Fat Layer Thickness Estimation Using Mechanical Impulse Stimulation and Transmitted Signal Analysis

Document Type : Original Article

Authors
1 Ferdowsi university of Mashhad
2 Ferdowsi University of Mashhad
3 Mechanical Engineering, Engineering Department, Ferdowsi university of Mashhad
Abstract
Accurate estimation of subcutaneous fat thickness is of particular importance in medical and biomedical engineering applications. However, the presence of this soft tissue layer leads to attenuation, scattering, and distortion of transmitted waves, thereby significantly reducing the accuracy of noninvasive measurement techniques. In the present study, the effect of natural fat thickness on the wave propagation pattern induced by an impulsive mechanical excitation was investigated through both numerical simulations and experimental measurements, with the aim of assessing the feasibility of developing a novel method for estimating adipose tissue thickness. In this approach, a periodic mechanical impact was applied to the tissue via a metal plate in direct contact with the surface, and the transmitted compressive wave, after propagating through fat layers of varying thicknesses, was received and recorded using an ultrasonic transducer. Experimental results demonstrated that increasing fat layer thickness leads to a continuous decrease in the amplitude, energy, and signal-to-noise ratio of the received signal. Furthermore, finite element simulations performed in COMSOL Multiphysics successfully reproduced this experimental trend and confirmed a monotonic reduction in signal amplitude and quality. These findings indicate that impulsive mechanical excitation, when combined with conventional ultrasonic techniques, can serve as a simple, low-cost, and reliable approach for noninvasive estimation of subcutaneous fat thickness and for improving the interpretation of acoustic measurement data.
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Articles in Press, Accepted Manuscript
Available Online from 20 June 2026

  • Receive Date 03 October 2025
  • Revise Date 09 June 2026
  • Accept Date 20 June 2026
  • First Publish Date 20 June 2026
  • Publish Date 20 June 2026