A computational framework to simulate the endolymph flow due to vestibular rehabilitation maneuvers assessed from accelerometer data

Abstract

Vertiginous symptoms are one of the most common symptoms in the world, therefore investing in new ways and therapies to avoid the sense of insecurity during the vertigo episodes is of great interest. The classical maneuvers used during vestibular rehabilitation consist in moving the head in specific ways, but it is not fully understood why those steps solve the problem. To better understand this mechanism, a three-dimensional computational model of the semicircular ducts of the inner ear was built using the finite element method, with the simulation of the fluid flow being obtained using particle methods. To simulate the exact movements performed during rehabilitation, data from an accelerometer were used as input for the boundary conditions in the model. It is shown that the developed model responds to the input data as expected, and the results successfully show the fluid flow of the endolymph behaving coherently as a function of accelerometer data. Numerical results at specific time steps are compared with the corresponding head movement, and both particle velocity and position follow the pattern that would be expected, confirming that the model is working as expected. The vestibular model built is an important starting point to simulate the classical maneuvers of the vestibular rehabilitation allowing to understand what happens in the endolymph during the rehabilitation process, which ultimately may be used to improve the maneuvers and the quality of life of patients suffering from vertigo.

Keywords:

• Inner ear
• Computational models
• Vestibular system
• Rehabilitation

Acknowledgments

The authors acknowledge the funding by Ministério da Ciência, Tecnologia e Ensino Superior–Fundacão para a Ciência e a Tecnologia, Portugal and POCH, by Fundo Social Europeu and MCTES under research grants SFRH/BD/108292/2015, IF/00159/2014 and by project funding MIT-EXPL/ISF/0084/2017. Additionally, the authors acknowledge the funding of Project NORTE-01-0145-FEDER-000022-SciTech cofinanced by Programa Operacional Regional do Norte (NORTE2020), through Fundo Europeu de Desenvolvimento Regional (FEDER).

Disclosure statement

No potential conflict of interest was reported by the authors.