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Biomedical subjects

V Sanguineti

Publications and source records attributed to V Sanguineti.

9 recordsLinked to original sources
PubMed1999

Computational implications of modeling grasping as a form of (multiple-parallel) reaching.

Although it is true that the specific research on grasping has been dominated in recent years by the canonical transport + grip model originally formulated by Jeannerod (1984), still one can find in the research on reaching a number of links and anticipations to the new view on grasping made explicit by the authors of the target article. This paper reviews some of the relevant concepts and outlines a modeling framework that aims at biological plausibility.

Biomechanical Phenomena↗
PubMed1998

Can non-linear muscle dynamics explain the smoothness of handwriting movements?

The paper addresses the issue of the role of non-linear muscle dynamics in determining the smoothness and invariance of handwriting trajectories. In particular, a specific neuromuscular control model is described that has recently been shown to explain the detailed time course of hand stiffness during arm reaching movements. In the paper the model is applied to more complex handwriting trajectories, with the purpose of verifying to which extent the load compensation capabilities of the periphery can subserve motor equivalence. Simulations show the power of the mechanism for movements of "normal" speed. For quicker movements periphery alone is not enough and a central load compensation action is clearly required.

Handwriting↗
PubMed1998

A dynamic biomechanical model for neural control of speech production.

A model of the midsagittal plane motion of the tongue, jaw, hyoid bone, and larynx is presented, based on the lambda version of equilibrium point hypothesis. The model includes muscle properties and realistic geometrical arrangement of muscles, modeled neural inputs and reflexes, and dynamics of soft tissue and bony structures. The focus is on the organization of control signals underlying vocal tract motions and on the dynamic behavior of articulators. A number of muscle synergies or "basic motions" of the system are identified. In particular, it is shown that systematic sources of variation in an x-ray data base of midsagittal vocal tract motions can be accounted for, at the muscle level, with six independent commands, each corresponding to a direction of articulator motion. There are two commands for the jaw (corresponding to sagittal plane jaw rotation and jaw protrusion), one command controlling larynx height, and three commands for the tongue (corresponding to forward and backward motion of the tongue body, arching and flattening of the tongue dorsum, and motion of the tongue tip). It is suggested that all movements of the system can be approximated as linear combinations of such basic motions. In other words, individual movements and sequences of movements can be accounted for by a simple additive control model. The dynamics of individual commands are also assessed. It is shown that the dynamic effects are not neglectable in speechlike movements because of the different dynamic behaviors of soft and bony structures.

Biomechanical Phenomena↗
PubMed1998

Are complex control signals required for human arm movement?

It has been proposed that the control signals underlying voluntary human arm movement have a "complex" nonmonotonic time-varying form, and a number of empirical findings have been offered in support of this idea. In this paper, we address three such findings using a model of two-joint arm motion based on the lambda version of the equilibrium-point hypothesis. The model includes six one- and two-joint muscles, reflexes, modeled control signals, muscle properties, and limb dynamics. First, we address the claim that "complex" equilibrium trajectories are required to account for nonmonotonic joint impedance patterns observed during multijoint movement. Using constant-rate shifts in the neurally specified equilibrium of the limb and constant cocontraction commands, we obtain patterns of predicted joint stiffness during simulated multijoint movements that match the nonmonotonic patterns reported empirically. We then use the algorithm proposed by Gomi and Kawato to compute a hypothetical equilibrium trajectory from simulated stiffness, viscosity, and limb kinematics. Like that reported by Gomi and Kawato, the resulting trajectory was nonmonotonic, first leading then lagging the position of the limb. Second, we address the claim that high levels of stiffness are required to generate rapid single-joint movements when simple equilibrium shifts are used. We compare empirical measurements of stiffness during rapid single-joint movements with the predicted stiffness of movements generated using constant-rate equilibrium shifts and constant cocontraction commands. Single-joint movements are simulated at a number of speeds, and the procedure used by Bennett to estimate stiffness is followed. We show that when the magnitude of the cocontraction command is scaled in proportion to movement speed, simulated joint stiffness varies with movement speed in a manner comparable with that reported by Bennett. Third, we address the related claim that nonmonotonic equilibrium shifts are required to generate rapid single-joint movements. Using constant-rate equilibrium shifts and constant cocontraction commands, rapid single-joint movements are simulated in the presence of external torques. We use the procedure reported by Latash and Gottlieb to compute hypothetical equilibrium trajectories from simulated torque and angle measurements during movement. As in Latash and Gottlieb, a nonmonotonic function is obtained even though the control signals used in the simulations are constant-rate changes in the equilibrium position of the limb. Differences between the "simple" equilibrium trajectory proposed in the present paper and those that are derived from the procedures used by Gomi and Kawato and Latash and Gottlieb arise from their use of simplified models of force generation.

Arm↗
PubMed1997

A control model of human tongue movements in speech.

Tongue movements during speech production have been investigated by means of a simple yet realistic biomechanical model, based on a finite elements modeling of soft tissues, in the framework of the equilibrium point hypothesis (lambda-model) of motor control. In particular, the model has been applied to the estimation of the "central" control commands issued to the muscles, for a data set of mid-sagittal digitized tracings of vocal tract shape, recorded by means of low-intensity X-ray cineradiographies during speech. In spite of the highly non-linear mapping between the shape of the oral cavity and its acoustic consequences, the organization of control commands preserves the peculiar spatial organization of vowel phonemes in acoustic space. A factor analysis of control commands, which have been decomposed into independent or "orthogonal" muscle groups, has shown that, in spite of the great mobility of the tongue and the highly complex arrangement of tongue muscles, its movements can be explained in terms of the activation of a small number of independent muscle groups, each corresponding to an elementary or "primitive" movement. These results are consistent with the hypothesis that the tongue is controlled by a small number of independent "articulators", for which a precise biomechanical substrate is provided. The influence of the effect of jaw and hyoid movements on tongue equilibrium has also been evaluated, suggesting that the bony structures cannot be considered as a moving frame of reference, but, indeed, there may be a substantial interaction between them and the tongue, that may only be accounted for by a "global" model. The reported results also define a simple control model for the tongue and, in analogy with similar modelling studies, they suggest that, because of the peculiar geometrical arrangement of tongue muscles, the central nervous system (CNS) may not need a detailed representation of tongue mechanics but rather may make use of a relatively small number of muscle synergies, that are invariant over the whole space of tongue configurations.

Humans↗
PubMed1993

Neurocomputing aspects in modelling cursive handwriting.

This paper describes a distributed modelling framework of the motor control processes that underly the planning of cursive handwriting. The model, that focuses on the hypothetical functions of the posterior parietal cortex combines a paradigm of self-organization (for building robust and coherent maps of the different motor spaces) with relaxation dynamics (for run-time incorporation of task constraints) and non-linear integration (for a smooth integration between via-points).

Cerebral Cortex↗