Literature DB >> 26650051

SSVEP-based Experimental Procedure for Brain-Robot Interaction with Humanoid Robots.

Jing Zhao1, Wei Li2, Xiaoqian Mao1, Mengfan Li1.   

Abstract

Brain-Robot Interaction (BRI), which provides an innovative communication pathway between human and a robotic device via brain signals, is prospective in helping the disabled in their daily lives. The overall goal of our method is to establish an SSVEP-based experimental procedure by integrating multiple software programs, such as OpenViBE, Choregraph, and Central software as well as user developed programs written in C++ and MATLAB, to enable the study of brain-robot interaction with humanoid robots. This is achieved by first placing EEG electrodes on a human subject to measure the brain responses through an EEG data acquisition system. A user interface is used to elicit SSVEP responses and to display video feedback in the closed-loop control experiments. The second step is to record the EEG signals of first-time subjects, to analyze their SSVEP features offline, and to train the classifier for each subject. Next, the Online Signal Processor and the Robot Controller are configured for the online control of a humanoid robot. As the final step, the subject completes three specific closed-loop control experiments within different environments to evaluate the brain-robot interaction performance. The advantage of this approach is its reliability and flexibility because it is developed by integrating multiple software programs. The results show that using this approach, the subject is capable of interacting with the humanoid robot via brain signals. This allows the mind-controlled humanoid robot to perform typical tasks that are popular in robotic research and are helpful in assisting the disabled.

Entities:  

Year:  2015        PMID: 26650051      PMCID: PMC4692746          DOI: 10.3791/53558

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  19 in total

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Review 2.  Removal of ocular artifact from the EEG: a review.

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Authors:  Jonathan R Wolpaw; Niels Birbaumer; Dennis J McFarland; Gert Pfurtscheller; Theresa M Vaughan
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4.  Steady-state visual evoked potential (SSVEP)-based communication: impact of harmonic frequency components.

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Authors:  Yijun Wang; Ruiping Wang; Xiaorong Gao; Bo Hong; Shangkai Gao
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2006-06       Impact factor: 3.802

Review 6.  Brain-machine interfaces: past, present and future.

Authors:  Mikhail A Lebedev; Miguel A L Nicolelis
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7.  An online multi-channel SSVEP-based brain-computer interface using a canonical correlation analysis method.

Authors:  Guangyu Bin; Xiaorong Gao; Zheng Yan; Bo Hong; Shangkai Gao
Journal:  J Neural Eng       Date:  2009-06-03       Impact factor: 5.379

8.  Control of a humanoid robot by a noninvasive brain-computer interface in humans.

Authors:  Christian J Bell; Pradeep Shenoy; Rawichote Chalodhorn; Rajesh P N Rao
Journal:  J Neural Eng       Date:  2008-05-15       Impact factor: 5.379

Review 9.  Steady-state visually evoked potentials: focus on essential paradigms and future perspectives.

Authors:  François-Benoît Vialatte; Monique Maurice; Justin Dauwels; Andrzej Cichocki
Journal:  Prog Neurobiol       Date:  2009-12-04       Impact factor: 11.685

10.  Evaluation and application of a hybrid brain computer interface for real wheelchair parallel control with multi-degree of freedom.

Authors:  Jie Li; Hongfei Ji; Lei Cao; Di Zang; Rong Gu; Bin Xia; Qiang Wu
Journal:  Int J Neural Syst       Date:  2014-03-27       Impact factor: 5.866

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  3 in total

Review 1.  Progress in EEG-Based Brain Robot Interaction Systems.

Authors:  Xiaoqian Mao; Mengfan Li; Wei Li; Linwei Niu; Bin Xian; Ming Zeng; Genshe Chen
Journal:  Comput Intell Neurosci       Date:  2017-04-05

2.  Cross-Platform Implementation of an SSVEP-Based BCI for the Control of a 6-DOF Robotic Arm.

Authors:  Eduardo Quiles; Javier Dadone; Nayibe Chio; Emilio García
Journal:  Sensors (Basel)       Date:  2022-07-02       Impact factor: 3.847

3.  A Systematic Review of Closed-Loop Feedback Techniques in Sleep Studies-Related Issues and Future Directions.

Authors:  Jinyoung Choi; Moonyoung Kwon; Sung Chan Jun
Journal:  Sensors (Basel)       Date:  2020-05-13       Impact factor: 3.576

  3 in total

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