Literature DB >> 20176528

An SSVEP-based brain-computer interface for the control of functional electrical stimulation.

Henrik Gollee1, Ivan Volosyak, Angus J McLachlan, Kenneth J Hunt, Axel Gräser.   

Abstract

A brain-computer interface (BCI) based on steady-state visual-evoked potentials (SSVEPs) is combined with a functional electrical stimulation (FES) system to allow the user to control stimulation settings and parameters. The system requires four flickering lights of distinct frequencies that are used to form a menu-based interface, enabling the user to interact with the FES system. The approach was evaluated in 12 neurologically intact subjects to change the parameters and operating mode of an abdominal stimulation system for respiratory assistance. No major influence of the FES on the raw EEG signal could be observed. In tests with a self-paced task, a mean accuracy of more than 90% was achieved, with detection times of approximately 7.7 s and an average information transfer rate of 12.5 bits/min. There was no significant dependency of the accuracy or time of detection on the FES stimulation intensity. The results indicate that the system could be used to control FES-based neuroprostheses with a high degree of accuracy and robustness.

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Mesh:

Year:  2010        PMID: 20176528     DOI: 10.1109/TBME.2010.2043432

Source DB:  PubMed          Journal:  IEEE Trans Biomed Eng        ISSN: 0018-9294            Impact factor:   4.538


  9 in total

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Authors:  Jerry J Shih; Dean J Krusienski; Jonathan R Wolpaw
Journal:  Mayo Clin Proc       Date:  2012-02-10       Impact factor: 7.616

2.  A multi-day and multi-band dataset for a steady-state visual-evoked potential-based brain-computer interface.

Authors:  Ga-Young Choi; Chang-Hee Han; Young-Jin Jung; Han-Jeong Hwang
Journal:  Gigascience       Date:  2019-11-01       Impact factor: 6.524

3.  Novel non-contact control system of electric bed for medical healthcare.

Authors:  Chi-Chun Lo; Shang-Ho Tsai; Bor-Shyh Lin
Journal:  Med Biol Eng Comput       Date:  2016-06-15       Impact factor: 2.602

4.  Gaming control using a wearable and wireless EEG-based brain-computer interface device with novel dry foam-based sensors.

Authors:  Lun-De Liao; Chi-Yu Chen; I-Jan Wang; Sheng-Fu Chen; Shih-Yu Li; Bo-Wei Chen; Jyh-Yeong Chang; Chin-Teng Lin
Journal:  J Neuroeng Rehabil       Date:  2012-01-28       Impact factor: 4.262

5.  A simple ERP method for quantitative analysis of cognitive workload in myoelectric prosthesis control and human-machine interaction.

Authors:  Sean Deeny; Caitlin Chicoine; Levi Hargrove; Todd Parrish; Arun Jayaraman
Journal:  PLoS One       Date:  2014-11-17       Impact factor: 3.240

6.  A Study on the Effect of Electrical Stimulation as a User Stimuli for Motor Imagery Classification in Brain-Machine Interface.

Authors:  Saugat Bhattacharyya; Maureen Clerc; Mitsuhiro Hayashibe
Journal:  Eur J Transl Myol       Date:  2016-06-13

7.  Assisting drinking with an affordable BCI-controlled wearable robot and electrical stimulation: a preliminary investigation.

Authors:  Ritik Looned; Jacob Webb; Zheng Gang Xiao; Carlo Menon
Journal:  J Neuroeng Rehabil       Date:  2014-04-07       Impact factor: 4.262

Review 8.  Challenges in clinical applications of brain computer interfaces in individuals with spinal cord injury.

Authors:  Rüdiger Rupp
Journal:  Front Neuroeng       Date:  2014-09-24

9.  An Efficient Asynchronous High-Frequency Steady-State Visual Evoked Potential-Based Brain-Computer Interface speller: The Problem of Individual Differences.

Authors:  Saba Ajami; Amin Mahnam; Samane Behtaj; Vahid Abootalebi
Journal:  J Med Signals Sens       Date:  2018 Oct-Dec
  9 in total

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