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Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients

Overview of attention for article published in Scientific Reports, August 2016
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • Among the highest-scoring outputs from this source (#37 of 93,661)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (99th percentile)

Mentioned by

news
191 news outlets
blogs
16 blogs
twitter
362 tweeters
patent
1 patent
facebook
31 Facebook pages
googleplus
10 Google+ users
video
1 video uploader

Citations

dimensions_citation
197 Dimensions

Readers on

mendeley
568 Mendeley
citeulike
1 CiteULike
Title
Long-Term Training with a Brain-Machine Interface-Based Gait Protocol Induces Partial Neurological Recovery in Paraplegic Patients
Published in
Scientific Reports, August 2016
DOI 10.1038/srep30383
Pubmed ID
Authors

Ana R. C. Donati, Solaiman Shokur, Edgard Morya, Debora S. F. Campos, Renan C. Moioli, Claudia M. Gitti, Patricia B. Augusto, Sandra Tripodi, Cristhiane G. Pires, Gislaine A. Pereira, Fabricio L. Brasil, Simone Gallo, Anthony A. Lin, Angelo K. Takigami, Maria A. Aratanha, Sanjay Joshi, Hannes Bleuler, Gordon Cheng, Alan Rudolph, Miguel A. L. Nicolelis

Abstract

Brain-machine interfaces (BMIs) provide a new assistive strategy aimed at restoring mobility in severely paralyzed patients. Yet, no study in animals or in human subjects has indicated that long-term BMI training could induce any type of clinical recovery. Eight chronic (3-13 years) spinal cord injury (SCI) paraplegics were subjected to long-term training (12 months) with a multi-stage BMI-based gait neurorehabilitation paradigm aimed at restoring locomotion. This paradigm combined intense immersive virtual reality training, enriched visual-tactile feedback, and walking with two EEG-controlled robotic actuators, including a custom-designed lower limb exoskeleton capable of delivering tactile feedback to subjects. Following 12 months of training with this paradigm, all eight patients experienced neurological improvements in somatic sensation (pain localization, fine/crude touch, and proprioceptive sensing) in multiple dermatomes. Patients also regained voluntary motor control in key muscles below the SCI level, as measured by EMGs, resulting in marked improvement in their walking index. As a result, 50% of these patients were upgraded to an incomplete paraplegia classification. Neurological recovery was paralleled by the reemergence of lower limb motor imagery at cortical level. We hypothesize that this unprecedented neurological recovery results from both cortical and spinal cord plasticity triggered by long-term BMI usage.

Twitter Demographics

The data shown below were collected from the profiles of 362 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 568 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 <1%
Singapore 2 <1%
Israel 1 <1%
Brazil 1 <1%
Ireland 1 <1%
United Kingdom 1 <1%
Canada 1 <1%
New Zealand 1 <1%
France 1 <1%
Other 1 <1%
Unknown 555 98%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 117 21%
Student > Master 105 18%
Researcher 76 13%
Student > Bachelor 69 12%
Student > Postgraduate 26 5%
Other 96 17%
Unknown 79 14%
Readers by discipline Count As %
Engineering 124 22%
Neuroscience 73 13%
Medicine and Dentistry 70 12%
Agricultural and Biological Sciences 49 9%
Psychology 31 5%
Other 111 20%
Unknown 110 19%

Attention Score in Context

This research output has an Altmetric Attention Score of 1852. 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 10 December 2020.
All research outputs
#2,502
of 17,408,409 outputs
Outputs from Scientific Reports
#37
of 93,661 outputs
Outputs of similar age
#41
of 272,188 outputs
Outputs of similar age from Scientific Reports
#3
of 4,666 outputs
Altmetric has tracked 17,408,409 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 99th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 93,661 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 16.7. This one has done particularly well, scoring higher than 99% of its peers.
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 272,188 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 99% of its contemporaries.
We're also able to compare this research output to 4,666 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 99% of its contemporaries.