Literature DB >> 27831885

An Asynchronous P300-Based Brain-Computer Interface Web Browser for Severely Disabled People.

Victor Martinez-Cagigal, Javier Gomez-Pilar, Daniel Alvarez, Roberto Hornero.   

Abstract

This paper presents an electroencephalographic (EEG) P300-based brain-computer interface (BCI) Internet browser. The system uses the "odd-ball" row-col paradigm for generating the P300 evoked potentials on the scalp of the user, which are immediately processed and translated into web browser commands. There were previous approaches for controlling a BCI web browser. However, to the best of our knowledge, none of them was focused on an assistive context, failing to test their applications with a suitable number of end users. In addition, all of them were synchronous applications, where it was necessary to introduce a "read-mode" command in order to avoid a continuous command selection. Thus, the aim of this study is twofold: 1) to test our web browser with a population of multiple sclerosis (MS) patients in order to assess the usefulness of our proposal to meet their daily communication needs; and 2) to overcome the aforementioned limitation by adding a threshold that discerns between control and non-control states, allowing the user to calmly read the web page without undesirable selections. The browser was tested with sixteen MS patients and five healthy volunteers. Both quantitative and qualitative metrics were obtained. MS participants reached an average accuracy of 84.14%, whereas 95.75% was achieved by control subjects. Results show that MS patients can successfully control the BCI web browser, improving their personal autonomy.

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Year:  2016        PMID: 27831885     DOI: 10.1109/TNSRE.2016.2623381

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


  6 in total

1.  An ERP-based BCI with peripheral stimuli: validation with ALS patients.

Authors:  Yangyang Miao; Erwei Yin; Brendan Z Allison; Yu Zhang; Yan Chen; Yi Dong; Xingyu Wang; Dewen Hu; Andrzej Chchocki; Jing Jin
Journal:  Cogn Neurodyn       Date:  2019-06-11       Impact factor: 5.082

2.  Efficient human-machine control with asymmetric marginal reliability input devices.

Authors:  John H Williamson; Melissa Quek; Iulia Popescu; Andrew Ramsay; Roderick Murray-Smith
Journal:  PLoS One       Date:  2020-06-01       Impact factor: 3.240

3.  Usability of a Hybrid System Combining P300-Based Brain-Computer Interface and Commercial Assistive Technologies to Enhance Communication in People With Multiple Sclerosis.

Authors:  Angela Riccio; Francesca Schettini; Valentina Galiotta; Enrico Giraldi; Maria Grazia Grasso; Febo Cincotti; Donatella Mattia
Journal:  Front Hum Neurosci       Date:  2022-05-26       Impact factor: 3.473

4.  Development of a Brain-Computer Interface Toggle Switch with Low False-Positive Rate Using Respiration-Modulated Photoplethysmography.

Authors:  Chang-Hee Han; Euijin Kim; Chang-Hwan Im
Journal:  Sensors (Basel)       Date:  2020-01-08       Impact factor: 3.576

5.  Asynchronous Control of P300-Based Brain-Computer Interfaces Using Sample Entropy.

Authors:  Víctor Martínez-Cagigal; Eduardo Santamaría-Vázquez; Roberto Hornero
Journal:  Entropy (Basel)       Date:  2019-02-27       Impact factor: 2.524

6.  EEG-Controlled Wall-Crawling Cleaning Robot Using SSVEP-Based Brain-Computer Interface.

Authors:  Lei Shao; Longyu Zhang; Abdelkader Nasreddine Belkacem; Yiming Zhang; Xiaoqi Chen; Ji Li; Hongli Liu
Journal:  J Healthc Eng       Date:  2020-01-11       Impact factor: 2.682

  6 in total

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