Toward exoskeleton control based on steady state visual evoked potentials

No Sang Kwak; Klaus Robert Müller; Seong Whan Lee

doi:10.1109/iww-BCI.2014.6782571

Toward exoskeleton control based on steady state visual evoked potentials

No Sang Kwak, Klaus Robert Müller, Seong Whan Lee

Research output: Contribution to conference › Paper › peer-review

17 Citations (Scopus)

Abstract

Brain-machine interfaces (BMIs) are systems that establish a direct connection between the human brain and a machine. These systems are applicable to neuro-rehabilitation. In this study, we propose a method of finding optimal threshold of canonical correlation analysis (CCA) based steady state visual evoked potentials (SSVEPs) classification for detecting resting state and reducing misclassification. As a result, we successfully found optimal threshold for the best performance. This result shows the possibility of SSVEP based exoskeleton online control with a proposed method.

Original language	English
DOIs	https://doi.org/10.1109/iww-BCI.2014.6782571
Publication status	Published - 2014
Event	2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 - Gangwon, Korea, Republic of Duration: 2014 Feb 17 → 2014 Feb 19

Other

Other	2014 International Winter Workshop on Brain-Computer Interface, BCI 2014
Country/Territory	Korea, Republic of
City	Gangwon
Period	14/2/17 → 14/2/19

Keywords

Brain Machine Interfaces
Electroencephalogram
Exoskeleton
Steady State Visual Evoked Potential (SSVEP)

ASJC Scopus subject areas

Human-Computer Interaction
Human Factors and Ergonomics

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10.1109/iww-BCI.2014.6782571

Cite this

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title = "Toward exoskeleton control based on steady state visual evoked potentials",

abstract = "Brain-machine interfaces (BMIs) are systems that establish a direct connection between the human brain and a machine. These systems are applicable to neuro-rehabilitation. In this study, we propose a method of finding optimal threshold of canonical correlation analysis (CCA) based steady state visual evoked potentials (SSVEPs) classification for detecting resting state and reducing misclassification. As a result, we successfully found optimal threshold for the best performance. This result shows the possibility of SSVEP based exoskeleton online control with a proposed method.",

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author = "Kwak, {No Sang} and M{\"u}ller, {Klaus Robert} and Lee, {Seong Whan}",

year = "2014",

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language = "English",

note = "2014 International Winter Workshop on Brain-Computer Interface, BCI 2014 ; Conference date: 17-02-2014 Through 19-02-2014",

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T1 - Toward exoskeleton control based on steady state visual evoked potentials

AU - Kwak, No Sang

AU - Müller, Klaus Robert

AU - Lee, Seong Whan

PY - 2014

Y1 - 2014

N2 - Brain-machine interfaces (BMIs) are systems that establish a direct connection between the human brain and a machine. These systems are applicable to neuro-rehabilitation. In this study, we propose a method of finding optimal threshold of canonical correlation analysis (CCA) based steady state visual evoked potentials (SSVEPs) classification for detecting resting state and reducing misclassification. As a result, we successfully found optimal threshold for the best performance. This result shows the possibility of SSVEP based exoskeleton online control with a proposed method.

AB - Brain-machine interfaces (BMIs) are systems that establish a direct connection between the human brain and a machine. These systems are applicable to neuro-rehabilitation. In this study, we propose a method of finding optimal threshold of canonical correlation analysis (CCA) based steady state visual evoked potentials (SSVEPs) classification for detecting resting state and reducing misclassification. As a result, we successfully found optimal threshold for the best performance. This result shows the possibility of SSVEP based exoskeleton online control with a proposed method.

KW - Brain Machine Interfaces

KW - Electroencephalogram

KW - Exoskeleton

KW - Steady State Visual Evoked Potential (SSVEP)

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DO - 10.1109/iww-BCI.2014.6782571

M3 - Paper

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T2 - 2014 International Winter Workshop on Brain-Computer Interface, BCI 2014

Y2 - 17 February 2014 through 19 February 2014

ER -

Toward exoskeleton control based on steady state visual evoked potentials

Abstract

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Keywords

ASJC Scopus subject areas

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