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research-article

A Third Order Model of Hip and Ankle Joints during Balance Recovery: Modeling and Parameter Estimation

[+] Author and Article Information
Alejandro Gonzalez de Alba

CONACyT-Universidad Autónoma, de San Luis Potosí, San Luis Potosí, San Luis Potosí, México
alejandro.gonzalez@uaslp.mx

Angel Cerda-Lugo

Universidad Autónoma, de San Luis Potosí, Faculty of Engineering, San Luis Potosí, San Luis Potosí, Mexico
angelcerda13@gmail.com

Antonio Cardenas

Universidad Autónoma, de San Luis Potosí, Faculty of Engineering, San Luis Potosí, San Luis Potosí, México
antonio.cardenas@uaslp.mx

Mauro Maya

Universidad Autónoma, de San Luis Potosí, Faculty of Engineering, San Luis Potosí, San Luis Potosí, México
mauro.maya@uaslp.mx

Davide Piovesan

Gannon University, Biomedical, Industrial and Systems Engineering Department, Erie, PA, USA
piovesan001@gannon.edu

1Corresponding author.

ASME doi:10.1115/1.4042527 History: Received August 01, 2018; Revised January 10, 2019

Abstract

Postural stability is important in everyday life as falls can cause severe injuries. Risk of injuries is higher in the elderly where balance is often impaired. Modeling postural stability and the parameters that govern it is important to understand balance mechanism and thus allowing the development of strategies to prevent falls. Several mathematical models have been proposed to represent postural stability of bipeds. They differ from one another based on the number of degrees of freedom of the skeletal structure, force generation function for the muscle models and capability to change their behavior as function of the task. This work proposes a non-linear model that captures the recovery from a fall using a hip-ankle strategy. The muscle actuation is modeled as a third-order Poynting-Thomson's mechanical system where muscles and tendons are represented as lumped parameters actuating the aforementioned joints. Both a regression technique and an Kalman filter have been utilized to identify the muscle-tendon parameters of the model. With a good model, that captures the targeted phenomena, direct estimation of these parameters could allow clinicians to improve postural stability in the elderly, monitor the deterioration of physical condition in individuals affected by neuro-degenerative diseases and develop rehabilitation appropriate processes.

Copyright (c) 2019 by ASME
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