Background: Balance control deteriorates with age and nearly 30% of the elderly population in the United States reports stability problems. Postural stability is an integral task to daily living reliant upon the control of the ankle and hip. To this end, the estimation of joint parameters can be a useful tool when analyzing compensatory actions aimed at maintaining postural stability. Methods: Using an analytical approach, this study expands on previous work and analyzes a two degrees of freedom human model. The first two modes of vibration of the system are represented by the neuro-mechanical parameters of a second-order, timevarying Kelvin-Voigt model actuated at the ankle and hip. The model is tested using a custom double inverted pendulum and healthy volunteers who were subjected to a positional step-like perturbation during quiet standing. An in silico sensitivity analysis of the influence of inertial parameters was also performed. Results: The proposed method is able to correctly identify the time-varying viscoelastic parameters of of a double inverted pendulum. We show that that the parameter estimation method can be applied to standing humans. These results appear to identify a subject-independent strategy to control quiet standing that combines both the modulation of stiffness, and the use of an intermittent control. Conclusions: This paper presents the analysis of the non-linear system of differential equations representing the control of lumped muscle-tendon units. It utilizes motion capture measurements to obtain the estimates of the system's control parameters by constructing a simple time-dependent regressor for estimating the time-varying parameters of the control with a single perturbation. This work is a step forward into the understanding of the neuro-mechanical control parameters of human recovering from a fall. In previous literature, the analysis is either restricted to the first vibrational mode of an inverted-pendulum model or assumed to be time-invariant. The proposed method allows for the analysis of hip related movement for stability control and highlights the importance of core training.

Postural stability is important in everyday life as falls can cause severe injuries. Risk of injuries is higher in the elderly whose balance is often impaired. Modeling postural stability and the parameters that govern it is important to understand the balance mechanism and allow for the development of fall prevention strategies. Several mathematical models have been proposed to represent postural stability of bipeds. These models differ on the number of degrees-of-freedom (DOF) of the skeletal structure, force generation function for the muscle models, and capability to change their behavior as a function of the task. This work proposes a nonlinear model that captures fall recovery using a hip–ankle strategy. The muscle actuation is modeled as a third-order Poynting–Thomson's (PT) mechanical system where muscles and tendons are represented as lumped parameters actuating the aforementioned joints. Both a regression technique and a Kalman Filter (KF) are used to estimate the muscle–tendon parameters of the model. With a good model, the direct estimation of these parameters would allow clinicians to improve postural stability in the elderly, monitor the deterioration of the physical condition in individuals affected by neuro-degenerative diseases, and develop rehabilitation appropriate processes.

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Balance control naturally deteriorates with age, so it comes as no surprise that nearly 30% of the elderly population in the United States report stability problems that lead to difficulty performing daily activities or even falling. Postural stability is an integral task to daily living which is reliant upon the control of the ankle and hip. To this end, the estimation of ankle and hip parameters in quiet standing can be a useful tool when analyzing compensatory actions aimed at maintaining postural stability. Using an analytical approach, this work builds upon the results obtained by the authors and expands it to a two degrees of freedom system where the first two modes of vibration of a standing human are considered. The physiological parameters a second-order Kelvin-Voigt model were estimated for the actuation of the ankle and hip. Estimates were obtained during quiet standing when healthy volunteers were subjected to a step-like perturbation. This paper presents the analysis of a second-order nonlinear system of differential equations representing the control of lumped muscle-tendon units at the ankle and hip. This paper utilizes motion capture measurements to obtain the estimates of the control parameters of the system. The dynamic measurements are utilized to construct a simple time-dependent regression that allows calculating the time-varying estimates of the control and body segment parameters with a single perturbation. This work represents a step forward in estimating the control parameters of human quiet standing where, usually, the analysis is either restricted to the first vibrational mode of an inverted pendulum model or the control parameters are assumed to be time-invariant. The proposed method allows for the analysis of hip related movement in the control of stability and highlights the importance of core muscle training.

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