Guo et al, 2008;Marshall et al, 2013) or P300 (Beveridge et al, 2019).…”

Section: Neurophysiological Distinctionsmentioning

confidence: 99%

“You Have Reached Your Destination”: A Single Trial EEG Classification Study

2020

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Studies have established that it is possible to differentiate between the brain's responses to observing correct and incorrect movements in navigation tasks. Furthermore, these classifications can be used as feedback for a learning-based BCI, to allow real or virtual robots to find quasi-optimal routes to a target. However, when navigating it is important not only to know we are moving in the right direction toward a target, but also to know when we have reached it. We asked participants to observe a virtual robot performing a 1-dimensional navigation task. We recorded EEG and then performed neurophysiological analysis on the responses to two classes of correct movements: those that moved closer to the target but did not reach it, and those that did reach the target. Further, we used a stepwise linear classifier on time-domain features to differentiate the classes on a single-trial basis. A second data set was also used to further test this single-trial classification. We found that the amplitude of the P300 was significantly greater in cases where the movement reached the target. Interestingly, we were able to classify the EEG signals evoked when observing the two classes of correct movements against each other with mean overall accuracy of 66.5 and 68.0% for the two data sets, with greater than chance levels of accuracy achieved for all participants. As a proof of concept, we have shown that it is possible to classify the EEG responses in observing these different correct movements against each other using single-trial EEG. This could be used as part of a learning-based BCI and opens a new door toward a more autonomous BCI navigation system.

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Section: Neurophysiological Distinctionsmentioning

confidence: 99%

“You Have Reached Your Destination”: A Single Trial EEG Classification Study

2020

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“…Controlling video games, virtual and/or augmented reality applications using BCIs. It is one of the most popular current trends in the field [196][197][198][199][200].…”

Section: Eeg Eog P300 Evoked Potentials Neurogaming and Vr/armentioning

confidence: 99%

Summary of over Fifty Years with Brain-Computer Interfaces—A Review

et al. 2021

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Over the last few decades, the Brain-Computer Interfaces have been gradually making their way to the epicenter of scientific interest. Many scientists from all around the world have contributed to the state of the art in this scientific domain by developing numerous tools and methods for brain signal acquisition and processing. Such a spectacular progress would not be achievable without accompanying technological development to equip the researchers with the proper devices providing what is absolutely necessary for any kind of discovery as the core of every analysis: the data reflecting the brain activity. The common effort has resulted in pushing the whole domain to the point where the communication between a human being and the external world through BCI interfaces is no longer science fiction but nowadays reality. In this work we present the most relevant aspects of the BCIs and all the milestones that have been made over nearly 50-year history of this research domain. We mention people who were pioneers in this area as well as we highlight all the technological and methodological advances that have transformed something available and understandable by a very few into something that has a potential to be a breathtaking change for so many. Aiming to fully understand how the human brain works is a very ambitious goal and it will surely take time to succeed. However, even that fraction of what has already been determined is sufficient e.g., to allow impaired people to regain control on their lives and significantly improve its quality. The more is discovered in this domain, the more benefit for all of us this can potentially bring.

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“…Then 359 titles and abstracts were reviewed and 203 were removed, according to the inclusion criteria (section Screening Process: Inclusion and Exclusion Criteria), leaving 156 articles that required full-text review. Twelve articles were subsequently identified as eligible for inclusion and grouping into sub-categories: seven relating to communication (Beveridge et al, 2017(Beveridge et al, , 2019Taherian et al, 2017;Norton et al, 2018;Zhang et al, 2019;Vařeka, 2020); and five concerning mobility (Sanchez et al, 2008;Breshears et al, 2011;Pistohl et al, 2012Pistohl et al, , 2013Jochumsen et al, 2018). The flowchart in Figure 2 details outcomes of: identification; screening; eligibility; inclusion steps.…”

Section: Study Selection and Taxonomymentioning

confidence: 99%

“…Eight studies (Ehlers et al, 2012;Beveridge et al, 2017Beveridge et al, , 2019Taherian et al, 2017;Jochumsen et al, 2018;Norton et al, 2018;Zhang et al, 2019;Vařeka, 2020) in this category used EEG as the non-invasive modality for interrogating the pediatric brain. The study by Jochumsen et al (2018) is the only one on non-invasive pediatric BCI related to manual ability.…”

Section: Non-invasive Pediatric Bcismentioning

confidence: 99%

Brain-Computer Interfaces for Children With Complex Communication Needs and Limited Mobility: A Systematic Review

Orlandi

House

Karlsson

et al. 2021

Front. Hum. Neurosci.

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Brain-computer interfaces (BCIs) represent a new frontier in the effort to maximize the ability of individuals with profound motor impairments to interact and communicate. While much literature points to BCIs' promise as an alternative access pathway, there have historically been few applications involving children and young adults with severe physical disabilities. As research is emerging in this sphere, this article aims to evaluate the current state of translating BCIs to the pediatric population. A systematic review was conducted using the Scopus, PubMed, and Ovid Medline databases. Studies of children and adolescents that reported BCI performance published in English in peer-reviewed journals between 2008 and May 2020 were included. Twelve publications were identified, providing strong evidence for continued research in pediatric BCIs. Research evidence was generally at multiple case study or exploratory study level, with modest sample sizes. Seven studies focused on BCIs for communication and five on mobility. Articles were categorized and grouped based on type of measurement (i.e., non-invasive and invasive), and the type of brain signal (i.e., sensory evoked potentials or movement-related potentials). Strengths and limitations of studies were identified and used to provide requirements for clinical translation of pediatric BCIs. This systematic review presents the state-of-the-art of pediatric BCIs focused on developing advanced technology to support children and youth with communication disabilities or limited manual ability. Despite a few research studies addressing the application of BCIs for communication and mobility in children, results are encouraging and future works should focus on customizable pediatric access technologies based on brain activity.

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Neurogaming With Motion-Onset Visual Evoked Potentials (mVEPs): Adults Versus Teenagers

Cited by 22 publications

References 46 publications

“You Have Reached Your Destination”: A Single Trial EEG Classification Study

“You Have Reached Your Destination”: A Single Trial EEG Classification Study

Summary of over Fifty Years with Brain-Computer Interfaces—A Review

Brain-Computer Interfaces for Children With Complex Communication Needs and Limited Mobility: A Systematic Review

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