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An investigation into closed-loop treatment of neurological disorders based on sensing mitochondrial dysfunction

Overview of attention for article published in Journal of NeuroEngineering and Rehabilitation, February 2018
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  • Good Attention Score compared to outputs of the same age (70th percentile)
  • Good Attention Score compared to outputs of the same age and source (75th percentile)

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Title
An investigation into closed-loop treatment of neurological disorders based on sensing mitochondrial dysfunction
Published in
Journal of NeuroEngineering and Rehabilitation, February 2018
DOI 10.1186/s12984-018-0349-z
Pubmed ID
Authors

Scott D. Adams, Abbas Z. Kouzani, Susannah J. Tye, Kevin E. Bennet, Michael Berk

Abstract

Dynamic feedback based closed-loop medical devices offer a number of advantages for treatment of heterogeneous neurological conditions. Closed-loop devices integrate a level of neurobiological feedback, which allows for real-time adjustments to be made with the overarching aim of improving treatment efficacy and minimizing risks for adverse events. One target which has not been extensively explored as a potential feedback component in closed-loop therapies is mitochondrial function. Several neurodegenerative and psychiatric disorders including Parkinson's disease, Major Depressive disorder and Bipolar disorder have been linked to perturbations in the mitochondrial respiratory chain. This paper investigates the potential to monitor this mitochondrial function as a method of feedback for closed-loop neuromodulation treatments. A generic model of the closed-loop treatment is developed to describe the high-level functions of any system designed to control neural function based on mitochondrial response to stimulation, simplifying comparison and future meta-analysis. This model has four key functional components including: a sensor, signal manipulator, controller and effector. Each of these components are described and several potential technologies for each are investigated. While some of these candidate technologies are quite mature, there are still technological gaps remaining. The field of closed-loop medical devices is rapidly evolving, and whilst there is a lot of interest in this area, widespread adoption has not yet been achieved due to several remaining technological hurdles. However, the significant therapeutic benefits offered by this technology mean that this will be an active area for research for years to come.

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 74 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 74 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 12 16%
Student > Bachelor 11 15%
Other 6 8%
Student > Doctoral Student 5 7%
Researcher 5 7%
Other 10 14%
Unknown 25 34%
Readers by discipline Count As %
Neuroscience 8 11%
Engineering 7 9%
Medicine and Dentistry 6 8%
Biochemistry, Genetics and Molecular Biology 6 8%
Psychology 5 7%
Other 16 22%
Unknown 26 35%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 06 April 2019.
All research outputs
#6,370,601
of 23,305,591 outputs
Outputs from Journal of NeuroEngineering and Rehabilitation
#373
of 1,303 outputs
Outputs of similar age
#132,738
of 447,566 outputs
Outputs of similar age from Journal of NeuroEngineering and Rehabilitation
#8
of 29 outputs
Altmetric has tracked 23,305,591 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 1,303 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 7.0. This one has gotten more attention than average, scoring higher than 71% 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 447,566 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 70% of its contemporaries.
We're also able to compare this research output to 29 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 75% of its contemporaries.