Control of reaching movements by muscle synergy combinations

Controlling the movement of the arm to achieve a goal, such as reaching for an object, is challenging because it requires coordinating many muscles acting on many joints. The central nervous system (CNS) might simplify the control of reaching by directly mapping initial states and goals into muscle activations through the combination of muscle synergies, coordinated recruitment of groups of muscles with specific activation profiles. Here we review recent results from the analysis of reaching muscle patterns supporting such a control strategy. Muscle patterns for point-to-point movements can be reconstructed by the combination of a small number of time-varying muscle synergies, modulated in amplitude and timing according to movement directions and speeds. Moreover, the modulation and superposition of the synergies identified from point-to-point movements captures the muscle patterns underlying multi-phasic movements, such as reaching through a via-point or to a target whose location changes after movement initiation. Thus, the sequencing of time-varying muscle synergies might implement an intermittent controller which would allow the construction of complex movements from simple building blocks

Gaze Behavior in One-Handed Catching and Its Relation with Interceptive Performance: What the Eyes Can't Tell

In ball sports, it is usually acknowledged that expert athletes track the ball more accurately than novices. However, there is also evidence that keeping the eyes on the ball is not always necessary for interception. Here we aimed at gaining new insights on the extent to which ocular pursuit performance is related to catching performance. To this end, we analyzed eye and head movements of nine subjects catching a ball projected by an actuated launching apparatus. Four different ball flight durations and two different ball arrival heights were tested and the quality of ocular pursuit was characterized by means of several timing and accuracy parameters. Catching performance differed across subjects and depended on ball flight characteristics. All subjects showed a similar sequence of eye movement events and a similar modulation of the timing of these events in relation to the characteristics of the ball trajectory. On a trial-by-trial basis there was a significant relationship only between pursuit duration and catching performance, confirming that keeping the eyes on the ball longer increases catching success probability. Ocular pursuit parameters values and their dependence on flight conditions as well as the eye and head contributions to gaze shift differed across subjects. However, the observed average individual ocular behavior and the eye-head coordination patterns were not directly related to the individual catching performance. These results suggest that several oculomotor strategies may be used to gather information on ball motion, and that factors unrelated to eye movements may underlie the observed differences in interceptive performance

Virtual Stiffness: A Novel Biomechanical Approach to Estimate Limb Stiffness of a Multi-Muscle and Multi-Joint System

In recent years, different groups have developed algorithms to control the stiffness of a robotic device through the electromyographic activity collected from a human operator. However, the approaches proposed so far require an initial calibration, have a complex subject-specific muscle model, or consider the activity of only a few pairs of antagonist muscles. This study described and tested an approach based on a biomechanical model to estimate the limb stiffness of a multi-joint, multi-muscle system from muscle activations. The “virtual stiffness” method approximates the generated stiffness as the stiffness due to the component of the muscle-activation vector that does not generate any endpoint force. Such a component is calculated by projecting the vector of muscle activations, estimated from the electromyographic signals, onto the null space of the linear mapping of muscle activations onto the endpoint force. The proposed method was tested by using an upper-limb model made of two joints and six Hill-type muscles and data collected during an isometric force-generation task performed with the upper limb. The null-space projection of the muscle-activation vector approximated the major axis of the stiffness ellipse or ellipsoid. The model provides a good approximation of the voluntary stiffening performed by participants that could be directly implemented in wearable myoelectric controlled devices that estimate, in real-time, the endpoint forces, or endpoint movement, from the mapping between muscle activation and force, without any additional calibrations

Protein kinase a distribution in meningioma

Deregulation of intracellular signal transduction pathways is a hallmark of cancer cells, clearly differentiating them from healthy cells. Differential intracellular distribution of the cAMP-dependent protein kinases (PKA) was previously detected in cell cultures and in vivo in glioblastoma and medulloblastoma. Our goal is to extend this observation to meningioma, to explore possible differences among tumors of different origins and prospective outcomes. The distribution of regulatory and catalytic subunits of PKA has been examined in tissue specimens obtained during surgery from meningioma patients. PKA RI subunit appeared more evenly distributed throughout the cytoplasm, but it was clearly detectable only in some tumors. RII was present in discrete spots, presumably at high local concentration; these aggregates could also be visualized under equilibrium binding conditions with fluorescent 8-substituted cAMP analogues, at variance with normal brain tissue and other brain tumors. The PKA catalytic subunit showed exactly overlapping pattern to RII and in fixed sections could be visualized by fluorescent cAMP analogues. Gene expression analysis showed that the PKA catalytic subunit revealed a significant correlation pattern with genes involved in meningioma. Hence, meningioma patients show a distinctive distribution pattern of PKA regulatory and catalytic subunits, different from glioblastoma, medulloblastoma, and healthy brain tissue. These observations raise the possibility of exploiting the PKA intracellular pathway as a diagnostic tool and possible therapeutic interventions

Smooth Coverage Path Planning for UAVs with Model Predictive Control Trajectory Tracking

Within the Industry 4.0 ecosystem, Inspection Robotics is one fundamental technology to speed up monitoring processes and obtain good accuracy and performance of the inspections while avoiding possible safety issues for human personnel. This manuscript investigates the robotics inspection of areas and surfaces employing Unmanned Aerial Vehicles (UAVs). The contribution starts by addressing the problem of coverage path planning and proposes a smoothing approach intended to reduce both flight time and memory consumption to store the target navigation path. Evaluation tests are conducted on a quadrotor equipped with a Model Predictive Control (MPC) policy and a Simultaneous Localization and Mapping (SLAM) algorithm to localize the UAV in the environment

Contraction level, but not force direction or wrist position, affects the spatial distribution of motor unit recruitment in the biceps brachii muscle

Purpose: Different motor units (MUs) in the biceps brachii (BB) muscle have been shown to be preferentially recruited during either elbow flexion or supination. Whether these different units reside within different regions is an open issue. In this study, we tested wheter MUs recruited during submaximal isometric tasks of elbow flexion and supination for two contraction levels and with the wrist fixed at two different angles are spatially localized in different BB portions. Methods: The MUs’ firing instants were extracted by decomposing high-density surface electromyograms (EMG), detected from the BB muscle of 12 subjects with a grid of electrodes (4 rows along the BB longitudinal axis, 16 columns medio-laterally). The firing instants were then used to trigger and average single-differential EMGs. The average rectified value was computed separately for each signal and the maximal value along each column in the grid was retained. The center of mass, defined as the weighted mean of the maximal, average rectified value across columns, was then consdiered to assess the medio-lateral changes in the MU surface representation between conditions. Results: Contraction level, but neither wrist position nor force direction (flexion vs. supination), affected the spatial distribution of BB MUs. In particular, higher forces were associated with the recruitment of BB MUs whose action potentials were represented more medially. Conclusion: Although the action potentials of BB MUs were represented locally across the muscle medio-lateral region, dicrimination between elbow flexion or supination seems unlikely from the surface representation of MUs action potentials

Multimodal Grasp Planner for Hybrid Grippers in Cluttered Scenes

Grasping a variety of objects is still an open problem in robotics, especially for cluttered scenarios. Multimodal grasping has been recognized as a promising strategy to improve the manipulation capabilities of a robotic system. This work presents a novel grasp planning algorithm for hybrid grippers that allows for multiple grasping modalities. In particular, the planner manages two-finger grasps, single or double suction grasps, and magnetic grasps. Grasps for different modalities are geometrically computed based on the cuboid and the material properties of the objects in the clutter. The presented framework is modular and can leverage any 6D pose estimation or material segmentation network as far as they satisfy the required interface. Furthermore, the planner can be applied to any (hybrid) gripper, provided the gripper clearance, finger width, and suction diameter. The approach is fast and has a low computational burden, as it uses geometric computations for grasp synthesis and selection. The performance of the system has been assessed with an experimental campaign in three manipulation scenarios of increasing difficulty using the objects of the YCB dataset and the DLR hybrid-compliant gripper

Exploiting Intrinsic Kinematic Null Space for Supernumerary Robotic Limbs Control

Supernumerary robotic limbs (SRLs) gained increasing interest in the last years for their applicability as healthcare and assistive technologies. These devices can either support or augment human sensorimotor capabilities, allowing users to complete tasks that are more complex than those feasible for their natural limbs. However, for a successful coordination between natural and artificial limbs, intuitiveness of interaction and perception of autonomy are key enabling features, especially for people suffering from motor disorders and impairments. The development of suitable human-robot interfaces is thus fundamental to foster the adoption of SRLs.With this work, we describe how to control an extra degree of freedom by taking advantage of what we defined the Intrinsic Kinematic Null Space, i.e. the redundancy of the human kinematic chain involved in the ongoing task. Obtained results demonstrated that the proposed control strategy is effective for performing complex tasks with a supernumerary robotic finger, and that practice improves users' control ability