Literature DB >> 28393761

Enhancing clinical communication assessments using an audiovisual BCI for patients with disorders of consciousness.

Fei Wang1, Yanbin He, Jun Qu, Qiuyou Xie, Qing Lin, Xiaoxiao Ni, Yan Chen, Jiahui Pan, Steven Laureys, Ronghao Yu, Yuanqing Li.   

Abstract

OBJECTIVE: The JFK coma recovery scale-revised (JFK CRS-R), a behavioral observation scale, is widely used in the clinical diagnosis/assessment of patients with disorders of consciousness (DOC). However, the JFK CRS-R is associated with a high rate of misdiagnosis (approximately 40%) because DOC patients cannot provide sufficient behavioral responses. A brain-computer interface (BCI) that detects command/intention-specific changes in electroencephalography (EEG) signals without the need for behavioral expression may provide an alternative method. APPROACH: In this paper, we proposed an audiovisual BCI communication system based on audiovisual 'yes' and 'no' stimuli to supplement the JFK CRS-R for assessing the communication ability of DOC patients. Specifically, patients were given situation-orientation questions as in the JFK CRS-R and instructed to select the answers using the BCI. MAIN
RESULTS: Thirteen patients (eight vegetative state (VS) and five minimally conscious state (MCS)) participated in our experiments involving both the BCI- and JFK CRS-R-based assessments. One MCS patient who received a score of 1 in the JFK CRS-R achieved an accuracy of 86.5% in the BCI-based assessment. Seven patients (four VS and three MCS) obtained unresponsive results in the JFK CRS-R-based assessment but responsive results in the BCI-based assessment, and 4 of those later improved scores in the JFK CRS-R-based assessment. Five patients (four VS and one MCS) obtained usresponsive results in both assessments. SIGNIFICANCE: The experimental results indicated that the audiovisual BCI could provide more sensitive results than the JFK CRS-R and therefore supplement the JFK CRS-R.

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Year:  2017        PMID: 28393761     DOI: 10.1088/1741-2552/aa6c31

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  7 in total

Review 1.  Brain-Computer Interfaces for Awareness Detection, Auxiliary Diagnosis, Prognosis, and Rehabilitation in Patients with Disorders of Consciousness.

Authors:  Jiahui Pan; Jun Xiao; Jing Wang; Fei Wang; Jingcong Li; Lina Qiu; Haibo Di; Yuanqing Li
Journal:  Semin Neurol       Date:  2022-07-14       Impact factor: 3.212

2.  The Self-Face Paradigm Improves the Performance of the P300-Speller System.

Authors:  Zhaohua Lu; Qi Li; Ning Gao; Jingjing Yang
Journal:  Front Comput Neurosci       Date:  2020-01-15       Impact factor: 2.380

Review 3.  Advances in Hybrid Brain-Computer Interfaces: Principles, Design, and Applications.

Authors:  Zina Li; Shuqing Zhang; Jiahui Pan
Journal:  Comput Intell Neurosci       Date:  2019-10-08

Review 4.  Managing disorders of consciousness: the role of electroencephalography.

Authors:  Yang Bai; Yajun Lin; Ulf Ziemann
Journal:  J Neurol       Date:  2020-09-11       Impact factor: 4.849

5.  How brain-computer interface technology may improve the diagnosis of the disorders of consciousness: A comparative study.

Authors:  Rossella Spataro; Yiyan Xu; Ren Xu; Giorgio Mandalà; Brendan Z Allison; Rupert Ortner; Alexander Heilinger; Vincenzo La Bella; Christoph Guger
Journal:  Front Neurosci       Date:  2022-08-11       Impact factor: 5.152

6.  Emotion-Related Consciousness Detection in Patients With Disorders of Consciousness Through an EEG-Based BCI System.

Authors:  Jiahui Pan; Qiuyou Xie; Haiyun Huang; Yanbin He; Yuping Sun; Ronghao Yu; Yuanqing Li
Journal:  Front Hum Neurosci       Date:  2018-05-15       Impact factor: 3.169

7.  Visual Fixation Assessment in Patients with Disorders of Consciousness Based on Brain-Computer Interface.

Authors:  Jun Xiao; Jiahui Pan; Yanbin He; Qiuyou Xie; Tianyou Yu; Haiyun Huang; Wei Lv; Jiechun Zhang; Ronghao Yu; Yuanqing Li
Journal:  Neurosci Bull       Date:  2018-07-17       Impact factor: 5.203

  7 in total

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