Literature DB >> 18367779

Emulation of computer mouse control with a noninvasive brain-computer interface.

Dennis J McFarland1, Dean J Krusienski, William A Sarnacki, Jonathan R Wolpaw.   

Abstract

Brain-computer interface (BCI) technology can provide nonmuscular communication and control to people who are severely paralyzed. BCIs can use noninvasive or invasive techniques for recording the brain signals that convey the user's commands. Although noninvasive BCIs are used for simple applications, it has frequently been assumed that only invasive BCIs, which use electrodes implanted in the brain, will be able to provide multidimensional sequential control of a robotic arm or a neuroprosthesis. The present study shows that a noninvasive BCI using scalp-recorded electroencephalographic (EEG) activity and an adaptive algorithm can provide people, including people with spinal cord injuries, with two-dimensional cursor movement and target selection. Multiple targets were presented around the periphery of a computer screen, with one designated as the correct target. The user's task was to use EEG to move a cursor from the center of the screen to the correct target and then to use an additional EEG feature to select the target. If the cursor reached an incorrect target, the user was instructed not to select it. Thus, this task emulated the key features of mouse operation. The results indicate that people with severe motor disabilities could use brain signals for sequential multidimensional movement and selection.

Entities:  

Mesh:

Year:  2008        PMID: 18367779      PMCID: PMC2757111          DOI: 10.1088/1741-2560/5/2/001

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


  35 in total

1.  Direct cortical control of 3D neuroprosthetic devices.

Authors:  Dawn M Taylor; Stephen I Helms Tillery; Andrew B Schwartz
Journal:  Science       Date:  2002-06-07       Impact factor: 47.728

2.  Temporal structure in neuronal activity during working memory in macaque parietal cortex.

Authors:  Bijan Pesaran; John S Pezaris; Maneesh Sahani; Partha P Mitra; Richard A Andersen
Journal:  Nat Neurosci       Date:  2002-08       Impact factor: 24.884

3.  Noninvasive brain-actuated control of a mobile robot by human EEG.

Authors:  José del R Millán; Frédéric Renkens; Josep Mouriño; Wulfram Gerstner
Journal:  IEEE Trans Biomed Eng       Date:  2004-06       Impact factor: 4.538

4.  BCI2000: a general-purpose brain-computer interface (BCI) system.

Authors:  Gerwin Schalk; Dennis J McFarland; Thilo Hinterberger; Niels Birbaumer; Jonathan R Wolpaw
Journal:  IEEE Trans Biomed Eng       Date:  2004-06       Impact factor: 4.538

5.  The effect of motor imagery on spinal segmental excitability.

Authors:  Sheng Li; Derek G Kamper; Jennifer A Stevens; William Z Rymer
Journal:  J Neurosci       Date:  2004-10-27       Impact factor: 6.167

6.  Multichannel EEG-based brain-computer communication.

Authors:  J R Wolpaw; D J McFarland
Journal:  Electroencephalogr Clin Neurophysiol       Date:  1994-06

7.  Task-specific EMG-characteristics during mental training.

Authors:  T Wehner; S Vogt; M Stadler
Journal:  Psychol Res       Date:  1984

8.  Cognitive control signals for neural prosthetics.

Authors:  S Musallam; B D Corneil; B Greger; H Scherberger; R A Andersen
Journal:  Science       Date:  2004-07-09       Impact factor: 47.728

9.  Electroencephalographic(EEG)-based communication: EEG control versus system performance in humans.

Authors:  Hesham Sheikh; Dennis J McFarland; William A Sarnacki; Jonathan R Wolpaw
Journal:  Neurosci Lett       Date:  2003-07-17       Impact factor: 3.046

10.  Learning to control a brain-machine interface for reaching and grasping by primates.

Authors:  Jose M Carmena; Mikhail A Lebedev; Roy E Crist; Joseph E O'Doherty; David M Santucci; Dragan F Dimitrov; Parag G Patil; Craig S Henriquez; Miguel A L Nicolelis
Journal:  PLoS Biol       Date:  2003-10-13       Impact factor: 8.029

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  41 in total

1.  Point-and-click cursor control with an intracortical neural interface system by humans with tetraplegia.

Authors:  Sung-Phil Kim; John D Simeral; Leigh R Hochberg; John P Donoghue; Gerhard M Friehs; Michael J Black
Journal:  IEEE Trans Neural Syst Rehabil Eng       Date:  2011-01-28       Impact factor: 3.802

2.  Active training paradigm for motor imagery BCI.

Authors:  Junhua Li; Liqing Zhang
Journal:  Exp Brain Res       Date:  2012-04-05       Impact factor: 1.972

Review 3.  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

4.  Evaluation of a wireless wearable tongue-computer interface by individuals with high-level spinal cord injuries.

Authors:  Xueliang Huo; Maysam Ghovanloo
Journal:  J Neural Eng       Date:  2010-03-23       Impact factor: 5.379

Review 5.  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

6.  A sensorimotor rhythm based goal selection brain-computer interface.

Authors:  Audrey S Royer; Andrew McCullough; Bin He
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

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.  Real-time two-dimensional asynchronous control of a computer cursor with a single subdural electrode.

Authors:  César Márquez-Chin; Milos R Popovic; Egor Sanin; Robert Chen; Andres M Lozano
Journal:  J Spinal Cord Med       Date:  2012-09       Impact factor: 1.985

9.  Optimization of electrode channels in Brain Computer Interfaces.

Authors:  M Kamrunnahar; N S Dias; S J Schiff
Journal:  Conf Proc IEEE Eng Med Biol Soc       Date:  2009

10.  Can Electrocorticography (ECoG) Support Robust and Powerful Brain-Computer Interfaces?

Authors:  Gerwin Schalk
Journal:  Front Neuroeng       Date:  2010-06-24
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