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by Keyword: Motor control


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Castillo-Escario, Y., Rodríguez-Cañón, M., García-Alías, G., Jané, R., (2020). Identifying muscle synergies from reaching and grasping movements in rats IEEE Access 8, 62517-62530

Reaching and grasping (R&G) is a skilled voluntary movement which is critical for animals. In this work, we aim to identify muscle synergy patterns from R&G movements in rats and show how these patterns can be used to characterize such movements and investigate their consistency and repeatability. For that purpose, we analyzed the electromyographic (EMG) activity of five forelimb muscles recorded while the animals were engaged in R&G tasks. Our dataset included 200 R&G attempts from three different rats. Non-negative matrix factorization was used to decompose EMG signals and extract muscle synergies. We compared all pairs of attempts and created cross-validated models to study intra- and inter-subject variability. We found that three synergies were enough to accurately reconstruct the EMG envelopes. These muscle synergies and their corresponding activation coefficients were very similar for all the attempts in the database, providing a general pattern to describe the movement. Results suggested that the movement strategy adopted by an individual in its different attempts was highly repetitive, but also resembled the strategies adopted by the other animals. Inter-subject variability was not much higher than intra-subject variability. This study is a proof-of-concept, but the proposed approaches can help to establish whether there is a stereotyped pattern of neuromuscular activity in R&G movement in healthy rats, and the changes that occur in animal models of acute neurological injuries. Research on muscle synergies could elucidate motor control mechanisms, and lead to quantitative tools for evaluating upper limb motor impairment after an injury.

Keywords: Electromyography, Motor control, Muscle synergies, Reaching and grasping, Upper limb


Maffei, Giovanni, Herreros, Ivan, Sanchez-Fibla, Marti, Friston, Karl J., Verschure, Paul F. M. J., (2017). The perceptual shaping of anticipatory actions Proceedings of the Royal Society B , 284, (1869)

Humans display anticipatory motor responses to minimize the adverse effects of predictable perturbations. A widely accepted explanation for this behavior relies on the notion of an inverse model that, learning from motor errors, anticipates corrective responses. Here, we propose and validate the alternative hypothesis that anticipatory control can be realized through a cascade of purely sensory predictions that drive the motor system, reflecting the causal sequence of the perceptual events preceding the error. We compare both hypotheses in a simulated anticipatory postural adjustment task. We observe that adaptation in the sensory domain, but not in the motor one, supports the robust and generalizable anticipatory control characteristic of biological systems. Our proposal unites the neurobiology of the cerebellum with the theory of active inference and provides a concrete implementation of its core tenets with great relevance both to our understanding of biological control systems and, possibly, to their emulation in complex artefacts.

Keywords: Active inference, Cerebellum, Computational model, Motor control, Perceptual learning


Hernansanz, A., Zerbato, D., Gasperotti, L., Scandola, M., Casals, A., Fiorini, P., (2012). Assessment of virtual fixtures for the development of basic skills in robotic surgery International Journal of Computer Assisted Radiology and Surgery CARS 2012 Computer Assisted Radiology and Surgery , Springer (Pisa, Italy) 7 (Supplement 1) - Surgical Modelling, Simulation and Education, S186-S188

Teleoperation, by adequately adapting computer interfaces, can benefit from the knowledge on human factors and psychomotor models in order to improve the effectiveness and efficiency in the execution of a task. While scaling is one of the performances frequently used in teleoperation tasks that require high precision, such as surgery, this article presents a scaling method that considers the system dynamics as well. The proposed dynamic scaling factor depends on the apparent position and velocity of the robot and targets. Such scaling improves the performance of teleoperation interfaces, thereby reducing user's workload.

Keywords: Human-robot interaction, Throughput, Scaling functions, Motor control performance


Muñoz, L. M., Casals, A., (2012). Dynamic scaling interface for assisted teleoperation IEEE International Conference on Robotics and Automation (ICRA) , IEEE (Minnesota, USA) , 4288-4293

Teleoperation, by adequately adapting computer interfaces, can benefit from the knowledge on human factors and psychomotor models in order to improve the effectiveness and efficiency in the execution of a task. While scaling is one of the performances frequently used in teleoperation tasks that require high precision, such as surgery, this article presents a scaling method that considers the system dynamics as well. The proposed dynamic scaling factor depends on the apparent position and velocity of the robot and targets. Such scaling improves the performance of teleoperation interfaces, thereby reducing user's workload.

Keywords: Human-robot interaction, Motor control performance, Scaling functions, Throughput