Fluidic Response and Sensing Mechanism of Meissner’s Corpuscles to Low-Frequency Mechanical Stimulation

TL;DR

This study explores how Meissner’s corpuscles detect vibrations by analyzing fluid flow and shear stress in response to different types of mechanical stimulation.

Contribution

A biomimetic microfluidic platform and CFD model were used to reveal direction-specific fluid dynamics in Meissner’s corpuscles.

Findings

Normal vibrations at 20 Hz caused localized vortices and higher shear stress along the short axis.

Tangential vibrations produced stable laminar flow with lower shear stress along the long axis.

The internal structure of Meissner’s corpuscles is key to converting mechanical inputs into specific fluid patterns.

Abstract

Meissner’s corpuscles are essential mechanoreceptors that detect low-frequency vibrations. However, the internal fluid dynamic processes that convert directional mechanical stimuli into neural signals are not yet fully understood. This study aims to clarify the direction-specific sensing mechanism by analyzing internal fluid flow and shear stress distribution under different vibration modes. A biomimetic microfluidic platform was developed and coupled with a dynamic mesh computational fluid dynamics (CFD) model to simulate the response of the corpuscle to 20 Hz normal and tangential vibrations. The simulation results showed clear differences in fluid behavior. Normal vibration produced localized vortices and peak wall shear stress greater than 0.0054 Pa along the short axis. In contrast, tangential vibration generated stable laminar flow with a lower average shear stress of about 0.0012 Pa along the long axis. These results suggest that the internal structure of the Meissner corpuscle is important for converting mechanical inputs from different directions into specific fluid patterns. This study provides a physical foundation for understanding mechanotransduction and supports the design of biomimetic sensors with improved directional sensitivity for use in smart skin and soft robotic systems.

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