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.

Implementation of perturbation training for elderly requires a validated measure to quantify someone’s ability to recover
when encountering a perturbation. A quantified recovery performance has been constructed for the anteroposterior
(QRP_AP) and for mediolateral (QRP_ML) plane, the QRP_AP and QRP_ML reflect the amount of deviation of the center of
pressure trajectory from the unperturbed walking pattern. The QRP_AP and QRP_ML were calculated for eleven elderly
subjects (>65 years), who experienced 66 perturbations (accelerations and decelerations) during treadmill walking.
The constructed QRP_AP and QRP_ML were validated in this study (1) by comparing them to the rated recovery performance
(RRT) as provided by physiotherapists and (2) by studying how they were affected by an increased specified
difficulty (SpD) of perturbations. The used perturbation characteristics for the SpD’s were validated with the perceived
difficulty (PD) as reported by the subjects for each perturbation. A positive relation confirmed the increase of PD with
an increase of SpD. Both for the QRP_AP and the QRP_ML a positive relation was found with the RRP and a negative relation
was found with the SpD. The QRPAP showed a stronger relation with the RRP and was found to be more sensitive
when compared to the QRP_ML. The relation of the QRP_AP with the RRP was consistent across physiotherapists. Implementation of the QRP_AP during perturbation training will decrease the attention demanded of physiotherapists and will remove the offset observed across physiotherapists. Progress can be monitored objectively and training difficulty can
be adjusted accordingly.