Literature DB >> 25668430

Performance variation in motor imagery brain-computer interface: a brief review.

Minkyu Ahn1, Sung Chan Jun2.   

Abstract

Brain-computer interface (BCI) technology has attracted significant attention over recent decades, and has made remarkable progress. However, BCI still faces a critical hurdle, in that performance varies greatly across and even within subjects, an obstacle that degrades the reliability of BCI systems. Understanding the causes of these problems is important if we are to create more stable systems. In this short review, we report the most recent studies and findings on performance variation, especially in motor imagery-based BCI, which has found that low-performance groups have a less-developed brain network that is incapable of motor imagery. Further, psychological and physiological states influence performance variation within subjects. We propose a possible strategic approach to deal with this variation, which may contribute to improving the reliability of BCI. In addition, the limitations of current work and opportunities for future studies are discussed.
Copyright © 2015 Elsevier B.V. All rights reserved.

Keywords:  BCI-illiteracy; Brain–computer interface; Motor imagery; Performance variation; Prediction

Mesh:

Year:  2015        PMID: 25668430     DOI: 10.1016/j.jneumeth.2015.01.033

Source DB:  PubMed          Journal:  J Neurosci Methods        ISSN: 0165-0270            Impact factor:   2.390


  59 in total

1.  Can time-resolved NIRS provide the sensitivity to detect brain activity during motor imagery consistently?

Authors:  Androu Abdalmalak; Daniel Milej; Mamadou Diop; Mahsa Shokouhi; Lorina Naci; Adrian M Owen; Keith St Lawrence
Journal:  Biomed Opt Express       Date:  2017-03-13       Impact factor: 3.732

Review 2.  Guidelines for Feature Matching Assessment of Brain-Computer Interfaces for Augmentative and Alternative Communication.

Authors:  Kevin M Pitt; Jonathan S Brumberg
Journal:  Am J Speech Lang Pathol       Date:  2018-08-06       Impact factor: 2.408

3.  Critiquing the Concept of BCI Illiteracy.

Authors:  Margaret C Thompson
Journal:  Sci Eng Ethics       Date:  2018-08-16       Impact factor: 3.525

4.  Learning in brain-computer interface control evidenced by joint decomposition of brain and behavior.

Authors:  Jennifer Stiso; Marie-Constance Corsi; Jean M Vettel; Javier Garcia; Fabio Pasqualetti; Fabrizio De Vico Fallani; Timothy H Lucas; Danielle S Bassett
Journal:  J Neural Eng       Date:  2020-07-24       Impact factor: 5.379

5.  Effects of Soft Drinks on Resting State EEG and Brain-Computer Interface Performance.

Authors:  Jianjun Meng; John Mundahl; Taylor Streitz; Kaitlin Maile; Nicholas Gulachek; Jeffrey He; Bin He
Journal:  IEEE Access       Date:  2017-09-11       Impact factor: 3.367

Review 6.  Progress in Brain Computer Interface: Challenges and Opportunities.

Authors:  Simanto Saha; Khondaker A Mamun; Khawza Ahmed; Raqibul Mostafa; Ganesh R Naik; Sam Darvishi; Ahsan H Khandoker; Mathias Baumert
Journal:  Front Syst Neurosci       Date:  2021-02-25

7.  Multiclass covert speech classification using extreme learning machine.

Authors:  Dipti Pawar; Sudhir Dhage
Journal:  Biomed Eng Lett       Date:  2020-03-03

8.  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

9.  Examining sensory ability, feature matching and assessment-based adaptation for a brain-computer interface using the steady-state visually evoked potential.

Authors:  Jonathan S Brumberg; Anh Nguyen; Kevin M Pitt; Sean D Lorenz
Journal:  Disabil Rehabil Assist Technol       Date:  2018-01-31

Review 10.  A review of the progression and future implications of brain-computer interface therapies for restoration of distal upper extremity motor function after stroke.

Authors:  Alexander Remsik; Brittany Young; Rebecca Vermilyea; Laura Kiekhoefer; Jessica Abrams; Samantha Evander Elmore; Paige Schultz; Veena Nair; Dorothy Edwards; Justin Williams; Vivek Prabhakaran
Journal:  Expert Rev Med Devices       Date:  2016-05       Impact factor: 3.166

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