Literature DB >> 18057501

Self-initiation of EEG-based brain-computer communication using the heart rate response.

R Scherer, G R Müller-Putz, G Pfurtscheller.   

Abstract

Self-initiation, that is the ability of a brain-computer interface (BCI) user to autonomously switch on and off the system, is a very important issue. In this work we analyze whether the respiratory heart rate response, induced by brisk inspiration, can be used as an additional communication channel. After only 20 min of feedback training, ten healthy subjects were able to self-initiate and operate a 4-class steady-state visual evoked potential-based (SSVEP) BCI by using one bipolar ECG and one bipolar EEG channel only. Threshold detection was used to measure a beat-to-beat heart rate increase. Despite this simple method, during a 30 min evaluation period on average only 2.9 non-intentional switches (heart rate changes) were detected.

Mesh:

Year:  2007        PMID: 18057501     DOI: 10.1088/1741-2560/4/4/L01

Source DB:  PubMed          Journal:  J Neural Eng        ISSN: 1741-2552            Impact factor:   5.379


  10 in total

1.  Noninvasive Brain-Computer Interfaces Based on Sensorimotor Rhythms.

Authors:  Bin He; Bryan Baxter; Bradley J Edelman; Christopher C Cline; Wendy Ye
Journal:  Proc IEEE Inst Electr Electron Eng       Date:  2015-05-20       Impact factor: 10.961

2.  Improved signal processing approaches in an offline simulation of a hybrid brain-computer interface.

Authors:  Clemens Brunner; Brendan Z Allison; Dean J Krusienski; Vera Kaiser; Gernot R Müller-Putz; Gert Pfurtscheller; Christa Neuper
Journal:  J Neurosci Methods       Date:  2010-02-11       Impact factor: 2.390

3.  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

Review 4.  A survey of stimulation methods used in SSVEP-based BCIs.

Authors:  Danhua Zhu; Jordi Bieger; Gary Garcia Molina; Ronald M Aarts
Journal:  Comput Intell Neurosci       Date:  2010-03-07

5.  The hybrid BCI.

Authors:  Gert Pfurtscheller; Brendan Z Allison; Clemens Brunner; Gunther Bauernfeind; Teodoro Solis-Escalante; Reinhold Scherer; Thorsten O Zander; Gernot Mueller-Putz; Christa Neuper; Niels Birbaumer
Journal:  Front Neurosci       Date:  2010-04-21       Impact factor: 4.677

6.  Combining Brain-Computer Interfaces and Assistive Technologies: State-of-the-Art and Challenges.

Authors:  J D R Millán; R Rupp; G R Müller-Putz; R Murray-Smith; C Giugliemma; M Tangermann; C Vidaurre; F Cincotti; A Kübler; R Leeb; C Neuper; K-R Müller; D Mattia
Journal:  Front Neurosci       Date:  2010-09-07       Impact factor: 4.677

7.  Switching between Manual Control and Brain-Computer Interface Using Long Term and Short Term Quality Measures.

Authors:  Alex Kreilinger; Vera Kaiser; Christian Breitwieser; John Williamson; Christa Neuper; Gernot R Müller-Putz
Journal:  Front Neurosci       Date:  2012-01-18       Impact factor: 4.677

Review 8.  A systematic review of hybrid brain-computer interfaces: Taxonomy and usability perspectives.

Authors:  Inchul Choi; Ilsun Rhiu; Yushin Lee; Myung Hwan Yun; Chang S Nam
Journal:  PLoS One       Date:  2017-04-28       Impact factor: 3.240

9.  Combining Mental Training and Physical Training With Goal-Oriented Protocols in Stroke Rehabilitation: A Feasibility Case Study.

Authors:  Xin Zhang; Ahmed M Elnady; Bubblepreet K Randhawa; Lara A Boyd; Carlo Menon
Journal:  Front Hum Neurosci       Date:  2018-04-03       Impact factor: 3.169

10.  User Experience May be Producing Greater Heart Rate Variability than Motor Imagery Related Control Tasks during the User-System Adaptation in Brain-Computer Interfaces.

Authors:  Luz M Alonso-Valerdi; David A Gutiérrez-Begovich; Janet Argüello-García; Francisco Sepulveda; Ricardo A Ramírez-Mendoza
Journal:  Front Physiol       Date:  2016-07-06       Impact factor: 4.566

  10 in total

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