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Elastic models of vocal fold tissues

Authors: F, Alipour-Haghighi; I R, Titze;

Elastic models of vocal fold tissues

Abstract

Elastic properties of canine vocal fold tissue (muscle and mucosa) were obtained through a series of experiments conducted in vitro and were modeled mathematically. The elastic properties play a significant role in quantitative analysis of vocal fold vibrations and theory of pitch control. Samples of vocalis muscle and mucosa were dissected and prepared from dog larynges a few minutes premortem and kept in a Krebs solution at a temperature of 37±1 °C and a pH of 7.4±0.05. Samples of muscle tissue and mucosa were stretched and released in a slow, sinusoidal fashion. Force and displacement of the samples were measured with a dual-servo system (ergometer). After digitization, stress–strain data for samples of muscle tissue and cover tissue were averaged. The stress–strain data were then fitted numerically by polynomial and exponential models.

Related Organizations
Keywords

Models, Anatomic, Dogs, Animals, Vocal Cords, Models, Theoretical, Elasticity, Muscle Contraction

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
130
Top 10%
Top 1%
Average
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