Literature DB >> 17367076

Electrocorticographically controlled brain-computer interfaces using motor and sensory imagery in patients with temporary subdural electrode implants. Report of four cases.

Elizabeth A Felton1, J Adam Wilson, Justin C Williams, P Charles Garell.   

Abstract

Brain-computer interface (BCI) technology can offer individuals with severe motor disabilities greater independence and a higher quality of life. The BCI systems take recorded brain signals and translate them into real-time actions, for improved communication, movement, or perception. Four patient participants with a clinical need for intracranial electrocorticography (ECoG) participated in this study. The participants were trained over multiple sessions to use motor and/or auditory imagery to modulate their brain signals in order to control the movement of a computer cursor. Participants with electrodes over motor and/or sensory areas were able to achieve cursor control over 2 to 7 days of training. These findings indicate that sensory and other brain areas not previously considered ideal for ECoG-based control can provide additional channels of control that may be useful for a motor BCI.

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Year:  2007        PMID: 17367076     DOI: 10.3171/jns.2007.106.3.495

Source DB:  PubMed          Journal:  J Neurosurg        ISSN: 0022-3085            Impact factor:   5.115


  47 in total

1.  Control of a visual keyboard using an electrocorticographic brain-computer interface.

Authors:  Dean J Krusienski; Jerry J Shih
Journal:  Neurorehabil Neural Repair       Date:  2010-10-04       Impact factor: 3.919

Review 2.  Brain-computer interfaces in medicine.

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

3.  Cortical activity during motor execution, motor imagery, and imagery-based online feedback.

Authors:  Kai J Miller; Gerwin Schalk; Eberhard E Fetz; Marcel den Nijs; Jeffrey G Ojemann; Rajesh P N Rao
Journal:  Proc Natl Acad Sci U S A       Date:  2010-02-16       Impact factor: 11.205

Review 4.  Advanced neurotechnologies for chronic neural interfaces: new horizons and clinical opportunities.

Authors:  Daryl R Kipke; William Shain; György Buzsáki; E Fetz; Jaimie M Henderson; Jamille F Hetke; Gerwin Schalk
Journal:  J Neurosci       Date:  2008-11-12       Impact factor: 6.167

5.  Characterization of the effects of the human dura on macro- and micro-electrocorticographic recordings.

Authors:  David T Bundy; Erik Zellmer; Charles M Gaona; Mohit Sharma; Nicholas Szrama; Carl Hacker; Zachary V Freudenburg; Amy Daitch; Daniel W Moran; Eric C Leuthardt
Journal:  J Neural Eng       Date:  2014-02       Impact factor: 5.379

6.  Decoding three-dimensional reaching movements using electrocorticographic signals in humans.

Authors:  David T Bundy; Mrinal Pahwa; Nicholas Szrama; Eric C Leuthardt
Journal:  J Neural Eng       Date:  2016-02-23       Impact factor: 5.379

Review 7.  Evolution of brain-computer interfaces: going beyond classic motor physiology.

Authors:  Eric C Leuthardt; Gerwin Schalk; Jarod Roland; Adam Rouse; Daniel W Moran
Journal:  Neurosurg Focus       Date:  2009-07       Impact factor: 4.047

8.  Clinical Applications of Brain-Computer Interfaces: Current State and Future Prospects.

Authors:  Joseph N Mak; Jonathan R Wolpaw
Journal:  IEEE Rev Biomed Eng       Date:  2009

9.  Decoding continuous limb movements from high-density epidural electrode arrays using custom spatial filters.

Authors:  A R Marathe; D M Taylor
Journal:  J Neural Eng       Date:  2013-04-23       Impact factor: 5.379

10.  Massively Parallel Signal Processing using the Graphics Processing Unit for Real-Time Brain-Computer Interface Feature Extraction.

Authors:  J Adam Wilson; Justin C Williams
Journal:  Front Neuroeng       Date:  2009-07-14
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