Literature DB >> 23339894

Commanding a robotic wheelchair with a high-frequency steady-state visual evoked potential based brain-computer interface.

Pablo F Diez1, Sandra M Torres Müller, Vicente A Mut, Eric Laciar, Enrique Avila, Teodiano Freire Bastos-Filho, Mário Sarcinelli-Filho.   

Abstract

This work presents a brain-computer interface (BCI) used to operate a robotic wheelchair. The experiments were performed on 15 subjects (13 of them healthy). The BCI is based on steady-state visual-evoked potentials (SSVEP) and the stimuli flickering are performed at high frequency (37, 38, 39 and 40 Hz). This high frequency stimulation scheme can reduce or even eliminate visual fatigue, allowing the user to achieve a stable performance for long term BCI operation. The BCI system uses power-spectral density analysis associated to three bipolar electroencephalographic channels. As the results show, 2 subjects were reported as SSVEP-BCI illiterates (not able to use the BCI), and, consequently, 13 subjects (12 of them healthy) could navigate the wheelchair in a room with obstacles arranged in four distinct configurations. Volunteers expressed neither discomfort nor fatigue due to flickering stimulation. A transmission rate of up to 72.5 bits/min was obtained, with an average of 44.6 bits/min in four trials. These results show that people could effectively navigate a robotic wheelchair using a SSVEP-based BCI with high frequency flickering stimulation.
Copyright © 2012 IPEM. Published by Elsevier Ltd. All rights reserved.

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Year:  2013        PMID: 23339894     DOI: 10.1016/j.medengphy.2012.12.005

Source DB:  PubMed          Journal:  Med Eng Phys        ISSN: 1350-4533            Impact factor:   2.242


  17 in total

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Authors:  Elias B Thorp; Konrad P Kording; Ferdinando A Mussa-Ivaldi
Journal:  J Neurophysiol       Date:  2016-11-23       Impact factor: 2.714

2.  Upper Body-Based Power Wheelchair Control Interface for Individuals With Tetraplegia.

Authors:  Elias B Thorp; Farnaz Abdollahi; David Chen; Ali Farshchiansadegh; Mei-Hua Lee; Jessica P Pedersen; Camilla Pierella; Elliot J Roth; Ismael Seanez Gonzalez; Ferdinando A Mussa-Ivaldi
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2015-06-01       Impact factor: 3.802

3.  Decoding of top-down cognitive processing for SSVEP-controlled BMI.

Authors:  Byoung-Kyong Min; Sven Dähne; Min-Hee Ahn; Yung-Kyun Noh; Klaus-Robert Müller
Journal:  Sci Rep       Date:  2016-11-03       Impact factor: 4.379

4.  Evaluating the Influence of Chromatic and Luminance Stimuli on SSVEPs from Behind-the-Ears and Occipital Areas.

Authors:  Alan Floriano; Pablo F Diez; Teodiano Freire Bastos-Filho
Journal:  Sensors (Basel)       Date:  2018-02-17       Impact factor: 3.576

5.  Adaptive Spatial Filter Based on Similarity Indices to Preserve the Neural Information on EEG Signals during On-Line Processing.

Authors:  Denis Delisle-Rodriguez; Ana Cecilia Villa-Parra; Teodiano Bastos-Filho; Alberto López-Delis; Anselmo Frizera-Neto; Sridhar Krishnan; Eduardo Rocon
Journal:  Sensors (Basel)       Date:  2017-11-25       Impact factor: 3.576

6.  Toward a semi-self-paced EEG brain computer interface: decoding initiation state from non-initiation state in dedicated time slots.

Authors:  Lingling Yang; Howard Leung; David A Peterson; Terrence J Sejnowski; Howard Poizner
Journal:  PLoS One       Date:  2014-02-21       Impact factor: 3.240

7.  Toward brain-computer interface based wheelchair control utilizing tactually-evoked event-related potentials.

Authors:  Tobias Kaufmann; Andreas Herweg; Andrea Kübler
Journal:  J Neuroeng Rehabil       Date:  2014-01-16       Impact factor: 4.262

8.  A Feasibility Study of SSVEP-Based Passive Training on an Ankle Rehabilitation Robot.

Authors:  Xiangfeng Zeng; Guoli Zhu; Lan Yue; Mingming Zhang; Shane Xie
Journal:  J Healthc Eng       Date:  2017-09-17       Impact factor: 2.682

9.  Application of a single-flicker online SSVEP BCI for spatial navigation.

Authors:  Jingjing Chen; Dan Zhang; Andreas K Engel; Qin Gong; Alexander Maye
Journal:  PLoS One       Date:  2017-05-31       Impact factor: 3.240

10.  Use of Sine Shaped High-Frequency Rhythmic Visual Stimuli Patterns for SSVEP Response Analysis and Fatigue Rate Evaluation in Normal Subjects.

Authors:  Ahmadreza Keihani; Zahra Shirzhiyan; Morteza Farahi; Elham Shamsi; Amin Mahnam; Bahador Makkiabadi; Mohsen R Haidari; Amir H Jafari
Journal:  Front Hum Neurosci       Date:  2018-05-28       Impact factor: 3.169

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