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Physical parameter estimation from porcine ex vivo vocal fold dynamics in an inverse problem framework

Overview of attention for article published in Biomechanics and Modeling in Mechanobiology, December 2017
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Title
Physical parameter estimation from porcine ex vivo vocal fold dynamics in an inverse problem framework
Published in
Biomechanics and Modeling in Mechanobiology, December 2017
DOI 10.1007/s10237-017-0992-5
Pubmed ID
Authors

Pablo Gómez, Anne Schützenberger, Stefan Kniesburges, Christopher Bohr, Michael Döllinger

Abstract

This study presents a framework for a direct comparison of experimental vocal fold dynamics data to a numerical two-mass-model (2MM) by solving the corresponding inverse problem of which parameters lead to similar model behavior. The introduced 2MM features improvements such as a variable stiffness and a modified collision force. A set of physiologically sensible degrees of freedom is presented, and three optimization algorithms are compared on synthetic vocal fold trajectories. Finally, a total of 288 high-speed video recordings of six excised porcine larynges were optimized to validate the proposed framework. Particular focus lay on the subglottal pressure, as the experimental subglottal pressure is directly comparable to the model subglottal pressure. Fundamental frequency, amplitude and objective function values were also investigated. The employed 2MM is able to replicate the behavior of the porcine vocal folds very well. The model trajectories' fundamental frequency matches the one of the experimental trajectories in [Formula: see text] of the recordings. The relative error of the model trajectory amplitudes is on average [Formula: see text]. The experiments feature a mean subglottal pressure of 10.16 (SD [Formula: see text]) [Formula: see text]; in the model, it was on average 7.61 (SD [Formula: see text]) [Formula: see text]. A tendency of the model to underestimate the subglottal pressure is found, but the model is capable of inferring trends in the subglottal pressure. The average absolute error between the subglottal pressure in the model and the experiment is 2.90 (SD [Formula: see text]) [Formula: see text] or [Formula: see text]. A detailed analysis of the factors affecting the accuracy in matching the subglottal pressure is presented.

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Geographical breakdown

Country Count As %
Unknown 12 100%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 2 17%
Unspecified 1 8%
Other 1 8%
Student > Master 1 8%
Researcher 1 8%
Other 2 17%
Unknown 4 33%
Readers by discipline Count As %
Engineering 3 25%
Unspecified 1 8%
Medicine and Dentistry 1 8%
Social Sciences 1 8%
Unknown 6 50%
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 13 December 2017.
All research outputs
#19,246,640
of 23,849,058 outputs
Outputs from Biomechanics and Modeling in Mechanobiology
#379
of 486 outputs
Outputs of similar age
#333,006
of 444,312 outputs
Outputs of similar age from Biomechanics and Modeling in Mechanobiology
#8
of 8 outputs
Altmetric has tracked 23,849,058 research outputs across all sources so far. This one is in the 11th percentile – i.e., 11% of other outputs scored the same or lower than it.
So far Altmetric has tracked 486 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.2. This one is in the 12th percentile – i.e., 12% of its peers scored the same or lower than it.
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