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Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review

Overview of attention for article published in Frontiers in Neurorobotics, October 2017
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Title
Selectivity and Longevity of Peripheral-Nerve and Machine Interfaces: A Review
Published in
Frontiers in Neurorobotics, October 2017
DOI 10.3389/fnbot.2017.00059
Pubmed ID
Authors

Usman Ghafoor, Sohee Kim, Keum-Shik Hong

Abstract

For those individuals with upper-extremity amputation, a daily normal living activity is no longer possible or it requires additional effort and time. With the aim of restoring their sensory and motor functions, theoretical and technological investigations have been carried out in the field of neuroprosthetic systems. For transmission of sensory feedback, several interfacing modalities including indirect (non-invasive), direct-to-peripheral-nerve (invasive), and cortical stimulation have been applied. Peripheral nerve interfaces demonstrate an edge over the cortical interfaces due to the sensitivity in attaining cortical brain signals. The peripheral nerve interfaces are highly dependent on interface designs and are required to be biocompatible with the nerves to achieve prolonged stability and longevity. Another criterion is the selection of nerves that allows minimal invasiveness and damages as well as high selectivity for a large number of nerve fascicles. In this paper, we review the nerve-machine interface modalities noted above with more focus on peripheral nerve interfaces, which are responsible for provision of sensory feedback. The invasive interfaces for recording and stimulation of electro-neurographic signals include intra-fascicular, regenerative-type interfaces that provide multiple contact channels to a group of axons inside the nerve and the extra-neural-cuff-type interfaces that enable interaction with many axons around the periphery of the nerve. Section Current Prosthetic Technology summarizes the advancements made to date in the field of neuroprosthetics toward the achievement of a bidirectional nerve-machine interface with more focus on sensory feedback. In the Discussion section, the authors propose a hybrid interface technique for achieving better selectivity and long-term stability using the available nerve interfacing techniques.

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Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 159 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 159 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 29 18%
Student > Ph. D. Student 28 18%
Student > Master 23 14%
Student > Bachelor 18 11%
Student > Doctoral Student 11 7%
Other 19 12%
Unknown 31 19%
Readers by discipline Count As %
Engineering 54 34%
Neuroscience 21 13%
Medicine and Dentistry 18 11%
Nursing and Health Professions 5 3%
Agricultural and Biological Sciences 4 3%
Other 18 11%
Unknown 39 25%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 1. 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 November 2017.
All research outputs
#18,575,277
of 23,007,053 outputs
Outputs from Frontiers in Neurorobotics
#583
of 879 outputs
Outputs of similar age
#251,920
of 328,927 outputs
Outputs of similar age from Frontiers in Neurorobotics
#10
of 15 outputs
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We're also able to compare this research output to 15 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.