Literature DB >> 16093411

An auditory brain-computer interface based on the self-regulation of slow cortical potentials.

Mirko Pham1, Thilo Hinterberger, Nicola Neumann, Andrea Kübler, Nadine Hofmayer, Anke Grether, Barbara Wilhelm, Jean-Jacques Vatine, Niels Birbaumer.   

Abstract

OBJECTIVES: Communication support for severely paralyzed patients with visual impairment is needed. Therefore, the feasibility of a brain-computer interface (BCI) using auditory stimuli alone, based on the self-regulation of slow cortical potentials (SCPs), was investigated.
METHODS: Auditory stimuli were used for task and feedback presentation in an SCP self-regulation paradigm. Voluntarily produced SCP responses and measures of communication performance were compared between 3 groups (total of N = 59) of visual, auditory, and cross-modal visual-auditory modality. Electroencephalogram recordings and training from Cz-mastoids were carried out on 3 consecutive sessions. Data of 1500 trials per subject were collected.
RESULTS: Best performance was achieved for the visual, followed by the auditory condition. The performance deficit of the auditory condition was partly due to decreased self-produced positivity. Larger SCP response variability also accounted for lower performance of the auditory condition. Cross-modally presented stimuli did not lead to significant learning and control of SCP.
CONCLUSIONS: Brain-computer communication using auditory stimuli only is possible. Smaller cortical positivity achieved in the auditory condition, as compared to the visual condition, may be a consequence of increased selective attention to simultaneously presented auditory stimuli. To optimize performance, auditory stimuli characteristics may have to be adapted. Other suggestions for enhancement of communication performance with auditory stimuli are discussed.

Entities:  

Mesh:

Year:  2005        PMID: 16093411     DOI: 10.1177/1545968305277628

Source DB:  PubMed          Journal:  Neurorehabil Neural Repair        ISSN: 1545-9683            Impact factor:   3.919


  11 in total

Review 1.  Brain-computer interface technology as a tool to augment plasticity and outcomes for neurological rehabilitation.

Authors:  Bruce H Dobkin
Journal:  J Physiol       Date:  2006-11-09       Impact factor: 5.182

2.  Exploration of computational methods for classification of movement intention during human voluntary movement from single trial EEG.

Authors:  Ou Bai; Peter Lin; Sherry Vorbach; Jiang Li; Steve Furlani; Mark Hallett
Journal:  Clin Neurophysiol       Date:  2007-10-29       Impact factor: 3.708

3.  Sensorimotor learning with stereo auditory feedback for a brain-computer interface.

Authors:  Karl A McCreadie; Damien H Coyle; Girijesh Prasad
Journal:  Med Biol Eng Comput       Date:  2012-11-30       Impact factor: 2.602

4.  Effects of augmentative visual training on audio-motor mapping.

Authors:  Gabrielle L Hands; Eric Larson; Cara E Stepp
Journal:  Hum Mov Sci       Date:  2014-02-12       Impact factor: 2.161

5.  Toward a high-throughput auditory P300-based brain-computer interface.

Authors:  D S Klobassa; T M Vaughan; P Brunner; N E Schwartz; J R Wolpaw; C Neuper; E W Sellers
Journal:  Clin Neurophysiol       Date:  2009-07-01       Impact factor: 3.708

6.  Combined Auditory and Vibrotactile Feedback for Human-Machine-Interface Control.

Authors:  Elias B Thorp; Eric Larson; Cara E Stepp
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2013-07-31       Impact factor: 3.802

7.  An auditory multiclass brain-computer interface with natural stimuli: Usability evaluation with healthy participants and a motor impaired end user.

Authors:  Nadine Simon; Ivo Käthner; Carolin A Ruf; Emanuele Pasqualotto; Andrea Kübler; Sebastian Halder
Journal:  Front Hum Neurosci       Date:  2015-01-09       Impact factor: 3.169

8.  The Encephalophone: A Novel Musical Biofeedback Device using Conscious Control of Electroencephalogram (EEG).

Authors:  Thomas A Deuel; Juan Pampin; Jacob Sundstrom; Felix Darvas
Journal:  Front Hum Neurosci       Date:  2017-04-26       Impact factor: 3.169

9.  The cost of space independence in P300-BCI spellers.

Authors:  Srivas Chennu; Abdulmajeed Alsufyani; Marco Filetti; Adrian M Owen; Howard Bowman
Journal:  J Neuroeng Rehabil       Date:  2013-07-29       Impact factor: 4.262

10.  Vibrotactile feedback for brain-computer interface operation.

Authors:  Febo Cincotti; Laura Kauhanen; Fabio Aloise; Tapio Palomäki; Nicholas Caporusso; Pasi Jylänki; Donatella Mattia; Fabio Babiloni; Gerolf Vanacker; Marnix Nuttin; Maria Grazia Marciani; José Del R Millán
Journal:  Comput Intell Neurosci       Date:  2007
View more

北京卡尤迪生物科技股份有限公司 © 2022-2023.