Literature DB >> 31708271

Dynamically Characterizing Skeletal Muscles via Acoustic Non-linearity Parameter: In Vivo Assessment for Upper Arms.

Jipeng Yan1, Xingchen Yang1, Zhenfeng Chen1, Honghai Liu2.   

Abstract

It is crucial to model skeletal muscles for muscle-centered health care, such as prosthetics. Here we hypothesize that the acoustic non-linearity parameter (B/A) can be utilized to partially represent the contraction state of skeletal muscles. Although previous work commonly measured the B/A value of tissues in vitro, the present study targets the biceps brachii muscle to investigate the relationship between the B/A value and the dynamics of the elbow. Furthermore, it is proposed that a correction method based on the angular spectrum theory be applied in vivo, and the dynamic metrics of the B/A value and its feasibility be verified through an underwater experiment. Seven participants were invited for the in vivo experiment, in which elbow torque and B/A values were measured simultaneously. The non-plane reflection was approximately treated through an integral method, leading to a modified B/A value. Then, linear regression was applied to characterize the B/A-torque relationship, with the calculated coefficient of determination (R2) ranging from 0.85-0.93. Experimental results indicate that the modified B/A value of the biceps brachii correlates well with elbow torque. This study not only paves the way to dynamic measurement of the B/A value of skeletal muscles in vivo, but also confirms that B/A can be used as a more comprehensive assessment criterion for muscle functions.
Copyright © 2019 World Federation for Ultrasound in Medicine & Biology. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Acoustic non-linearity parameter; Angular spectrum theory; Deflection correction; Elbow torque; Skeletal muscles

Year:  2019        PMID: 31708271     DOI: 10.1016/j.ultrasmedbio.2019.08.007

Source DB:  PubMed          Journal:  Ultrasound Med Biol        ISSN: 0301-5629            Impact factor:   2.998


  1 in total

1.  Classifying Muscle States with One-Dimensional Radio-Frequency Signals from Single Element Ultrasound Transducers.

Authors:  Lukas Brausch; Holger Hewener; Paul Lukowicz
Journal:  Sensors (Basel)       Date:  2022-04-05       Impact factor: 3.576

  1 in total

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