R. Jacobs

A multisensory integration model of human stance control.

Abstract. A model is presented to study and quantify the contribution of all available sensory information to human standing based on optimal estimation theory. In the model, delayed sensory information is integrated in such a way that a best estimate of body orientation is obtained. The model approach agrees with the present theory of the goal of human balance control. The model is not based on purely inverted pendulum body dynamics, but rather on a three-link segment model of a standing human on a movable support base. In addition, the model is non-linear and explicitly addresses the problem of multisensory integration and neural time delays. A predictive element is included in the controller to compensate for time delays, necessary to maintain erect body orientation. Model results of sensory perturbations on total body sway closely resemble experimental results. Despite internal and external perturbations, the controller is able to stabilise the model of an inherently unstable standing human with neural time delays of 100 ms. It is concluded, that the model is capable of studying and quantifying multisensory integration in human stance control. We aim to apply the model in (1) the design and development of prostheses and orthoses and (2) the diagnosis of neurological balance disorders.

An adaptive model of sensory integration in a dynamic environment applied to human stance control

Abstract. An adaptive estimator model of human spatial orientation is presented. The adaptive model dynamically weights sensory error signals. More specific, the model weights the difference between expected and actual sensory signals as a function of environmental conditions. The model does not require any changes in model parameters. Differences with existing models of spatial orientation are that: (1) environmental conditions are not specified but estimated, (2) the sensor noise characteristics are the only parameters supplied by the model designer, (3) history-dependent effects and mental resources can be modelled, and (4) vestibular thresholds are not included in the model; instead vestibular-related threshold effects are predicted by the model. The model was applied to human stance control and evaluated with results of a visually induced sway experiment. From these experiments it is known that the amplitude of visually induced sway reaches a saturation level as the stimulus level increases. This saturation level is higher when the support base is sway referenced. For subjects experiencing vestibular loss, these saturation effects do not occur. Unknown sensory noise characteristics were found by matching model predictions with these experimental results. Using only five model parameters, far more than five data points were successfully predicted. Model predictions showed that both the saturation levels are vestibular related since removal of the vestibular organs in the model removed the saturation effects, as was also shown in the experiments. It seems that the nature of these vestibular-related threshold effects is not physical, since in the model no threshold is included. The model results suggest that vestibular-related thresholds are the result of the processing of noisy sensory and motor output signals. Model analysis suggests that, especially for slow and small movements, the environment postural orientation can not be estimated optimally, which causes sensory illusions. The model also confirms the experimental finding that postural orientation is history dependent and can be shaped by instruction or mental knowledge. In addition the model predicts that: (1) vestibular-loss patients cannot handle sensory conflicting situations and will fall down, (2) during sinusoidal support-base translations vestibular function is needed to prevent falling, (3) loss of somatosensory information from the feet results in larger postural sway for sinusoidal support-base translations, and (4) loss of vestibular function results in falling for large support-base rotations with the eyes closed. These predictions are in agreement with experimental results.

An alternative approach to synthesizing bipedal walking

Abstract. Based on mechanical analysis, three gait descriptors are found which should be controlled to generate cyclic gait of a seven-link humanoid biped in the sagittal plane: (i) step length, (ii) step time, and (iii) the velocity of the center of mass (CoM) at push off. Two of these three gait descriptors can be chosen independently, since the CoM moves almost ballistically during the swing phase. These gait descriptors are formulated as end-point conditions and are regulated by a model predictive controller. In addition, continuous controls at the trunk and knees are implemented to maintain the trunk upright and to ensure weight bearing. The model predictive controller is realized by quadratic dynamic matrix control, which offers the possibility of including constraints that are exposed by the environment and the biped itself. Specifying step length and CoM velocity at push off, the controller generates a symmetric and stable gait. The proposed control scheme serves as a general-purpose solution for the generation of a bipedal gait. The proposed model contains fewer parameters than other models, and they are all directly related to determinants of bipedal gait: step length, trunk orientation, step time, walking velocity, and weight bearing. The proposed control objectives and the model of humanoid bipedal walking have potential applications in robotics and rehabilitation engineering.

Control model of human stance using fuzzy logic

Abstract. A control model of human stance is proposed based on knowledge from behavioral experiments and physiological systems. The proposed model is based on the control of global variables specific to body orientation and alignment, rather than on the control of the body’s center of mass within the base of support. Furthermore, the proposed control model is not based on purely inverted pendulum body mechanics where only motion at one joint is controlled, as for instance the ankle. In the proposed model, the degrees of freedom are controlled by using reciprocal and synergistic muscle actions at multiple joints. The control model is based on three sets of different global variables which act in parallel: (1) limb length and its derivative, (2) limb orientation and its derivative, and (3) trunk attitude and its derivative. An important feature of the control model is the use of fuzzy logic, which enables us to model experimental findings and physiological knowledge in a meaningful and explicit way using fuzzy if-then rules. In the control model, 36 fuzzy if-then rules are implemented and applied using a four-linked segment model consisting of a trunk, thigh, shank and foot. Uni- and biarticular limb muscles and trunk muscles are represented as torque actuators at each individual joint. In the model, three sets of global variables act in parallel and make corrective and coordinated responses to internal, self-induced perturbations. The data show that the use of global variables and fuzzy logic successfully enables us to model human standing with sway about a point of equilibrium. Small changes in, for example, total body sway are comparable to those seen during natural sway in human stance. The selected controllers—limb length, limb orientation and trunk attitude—seem to be appropriate for human stance control.

Quantification of sensory information in human balance control

A human balance control model is developed, which includes the different sensory systems as well as neural time delays. The model is based on optimal control theory. Platform perturbation experiments were done to quantify the precision of the different sensory systems by matching model predictions with experimental results. The precision of the sensors was quantified by the variances of sensor noise. The noise to signal ratios for the muscle spindles are 3-7% and for vision 11-14%. For the vestibular organs unambiguous noise to signal ratios could not be found. To find the noise to signal ratios of the vestibular organs the method of identification of sensory information has to be modified.