Toward more intuitive brain–computer interfacing: classification of binary covert intentions using functional near-infrared spectroscopy-Reference-Cited by-同舟云学术

Toward more intuitive brain–computer interfacing: classification of binary covert intentions using functional near-infrared spectroscopy

Published:2016-04-05 Issue:9 Volume:21 Page:091303
ISSN:1083-3668
Container-title:Journal of Biomedical Optics
language:en
Short-container-title:J. Biomed. Opt

Author:

Hwang Han-Jeong¹,Choi Han²,Kim Jeong-Youn²,Chang Won-Du²,Kim Do-Won³,Kim Kiwoong⁴,Jo Sungho⁵,Im Chang-Hwan²

Affiliation:

1. Kumoh National Institute of Technology, Department of Medical IT Convergence Engineering, 61 Daehak-ro, Gumi, Gyeongbuk 730-701, Republic of Korea

2. Hanyang University, Department of Biomedical Engineering, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Republic of Korea

3. Hanyang University, Department of Biomedical Engineering, 222 Wangsimni-ro, Seongdong-gu, Seoul 04763, Republic of KoreacBerlin Institute of Technology, Machine Learning Group, Marchstraße 23, 10587 Berlin, Germany

4. Korea Research Institute of Standard and Science, 267 Gajeong-ro, Yuseong-gu, Daejeon 34113, Republic of Korea

5. Korea Advanced Institute of Science and Technology, Department of Computer Science, Daehak-ro, Yuseong-gu, Daejeon 34141, Republic of Korea

Publisher

SPIE-Intl Soc Optical Eng

Subject

Biomedical Engineering,Atomic and Molecular Physics, and Optics,Biomaterials,Electronic, Optical and Magnetic Materials

Reference39 articles.

1. EEG-Based Brain-Computer Interfaces: A Thorough Literature Survey

2. fNIRS-based brain-computer interfaces: a review

3. Classification of frontal cortex haemodynamic responses during cognitive tasks using wavelet transforms and machine learning algorithms

4. Single-trial classification of antagonistic oxyhemoglobin responses during mental arithmetic

5. Single-trial classification of motor imagery differing in task complexity: a functional near-infrared spectroscopy study

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