scholarly journals Stability in a frontal plane model of balance requires coupled changes to postural configuration and neural feedback control

2011 ◽  
Vol 106 (1) ◽  
pp. 437-448 ◽  
Author(s):  
Jeffrey T. Bingham ◽  
Julia T. Choi ◽  
Lena H. Ting
Keyword(s):  
Feedback Control ◽  
Frontal Plane ◽  
Delayed Feedback ◽  
The Body ◽  
Joint Torque ◽  
Plane Model ◽  
Postural Responses ◽  
Gain Margin ◽  
Lift Off ◽  
Neural Feedback

Postural stability depends on interactions between the musculoskeletal system and neural control mechanisms. We present a frontal plane model stabilized by delayed feedback to analyze the effects of altered stance width on postural responses to perturbations. We hypothesized that changing stance width alters the mechanical dynamics of the body and limits the range of delayed feedback gains that produce stable postural behaviors. Surprisingly, mechanical stability was found to decrease as stance width increased due to decreased effective inertia. Furthermore, due to sensorimotor delays and increased leverage of hip joint torque on center-of-mass motion, the magnitudes of the stabilizing delayed feedback gains decreased as stance width increased. Moreover, the ranges of the stable feedback gains were nonoverlapping across different stance widths such that using a single neural feedback control strategy at both narrow and wide stances could lead to instability. The set of stable feedback gains was further reduced by constraints on foot lift-off and perturbation magnitude. Simulations were fit to experimentally measured kinematics, and the identified feedback gains corroborated model predictions. In addition, analytical gain margin of the linearized system was found to predict step transitions without the need for simulation. In conclusion, this model offers a method to dissociate the complex interactions between postural configuration, delayed sensorimotor feedback, and nonlinear foot lift-off constraints. The model demonstrates that stability at wide stances can only be achieved if delayed neural feedback gains decrease. This model may be useful in explaining both expected and paradoxical changes in stance width in healthy and neurologically impaired individuals.

Effect of Initial Lean on Scaling of Postural Feedback Responses

2005 ◽  
Vol 277-279 ◽  
pp. 142-147
Author(s):  
Suk Yung Park ◽  
Fay B. Horak ◽  
Arthur D. Kuo
Keyword(s):  
Central Nervous System ◽  
Nervous System ◽  
Feedback Control ◽  
Ankle Joint ◽  
Joint Torque ◽  
Postural Responses ◽  
Body Dynamics ◽  
The Central Nervous System ◽  
Biomechanical Constraints ◽  
Perturbation Magnitude

We examined how the central nervous system adjusts postural responses to an increased postural challenge due to an initial lean. Postural feedback responses scale to accommodate biomechanical constraints, such as an allowable ankle joint torque. Initial forward leaning, which is observed among the elderly who are inactive or afraid of falling, brings subjects near to the limit of stability and makes the biomechanical constraints more difficult to obey. We hypothesized that the central nervous system is aware of body dynamics and restrains postural responses when subjects initially lean forward. To test this hypothesis, fast backwards perturbations of various magnitudes were applied to 12 healthy young subjects (3 male, 9 female) aged 20 to 32 years. The subjects were instructed to stand quietly on a hydraulic servo-controlled force platform with their arms crossed over their chests, then to recover from a perturbation by returning to their upright position, without stepping or lifting their heels off the ground, if possible. Initially, the subjects were either standing upright or leaning forward. The force platform was movable in the translational direction and programmed to move backward with various ramp displacements ranging from 1.2 to 15 cm, all with the duration of 275 msec. For each trial, the kinematics and ground reaction force data were recorded, then used to compute the net joint torques, employing a least squares inverse dynamics method. Optimization methods were used to identify a set of equivalent feedback control gains for each trial so that the biomechanical model incorporating this feedback control would reproduce the empirical response. The results showed that the kinematics, joint torque, and feedback gains gradually scaled as a function of the perturbation magnitude before they reached the biomechanical constraint, and the scaling became more severe with an initial forward lean. For example, the model suggested that the magnitude of the ankle joint angle feedback to ankle torque was smaller in the leaning trials than in the initially upright trials, as if the subjects experienced a larger postural perturbation in the leaning trials. These results imply that the central nervous system restrained the postural responses to accommodate the additional biomechanical constraint imposed by the forward posture, thereby suggesting that the central nervous system is aware of body dynamics and biomechanical constraints. The scaling of the postural feedback gains with the perturbation magnitude and initial lean indicates that the postural control can be interpreted as a feedback scheme with scalable gains.

Postural Control in the Rabbit Maintaining Balance on the Tilting Platform

2003 ◽  
Vol 90 (6) ◽  
pp. 3783-3793 ◽  
Author(s):  
I. N. Beloozerova ◽  
P. V. Zelenin ◽  
L. B. Popova ◽  
G. N. Orlovsky ◽  
S. Grillner ◽  
...  
Keyword(s):  
Frontal Plane ◽  
Threshold Value ◽  
Dorsal Side ◽  
The Body ◽  
Body Posture ◽  
Vestibular Input ◽  
Postural Responses ◽  
Extensor Muscles ◽  
Somatosensory Input ◽  
Emg Patterns

A deviation from the dorsal-side-up body posture in quadrupeds activates the mechanisms for postural corrections. Operation of these mechanisms was studied in the rabbit maintaining balance on a platform periodically tilted in the frontal plane. First, we characterized the kinematics and electromyographic (EMG) patterns of postural responses to tilts. It was found that a reaction to tilt includes an extension of the limbs on the side moving down and flexion on the opposite side. These limb movements are primarily due to a modulation of the activity of extensor muscles. Second, it was found that rabbits can effectively maintain the dorsal-side-up body posture when complex postural stimuli are applied, i.e., asynchronous tilts of the platforms supporting the anterior and posterior parts of the body. These data suggest that the nervous mechanisms controlling positions of these parts of the body can operate independently of each other. Third, we found that normally the somatosensory input plays a predominant role for the generation of postural responses. However, when the postural response appears insufficient to maintain balance, the vestibular input contributes considerably to activation of postural mechanisms. We also found that an asymmetry in the tonic vestibular input, caused by galvanic stimulation of the labyrinths, can affect the stabilized body orientation while the magnitude of postural responses to tilts remains unchanged. Fourth, we found that the mechanisms for postural corrections respond only to tilts that exceed a certain (threshold) value.

Emphasizing Mechanical Feedback in Bio-Inspired Design and Education

2011 ◽  
Author(s):  
Justin Seipel
Keyword(s):  
Feedback Control ◽  
The Body ◽  
The Self ◽  
Biological Research ◽  
Biologically Inspired ◽  
System Architectures ◽  
Mechanical Control ◽  
Conventional View ◽  
Neural Feedback ◽  
Mechanical Feedback

Mechanical feedback in nature is a useful concept proposed by many researchers in different areas of biological research. The concept, at its core, is simply the idea that many mechanical processes in biology effectively act to assist in the self-stabilization of tasks, and therefore, serve functionally as a first level of feedback control. However, due to a conventional view of the nervous system as the ‘controller’ of the body, it has historically been assumed that the control of tasks does not critically depend on the self-stability properties of the mechanical (musculo-skeletal) system. More recent biological research has provided many examples that show neural feedback alone is not sufficient to control many tasks. This forces us to reframe our conventional view of feedback control in neuro-mechanical systems, and by extension, provide a more appropriate perspective when designing biologically-inspired system architectures. Here two ways of diagraming neuro-mechanical control are compared to understand whether one may be more helpful in framing neuro-mechanical control problems and biologically-inspired system design for engineering practitioners and students. This work, when developed further, is expected to provide new pedagogical frameworks for teaching neuromechanics, motor-control, and biologically-inspired methods of control.

Human Postural Feedback Response Described by Eigenvector

2006 ◽  
Vol 326-328 ◽  
pp. 739-742 ◽  
Author(s):  
Se Young Kim ◽  
Suk Yung Park
Keyword(s):  
Feedback Control ◽  
State Feedback ◽  
State Feedback Control ◽  
Joint Torque ◽  
Modal Control ◽  
Control Input ◽  
Postural Responses ◽  
Control Gain ◽  
Full State ◽  
Full State Feedback

Human postural responses appeared to have stereotyped modality, such as ankle mode, knee mode, and hip mode in response to various levels of postural challenges. We examined whether human postural control gain of full-state feedback could be decoupled along with the eigenvectors. To verify the model, postural responses subjected to fast backward perturbation were used. Upright posture was modeled as 3-segment inverted pendulum incorporated with linear feedback control, and joint torques were calculated using inverse dynamics. Postural modalities, such as ankle, knee and hip mode, were obtained from eigenvectors of biomechanics model. As oppose to the full-state feedback control, independent modal control assumes that modal control input is determined by the linear combinations of corresponding modality. We used linear regression to obtain and compare the feedback gains for both eigenvector control gain and full-state feedback. As a result, we found that both feedback gains of two control models that fit the joint torque data are reasonably closed each other especially at the joint angle feedback gains. This implies that the simple parameterization using eigenvectors may be used to correlate the feedback gains of full-state feedback control.

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