Modelling sensory integration for ankle- and hip control in human balance

Modelling sensory integration for ankle- and hip control in human balance

van der Zwaag, Peterke (TU Delft Mechanical, Maritime and Materials Engineering)

Schouten, Alfred (mentor)
van Kordelaar-Eegdeman, Joost (mentor)
Pasma, Jantsje (mentor)
Dodou, Dimitra (graduation committee)
van Paassen, Rene (graduation committee)

Delft University of Technology

Mechanical Engineering | BioMechanical Design

2019-04-17

Falling is a problem in elderly, affecting 30% of people over 65 years old, and leading to serious injuries in 10% of the cases. Because balance is controlled in a closed loop system with a high level of redundancy, the cause of impaired balance control is often unknown. A balance control model in combination with perturbed balance experiments could be a useful aid to detect the underlying cause of balance impairment, which would allow for better treatment. A disturbance estimation and compensation (DEC) model has a strong neurological basis and is able to describe multiple conditions with one set of parameters. An existing DEC model, containing separate ankle and hip control, was extended by adding visual and mechanical disturbance estimations. The model was fitted to experimental data of elderly subjects maintaining balance in three conditions containing four disturbances simultaneously; visual and ankle proprioceptive perturbations and mechanical perturbations at the hip and shoulder level. To validate the fitting procedure, the model parameters were also fitted to data simulated by the model, and a sensitivity analysis was done.Being fitted to experimental data, the model could reproduce about 60% of the behaviour. Mainly the low frequency behaviour could not fully be tracked. Parameter estimation proved challenging, with some parameters consistently estimated larger or smaller than expected or physiologically plausible. Fitting the model on its own simulated data could reproduce >99.9% of the behaviour, but with some parameters consistently estimated up to a factor 10 too small or too large. Many adaptations and extensions to the existing DEC model were made simultaneously and with the available experimental data it was not possible to investigate the individual influence of each adaptation. If a broader range of experimental data is available, with conditions where only one, two or three perturbations are applied, it is possible to validate each model adaptation separately. This would likely improve the model. With the suggested improvements, the multisegmental DEC model opens up the way towards better treatment for balance impairment.

human balance control
non-linear model
closed-loop identification

http://resolver.tudelft.nl/uuid:8370513d-9f9a-4543-a3da-e1006b1f8bae

Student theses

master thesis

© 2019 Peterke van der Zwaag