Identification of the contribution of the ankle and hip joints to multi-segmental balance control

Abstract

BackgroundHuman stance involves multiple segments, including the legs and trunk, and requires coordinated actions of both. A novel method was developed that reliably estimates the contribution of the left and right leg (i.e., the ankle and hip joints) to the balance control of individual subjects.MethodsThe method was evaluated using simulations of a double-inverted pendulum model and the applicability was demonstrated with an experiment with seven healthy and one Parkinsonian participant. Model simulations indicated that two perturbations are required to reliably estimate the dynamics of a double-inverted pendulum balance control system. In the experiment, two multisine perturbation signals were applied simultaneously. The balance control system dynamic behaviour of the participants was estimated by Frequency Response Functions (FRFs), which relate ankle and hip joint angles to joint torques, using a multivariate closed-loop system identification technique.ResultsIn the model simulations, the FRFs were reliably estimated, also in the presence of realistic levels of noise. In the experiment, the participants responded consistently to the perturbations, indicated by low noise-to-signal ratios of the ankle angle (0.24), hip angle (0.28), ankle torque (0.07), and hip torque (0.33). The developed method could detect that the Parkinson patient controlled his balance asymmetrically, that is, the right ankle and hip joints produced more corrective torque.ConclusionThe method allows for a reliable estimate of the multisegmental feedback mechanism that stabilizes stance, of individual participants and of separate legs.

Extraction of spatial information for low-bandwidth telerehabilitation applications

“…In some exercises, human skeleton-based assessment can be very useful to the physician, such as during cane height assessment, balancing tests such as double-leg stance and single-leg stance [18], and even finger-to-nose task performance tests [19]. The user can select the joints to be tracked and plot the corresponding depth information on a graph.…”

Assessing Standing Balance using MIMO Closed Loop System Identification Techniques

“…The application of the perturbation of the leg and trunk segment makes it possible to investigate the dynamics of the hip and ankle joint and their coupling (Boonstra et al 2013;Engelhart et al 2014b). …”

“…Previous research already showed that it is possible to describe underlying mechanisms involved in standing balance using perturbations and multi-input-multi-output closed loop system identification techniques (MIMO-CLSIT) (Boonstra et al 2013;Engelhart et al 2014b;Peterka 2002). In those studies, several systems were perturbed one by one during quiet stance, while the subject kept his balance.…”

Identification of connectivity in human motor control: exciting the afferent pathways

“…The newly developed techniques are based on a concept from the field of system identification: the application of external (mechanical) perturbations to 'open' the closed loop of motor control (Ljung, 1999;Pintelon and Schoukens, 2001). Previously this approach has successfully been applied to identify different types of reflexes in posture control (van der Helm et al, 2002;Schouten et al, 2008;Mugge et al, 2010) and to separate the contribution of the legs and joints involved in upright balance control (van Asseldonk et al, 2006;Pasma et al, 2012;Boonstra et al, 2013).…”