Literature DB >> 30869627

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

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

Abstract

Motion-onset visually evoked potentials (mVEPs) are neural potentials that are time-locked to the onset of motion of evoking stimuli. Due to their visually elegant properties, mVEP stimuli may be suited to video game control given gaming's inherent demand on the users' visual attention and the requirement to process rapidly changing visual information. Here, we investigate mVEPs associated with five different stimuli to control the position of a car in a visually rich 3D racing game in a group of 15 BCI naïve teenagers and compared with 19 BCI naive adults. Results from an additional 14 BCI experienced adults were compared with BCI naïve adults. Our results demonstrate that the game control accuracy is related to the number of trials used to make a decision on the users' chosen button/stimulus (76%, 62%, and 35% for 5, 3, and 1 trials, respectively) and information transfer rate (ITR) (13.4, 13.9, and 6.6 bits per minute (BPM)), although, even though accuracy decreases when using three compared to the commonly used five trial repetitions, ITR is maintained. A Kruskal-Wallis test suggests that BCI naïve adults do not outperform BCI naïve teenagers in the 3D racing game in the first and seconds laps (p > 0.05), but do outperform in the third lap (p < 0.05). A comparison between BCI naïve and BCI experienced adults indicates BCI experienced adults do not perform better than BCI naïve adults (p > 0.05).

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Year:  2019        PMID: 30869627     DOI: 10.1109/TNSRE.2019.2904260

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  4 in total

Review 1.  Bacomics: a comprehensive cross area originating in the studies of various brain-apparatus conversations.

Authors:  Dezhong Yao; Yangsong Zhang; Tiejun Liu; Peng Xu; Diankun Gong; Jing Lu; Yang Xia; Cheng Luo; Daqing Guo; Li Dong; Yongxiu Lai; Ke Chen; Jianfu Li
Journal:  Cogn Neurodyn       Date:  2020-03-17       Impact factor: 3.473

Review 2.  Summary of over Fifty Years with Brain-Computer Interfaces-A Review.

Authors:  Aleksandra Kawala-Sterniuk; Natalia Browarska; Amir Al-Bakri; Mariusz Pelc; Jaroslaw Zygarlicki; Michaela Sidikova; Radek Martinek; Edward Jacek Gorzelanczyk
Journal:  Brain Sci       Date:  2021-01-03

3.  DF-SSmVEP: Dual Frequency Aggregated Steady-State Motion Visual Evoked Potential Design with Bifold Canonical Correlation Analysis.

Authors:  Raika Karimi; Arash Mohammadi; Amir Asif; Habib Benali
Journal:  Sensors (Basel)       Date:  2022-03-27       Impact factor: 3.576

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

Authors:  Silvia Orlandi; Sarah C House; Petra Karlsson; Rami Saab; Tom Chau
Journal:  Front Hum Neurosci       Date:  2021-07-14       Impact factor: 3.169

  4 in total

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