Literature DB >> 19000739

Brain-computer interface: changes in performance using virtual reality techniques.

Ricardo Ron-Angevin1, Antonio Díaz-Estrella.   

Abstract

The ability to control electroencephalographic (EEG) signals when different mental tasks are carried out would provide a method of communication for people with serious motor function problems. This system is known as a brain-computer interface (BCI). Due to the difficulty of controlling one's own EEG signals, a suitable training protocol is required to motivate subjects, as it is necessary to provide some type of visual feedback allowing subjects to see their progress. Conventional systems of feedback are based on simple visual presentations, such as a horizontal bar extension. However, virtual reality is a powerful tool with graphical possibilities to improve BCI-feedback presentation. The objective of the study is to explore the advantages of the use of feedback based on virtual reality techniques compared to conventional systems of feedback. Sixteen untrained subjects, divided into two groups, participated in the experiment. A group of subjects was trained using a BCI system, which uses conventional feedback (bar extension), and another group was trained using a BCI system, which submits subjects to a more familiar environment, such as controlling a car to avoid obstacles. The obtained results suggest that EEG behaviour can be modified via feedback presentation. Significant differences in classification error rates between both interfaces were obtained during the feedback period, confirming that an interface based on virtual reality techniques can improve the feedback control, specifically for untrained subjects.

Entities:  

Mesh:

Year:  2008        PMID: 19000739     DOI: 10.1016/j.neulet.2008.10.099

Source DB:  PubMed          Journal:  Neurosci Lett        ISSN: 0304-3940            Impact factor:   3.046


  15 in total

1.  EEG control of a virtual helicopter in 3-dimensional space using intelligent control strategies.

Authors:  Audrey S Royer; Alexander J Doud; Minn L Rose; Bin He
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2010-09-27       Impact factor: 3.802

2.  Noninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms.

Authors:  Bin He; Bryan Baxter; Bradley J Edelman; Christopher C Cline; Wendy Ye
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2015-05-20       Impact factor: 10.961

3.  Change in brain activity through virtual reality-based brain-machine communication in a chronic tetraplegic subject with muscular dystrophy.

Authors:  Yasunari Hashimoto; Junichi Ushiba; Akio Kimura; Meigen Liu; Yutaka Tomita
Journal:  BMC Neurosci       Date:  2010-09-16       Impact factor: 3.288

4.  Brain-computer interface control in a virtual reality environment and applications for the internet of things.

Authors:  Christopher G Coogan; Bin He
Journal:  IEEE Access       Date:  2018-02-27       Impact factor: 3.367

Review 5.  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 6.  Enrichment of Human-Computer Interaction in Brain-Computer Interfaces via Virtual Environments.

Authors:  Alonso-Valerdi Luz María; Mercado-García Víctor Rodrigo; Luz María Alonso-Valerdi; Víctor Rodrigo Mercado-García
Journal:  Comput Intell Neurosci       Date:  2017-11-29

7.  3D visualization of movements can amplify motor cortex activation during subsequent motor imagery.

Authors:  Teresa Sollfrank; Daniel Hart; Rachel Goodsell; Jonathan Foster; Tele Tan
Journal:  Front Hum Neurosci       Date:  2015-08-20       Impact factor: 3.169

8.  Flaws in current human training protocols for spontaneous Brain-Computer Interfaces: lessons learned from instructional design.

Authors:  Fabien Lotte; Florian Larrue; Christian Mühl
Journal:  Front Hum Neurosci       Date:  2013-09-17       Impact factor: 3.169

9.  Functional recovery from chronic writer's cramp by brain-computer interface rehabilitation: a case report.

Authors:  Yasunari Hashimoto; Tetsuo Ota; Masahiko Mukaino; Meigen Liu; Junichi Ushiba
Journal:  BMC Neurosci       Date:  2014-09-01       Impact factor: 3.288

10.  Computer task performance by subjects with Duchenne muscular dystrophy.

Authors:  Silvia Regina Pinheiro Malheiros; Talita Dias da Silva; Francis Meire Favero; Luiz Carlos de Abreu; Felipe Fregni; Denise Cardoso Ribeiro; Carlos Bandeira de Mello Monteiro
Journal:  Neuropsychiatr Dis Treat       Date:  2015-12-30       Impact factor: 2.570

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