Standing balance requires multijoint coordination between the ankles and hips. We investigated how humans adapt their multijoint coordination to adjust to various conditions and whether the adaptation differed between healthy young participants and healthy elderly. Balance was disturbed by push/pull rods, applying two continuous and independent force disturbances at the level of the hip and between the shoulder blades. In addition, external force fields were applied, represented by an external stiffness at the hip, either stabilizing or destabilizing the participants' balance. Multivariate closed-loop system-identification techniques were used to describe the neuromuscular control mechanisms by quantifying the corrective joint torques as a response to body sway, represented by frequency response functions (FRFs). Model fits on the FRFs resulted in an estimation of time delays, intrinsic stiffness, reflexive stiffness, and reflexive damping of both the ankle and hip joint. The elderly generated similar corrective joint torques but had reduced body sway compared with the young participants, corresponding to the increased FRF magnitude with age. When a stabilizing or destabilizing external force field was applied at the hip, both young and elderly participants adapted their multijoint coordination by lowering or respectively increasing their neuromuscular control actions around the ankles, expressed in a change of FRF magnitude. However, the elderly adapted less compared with the young participants. Model fits on the FRFs showed that elderly had higher intrinsic and reflexive stiffness of the ankle, together with higher time delays of the hip. Furthermore, the elderly adapted their reflexive stiffness around the ankle joint less compared with young participants. These results imply that elderly were stiffer and were less able to adapt to external force fields.

The incidence of impaired balance control and falls increases with age and disease and has a significant impact on daily life. Detection of early-stage balance impairments is difficult as many intertwined mechanisms contribute to balance control. Current clinical balance tests are unable to quantify these underlying mechanisms, and it is therefore difficult to provide targeted interventions to prevent falling. System identification techniques in combination with external disturbances may provide a way to detect impairments of the underlying mechanisms. This is especially challenging when studying multi-joint coordination, i.e. the contribution of both the ankles and hips to balance control.

With model simulations we compared various existing non-parametric and parametric system identification techniques in combination with external disturbances and evaluated their performance. All methods are considered multi-segmental (both the ankles and the hips contribute to maintaining balance) closed-loop balance control. Validation of the techniques was based on the prediction of time series and frequency domain data. Parametric system identification could not be applied in a straightforward manner in human balance control due to assumed model structure and biological noise in the system. Although the time series were estimated reliably, the dynamics in the frequency domain were not correctly estimated. Non-parametric system identification techniques did estimate the underlying dynamics of balance control reliably in both time and frequency domain. The choice of the external disturbance signal is a trade-off between frequency resolution and measurement time and thus depends on the specific research question and the studied population.

With this overview of the applicability as well as the (dis)advantages of the various system identification techniques, we can work toward the application of system identification techniques in a clinical setting.