Literature DB >> 19963794

Asynchronous non-invasive brain-actuated control of an intelligent wheelchair.

J J Del R Millan1, F Galan, D Vanhooydonck, E Lew, J Philips, M Nuttin.   

Abstract

In this paper we present further results of our asynchronous and non-invasive BMI for the continuous control of an intelligent wheelchair. Three subjects participated in two experiments where they steered the wheelchair spontaneously, without any external cue. To do so the users learn to voluntary modulate EEG oscillatory rhythms by executing three mental tasks (i.e., mental imagery) that are associated to different steering commands. Importantly, we implement shared control techniques between the BMI and the intelligent wheelchair to assist the subject in the driving task. The results show that the three subjects could achieve a significant level of mental control, even if far from optimal, to drive an intelligent wheelchair.

Mesh:

Year:  2009        PMID: 19963794     DOI: 10.1109/IEMBS.2009.5332828

Source DB:  PubMed          Journal:  Conf Proc IEEE Eng Med Biol Soc        ISSN: 1557-170X


  19 in total

1.  An asynchronous wheelchair control by hybrid EEG-EOG brain-computer interface.

Authors:  Hongtao Wang; Yuanqing Li; Jinyi Long; Tianyou Yu; Zhenghui Gu
Journal:  Cogn Neurodyn       Date:  2014-05-24       Impact factor: 5.082

2.  Efficient human-machine control with asymmetric marginal reliability input devices.

Authors:  John H Williamson; Melissa Quek; Iulia Popescu; Andrew Ramsay; Roderick Murray-Smith
Journal:  PLoS One       Date:  2020-06-01       Impact factor: 3.240

Review 3.  Towards neural co-processors for the brain: combining decoding and encoding in brain-computer interfaces.

Authors:  Rajesh Pn Rao
Journal:  Curr Opin Neurobiol       Date:  2019-04-04       Impact factor: 6.627

Review 4.  The use of intracranial recordings to decode human language: Challenges and opportunities.

Authors:  Stephanie Martin; José Del R Millán; Robert T Knight; Brian N Pasley
Journal:  Brain Lang       Date:  2016-07-01       Impact factor: 2.381

5.  Comparison of sensor selection mechanisms for an ERP-based brain-computer interface.

Authors:  David Feess; Mario M Krell; Jan H Metzen
Journal:  PLoS One       Date:  2013-07-02       Impact factor: 3.240

6.  Detection of self-paced reaching movement intention from EEG signals.

Authors:  Eileen Lew; Ricardo Chavarriaga; Stefano Silvoni; José Del R Millán
Journal:  Front Neuroeng       Date:  2012-07-12

7.  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

Review 8.  Creating new functional circuits for action via brain-machine interfaces.

Authors:  Amy L Orsborn; Jose M Carmena
Journal:  Front Comput Neurosci       Date:  2013-11-05       Impact factor: 2.380

9.  On the applicability of brain reading for predictive human-machine interfaces in robotics.

Authors:  Elsa Andrea Kirchner; Su Kyoung Kim; Sirko Straube; Anett Seeland; Hendrik Wöhrle; Mario Michael Krell; Marc Tabie; Manfred Fahle
Journal:  PLoS One       Date:  2013-12-16       Impact factor: 3.240

Review 10.  Challenges in clinical applications of brain computer interfaces in individuals with spinal cord injury.

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