↓ Skip to main content

An osseointegrated human-machine gateway for long-term sensory feedback and motor control of artificial limbs

Overview of attention for article published in Science Translational Medicine, October 2014
Altmetric Badge

About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • 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)

Citations

dimensions_citation
163 Dimensions

Readers on

mendeley
374 Mendeley
citeulike
1 CiteULike
Title
An osseointegrated human-machine gateway for long-term sensory feedback and motor control of artificial limbs
Published in
Science Translational Medicine, October 2014
DOI 10.1126/scitranslmed.3008933
Pubmed ID
Authors

M. Ortiz-Catalan, B. Hakansson, R. Branemark

Abstract

A major challenge since the invention of implantable devices has been a reliable and long-term stable transcutaneous communication. In the case of prosthetic limbs, existing neuromuscular interfaces have been unable to address this challenge and provide direct and intuitive neural control. Although prosthetic hardware and decoding algorithms are readily available, there is still a lack of appropriate and stable physiological signals for controlling the devices. We developed a percutaneous osseointegrated (bone-anchored) interface that allows for permanent and unlimited bidirectional communication with the human body. With this interface, an artificial limb can be chronically driven by implanted electrodes in the peripheral nerves and muscles of an amputee, outside of controlled environments and during activities of daily living, thus reducing disability and improving quality of life. We demonstrate in one subject, for more than 1 year, that implanted electrodes provide a more precise and reliable control than surface electrodes, regardless of limb position and environmental conditions, and with less effort. Furthermore, long-term stable myoelectric pattern recognition and appropriate sensory feedback elicited via neurostimulation was demonstrated. The opportunity to chronically record and stimulate the neuromuscular system allows for the implementation of intuitive control and naturally perceived sensory feedback, as well as opportunities for the prediction of complex limb motions and better understanding of sensory perception. The permanent bidirectional interface presented here is a critical step toward more natural limb replacement, by combining stable attachment with permanent and reliable human-machine communication.

Twitter Demographics

The data shown below were collected from the profiles of 26 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 374 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 6 2%
Germany 4 1%
United Kingdom 2 <1%
Brazil 1 <1%
France 1 <1%
Canada 1 <1%
Israel 1 <1%
Unknown 358 96%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 97 26%
Student > Master 72 19%
Student > Bachelor 55 15%
Researcher 54 14%
Student > Doctoral Student 21 6%
Other 53 14%
Unknown 22 6%
Readers by discipline Count As %
Engineering 195 52%
Medicine and Dentistry 45 12%
Neuroscience 29 8%
Agricultural and Biological Sciences 24 6%
Computer Science 11 3%
Other 36 10%
Unknown 34 9%

Attention Score in Context

This research output has an Altmetric Attention Score of 407. 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 17 December 2019.
All research outputs
#26,991
of 14,150,424 outputs
Outputs from Science Translational Medicine
#133
of 3,948 outputs
Outputs of similar age
#387
of 212,900 outputs
Outputs of similar age from Science Translational Medicine
#1
of 129 outputs
Altmetric has tracked 14,150,424 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 3,948 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 61.6. This one has done particularly well, scoring higher than 96% 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 212,900 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 129 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.