Literature DB >> 22344949

Restoration of whole body movement: toward a noninvasive brain-machine interface system.

José Contreras-Vidal1, Alessandro Presacco, Harshavardhan Agashe, Andrew Paek.   

Abstract

This article highlights recent advances in the design of noninvasive neural interfaces based on the scalp electroencephalogram (EEG). The simplest of physical tasks, such as turning the page to read this article, requires an intense burst of brain activity. It happens in milliseconds and requires little conscious thought. But for amputees and stroke victims with diminished motor-sensory skills, this process can be difficult or impossible. Our team at the University of Maryland, in conjunction with the Johns Hopkins Applied Physics Laboratory (APL) and the University of Maryland School of Medicine, hopes to offer these people newfound mobility and dexterity. In separate research thrusts, were using data gleaned from scalp EEG to develop reliable brainmachine interface (BMI) systems that could soon control modern devices such as prosthetic limbs or powered robotic exoskeletons.

Entities:  

Mesh:

Year:  2012        PMID: 22344949      PMCID: PMC3357625          DOI: 10.1109/MPUL.2011.2175635

Source DB:  PubMed          Journal:  IEEE Pulse        ISSN: 2154-2287            Impact factor:   0.924


  4 in total

1.  Fast attainment of computer cursor control with noninvasively acquired brain signals.

Authors:  Trent J Bradberry; Rodolphe J Gentili; José L Contreras-Vidal
Journal:  J Neural Eng       Date:  2011-04-15       Impact factor: 5.379

2.  Reconstructing three-dimensional hand movements from noninvasive electroencephalographic signals.

Authors:  Trent J Bradberry; Rodolphe J Gentili; José L Contreras-Vidal
Journal:  J Neurosci       Date:  2010-03-03       Impact factor: 6.167

3.  Neural decoding of treadmill walking from noninvasive electroencephalographic signals.

Authors:  Alessandro Presacco; Ronald Goodman; Larry Forrester; Jose Luis Contreras-Vidal
Journal:  J Neurophysiol       Date:  2011-07-13       Impact factor: 2.714

4.  Extracting kinematic parameters for monkey bipedal walking from cortical neuronal ensemble activity.

Authors:  Nathan A Fitzsimmons; Mikhail A Lebedev; Ian D Peikon; Miguel A L Nicolelis
Journal:  Front Integr Neurosci       Date:  2009-03-09
  4 in total
  3 in total

1.  Applications of Brain-Machine Interface Systems in Stroke Recovery and Rehabilitation.

Authors:  Anusha Venkatakrishnan; Gerard E Francisco; Jose L Contreras-Vidal
Journal:  Curr Phys Med Rehabil Rep       Date:  2014-06-01

2.  Volition-adaptive control for gait training using wearable exoskeleton: preliminary tests with incomplete spinal cord injury individuals.

Authors:  Vijaykumar Rajasekaran; Eduardo López-Larraz; Fernando Trincado-Alonso; Joan Aranda; Luis Montesano; Antonio J Del-Ama; Jose L Pons
Journal:  J Neuroeng Rehabil       Date:  2018-01-03       Impact factor: 4.262

3.  A large electroencephalographic motor imagery dataset for electroencephalographic brain computer interfaces.

Authors:  Murat Kaya; Mustafa Kemal Binli; Erkan Ozbay; Hilmi Yanar; Yuriy Mishchenko
Journal:  Sci Data       Date:  2018-10-16       Impact factor: 6.444

  3 in total

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