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MEG-based neurofeedback for hand rehabilitation

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, September 2015
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About this Attention Score

  • Above-average Attention Score compared to outputs of the same age (52nd percentile)
  • Average Attention Score compared to outputs of the same age and source

Mentioned by

twitter
3 tweeters

Citations

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30 Dimensions

Readers on

mendeley
122 Mendeley
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1 CiteULike
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Title
MEG-based neurofeedback for hand rehabilitation
Published in
Journal of NeuroEngineering and Rehabilitation, September 2015
DOI 10.1186/s12984-015-0076-7
Pubmed ID
Authors

Stephen T. Foldes, Douglas J. Weber, Jennifer L. Collinger

Abstract

Providing neurofeedback (NF) of motor-related brain activity in a biologically-relevant and intuitive way could maximize the utility of a brain-computer interface (BCI) for promoting therapeutic plasticity. We present a BCI capable of providing intuitive and direct control of a video-based grasp. Utilizing magnetoencephalography's (MEG) high temporal and spatial resolution, we recorded sensorimotor rhythms (SMR) that were modulated by grasp or rest intentions. SMR modulation controlled the grasp aperture of a stop motion video of a human hand. The displayed hand grasp position was driven incrementally towards a closed or opened state and subjects were required to hold the targeted position for a time that was adjusted to change the task difficulty. We demonstrated that three individuals with complete hand paralysis due to spinal cord injury (SCI) were able to maintain brain-control of closing and opening a virtual hand with an average of 63 % success which was significantly above the average chance rate of 19 %. This level of performance was achieved without pre-training and less than 4 min of calibration. In addition, successful grasp targets were reached in 1.96 ± 0.15 s. Subjects performed 200 brain-controlled trials in approximately 30 min excluding breaks. Two of the three participants showed a significant improvement in SMR indicating that they had learned to change their brain activity within a single session of NF. This study demonstrated the utility of a MEG-based BCI system to provide realistic, efficient, and focused NF to individuals with paralysis with the goal of using NF to induce neuroplasticity.

Twitter Demographics

The data shown below were collected from the profiles of 3 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 122 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United Kingdom 1 <1%
India 1 <1%
United States 1 <1%
Brazil 1 <1%
Unknown 118 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 29 24%
Student > Master 20 16%
Researcher 11 9%
Student > Bachelor 9 7%
Student > Doctoral Student 9 7%
Other 22 18%
Unknown 22 18%
Readers by discipline Count As %
Engineering 26 21%
Neuroscience 20 16%
Medicine and Dentistry 12 10%
Psychology 12 10%
Computer Science 7 6%
Other 15 12%
Unknown 30 25%

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 19 October 2015.
All research outputs
#6,205,756
of 11,041,735 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#307
of 590 outputs
Outputs of similar age
#111,021
of 252,252 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#14
of 27 outputs
Altmetric has tracked 11,041,735 research outputs across all sources so far. This one is in the 41st percentile – i.e., 41% of other outputs scored the same or lower than it.
So far Altmetric has tracked 590 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 6.9. This one is in the 43rd percentile – i.e., 43% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 252,252 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 52% of its contemporaries.
We're also able to compare this research output to 27 others from the same source and published within six weeks on either side of this one. This one is in the 37th percentile – i.e., 37% of its contemporaries scored the same or lower than it.