Single-trial classification of fNIRS signal measured from prefrontal cortex during four directions motor imagery tasks

Hong Peng; Jinlong Chao; Yongzong Wang; Bin Hu; Dennis Majoe

doi:10.1109/BIBM.2017.8217676

Single-trial classification of fNIRS signal measured from prefrontal cortex during four directions motor imagery tasks

Hong Peng, Jinlong Chao, Yongzong Wang, Bin Hu^*, Dennis Majoe

^*Corresponding author for this work

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

Abstract

As a promising non-invasive technique, functional near-infrared spectroscopy(fNIRS) can easily detect the hemodynamic responses of cortical brain activities. This paper investigated the multiclass classification of motor imagery(MI)based on fNIRS. 10 healthy individuals were recruited to move an object using their imagination. A multi-channel continuous-wave fNIRS equipment was applied to obtain the signals from the prefrontal cortex(PFC). The combined Ensemble Empirical Mode Decomposition (EEMD) and Independent Component Analysis(ICA) method was used to solve the signal-noise frequency spectrum aliasing issues caused by Mayer wave(0.1Hz), then the signal means(SM) features were extracted as an input of Support Vector Machine(SVM) classifier. The average accuracies of 4 directions, up-down and left-right were 40.55%, 73.05%, 70.7% respectively using Hbo2(8-21s). This study demonstrated that Brodmann area 4 was activated, which is consistent with previous conclusions. Furthermore, we found that the orbitofrontal cortex is also involved in MI and O2sat can also serve as a classified index.

Original language	English
Title of host publication	Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Editors	Illhoi Yoo, Jane Huiru Zheng, Yang Gong, Xiaohua Tony Hu, Chi-Ren Shyu, Yana Bromberg, Jean Gao, Dmitry Korkin
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	360-366
Number of pages	7
ISBN (Electronic)	9781509030491
DOIs	https://doi.org/10.1109/BIBM.2017.8217676
Publication status	Published - 15 Dec 2017
Externally published	Yes
Event	2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 - Kansas City, United States Duration: 13 Nov 2017 → 16 Nov 2017

Publication series

Name	Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Volume	2017-January

Conference

Conference	2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017
Country/Territory	United States
City	Kansas City
Period	13/11/17 → 16/11/17

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10.1109/BIBM.2017.8217676

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Peng, H., Chao, J., Wang, Y., Hu, B., & Majoe, D. (2017). Single-trial classification of fNIRS signal measured from prefrontal cortex during four directions motor imagery tasks. In I. Yoo, J. H. Zheng, Y. Gong, X. T. Hu, C.-R. Shyu, Y. Bromberg, J. Gao, & D. Korkin (Eds.), Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 (pp. 360-366). (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BIBM.2017.8217676

Peng, Hong ; Chao, Jinlong ; Wang, Yongzong et al. / Single-trial classification of fNIRS signal measured from prefrontal cortex during four directions motor imagery tasks. Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. editor / Illhoi Yoo ; Jane Huiru Zheng ; Yang Gong ; Xiaohua Tony Hu ; Chi-Ren Shyu ; Yana Bromberg ; Jean Gao ; Dmitry Korkin. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 360-366 (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017).

@inproceedings{87a727f803504b779398510f0d03bcc1,

title = "Single-trial classification of fNIRS signal measured from prefrontal cortex during four directions motor imagery tasks",

abstract = "As a promising non-invasive technique, functional near-infrared spectroscopy(fNIRS) can easily detect the hemodynamic responses of cortical brain activities. This paper investigated the multiclass classification of motor imagery(MI)based on fNIRS. 10 healthy individuals were recruited to move an object using their imagination. A multi-channel continuous-wave fNIRS equipment was applied to obtain the signals from the prefrontal cortex(PFC). The combined Ensemble Empirical Mode Decomposition (EEMD) and Independent Component Analysis(ICA) method was used to solve the signal-noise frequency spectrum aliasing issues caused by Mayer wave(0.1Hz), then the signal means(SM) features were extracted as an input of Support Vector Machine(SVM) classifier. The average accuracies of 4 directions, up-down and left-right were 40.55%, 73.05%, 70.7% respectively using Hbo2(8-21s). This study demonstrated that Brodmann area 4 was activated, which is consistent with previous conclusions. Furthermore, we found that the orbitofrontal cortex is also involved in MI and O2sat can also serve as a classified index.",

author = "Hong Peng and Jinlong Chao and Yongzong Wang and Bin Hu and Dennis Majoe",

note = "Publisher Copyright: {\textcopyright} 2017 IEEE.; 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017 ; Conference date: 13-11-2017 Through 16-11-2017",

year = "2017",

month = dec,

day = "15",

doi = "10.1109/BIBM.2017.8217676",

language = "English",

series = "Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017",

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

pages = "360--366",

editor = "Illhoi Yoo and Zheng, {Jane Huiru} and Yang Gong and Hu, {Xiaohua Tony} and Chi-Ren Shyu and Yana Bromberg and Jean Gao and Dmitry Korkin",

booktitle = "Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017",

address = "United States",

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Peng, H, Chao, J, Wang, Y, Hu, B & Majoe, D 2017, Single-trial classification of fNIRS signal measured from prefrontal cortex during four directions motor imagery tasks. in I Yoo, JH Zheng, Y Gong, XT Hu, C-R Shyu, Y Bromberg, J Gao & D Korkin (eds), Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, vol. 2017-January, Institute of Electrical and Electronics Engineers Inc., pp. 360-366, 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017, Kansas City, United States, 13/11/17. https://doi.org/10.1109/BIBM.2017.8217676

Single-trial classification of fNIRS signal measured from prefrontal cortex during four directions motor imagery tasks. / Peng, Hong; Chao, Jinlong; Wang, Yongzong et al.
Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. ed. / Illhoi Yoo; Jane Huiru Zheng; Yang Gong; Xiaohua Tony Hu; Chi-Ren Shyu; Yana Bromberg; Jean Gao; Dmitry Korkin. Institute of Electrical and Electronics Engineers Inc., 2017. p. 360-366 (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017; Vol. 2017-January).

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

TY - GEN

T1 - Single-trial classification of fNIRS signal measured from prefrontal cortex during four directions motor imagery tasks

AU - Peng, Hong

AU - Chao, Jinlong

AU - Wang, Yongzong

AU - Hu, Bin

AU - Majoe, Dennis

PY - 2017/12/15

Y1 - 2017/12/15

N2 - As a promising non-invasive technique, functional near-infrared spectroscopy(fNIRS) can easily detect the hemodynamic responses of cortical brain activities. This paper investigated the multiclass classification of motor imagery(MI)based on fNIRS. 10 healthy individuals were recruited to move an object using their imagination. A multi-channel continuous-wave fNIRS equipment was applied to obtain the signals from the prefrontal cortex(PFC). The combined Ensemble Empirical Mode Decomposition (EEMD) and Independent Component Analysis(ICA) method was used to solve the signal-noise frequency spectrum aliasing issues caused by Mayer wave(0.1Hz), then the signal means(SM) features were extracted as an input of Support Vector Machine(SVM) classifier. The average accuracies of 4 directions, up-down and left-right were 40.55%, 73.05%, 70.7% respectively using Hbo2(8-21s). This study demonstrated that Brodmann area 4 was activated, which is consistent with previous conclusions. Furthermore, we found that the orbitofrontal cortex is also involved in MI and O2sat can also serve as a classified index.

AB - As a promising non-invasive technique, functional near-infrared spectroscopy(fNIRS) can easily detect the hemodynamic responses of cortical brain activities. This paper investigated the multiclass classification of motor imagery(MI)based on fNIRS. 10 healthy individuals were recruited to move an object using their imagination. A multi-channel continuous-wave fNIRS equipment was applied to obtain the signals from the prefrontal cortex(PFC). The combined Ensemble Empirical Mode Decomposition (EEMD) and Independent Component Analysis(ICA) method was used to solve the signal-noise frequency spectrum aliasing issues caused by Mayer wave(0.1Hz), then the signal means(SM) features were extracted as an input of Support Vector Machine(SVM) classifier. The average accuracies of 4 directions, up-down and left-right were 40.55%, 73.05%, 70.7% respectively using Hbo2(8-21s). This study demonstrated that Brodmann area 4 was activated, which is consistent with previous conclusions. Furthermore, we found that the orbitofrontal cortex is also involved in MI and O2sat can also serve as a classified index.

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M3 - Conference contribution

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T3 - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

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BT - Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017

A2 - Yoo, Illhoi

A2 - Zheng, Jane Huiru

A2 - Gong, Yang

A2 - Hu, Xiaohua Tony

A2 - Shyu, Chi-Ren

A2 - Bromberg, Yana

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A2 - Korkin, Dmitry

PB - Institute of Electrical and Electronics Engineers Inc.

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Peng H, Chao J, Wang Y, Hu B, Majoe D. Single-trial classification of fNIRS signal measured from prefrontal cortex during four directions motor imagery tasks. In Yoo I, Zheng JH, Gong Y, Hu XT, Shyu CR, Bromberg Y, Gao J, Korkin D, editors, Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 360-366. (Proceedings - 2017 IEEE International Conference on Bioinformatics and Biomedicine, BIBM 2017). doi: 10.1109/BIBM.2017.8217676

Single-trial classification of fNIRS signal measured from prefrontal cortex during four directions motor imagery tasks

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