A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation

This paper proposed a novel tactile-stimuli P300 paradigm for Brain-Computer Interface (BCI), which potentially targeted at people with less learning ability or difficulty in maintaining attention. The new paradigm using only two types of stimuli was designed, and different targets were distinguishe...

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Main Authors: Chenxi Chu, Jingjing Luo, Xiwei Tian, Xiangke Han, Shijie Guo
Format: Article
Language:English
Published: Frontiers Media S.A. 2021-04-01
Series:Frontiers in Human Neuroscience
Subjects:
Online Access:https://www.frontiersin.org/articles/10.3389/fnhum.2021.641357/full
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spelling doaj-fef8b217374c426d9a851f6bedccbd562021-04-14T05:46:22ZengFrontiers Media S.A.Frontiers in Human Neuroscience1662-51612021-04-011510.3389/fnhum.2021.641357641357A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile StimulationChenxi Chu0Chenxi Chu1Jingjing Luo2Jingjing Luo3Xiwei Tian4Xiangke Han5Shijie Guo6Shijie Guo7Shijie Guo8Institute of Artificial Intelligence (AI) and Robotics, Academy for Engineering and Technology, Fudan University, as well as Engineering Research Center of AI & Robotics, Ministry of Education, Shanghai, ChinaGuanghua Lingang Engineering Application and Technology R&D (Shanghai) Co., Ltd., Shanghai, ChinaInstitute of Artificial Intelligence (AI) and Robotics, Academy for Engineering and Technology, Fudan University, as well as Engineering Research Center of AI & Robotics, Ministry of Education, Shanghai, ChinaJihua Laboratory, Guangzhou, ChinaDepartment of the State Key Laboratory of Reliability and Intelligence of Electrical Equipment and The Hebei Key Laboratory of Robot Perception and Human-Robot Interaction, Hebei University of Technology, Tianjin, ChinaDepartment of the State Key Laboratory of Reliability and Intelligence of Electrical Equipment and The Hebei Key Laboratory of Robot Perception and Human-Robot Interaction, Hebei University of Technology, Tianjin, ChinaInstitute of Artificial Intelligence (AI) and Robotics, Academy for Engineering and Technology, Fudan University, as well as Engineering Research Center of AI & Robotics, Ministry of Education, Shanghai, ChinaGuanghua Lingang Engineering Application and Technology R&D (Shanghai) Co., Ltd., Shanghai, ChinaDepartment of the State Key Laboratory of Reliability and Intelligence of Electrical Equipment and The Hebei Key Laboratory of Robot Perception and Human-Robot Interaction, Hebei University of Technology, Tianjin, ChinaThis paper proposed a novel tactile-stimuli P300 paradigm for Brain-Computer Interface (BCI), which potentially targeted at people with less learning ability or difficulty in maintaining attention. The new paradigm using only two types of stimuli was designed, and different targets were distinguished by frequency and spatial information. The classification algorithm was developed by introducing filters for frequency bands selection and conducting optimization with common spatial pattern (CSP) on the tactile evoked EEG signals. It features a combination of spatial and frequency information, with the spatial information distinguishing the sites of stimuli and frequency information identifying target stimuli and disturbances. We investigated both electrical stimuli and vibration stimuli, in which only one target site was stimulated in each block. The results demonstrated an average accuracy of 94.88% for electrical stimuli and 95.21% for vibration stimuli, respectively.https://www.frontiersin.org/articles/10.3389/fnhum.2021.641357/fullbrain-computer interfacevibro-tactile stimulielectro-tactile stimuliP300 paradigmspatial-frequency paradigm
collection DOAJ
language English
format Article
sources DOAJ
author Chenxi Chu
Chenxi Chu
Jingjing Luo
Jingjing Luo
Xiwei Tian
Xiangke Han
Shijie Guo
Shijie Guo
Shijie Guo
spellingShingle Chenxi Chu
Chenxi Chu
Jingjing Luo
Jingjing Luo
Xiwei Tian
Xiangke Han
Shijie Guo
Shijie Guo
Shijie Guo
A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation
Frontiers in Human Neuroscience
brain-computer interface
vibro-tactile stimuli
electro-tactile stimuli
P300 paradigm
spatial-frequency paradigm
author_facet Chenxi Chu
Chenxi Chu
Jingjing Luo
Jingjing Luo
Xiwei Tian
Xiangke Han
Shijie Guo
Shijie Guo
Shijie Guo
author_sort Chenxi Chu
title A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation
title_short A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation
title_full A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation
title_fullStr A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation
title_full_unstemmed A P300 Brain-Computer Interface Paradigm Based on Electric and Vibration Simple Command Tactile Stimulation
title_sort p300 brain-computer interface paradigm based on electric and vibration simple command tactile stimulation
publisher Frontiers Media S.A.
series Frontiers in Human Neuroscience
issn 1662-5161
publishDate 2021-04-01
description This paper proposed a novel tactile-stimuli P300 paradigm for Brain-Computer Interface (BCI), which potentially targeted at people with less learning ability or difficulty in maintaining attention. The new paradigm using only two types of stimuli was designed, and different targets were distinguished by frequency and spatial information. The classification algorithm was developed by introducing filters for frequency bands selection and conducting optimization with common spatial pattern (CSP) on the tactile evoked EEG signals. It features a combination of spatial and frequency information, with the spatial information distinguishing the sites of stimuli and frequency information identifying target stimuli and disturbances. We investigated both electrical stimuli and vibration stimuli, in which only one target site was stimulated in each block. The results demonstrated an average accuracy of 94.88% for electrical stimuli and 95.21% for vibration stimuli, respectively.
topic brain-computer interface
vibro-tactile stimuli
electro-tactile stimuli
P300 paradigm
spatial-frequency paradigm
url https://www.frontiersin.org/articles/10.3389/fnhum.2021.641357/full
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