Computational parametric analysis of the mechanical response of structurally varying pacinian corpuscles

Julia C. Quindlen, Burak Güçlü, Eric A. Schepis, Victor H Barocas

Research output: Contribution to journalArticlepeer-review

4 Scopus citations

Abstract

The Pacinian corpuscle (PC) is a cutaneous mechanoreceptor that senses low-amplitude, high-frequency vibrations. The PC contains a nerve fiber surrounded by alternating layers of solid lamellae and interlamellar fluid, and this structure is hypothesized to contribute to the PCs role as a band-pass filter for vibrations. In this study, we sought to evaluate the relationship between the PCs material and geometric parameters and its response to vibration. We used a spherical finite element mechanical model based on shell theory and lubrication theory to model the PCs outer core. Specifically, we analyzed the effect of the following structural properties on the PCs frequency sensitivity: lamellar modulus (E), lamellar thickness (h), fluid viscosity (l), PC outer radius (Ro), and number of lamellae (N). The frequency of peak strain amplification (henceforth "peak frequency") and frequency range over which strain amplification occurred (henceforth "bandwidth") increased with lamellar modulus or lamellar thickness and decreased with an increase in fluid viscosity or radius. All five structural parameters were combined into expressions for the relationship between the parameters and peak frequency, ωpeak = 1:605 × 10-6N3:475 (Eh/μRo), or bandwidth, B = 1:747 × 10-6N3:951 (Eh/μRo). Although further work is needed to understand how mechanical variability contributes to functional variability in PCs and how factors such as PC eccentricity also affect PC behavior, this study provides two simple expressions that can be used to predict the impact of structural or material changes with aging or disease on the frequency response of the PC.

Original languageEnglish (US)
Article number071012
JournalJournal of Biomechanical Engineering
Volume139
Issue number7
DOIs
StatePublished - Jul 1 2017

Keywords

  • biomechanics
  • haptics
  • neuroscience
  • somatosensory
  • vibration

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