Literature DB >> 20875978

An SSVEP BCI to control a hand orthosis for persons with tetraplegia.

Rupert Ortner1, Brendan Z Allison, Gerd Korisek, Herbert Gaggl, Gert Pfurtscheller.   

Abstract

Brain-computer interface (BCI) systems allow people to send messages or commands without moving, and hence can provide an alternative communication and control channel for people with limited motor function. In this study, we demonstrate a BCI system for orthosis control. Our BCI was asynchronous, meaning that subjects could move the orthosis whenever they wanted, instead of pacing themselves to external cues. Seven subjects each performed two tasks with a BCI that relied on steady state visual evoked potentials (SSVEPs). Although none of the subjects had any training, six subjects showed good control with a positive predictive value (PPV) higher than 60%. The overall PPV for all subjects reached 78% ±10%. However, the false positive rate was high, and some subjects dislike the flickering lights required in SSVEP BCIs. In follow-up work, we hope to reduce both the false positive rate and the annoyance produced by flickering lights by hybridizing this BCI with a "brain switch," which could allow people to turn the SSVEP system on or off using a second type of brain activity when they do not wish to control the orthosis. We also hope to validate this approach with people with tetraplegia.

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Mesh:

Year:  2010        PMID: 20875978     DOI: 10.1109/TNSRE.2010.2076364

Source DB:  PubMed          Journal:  IEEE Trans Neural Syst Rehabil Eng        ISSN: 1534-4320            Impact factor:   3.802


  43 in total

1.  Combined motor imagery and SSVEP based BCI control of a 2 DoF artificial upper limb.

Authors:  Petar Horki; Teodoro Solis-Escalante; Christa Neuper; Gernot Müller-Putz
Journal:  Med Biol Eng Comput       Date:  2011-03-11       Impact factor: 2.602

Review 2.  Interfacing to the brain's motor decisions.

Authors:  Giovanni Mirabella; Mikhail А Lebedev
Journal:  J Neurophysiol       Date:  2016-12-21       Impact factor: 2.714

3.  Studying modulation on simultaneously activated SSVEP neural networks by a cognitive task.

Authors:  Zhenghua Wu
Journal:  J Biol Phys       Date:  2014-01-13       Impact factor: 1.365

4.  Plug&Play Brain-Computer Interfaces for effective Active and Assisted Living control.

Authors:  Niccolò Mora; Ilaria De Munari; Paolo Ciampolini; José Del R Millán
Journal:  Med Biol Eng Comput       Date:  2016-11-17       Impact factor: 2.602

Review 5.  New generation emerging technologies for neurorehabilitation and motor assistance.

Authors:  Antonio Frisoli; Massimiliano Solazzi; Claudio Loconsole; Michele Barsotti
Journal:  Acta Myol       Date:  2016-12

Review 6.  Neural interfaces for the brain and spinal cord--restoring motor function.

Authors:  Andrew Jackson; Jonas B Zimmermann
Journal:  Nat Rev Neurol       Date:  2012-11-13       Impact factor: 42.937

7.  Exploring Cognitive Flexibility With a Noninvasive BCI Using Simultaneous Steady-State Visual Evoked Potentials and Sensorimotor Rhythms.

Authors:  Bradley J Edelman; Jianjun Meng; Nicholas Gulachek; Christopher C Cline; Bin He
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2018-05       Impact factor: 3.802

8.  Adaptive Laplacian filtering for sensorimotor rhythm-based brain-computer interfaces.

Authors:  Jun Lu; Dennis J McFarland; Jonathan R Wolpaw
Journal:  J Neural Eng       Date:  2012-12-10       Impact factor: 5.379

9.  Three-Dimensional Brain-Computer Interface Control Through Simultaneous Overt Spatial Attentional and Motor Imagery Tasks.

Authors:  Jianjun Meng; Taylor Streitz; Nicholas Gulachek; Daniel Suma; Bin He
Journal:  IEEE Trans Biomed Eng       Date:  2018-10-01       Impact factor: 4.538

10.  Implementation of an Embedded Web Server Application for Wireless Control of Brain Computer Interface Based Home Environments.

Authors:  Eda Akman Aydın; Ömer Faruk Bay; İnan Güler
Journal:  J Med Syst       Date:  2015-11-07       Impact factor: 4.460

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