Compliant support surfaces affect sensory reweighting during balance control

To maintain upright posture and prevent falling, balance control involves the complex interaction between nervous, muscular and sensory systems, such as sensory reweighting. When balance is impaired, compliant foam mats are used in training methods to improve balance control. However, the effect of the compliance of these foam mats on sensory reweighting remains unclear. In this study, eleven healthy subjects maintained standing balance with their eyes open while continuous support surface (SS) rotations disturbed the proprioception of the ankles. Multisine disturbance torques were applied in 9 trials; three levels of SS compliance, combined with three levels of desired SS rotation amplitude. Two trials were repeated with eyes closed. The corrective ankle torques, in response to the SS rotations, were assessed in frequency response functions (FRF). Lower frequency magnitudes (LFM) were calculated by averaging the FRF magnitudes in a lower frequency window, representative for sensory reweighting. Results showed that increasing the SS rotation amplitude leads to a decrease in LFM. In addition there was an interaction effect; the decrease in LFM by increasing the SS rotation amplitude was less when the SS was more compliant. Trials with eyes closed had a larger LFM compared to trials with eyes open. We can conclude that when balance control is trained using foam mats, two different effects should be kept in mind. An increase in SS compliance has a known effect causing larger SS rotations and therefore greater down weighting of proprioceptive information. However, SS compliance itself influences the sensitivity of sensory reweighting to changes in SS rotation amplitude with relatively less reweighting occurring on more compliant surfaces as SS amplitude change

Assessment of Multi-Joint Coordination and Adaptation in Standing Balance: A Novel Device and System Identification Technique

The ankles and hips play an important role in maintaining standing balance and the coordination between joints adapts with task and conditions, like the disturbance magnitude and type, and changes with age. Assessment of multi-joint coordination requires the application of multiple continuous and independent disturbances and closed loop system identification techniques (CLSIT). This paper presents a novel device, the double inverted pendulum perturbator (DIPP), which can apply disturbing forces at the hip level and between the shoulder blades. In addition to the disturbances, the device can provide force fields to study adaptation of multi-joint coordination. The performance of the DIPP and a novel CLSIT was assessed by identifying a system with known mechanical properties and model simulations. A double inverted pendulum was successfully identified, while force fields were able to keep the pendulum upright. The estimated dynamics were similar as the theoretical derived dynamics. The DIPP has a sufficient bandwidth of 7 Hz to identify multi-joint coordination dynamics. An experiment with human subjects where a stabilizing force field was rendered at the hip (1500 N/m), showed that subjects adapt by lowering their control actions around the ankles. The stiffness from upper and lower segment motion to ankle torque dropped with 30% and 48%, respectively. Our methods allow to study (pathological) changes in multi-joint coordination as well as adaptive capacity to maintain standing balance

Less is more: Efficient identification of human stance control with a parametric subspace method

The human balance control system is a complex mechanism with many underlying neural feedback loops. In order to identify the stabilizing mechanisms generated by the central nervous system during upright stance, perturbations and closed-loop system identification techniques (CLSIT) are required [v.d. Kooij, 2005]. Many CLSIT used to investigate human balance control are based on non-parametric methods in the frequency domain, relating the signals with the external perturbations. Although, these non-parametric CLSIT give insight about specific dynamic behavior of a human, they do not directly quantify the underlying physiological parameters of the feedback loops and do not take advantage of the common structure between the signals and the perturbations. As an alternative identification technique, we have adopted the Prediction Based Subspace Identification (PBSID) method [v. Wingerden, 2008]. This method has several theoretical advantages for use in closed loop data, as with the central nervous system controlling the human body. With subspace techniques a parametric model structure is obtained, relating to physiological parameters, without a priori assumptions about the underlying model structure. In addition subspace identification is well suited for Multiple-Input-Multiple-Output (MIMO) systems; in case of the human stance model the contribution of both ankle and hip joints can easily be incorporated for a more realistic representation of the human body. To test the PBSID subspace identification method for balance control, simulations were performed in Matlab. The human body is modeled as a double inverted pendulum, incorporating an ankle and hip joint, with a stabilizing mechanism (controller), activating dynamics and neural time delays. In the simulations two independent continuous perturbations are applied at hip and shoulder level and multiple realistic levels of measurement noise were simulated. The simulations demonstrate that subspace identification estimates the stabilizing mechanism at least as good as a non-parametric CLSIT. The PBSID algorithm provides consistent estimates, also in case of short sample lengths. Furthermore, the method is robust against measurement noise, which can reduce experimental measurement time in humans. Reduction of experimental time is an advantage especially in pathological stance. A drawback of the method is that consistency depends on proper model order selection, which can be difficult in case of high noise. In short, subspace is a good alternative over nonparametric methods, implicitly handles MIMO systems, and can deal with short measurement time

Sensory reweighting of proprioceptive input during balance control as function of age and disease

Background and aim: Sensory (re)weighting is the automated and unconscious process of dynamically combining sensory inputs, e.g. proprioception, graviception and vision, during balance control. Typically, reliable sensory inputs are weighted more than unreliable and noisy sensory inputs, to prevent decline of balance control. Malfunctioning of sensory reweighting in case of sensory deterioration may be an important determinant of impaired balance in elderly with the consequence of physical impairment and falls. In this study, we used closed loop system identification techniques (CLSIT) to assess sensory weighting and reweighting of proprioceptive input of the ankle during upright stance as function of age and disease. Methods: Ten healthy young (age 25.4±2.2 years), ten healthy elderly (age 76.8±1.8 years), ten elderly with cataract (age 76.7±6.8 years) and ten elderly with polyneuropathy (age 73.7±8.0 years) were asked to maintain balance while the proprioceptive input of each ankle was disturbed by rotation of the support surface (SS) around the ankle axes. SS rotations were applied with specific frequency content and the perturbation amplitude increased over trials. Body sway and the total reactive ankle torque were recorded. The sensitivity functions of the ankle torque to the perturbation amplitude was determined using CLSIT. The gain of the sensitivity function (S) describes the ratio of the perturbation amplitude and the ankle torque as function of frequency and represents the proprioceptive weighting. Parameters describing the sensitivity functions were estimated using optimized model fits, of which one was the proprioceptive weight (Wp). Results: Healthy elderly were more sensitive to SS rotations as reflected by a significantly higher gain of S (p<0.001) compared with the young. In comparison with healthy elderly, elderly with a cataract had a significantly higher gain of S (p=0.038), unlike elderly with polyneuropathy (p=0.37). In all groups, the gain of S decreased significantly with increased disturbance amplitude (p<0.001). There was no interaction effect between perturbation amplitude and groups (p=0.68).The estimated Wp was significantly higher in healthy elderly compared with the young (p=0.001). Compared with healthy elderly, elderly with cataract had a significantly higher Wp (p=0.003), unlike elderly with polyneuropathy (p=0.24). In all groups, Wp decreased with increased perturbation amplitude (p<0.001). There was an interaction effect (p=0.001) between perturbation amplitude and groups. Conclusions: Using CLSIT, proprioceptive weighting and reweighting could be established as function of age and cataract; healthy elderly rely more on proprioceptive input compared with the young and elderly with cataract rely even more on proprioceptive input. Assessing the interplay between available sensory inputs is necessary to identify the weakest link in impaired balance as a primary therapeutic target

Comparison of closed-loop system identification techniques to quantify multi-joint human balance control

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 settin

Adaptation of multi-joint balance coordination to whole body force fields

Background and aim: The ankles and the hips play an important role in standing balance. Multi-joint coordination adapts with task, the magnitude and type of disturbance [1]. Arm studies show that postural responses are highly dependent on externally applied force fields [2]. Our aim is to study how multi-joint postural responses in standing depend on such force fields, using closed loop system identification techniques (CLSIT) where two disturbances are applied [3]. This offers knowledge about the plasticity of the neuromuscular controller; e.g. the adaptive capacity to maintain standing balance. We hypothesize that application of a stabilizing force field will lead to downscaling of postural responses. Methods: Ten healthy subjects maintained standing balance while whole-body force fields were applied in three conditions 1) no force field 2) stiffness at the hip and 3) stiffness at the shoulder. In addition, unpredictable continuous pushing and pulling forces (0.05-5Hz) were applied at hip and shoulder level (Figure 1). Leg and trunk segment angles were recorded and the ankle and hip torques were obtained from ground reaction forces and torques by inverse dynamics. With CLSIT, the Frequency Response Function (FRF) of the neuromuscular controller was estimated. The FRF describes for each frequency in the disturbance signal the magnitude and relative timing (gain and phase) of corrective joint torques evoked by motions of the leg and trunk segment. Results: Figure 2 shows that the ankle provides relatively more torque at low frequencies and the hip is dominant at higher frequencies. Hip torque compensates for both trunk and leg movement, whereas ankle torque only compensates for movement in the legs. The phases of all neuromuscular controller FRFs decreased with frequency, indicating a delayed response. Addition of force fields decreased FRF magnitude mainly at the low frequencies, where stiffness dominates. Stiffness at the hip or shoulder both reduce the corrective ankle torque to maintain standing balance. Hip torque is only slightly reduced by additional shoulder stiffness. Conclusion: By adding force fields (i.e. stiffness) in standing balance, subjects adapt by lowering their control action mainly in the ankle torque. The gain of the neuromuscular controller is reduced, as subjects are externally stabilized and balance maintenance becomes easier. Downscaling of postural responses indeed occurs. In future studies, our methods allow to study pathological changes in multi-joint coordination as well as its adaptive capacity. References: [1] Kim et al, J Biomech, 2012 [2] Franklin et al, Exp Brain Res, 2003 [3] Boonstra et al, JNER, 201

Changes in sensory reweighting of proprioceptive information during standing balance with age and disease

Pathofysiological analysis of movement disorders in relation to functio

Impaired standing balance: The clinical need for closing the loop

Impaired balance may limit mobility and daily activities, and plays a key role in the elderly falling. Maintaining balance requires a concerted action of the sensory, nervous and motor systems, whereby cause and effect mutually affect each other within a closed loop. Aforementioned systems and their connecting pathways are prone to chronological age and disease-related deterioration. System redundancy allows for compensation strategies, e.g. sensory reweighting, to maintain standing balance in spite of the deterioration of underlying systems. Once those strategies fail, impaired balance and possible falls may occur. Targeted interventions to prevent falling require knowledge of the quality of the underlying systems and the compensation strategies used. As current clinical balance tests only measure the ability to maintain standing balance and cannot distinguish between cause and effect in a closed loop, there is a clear clinical need for new techniques to assess standing balance. A way to disentangle cause-and-effect relations to identify primary defects and compensation strategies is based on the application of external disturbances and system identification techniques, applicable in clinical practice. This paper outlines the multiple deteriorations of the underlying systems that may be involved in standing balance, which have to be detected early to prevent impaired standing balance. An overview of clinically used balance tests shows that early detection of impaired standing balance and identification of causal mechanisms is difficult with current tests, thereby hindering the development of well-timed and target-oriented interventions as described next. Finally, a new approach to assess standing balance and to detect the underlying deteriorations is proposed