Biomedical subjects

R Happee

Publications and source records attributed to R Happee.

4 recordsLinked to original sources

PubMed1995

The control of shoulder muscles during goal directed movements, an inverse dynamic analysis.

Fast goal directed arm movements in the sagittal plane were analyzed with a three-dimensional shoulder model with 95 muscle elements. Dynamics of the muscle elements were described by a third-order nonlinear muscle model. Muscle forces and activation were estimated using the method of inverse muscular dynamics, an optimization scheme which uses only very limited computational power. Most model results were similar to the EMG but some differences between model results and EMG were found in muscles where the EMG activity was subject dependent. For the movement studied, the thoracoscapular muscles were shown to deliver about 40% of the energy required for the acceleration of the arm during anteflexion and about 22% during retroflexion. Activity of thoracoscapular muscles was also required to ensure contact between the thorax and the scapula which is important for the mechanical stability of the shoulder. The rotator cuff muscles were found to deliver about 19% of the energy required for the acceleration of the arm during anteflexion and about 8% during retroflexion.

Biomechanical Phenomena↗

PubMed1994

The use of internal representation in fast gold-directed movements: a modeling approach.

This study investigates the role of the human central nervous system (CNS) in the control of fast goal-directed movements. The main problem is that the latencies inherent in the transmission of physiological signals cause a delayed feedback of sensory information. Therefore, the muscle command signals cannot be explained by a simple servo-loop, so a more sophisticated control structure is required. Our hypothesis is that the CNS employs an internal representation of the controlled system in order to circumvent the drawbacks of the physiological loop delay. To test this hypothesis a mathematical model based on an internal representation and an internal state feedback has been developed. Computer simulations of double-step stimuli (control behaviour), tendon vibration and torque disturbances (disturbance behaviour) and load perturbations (adaptation behaviour) proved to agree remarkably well with experimental observations. The proposed control model can explain the open-loop and closed-loop aspects of human motor control. Hence, the use of an internal representation in generating the muscle command signals is very plausible.

Central Nervous System↗

PubMed1994

Inverse dynamic optimization including muscular dynamics, a new simulation method applied to goal directed movements.

This paper presents a new method for estimating muscular force and activation from experimental kinematic data. The method combines conventional inverse dynamics with optimization utilizing a dynamic muscle model. The method uses only very limited computational power, which makes it a useful tool especially for complex systems like the shoulder or the locomotor system. The net torques/forces are calculated by using conventional inverse dynamics. A solution of the load sharing problem is determined by minimization of the weighted sum of squared muscle forces. The load sharing problem is solved with a dynamic constraint reflecting physiological muscle properties. This constraint takes into account the nonlinear dynamics of the contractile element (CE) and the series elastic element (SE), active state dynamics and neural excitation dynamics. This physiological constraint is determined with an inverse muscle model. With this model, muscular states and neural inputs are also estimated. The method of inverse dynamics requires position, velocity and acceleration signals as input. A method to prepare such signals from noisy measured data is presented.

Acceleration↗

PubMed1992

Time optimality in the control of human movements.

In a simulation study the control of maximally fast goal directed movements has been analyzed. For a simple linear model it is shown that the presence of a third input block reduces the movement duration. The time optimal size of the third block depends on the ratio of a neuromuscular time constant (first-order lag) and movement time. As a second step a non-linear muscle model was simulated. By an optimization of input parameters it was found that the time optimal input, as expected, switches between maximal agonist and maximal antagonist activation. As for the linear model, a third phase was required for an optimal movement. It was found that the third phase serves to compensate the slowly decaying antagonist force. Also an input similar to experimentally found activation patterns was simulated. This input contains a silent period between the first two bursts and the second and the third burst have submaximal amplitudes. This input led to a near time optimal movement with a duration 9% larger than the minimal duration but with largely reduced muscle forces. This suggests that a criterion is minimized which also takes into account the effort spent. Including gravity in the model indicates optimality of a silent period between the third phase and a final agonist activity to resist gravity. When assuming different dynamics for agonist and antagonist, the optimal switch times for agonist and antagonist no longer coincide, also after the three block pattern some extra activity is required to obtain a cancellation of the slowly decaying force in agonist and antagonist.

Biological Clocks↗