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Rehabilitation robots for the treatment of sensorimotor deficits: a neurophysiological perspective

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, June 2018
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • One of the highest-scoring outputs from this source (#2 of 1,314)
  • High Attention Score compared to outputs of the same age (99th percentile)
  • High Attention Score compared to outputs of the same age and source (96th percentile)

Mentioned by

news
40 news outlets
blogs
1 blog
twitter
7 X users

Citations

dimensions_citation
261 Dimensions

Readers on

mendeley
645 Mendeley
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Title
Rehabilitation robots for the treatment of sensorimotor deficits: a neurophysiological perspective
Published in
Journal of NeuroEngineering and Rehabilitation, June 2018
DOI 10.1186/s12984-018-0383-x
Pubmed ID
Authors

Roger Gassert, Volker Dietz

Abstract

The past decades have seen rapid and vast developments of robots for the rehabilitation of sensorimotor deficits after damage to the central nervous system (CNS). Many of these innovations were technology-driven, limiting their clinical application and impact. Yet, rehabilitation robots should be designed on the basis of neurophysiological insights underlying normal and impaired sensorimotor functions, which requires interdisciplinary collaboration and background knowledge.Recovery of sensorimotor function after CNS damage is based on the exploitation of neuroplasticity, with a focus on the rehabilitation of movements needed for self-independence. This requires a physiological limb muscle activation that can be achieved through functional arm/hand and leg movement exercises and the activation of appropriate peripheral receptors. Such considerations have already led to the development of innovative rehabilitation robots with advanced interaction control schemes and the use of integrated sensors to continuously monitor and adapt the support to the actual state of patients, but many challenges remain. For a positive impact on outcome of function, rehabilitation approaches should be based on neurophysiological and clinical insights, keeping in mind that recovery of function is limited. Consequently, the design of rehabilitation robots requires a combination of specialized engineering and neurophysiological knowledge. When appropriately applied, robot-assisted therapy can provide a number of advantages over conventional approaches, including a standardized training environment, adaptable support and the ability to increase therapy intensity and dose, while reducing the physical burden on therapists. Rehabilitation robots are thus an ideal means to complement conventional therapy in the clinic, and bear great potential for continued therapy and assistance at home using simpler devices.This review summarizes the evolution of the field of rehabilitation robotics, as well as the current state of clinical evidence. It highlights fundamental neurophysiological factors influencing the recovery of sensorimotor function after a stroke or spinal cord injury, and discusses their implications for the development of effective rehabilitation robots. It thus provides insights on essential neurophysiological mechanisms to be considered for a successful development and clinical inclusion of robots in rehabilitation.

X Demographics

X Demographics

The data shown below were collected from the profiles of 7 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 645 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 645 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 92 14%
Student > Master 87 13%
Student > Bachelor 70 11%
Researcher 54 8%
Other 24 4%
Other 80 12%
Unknown 238 37%
Readers by discipline Count As %
Engineering 185 29%
Nursing and Health Professions 45 7%
Neuroscience 40 6%
Medicine and Dentistry 34 5%
Unspecified 11 2%
Other 64 10%
Unknown 266 41%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 319. 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 20 April 2023.
All research outputs
#93,405
of 23,578,918 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#2
of 1,314 outputs
Outputs of similar age
#2,353
of 330,563 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#1
of 28 outputs
Altmetric has tracked 23,578,918 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 1,314 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.3. 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 330,563 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 28 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 96% of its contemporaries.