Enhancing detection of steady-state visual evoked potentials using frequency and harmonics of that frequency in OpenVibe

In recent years, the use of Brain Computer Interface (BCI) systems has become more popular due to rehabilitation applications, easy installation, cheapness, and so forth.Brain Computer Interface Systems can receive brain signals and input them into a computer. These signals can then be analysed. An...

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Autores principales:	Babak Asheri, Arash Haratian, Malihe Mohamadi, Faezeh Asadi, Parham Yasini, Navid Zarepak, Danial Saber Samiei, Mohammad Bagher Menhaj
Formato:	article
Lenguaje:	EN
Publicado:	Elsevier 2021
Materias:	Medical technology R855-855.5
Acceso en línea:	https://doaj.org/article/41a085924a954711a4f84d7d52bb5210
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spelling	oai:doaj.org-article:41a085924a954711a4f84d7d52bb52102021-11-30T04:18:01ZEnhancing detection of steady-state visual evoked potentials using frequency and harmonics of that frequency in OpenVibe2667-099210.1016/j.bea.2021.100022https://doaj.org/article/41a085924a954711a4f84d7d52bb52102021-12-01T00:00:00Zhttp://www.sciencedirect.com/science/article/pii/S2667099221000220https://doaj.org/toc/2667-0992In recent years, the use of Brain Computer Interface (BCI) systems has become more popular due to rehabilitation applications, easy installation, cheapness, and so forth.Brain Computer Interface Systems can receive brain signals and input them into a computer. These signals can then be analysed. An important feature of BCI systems is that they have the ability to help people with disabilities or special needs, so that these people can use the system to control external devices or computer applications.In the presented paper, we have used BCI-SSVEP-Training dataset and OpenVibe open-source software. In OpenVibe, the CSP (Common Spatial Pattern) is used to detect the frequency of the stimulus that each subject looks at. We also considered the stimulus frequency harmonics and used the FBCSP (Filter Bank Common Spatial Pattern) and compared the results with each other.This study shows that using the FBCSP algorithm with Butterworth filter and High-cut and Low-cut equal to ± 1 Hz on the considered stimuli (12, 15 and 20) can improve the classification and detection accuracy in SSVEP data while the harmonic stimuli is considered. Therefore, for frequencies of 12, 15, 20 Hertz the accuracies are 92.91%, 98.95% and 94.50% with an ITR of 76.34bitmin .Babak AsheriArash HaratianMalihe MohamadiFaezeh AsadiParham YasiniNavid ZarepakDanial Saber SamieiMohammad Bagher MenhajElsevierarticleMedical technologyR855-855.5ENBiomedical Engineering Advances, Vol 2, Iss , Pp 100022- (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medical technology R855-855.5
spellingShingle	Medical technology R855-855.5 Babak Asheri Arash Haratian Malihe Mohamadi Faezeh Asadi Parham Yasini Navid Zarepak Danial Saber Samiei Mohammad Bagher Menhaj Enhancing detection of steady-state visual evoked potentials using frequency and harmonics of that frequency in OpenVibe
description	In recent years, the use of Brain Computer Interface (BCI) systems has become more popular due to rehabilitation applications, easy installation, cheapness, and so forth.Brain Computer Interface Systems can receive brain signals and input them into a computer. These signals can then be analysed. An important feature of BCI systems is that they have the ability to help people with disabilities or special needs, so that these people can use the system to control external devices or computer applications.In the presented paper, we have used BCI-SSVEP-Training dataset and OpenVibe open-source software. In OpenVibe, the CSP (Common Spatial Pattern) is used to detect the frequency of the stimulus that each subject looks at. We also considered the stimulus frequency harmonics and used the FBCSP (Filter Bank Common Spatial Pattern) and compared the results with each other.This study shows that using the FBCSP algorithm with Butterworth filter and High-cut and Low-cut equal to ± 1 Hz on the considered stimuli (12, 15 and 20) can improve the classification and detection accuracy in SSVEP data while the harmonic stimuli is considered. Therefore, for frequencies of 12, 15, 20 Hertz the accuracies are 92.91%, 98.95% and 94.50% with an ITR of 76.34bitmin .
format	article
author	Babak Asheri Arash Haratian Malihe Mohamadi Faezeh Asadi Parham Yasini Navid Zarepak Danial Saber Samiei Mohammad Bagher Menhaj
author_facet	Babak Asheri Arash Haratian Malihe Mohamadi Faezeh Asadi Parham Yasini Navid Zarepak Danial Saber Samiei Mohammad Bagher Menhaj
author_sort	Babak Asheri
title	Enhancing detection of steady-state visual evoked potentials using frequency and harmonics of that frequency in OpenVibe
title_short	Enhancing detection of steady-state visual evoked potentials using frequency and harmonics of that frequency in OpenVibe
title_full	Enhancing detection of steady-state visual evoked potentials using frequency and harmonics of that frequency in OpenVibe
title_fullStr	Enhancing detection of steady-state visual evoked potentials using frequency and harmonics of that frequency in OpenVibe
title_full_unstemmed	Enhancing detection of steady-state visual evoked potentials using frequency and harmonics of that frequency in OpenVibe
title_sort	enhancing detection of steady-state visual evoked potentials using frequency and harmonics of that frequency in openvibe
publisher	Elsevier
publishDate	2021
url	https://doaj.org/article/41a085924a954711a4f84d7d52bb5210
work_keys_str_mv	AT babakasheri enhancingdetectionofsteadystatevisualevokedpotentialsusingfrequencyandharmonicsofthatfrequencyinopenvibe AT arashharatian enhancingdetectionofsteadystatevisualevokedpotentialsusingfrequencyandharmonicsofthatfrequencyinopenvibe AT malihemohamadi enhancingdetectionofsteadystatevisualevokedpotentialsusingfrequencyandharmonicsofthatfrequencyinopenvibe AT faezehasadi enhancingdetectionofsteadystatevisualevokedpotentialsusingfrequencyandharmonicsofthatfrequencyinopenvibe AT parhamyasini enhancingdetectionofsteadystatevisualevokedpotentialsusingfrequencyandharmonicsofthatfrequencyinopenvibe AT navidzarepak enhancingdetectionofsteadystatevisualevokedpotentialsusingfrequencyandharmonicsofthatfrequencyinopenvibe AT danialsabersamiei enhancingdetectionofsteadystatevisualevokedpotentialsusingfrequencyandharmonicsofthatfrequencyinopenvibe AT mohammadbaghermenhaj enhancingdetectionofsteadystatevisualevokedpotentialsusingfrequencyandharmonicsofthatfrequencyinopenvibe
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Enhancing detection of steady-state visual evoked potentials using frequency and harmonics of that frequency in OpenVibe

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