Evidence in Support of the Independent Channel Model Describing the Sensorimotor Control of Human Stance Using a Humanoid Robot

The Independent Channel (IC) model is a commonly used linear balance control model in the frequency domain to analyze human balance control using system identification and parameter estimation. The IC model is a rudimentary and noise-free description of balance behavior in the frequency domain, where a stable model representation is not guaranteed. In this study, we conducted firstly time-domain simulations with added noise, and secondly robot experiments by implementing the IC model in a real-world robot (PostuRob II) to test the validity and stability of the model in the time domain and for real world situations. Balance behavior of seven healthy participants was measured during upright stance by applying pseudorandom continuous support surface rotations. System identification and parameter estimation were used to describe the balance behavior with the IC model in the frequency domain. The IC model with the estimated parameters from human experiments was implemented in Simulink for computer simulations including noise in the time domain and robot experiments using the humanoid robot PostuRob II. Again, system identification and parameter estimation were used to describe the simulated balance behavior. Time series, Frequency Response Functions, and estimated parameters from human experiments, computer simulations, and robot experiments were compared with each other. The computer simulations showed similar balance behavior and estimated control parameters compared to the human experiments, in the time and frequency domain. Also, the IC model was able to control the humanoid robot by keeping it upright, but showed small differences compared to the human experiments in the time and frequency domain, especially at high frequencies. We conclude that the IC model, a descriptive model in the frequency domain, can imitate human balance behavior also in the time domain, both in computer simulations with added noise and real world situations with a humanoid robot. This provides further evidence that the IC model is a valid description of human balance control.

Assessment of the underlying systems involved in standing balance: the additional value of electromyography in system identification and parameter estimation

Background

Closed loop system identification (CLSIT) is a method to disentangle the contribution of underlying systems in standing balance. We investigated whether taking into account lower leg muscle activation in CLSIT could improve the reliability and accuracy of estimated parameters identifying the underlying systems.

Methods

Standing balance behaviour of 20 healthy young participants was measured using continuous rotations of the support surface (SS). The dynamic balance behaviour obtained with CLSIT was expressed by sensitivity functions of the ankle torque, body sway and muscle activation of the lower legs to the SS rotation. Balance control models, 1) without activation dynamics, 2) with activation dynamics and 3) with activation dynamics and acceleration feedback, were fitted on the data of all possible combinations of the 3 sensitivity functions. The reliability of the estimated model parameters was represented by the mean relative standard errors of the mean (mSEM) of the estimated parameters, expressed for the basic parameters, the activation dynamics parameters and the acceleration feedback parameter. To investigate the accuracy, a model validation study was performed using simulated data obtained with a comprehensive balance control model. The accuracy of the estimated model parameters was described by the mean relative difference (mDIFF) between the estimated parameters and original parameters.

Results

The experimental data showed a low mSEM of the basic parameters, activation dynamics parameters and acceleration feedback parameter by adding muscle activation in combination with activation dynamics and acceleration feedback to the fitted model. From the simulated data, the mDIFF of the basic parameters varied from 22.2–22.4% when estimated using the torque and body sway sensitivity functions. Adding the activation dynamics, acceleration feedback and muscle activation improved mDIFF to 13.1–15.1%.

Conclusions

Adding the muscle activation in combination with the activation dynamics and acceleration feedback to CLSIT improves the accuracy and reliability of the estimated parameters and gives the possibility to separate the neural time delay, electromechanical delay and the intrinsic and reflexive dynamics. To diagnose impaired balance more specifically, it is recommended to add electromyography (EMG) to body sway (with or without torque) measurements in the assessment of the underlying systems.

Electronic supplementary material

The online version of this article (10.1186/s12984-017-0299-x) contains supplementary material, which is available to authorized users.

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 changes.

Reliability of System Identification Techniques to Assess Standing Balance in Healthy Elderly

Objectives

System identification techniques have the potential to assess the contribution of the underlying systems involved in standing balance by applying well-known disturbances. We investigated the reliability of standing balance parameters obtained with multivariate closed loop system identification techniques.

Methods

In twelve healthy elderly balance tests were performed twice a day during three days. Body sway was measured during two minutes of standing with eyes closed and the Balance test Room (BalRoom) was used to apply four disturbances simultaneously: two sensory disturbances, to the proprioceptive and the visual system, and two mechanical disturbances applied at the leg and trunk segment. Using system identification techniques, sensitivity functions of the sensory disturbances and the neuromuscular controller were estimated. Based on the generalizability theory (G theory), systematic errors and sources of variability were assessed using linear mixed models and reliability was assessed by computing indexes of dependability (ID), standard error of measurement (SEM) and minimal detectable change (MDC).

Results

A systematic error was found between the first and second trial in the sensitivity functions. No systematic error was found in the neuromuscular controller and body sway. The reliability of 15 of 25 parameters and body sway were moderate to excellent when the results of two trials on three days were averaged. To reach an excellent reliability on one day in 7 out of 25 parameters, it was predicted that at least seven trials must be averaged.

Conclusion

This study shows that system identification techniques are a promising method to assess the underlying systems involved in standing balance in elderly. However, most of the parameters do not appear to be reliable unless a large number of trials are collected across multiple days. To reach an excellent reliability in one third of the parameters, a training session for participants is needed and at least seven trials of two minutes must be performed on one day.

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

With sensory reweighting, reliable sensory information is selected over unreliable information during balance by dynamically combining this information. We used system identification techniques to show the weight and the adaptive process of weight change of proprioceptive information during standing balance with age and specific diseases. Ten healthy young subjects (aged between 20 and 30 yr) and 44 elderly subjects (aged above 65 yr) encompassing 10 healthy elderly, 10 with cataract, 10 with polyneuropathy, and 14 with impaired balance, participated in the study. During stance, proprioceptive information of the ankles was disturbed by rotation of the support surface with specific frequency content where disturbance amplitude increased over trials. Body sway and reactive ankle torque were measured to determine sensitivity functions of these responses to the disturbance amplitude. Model fits resulted in a proprioceptive weight (changing over trials), time delay, force feedback, reflexive stiffness, and damping. The proprioceptive weight was higher in healthy elderly compared with young subjects and higher in elderly subjects with cataract and with impaired balance compared with healthy elderly subjects. Proprioceptive weight decreased with increasing disturbance amplitude; decrease was similar in all groups. In all groups, the time delay was higher and the reflexive stiffness was lower compared with young or healthy elderly subjects. In conclusion, proprioceptive information is weighted more with age and in patients with cataract and impaired balance. With age and specific diseases the time delay was higher and reflexive stiffness was lower. These results illustrate the opportunity to detect the underlying cause of impaired balance in the elderly with system identification.

Impaired standing balance in elderly: a new engineering method helps to unravel causes and effects

Deteriorated balance control is the most frequent cause of falls and injuries in the elderly. Balance control comprises a complex interplay of several underlying systems (ie, the sensory systems, the motor system, and the nervous system). Available clinical balance tests determine the patient's ability to maintain standing balance under defined test conditions and aim to describe the current state of this ability. However, these tests do not reveal which of the underlying systems is deteriorated and to what extent, so that the relation between cause and effect often remains unclear. Especially detection of early-stage balance control deterioration is difficult, because the balance control system is redundant and elderly may use compensation strategies. This article describes a new method that is able to identify causal relationships in deteriorated balance control, called CLSIT (Closed Loop System Identification Technique). Identification of impaired balance with CLSIT is a base for development of tailored interventions and compensation strategies to reduce the often serious consequences of deteriorated balance control in the elderly.

Sensory reweighting of proprioceptive information of the left and right leg during human balance control

To keep balance, information from different sensory systems is integrated to generate corrective torques. Current literature suggests that this information is combined according to the sensory reweighting hypothesis, i.e., more reliable information is weighted more strongly than less reliable information. In this approach, no distinction has been made between the contributions of both legs. In this study, we investigated how proprioceptive information from both legs is combined to maintain upright stance. Healthy subjects maintained balance with eyes closed while proprioceptive information of each leg was perturbed independently by continuous rotations of the support surfaces (SS) and the human body by platform translation. Two conditions were tested: perturbation amplitude of one SS was increased over trials while the other SS 1) did not move or 2) was perturbed with constant amplitude. With the use of system identification techniques, the response of the ankle torques to the perturbation amplitudes (i.e., the torque sensitivity functions) was determined and how much each leg contributed to stabilize stance (i.e., stabilizing mechanisms) was estimated. Increased amplitude of one SS resulted in a decreased torque sensitivity. The torque sensitivity to the constant perturbed SS showed no significant differences. The properties of the stabilizing mechanisms remained constant during perturbations of each SS. This study demonstrates that proprioceptive information from each leg is weighted independently and that the weight decreases with perturbation amplitude. Weighting of proprioceptive information of one leg has no influence on the weight of the proprioceptive information of the other leg. According to the sensory reweighting hypothesis, vestibular information must be up-weighted, because closing the eyes eliminates visual information.