Literature DB >> 27914171

Clinical feasibility of brain-computer interface based on steady-state visual evoked potential in patients with locked-in syndrome: Case studies.

Han-Jeong Hwang1,2, Chang-Hee Han1, Jeong-Hwan Lim1, Yong-Wook Kim1, Soo-In Choi2, Kwang-Ok An3, Jun-Hak Lee1, Ho-Seung Cha1, Seung Hyun Kim4, Chang-Hwan Im1.   

Abstract

Although the feasibility of brain-computer interface (BCI) systems based on steady-state visual evoked potential (SSVEP) has been extensively investigated, only a few studies have evaluated its clinical feasibility in patients with locked-in syndrome (LIS), who are the main targets of BCI technology. The main objective of this case report was to share our experiences of SSVEP-based BCI experiments involving five patients with LIS, thereby providing researchers with useful information that can potentially help them to design BCI experiments for patients with LIS. In our experiments, a four-class online SSVEP-based BCI system was implemented and applied to four of five patients repeatedly on multiple days to investigate its test-retest reliability. In the last experiments with two of the four patients, the practical usability of our BCI system was tested using a questionnaire survey. All five patients showed clear and distinct SSVEP responses at all four fundamental stimulation frequencies (6, 6.66, 7.5, 10 Hz), and responses at harmonic frequencies were also observed in three patients. Mean classification accuracy was 76.99% (chance level = 25%). The test-retest reliability experiments demonstrated stable performance of our BCI system over different days even when the initial experimental settings (e.g., electrode configuration, fixation time, visual angle) used in the first experiment were used without significant modifications. Our results suggest that SSVEP-based BCI paradigms might be successfully used to implement clinically feasible BCI systems for severely paralyzed patients.
© 2016 Society for Psychophysiological Research.

Entities:  

Keywords:  Amyotrophic lateral sclerosis (ALS); Brain-computer interface (BCI); Clinical feasibility; EEG; Locked-in syndrome (LIS); Steady-state visual evoked potential (SSVEP)

Mesh:

Year:  2016        PMID: 27914171     DOI: 10.1111/psyp.12793

Source DB:  PubMed          Journal:  Psychophysiology        ISSN: 0048-5772            Impact factor:   4.016


  9 in total

1.  eldBETA: A Large Eldercare-oriented Benchmark Database of SSVEP-BCI for the Aging Population.

Authors:  Bingchuan Liu; Yijun Wang; Xiaorong Gao; Xiaogang Chen
Journal:  Sci Data       Date:  2022-05-31       Impact factor: 8.501

2.  Behind the Scenes of Noninvasive Brain-Computer Interfaces: A Review of Electroencephalography Signals, How They Are Recorded, and Why They Matter.

Authors:  Kevin M Pitt; Jonathan S Brumberg; Jeremy D Burnison; Jyutika Mehta; Juhi Kidwai
Journal:  Perspect ASHA Spec Interest Groups       Date:  2019-11-09

Review 3.  A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives.

Authors:  Inchul Choi; Ilsun Rhiu; Yushin Lee; Myung Hwan Yun; Chang S Nam
Journal:  PLoS One       Date:  2017-04-28       Impact factor: 3.240

4.  Eyes-closed hybrid brain-computer interface employing frontal brain activation.

Authors:  Jaeyoung Shin; Klaus-Robert Müller; Han-Jeong Hwang
Journal:  PLoS One       Date:  2018-05-07       Impact factor: 3.240

5.  Long-term use of a neural prosthesis in progressive paralysis.

Authors:  Yoji Okahara; Kouji Takano; Masahiro Nagao; Kiyohiko Kondo; Yasuo Iwadate; Niels Birbaumer; Kenji Kansaku
Journal:  Sci Rep       Date:  2018-11-14       Impact factor: 4.379

6.  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

7.  SSVEP BCI and Eye Tracking Use by Individuals With Late-Stage ALS and Visual Impairments.

Authors:  Betts Peters; Steven Bedrick; Shiran Dudy; Brandon Eddy; Matt Higger; Michelle Kinsella; Deirdre McLaughlin; Tab Memmott; Barry Oken; Fernando Quivira; Scott Spaulding; Deniz Erdogmus; Melanie Fried-Oken
Journal:  Front Hum Neurosci       Date:  2020-11-20       Impact factor: 3.169

8.  Motor Imagery Under Distraction- An Open Access BCI Dataset.

Authors:  Stephanie Brandl; Benjamin Blankertz
Journal:  Front Neurosci       Date:  2020-10-19       Impact factor: 4.677

9.  High-gamma oscillations precede visual steady-state responses: A human electrocorticography study.

Authors:  Benjamin Wittevrongel; Elvira Khachatryan; Evelien Carrette; Paul Boon; Alfred Meurs; Dirk Van Roost; Marc M Van Hulle
Journal:  Hum Brain Mapp       Date:  2020-09-04       Impact factor: 5.038

  9 in total

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