Hybrid EEG-NIRS brain-computer interface under eyes-closed condition

Jaeyoung Shin; Klaus Robert Muller; Han Jeong Hwang

doi:10.1109/APSIPA.2017.8282127

Hybrid EEG-NIRS brain-computer interface under eyes-closed condition

Jaeyoung Shin, Klaus Robert Muller, Han Jeong Hwang

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

1 Citation (Scopus)

Abstract

In this study, we propose a hybrid BCI combining electroencephalography (EEG) and near-infrared spectroscopy (NIRS) that can be potentially operated in eyes-closed condition for paralyzed patients with oculomotor dysfunctions. In the experiment, seven healthy participants performed mental subtraction and stayed relaxed (baseline state), during which EEG and NIRS data were simultaneously measured. To evaluate the feasibility of the hybrid BCI, we classified frontal brain activities inducted by mental subtraction and baseline state, and compared classification accuracies obtained using unimodal EEG and NIRS BCI and the hybrid BCI. As a result, the hybrid BCI (85.54 % ± 8.59) showed significantly higher classification accuracy than those of unimodal EEG (80.77 % ± 11.15) and NIRS BCI (77.12 % ± 7.63) (Wilcoxon signed rank test, Bonferroni corrected p < 0.05). The result demonstrated that our eyes-closed hybrid BCI approach could be potentially applied to neurodegenerative patients with impaired motor functions accompanied by a decline of visual functions.

Original language	English
Title of host publication	Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	721-723
Number of pages	3
ISBN (Electronic)	9781538615423
DOIs	https://doi.org/10.1109/APSIPA.2017.8282127
Publication status	Published - 2017 Jul 2
Event	9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 - Kuala Lumpur, Malaysia Duration: 2017 Dec 12 → 2017 Dec 15

Publication series

Name	Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Volume	2018-February

Other

Other	9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017
Country/Territory	Malaysia
City	Kuala Lumpur
Period	17/12/12 → 17/12/15

Bibliographical note

Publisher Copyright:
© 2017 IEEE.

ASJC Scopus subject areas

Artificial Intelligence
Human-Computer Interaction
Information Systems
Signal Processing

Access to Document

10.1109/APSIPA.2017.8282127

Cite this

Shin, J., Muller, K. R., & Hwang, H. J. (2017). Hybrid EEG-NIRS brain-computer interface under eyes-closed condition. In Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 (pp. 721-723). (Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017; Vol. 2018-February). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/APSIPA.2017.8282127

Hybrid EEG-NIRS brain-computer interface under eyes-closed condition. / Shin, Jaeyoung; Muller, Klaus Robert; Hwang, Han Jeong.
Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. p. 721-723 (Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017; Vol. 2018-February).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Shin, J, Muller, KR & Hwang, HJ 2017, Hybrid EEG-NIRS brain-computer interface under eyes-closed condition. in Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017. Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017, vol. 2018-February, Institute of Electrical and Electronics Engineers Inc., pp. 721-723, 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017, Kuala Lumpur, Malaysia, 17/12/12. https://doi.org/10.1109/APSIPA.2017.8282127

Shin J, Muller KR, Hwang HJ. Hybrid EEG-NIRS brain-computer interface under eyes-closed condition. In Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 721-723. (Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017). doi: 10.1109/APSIPA.2017.8282127

Shin, Jaeyoung ; Muller, Klaus Robert ; Hwang, Han Jeong. / Hybrid EEG-NIRS brain-computer interface under eyes-closed condition. Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 721-723 (Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017).

@inproceedings{a06b8af0edc74f8ab64c5d2544229db2,

title = "Hybrid EEG-NIRS brain-computer interface under eyes-closed condition",

abstract = "In this study, we propose a hybrid BCI combining electroencephalography (EEG) and near-infrared spectroscopy (NIRS) that can be potentially operated in eyes-closed condition for paralyzed patients with oculomotor dysfunctions. In the experiment, seven healthy participants performed mental subtraction and stayed relaxed (baseline state), during which EEG and NIRS data were simultaneously measured. To evaluate the feasibility of the hybrid BCI, we classified frontal brain activities inducted by mental subtraction and baseline state, and compared classification accuracies obtained using unimodal EEG and NIRS BCI and the hybrid BCI. As a result, the hybrid BCI (85.54 % ± 8.59) showed significantly higher classification accuracy than those of unimodal EEG (80.77 % ± 11.15) and NIRS BCI (77.12 % ± 7.63) (Wilcoxon signed rank test, Bonferroni corrected p < 0.05). The result demonstrated that our eyes-closed hybrid BCI approach could be potentially applied to neurodegenerative patients with impaired motor functions accompanied by a decline of visual functions.",

author = "Jaeyoung Shin and Muller, {Klaus Robert} and Hwang, {Han Jeong}",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017 ; Conference date: 12-12-2017 Through 15-12-2017",

year = "2017",

month = jul,

day = "2",

doi = "10.1109/APSIPA.2017.8282127",

language = "English",

series = "Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017",

publisher = "Institute of Electrical and Electronics Engineers Inc.",

pages = "721--723",

booktitle = "Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017",

}

TY - GEN

T1 - Hybrid EEG-NIRS brain-computer interface under eyes-closed condition

AU - Shin, Jaeyoung

AU - Muller, Klaus Robert

AU - Hwang, Han Jeong

PY - 2017/7/2

Y1 - 2017/7/2

N2 - In this study, we propose a hybrid BCI combining electroencephalography (EEG) and near-infrared spectroscopy (NIRS) that can be potentially operated in eyes-closed condition for paralyzed patients with oculomotor dysfunctions. In the experiment, seven healthy participants performed mental subtraction and stayed relaxed (baseline state), during which EEG and NIRS data were simultaneously measured. To evaluate the feasibility of the hybrid BCI, we classified frontal brain activities inducted by mental subtraction and baseline state, and compared classification accuracies obtained using unimodal EEG and NIRS BCI and the hybrid BCI. As a result, the hybrid BCI (85.54 % ± 8.59) showed significantly higher classification accuracy than those of unimodal EEG (80.77 % ± 11.15) and NIRS BCI (77.12 % ± 7.63) (Wilcoxon signed rank test, Bonferroni corrected p < 0.05). The result demonstrated that our eyes-closed hybrid BCI approach could be potentially applied to neurodegenerative patients with impaired motor functions accompanied by a decline of visual functions.

AB - In this study, we propose a hybrid BCI combining electroencephalography (EEG) and near-infrared spectroscopy (NIRS) that can be potentially operated in eyes-closed condition for paralyzed patients with oculomotor dysfunctions. In the experiment, seven healthy participants performed mental subtraction and stayed relaxed (baseline state), during which EEG and NIRS data were simultaneously measured. To evaluate the feasibility of the hybrid BCI, we classified frontal brain activities inducted by mental subtraction and baseline state, and compared classification accuracies obtained using unimodal EEG and NIRS BCI and the hybrid BCI. As a result, the hybrid BCI (85.54 % ± 8.59) showed significantly higher classification accuracy than those of unimodal EEG (80.77 % ± 11.15) and NIRS BCI (77.12 % ± 7.63) (Wilcoxon signed rank test, Bonferroni corrected p < 0.05). The result demonstrated that our eyes-closed hybrid BCI approach could be potentially applied to neurodegenerative patients with impaired motor functions accompanied by a decline of visual functions.

UR - http://www.scopus.com/inward/record.url?scp=85050805475&partnerID=8YFLogxK

U2 - 10.1109/APSIPA.2017.8282127

DO - 10.1109/APSIPA.2017.8282127

M3 - Conference contribution

AN - SCOPUS:85050805475

T3 - Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017

SP - 721

EP - 723

BT - Proceedings - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017

PB - Institute of Electrical and Electronics Engineers Inc.

T2 - 9th Asia-Pacific Signal and Information Processing Association Annual Summit and Conference, APSIPA ASC 2017

Y2 - 12 December 2017 through 15 December 2017

ER -

Hybrid EEG-NIRS brain-computer interface under eyes-closed condition

Abstract

Publication series

Other

Bibliographical note

ASJC Scopus subject areas

Access to Document

Other files and links

Fingerprint

Cite this