Artificial cognition vs. artificial intelligence for next-generation autonomous robotic agents

The trend in industrial/service robotics is to develop robots that can cooperate with people, interacting with them in an autonomous, safe and purposive way. These are the fundamental elements characterizing the fourth and the fifth industrial revolutions (4IR, 5IR): the crucial innovation is the adoption of intelligent technologies that can allow the development of cyber-physical systems, similar if not superior to humans. The common wisdom is that intelligence might be provided by AI (Artificial Intelligence), a claim that is supported more by media coverage and commercial interests than by solid scientific evidence. AI is currently conceived in a quite broad sense, encompassing LLMs and a lot of other things, without any unifying principle, but self-motivating for the success in various areas. The current view of AI robotics mostly follows a purely disembodied approach that is consistent with the old-fashioned, Cartesian mind-body dualism, reflected in the software-hardware distinction inherent to the von Neumann computing architecture. The working hypothesis of this position paper is that the road to the next generation of autonomous robotic agents with cognitive capabilities requires a fully brain-inspired, embodied cognitive approach that avoids the trap of mind-body dualism and aims at the full integration of Bodyware and Cogniware. We name this approach Artificial Cognition (ACo) and ground it in Cognitive Neuroscience. It is specifically focused on proactive knowledge acquisition based on bidirectional human-robot interaction: the practical advantage is to enhance generalization and explainability. Moreover, we believe that a brain-inspired network of interactions is necessary for allowing humans to cooperate with artificial cognitive agents, building a growing level of personal trust and reciprocal accountability: this is clearly missing, although actively sought, in current AI. The ACo approach is a work in progress that can take advantage of a number of research threads, some of them antecedent the early attempts to define AI concepts and methods. In the rest of the paper we will consider some of the building blocks that need to be re-visited in a unitary framework: the principles of developmental robotics, the methods of action representation with prospection capabilities, and the crucial role of social interaction.

Discrete cortical control during quiet stance revealed by desynchronization and rebound of beta oscillations

Postural sway during quiet stance often exhibits a repetition of micro-fall and the subsequent micro-recovery. The classical view -that the quiet bipedal stance is stabilized by the ankle joint stiffness- has been challenged by paradoxical non-spring-like behaviors of calf muscles: gastrocnemius muscles are shortened and then lengthened, respectively, during the micro-fall and the micro-recovery. Here, we examined EEG based brain activity during quiet stance, and identified desynchronization and synchronization of beta oscillations that were associated, respectively, with the micro-fall and the micro-recovery. Based on a widely accepted scenario for beta-band desynchronization during movement and post-movement rebound in the control of discrete voluntary movement, our results reveal that the beta rebound can be considered as a manifestation of stop command to punctuate the motor control for every fall-recovery cycle. Namely, cortical interventions to the automatic postural control are discrete, rather than continuous modulations. The finding is highly compatible with the intermittent control model, rather than the stiffness control model.

μ-band desynchronization in the contralateral central and central-parietal areas predicts proprioceptive acuity

Introduction

Position sense, which belongs to the sensory stream called proprioception, is pivotal for proper movement execution. Its comprehensive understanding is needed to fill existing knowledge gaps in human physiology, motor control, neurorehabilitation, and prosthetics. Although numerous studies have focused on different aspects of proprioception in humans, what has not been fully investigated so far are the neural correlates of proprioceptive acuity at the joints.

Methods

Here, we implemented a robot-based position sense test to elucidate the correlation between patterns of neural activity and the degree of accuracy and precision exhibited by the subjects. Eighteen healthy participants performed the test, and their electroencephalographic (EEG) activity was analyzed in its μ band (8–12 Hz), as the frequency band related to voluntary movement and somatosensory stimulation.

Results

We observed a significant positive correlation between the matching error, representing proprioceptive acuity, and the strength of the activation in contralateral hand motor and sensorimotor areas (left central and central-parietal areas). In absence of visual feedback, these same regions of interest (ROIs) presented a higher activation level compared to the association and visual areas. Remarkably, central and central-parietal activation was still observed when visual feedback was added, although a consistent activation in association and visual areas came up.

Conclusion

Summing up, this study supports the existence of a specific link between the magnitude of activation of motor and sensorimotor areas related to upper limb proprioceptive processing and the proprioceptive acuity at the joints.

The Quest for Cognition in Purposive Action: From Cybernetics to Quantum Computing

Norbert Wiener and Nikolai Bernstein set the stage for a worldwide multidisciplinary attempt to understand how purposive action is integrated with cognition in a circular, bidirectional manner, both in life sciences and engineering. Such a 'workshop' is still open and far away from a satisfactory level of understanding, despite the current hype surrounding Artificial Intelligence (AI). The problem is that Cognition is frequently confused with Intelligence, overlooking a crucial distinction: the type of cognition that is required of a cognitive agent to meet the challenge of adaptive behavior in a changing environment is Embodied Cognition, which is antithetical to the disembodied and dualistic nature of the current wave of AI. This essay is the perspective formulation of a cybernetic framework for the representation of actions that, following Bernstein, is focused on what has long been considered the fundamental issue underlying action and motor control, namely the degrees of freedom problem. In particular, the paper reviews a solution to this problem based on a model of ideomotor/muscle-less synergy formation, namely the Passive Motion Paradigm (PMP). Moreover, it is shown how this modeling approach can be reformulated in a distributed manner based on a self-organizing neural paradigm consisting of multiple topology-representing networks with attractor dynamics. The computational implication of such an approach is also briefly analyzed looking at possible alternatives of the von Neuman paradigm, namely neuromorphic and quantum computing, aiming in perspective at a hybrid computational framework for integrating digital information, analog information, and quantum information. It is also suggested that such a framework is crucial not only for the neurobiological modeling of motor cognition but also for the design of the cognitive architecture of autonomous robots of industry 4.0 that are supposed to interact and communicate naturally with human partners.

Integrating ankle and hip strategies for the stabilization of upright standing: An intermittent control model

Even in unperturbed upright standing of healthy young adults, body sway involves concurrent oscillations of ankle and hip joints, thus suggesting to using biomechanical models with at least two degrees of freedom, namely, a double inverted pendulum (DIP) framework. However, in a previous study, it was demonstrated that the observed coordinated ankle-hip patterns do not necessarily require the independent active control of the two joints but can be explained by a simpler hybrid control system, with a single active component (intermittent, delayed sensory feedback of the ongoing sway) applied to the ankle joint and a passive component (stiffness control) applied to the hip joint. In particular, the proposed active component was based on the internal representation of a virtual inverted pendulum (VIP) that links the ankle to the current position of the global center of mass (CoM). This hybrid control system, which can also be described as an ankle strategy, is consistent with the known kinematics of the DIP and, in particular, with the anti-phase correlation of the acceleration profiles of the two joints. The purpose of this study is to extend the hybrid control model in order to apply to both the ankle and hip strategy, clarifying as well the rationale of mixed strategies. The extension consists of applying the hybrid control scheme to both joints: a passive stiffness component and an active intermittent component, based on the same feedback signals derived from the common VIP but with independent parameter gains for the two joints. Thus, the hip gains are null in the pure ankle strategy, the ankle gains are null in the pure hip strategy, and both ankle and hip gains are specifically tuned in mixed strategies. The simulation of such an extended model shows that it can reproduce both strategies; moreover, the pure ankle strategy is more robust than the hip strategy, because the range of variation (RoV) of the intermittent control gains is larger in the former case than in the latter, and the pure ankle strategy is also more energy efficient. Generally, the simulations suggest that there is no advantage to employ mixed strategies, except in borderline situations in which the control gains are just outside the RoV that provides stable control for either pure strategy: in this case, a stable mixed strategy can emerge from the combination of two marginally unstable pure strategies.

A Dynamic Submaximal Fatigue Protocol Alters Wrist Biomechanical Properties and Proprioception

Fatigue is a temporary condition that arises as a result of intense and/or prolonged use of muscles and can affect skilled human performance. Therefore, the quantitative analysis of these effects is a topic of crucial interest in both ergonomics and clinical settings. This study introduced a novel protocol, based on robotic techniques, to quantitatively assess the effects of fatigue on the human wrist joint. A wrist manipulandum was used for two concurrent purposes: (1) implementing the fatigue task and (2) assessing the functional changes both before and at four time points after the end of the fatigue task. Fourteen participants completed the experimental protocol, which included the fatigue task and assessment sessions over 2 days. Specifically, the assessments performed are related to the following indicators: (1) isometric forces, (2) biomechanical properties of the wrist, (3) position sense, and (4) stretch reflexes of the muscles involved. The proposed fatigue task was a short-term, submaximal and dynamic wrist flexion/extension task designed with a torque opposing wrist flexion. A novel task termination criterion was employed and based on a percentage decrease in the mean frequency of muscles measured using surface electromyography. The muscle fatigue analysis demonstrated a change in mean frequency for both the wrist flexors and extensors, however, only the isometric flexion force decreased 4 min after the end of the task. At the same time point, wrist position sense was significantly improved and stiffness was the lowest. Viscosity presented different behaviors depending on the direction evaluated. At the end of the experiment (about 12 min after the end of the fatigue task), wrist position sense recovered to pre-fatigue values, while biomechanical properties did not return to their pre-fatigue values. Due to the wide variety of fatigue tasks proposed in the literature, it has been difficult to define a complete framework that presents the dynamic of fatigue-related changes in different components associated with wrist function. This work enables us to discuss the possible causes and the mutual relationship of the changes detected after the same task.

A Vexing Question in Motor Control: The Degrees of Freedom Problem

The human “marionette” is extremely complex and multi-articulated: anatomical redundancy (in terms of Degrees of Freedom: DoFs), kinematic redundancy (movements can have different trajectories, velocities, and accelerations and yet achieve the same goal, according to the principle of Motor Equivalence), and neurophysiological redundancy (many more muscles than DoFs and multiple motor units for each muscle). Although it is quite obvious that such abundance is not noxious at all because, in contrast, it is instrumental for motor learning, allowing the nervous system to “explore” the space of feasible actions before settling on an elegant and possibly optimal solution, the crucial question then boils down to figure out how the nervous system “chooses/selects/recruits/modulates” task-dependent subsets of countless assemblies of DoFs as functional motor synergies. Despite this daunting conceptual riddle, human purposive behavior in daily life activities is a proof of concept that solutions can be found easily and quickly by the embodied brain of the human cognitive agent. The point of view suggested in this essay is to frame the question above in the old-fashioned but still seminal observation by Marr and Poggio that cognitive agents should be regarded as Generalized Information Processing Systems (GIPS) and should be investigated according to three nearly independent but complementary levels of analysis: 1) the computational level, 2) the algorithmic level, and 3) the implementation level. In this framework, we attempt to discriminate as well as aggregate the different hypotheses and solutions proposed so far: the optimal control hypothesis, the muscle synergy hypothesis, the equilibrium point hypothesis, or the uncontrolled manifold hypothesis, to mention the most popular ones. The proposed GIPS follows the strategy of factoring out shaping and timing by adopting a force-field based approach (the Passive Motion Paradigm) that is inspired by the Equilibrium Point Hypothesis, extended in such a way to represent covert as well overt actions. In particular, it is shown how this approach can explain spatio-temporal invariances and, at the same time, solve the Degrees of Freedom Problem.

Implementing a robust wrist dynamic fatigue task: repeatability and investigation of the features involved

In this study, we implemented a protocol for the robotic assessment of the effects of forearm muscle fatigue on wrist dynamics. The potential of robotic devices lies in the possibility to control and measure a wide variety of kinematic and physiological variables, both in repeated sessions over time and during real-time assessments. The implemented fatigue task is tailored to the robotically assessed single-subject maximal force and based on a real-time evaluation of muscle activity. The protocol resulted to be repeatable across sessions evaluated on the same subject and a preliminary step toward a better understanding of which features should be monitored to design a robust and strongly controlled dynamic fatiguing task.

Evaluating Viscoelastic Properties of the Wrist Joint During External Perturbations: Influence of Velocity, Grip, and Handedness

In this study, we designed a robot-based method to compute a mechanical impedance model that could extract the viscoelastic properties of the wrist joint. Thirteen subjects participated in the experiment, testing both dominant and nondominant hands. Specifically, the robotic device delivered position-controlled disturbances in the flexion-extension degree of freedom of the wrist. The external perturbations were characterized by small amplitudes and fast velocities, causing rotation at the wrist joint. The viscoelastic characteristics of the mechanical impedance of the joint were evaluated from the wrist kinematics and corresponding torques. Since the protocol used position inputs to determine changes in mean wrist torque, a detailed analysis of wrist joint dynamics could be made. The scientific question was whether and how these mechanical features changed with various grip demands and perturbation velocities. Nine experimental conditions were tested for each hand, given by the combination of three velocity perturbations (fast, medium, and slow) and three hand grip conditions [self-selected grip, medium and high grip force, as percentage of the maximum voluntary contraction (MVC)]. Throughout the experiments, electromyographic signals of the extensor carpi radialis (ECR) and the flexor carpi radialis (FCR) were recorded. The novelty of this work included a custom-made soft grip sensor, wrapped around the robotic handle, to accurately quantify the grip force exerted by the subjects during experimentation. Damping parameters were in the range of measurements from prior studies and consistent among the different experimental conditions. Stiffness was independent of both direction and velocity of perturbations and increased with increasing grip demand. Both damping and stiffness were not different between the dominant and nondominant hands. These results are crucial to improving our knowledge of the mechanical characteristics of the wrist, and how grip demands influence these properties. This study is the foundation for future work on how mechanical characteristics of the wrist are affected in pathological conditions.

Wrist Position Sense in Two Dimensions: Between-Hand Symmetry and Anisotropic Accuracy Across the Space

A deep investigation of proprioceptive processes is necessary to understand the relationship between sensory afferent inputs and motor outcomes. In this work, we investigate whether and how perception of wrist position is influenced by the direction along which the movement occurs. Most previous studies have tested Joint Position Sense (JPS) through 1 degree of freedom (DoF) wrist movements, such as flexion/extension (FE) or radial/ulnar deviation (RUD). However, the wrist joint has 3-DoF and many activities of daily living produce combined movements, requiring at least 2-DoF wrist coordination. For this reason, in this study, target positions involved movement directions that combined wrist flexion or extension with radial or ulnar deviation. The chosen task was a robot-aided Joint Position Matching (JPM), in which blindfolded participants actively reproduced a previously passively assumed target joint configuration. The JPM performance of 20 healthy participants was quantified through measures of accuracy and precision, in terms of both perceived target direction and distance along each direction of movement. Twelve different directions of movement were selected and both hands tested. The left and right hand led to comparable results, both target extents and directions were differently perceived according to the target direction on the FE/RUD space. Moreover, during 2-DoF combined movements, subjects' perception of directions was impaired when compared to 1-DoF target movements. In summary, our results showed that human perception of wrist position on the FE/RUD space is symmetric between hands but not isotropic among movement directions.

Spontaneous movements in the newborns: a tool of quantitative video analysis of preterm babies

BACKGROUND AND OBJECTIVES

The number of preterm babies is steadily growing world-wide and these neonates are at risk of neuro-motor-cognitive deficits. The observation of spontaneous movements in the first three months of age is known to predict such risk. However, the analysis by specifically trained physiotherapists is not suited for the clinical routine, motivating the development of simple computerized video analysis systems, integrated with a well-structured Biobank to make available for preterm babies a growing service with diagnostic, prognostic and epidemiological purposes.

METHODS

MIMAS (Markerless Infant Movement Analysis System) is a simple, low-cost system of video analysis of spontaneous movements of newborns in their natural environment, based on a single standard RGB camera, without markers attached to the body. The original videos are transformed into binarized sequences highlighting the silhouette of the baby, in order to minimize the illumination effects and increase the robustness of the analysis; such sequences are then coded by a large set of parameters (39) related to the spatial and spectral changes of the silhouette. The parameter vectors of each baby were stored in the Biobank together with related clinical information.

RESULTS

The preliminary test of the system was carried out at the Gaslini Pediatric Hospital in Genoa, where 46 preterm (PT) and 21 full-term (FT) babies (as controls) were recorded at birth (T0) and 8-12 weeks thereafter (T1). A simple statistical analysis of the data showed that the coded parameters are sensitive to the degree of maturation of the newborns (comparing T0 with T1, for both PT and FT babies), and to the conditions at birth (PT vs. FT at T0), whereas this difference tends to vanish at T1. Moreover, the coding method seems also able to detect the few 'abnormal' preterm babies in the PT populations that were analyzed as specific case studies.

CONCLUSIONS

Preliminary results motivate the adoption of this tool in clinical practice allowing for a systematic accumulation of cases in the Biobank, thus for improving the accuracy of data analysis performed by MIMAS and ultimately allowing the adoption of data mining techniques.

Postural instability via a loss of intermittent control in elderly and patients with Parkinson's disease: A model-based and data-driven approach

Postural instability is one of the major symptoms of Parkinson's disease. Here, we assimilated a model of intermittent delay feedback control during quiet standing into postural sway data from healthy young and elderly individuals as well as patients with Parkinson's disease to elucidate the possible mechanisms of instability. Specifically, we estimated the joint probability distribution of a set of parameters in the model using the Bayesian parameter inference such that the model with the inferred parameters can best-fit sway data for each individual. It was expected that the parameter values for three populations would distribute differently in the parameter space depending on their balance capability. Because the intermittent control model is parameterized by a parameter associated with the degree of intermittency in the control, it can represent not only the intermittent model but also the traditional continuous control model with no intermittency. We showed that the inferred parameter values for the three groups of individuals are classified into two major groups in the parameter space: one represents the intermittent control mostly for healthy people and patients with mild postural symptoms and the other the continuous control mostly for some elderly and patients with severe postural symptoms. The results of this study may be interpreted by postulating that increased postural instability in most Parkinson's patients and some elderly persons might be characterized as a dynamical disease.

Centre of pressure versus centre of mass stabilization strategies: the tightrope balancing case

This study proposes a generalization of the ankle and hip postural strategies to be applied to the large class of skills that share the same basic challenge of defeating the destabilizing effect of gravity on the basis of the same neuromotor control organization, adapted and specialized to a variable number of degrees of freedom, different body parts, different muscles and different sensory feedback channels. In all the cases, we can identify two crucial elements (the CoP, centre of pressure and the CoM, centre of mass) and the central point of the paper is that most balancing skills can be framed in the CoP-CoM interplay and can be modelled as a combination/alternation of two basic stabilization strategies: the standard well-investigated COPS (or CoP stabilization strategy, the default option), where the CoM is the controlled variable and the CoP is the control variable, and the less investigated COMS (or CoM stabilization strategy), where CoP and CoM must exchange their role because the range of motion of the CoP is strongly constrained by environmental conditions. The paper focuses on the tightrope balancing skill where sway control in the sagittal plane is modelled in terms of the COPS while the more challenging sway in the coronal plane is modelled in terms of the COMS, with the support of a suitable balance pole. Both stabilization strategies are implemented as state-space intermittent, delayed feedback controllers, independent of each other. Extensive simulations support the degree of plausibility, generality and robustness of the proposed approach.

Vibrotactile Feedback for Improving Standing Balance

Maintaining balance standing upright is an active process that complements the stabilizing properties of muscle stiffness with feedback control driven by independent sensory channels: proprioceptive, visual, and vestibular. Considering that the contribution of these channels is additive, we investigated to what extent providing an additional channel, based on vibrotactile stimulation, may improve balance control. This study focused only on healthy young participants for evaluating the effects of different encoding methods and the importance of the informational content. We built a device that provides a vibrotactile feedback using two vibration motors placed on the anterior and posterior part of the body, at the L5 level. The vibration was synchronized with an accelerometric measurement encoding a combination of the position and acceleration of the body center of mass in the anterior-posterior direction. The goal was to investigate the efficacy of the information encoded by this feedback in modifying postural patterns, comparing, in particular, two different encoding methods: vibration always on and vibration with a dead zone, i.e., silent in a region around the natural stance posture. We also studied if after the exposure, the participants modified their normal oscillation patterns, i.e., if there were after effects. Finally, we investigated if these effects depended on the informational content of the feedback, introducing trials with vibration unrelated to the actual postural oscillations (sham feedback). Twenty-four participants were asked to stand still with their eyes closed, alternating trials with and without vibrotactile feedback: nine were tested with vibration always on and sham feedback, fifteen with dead zone feedback. The results show that synchronized vibrotactile feedback reduces significantly the sway amplitude while increasing the frequency in anterior-posterior and medial-lateral directions. The two encoding methods had no different effects of reducing the amount of postural sway during exposure to vibration, however only the dead-zone feedback led to short-term after effects. The presence of sham vibration, instead, increased the sway amplitude, highlighting the importance of the encoded information.

Phase resetting and intermittent control at the edge of stability in a simple biped model generates 1/f-like gait cycle variability

The 1/f-like gait cycle variability, characterized by temporal changes in stride-time intervals during steady-state human walking, is a well-documented gait characteristic. Such gait fractality is apparent in healthy young adults, but tends to disappear in the elderly and patients with neurological diseases. However, mechanisms that give rise to gait fractality have yet to be fully clarified. We aimed to provide novel insights into neuro-mechanical mechanisms of gait fractality, based on a numerical simulation model of biped walking. A previously developed heel-toe footed, seven-rigid-link biped model with human-like body parameters in the sagittal plane was implemented and expanded. It has been shown that the gait model, stabilized rigidly by means of impedance control with large values of proportional (P) and derivative (D) gains for a linear feedback controller, is destabilized only in a low-dimensional eigenspace, as P and D decrease below and even far below critical values. Such low-dimensional linear instability can be compensated by impulsive, phase-dependent actions of nonlinear controllers (phase resetting and intermittent controllers), leading to the flexible walking with joint impedance in the model being as small as that in humans. Here, we added white noise to the model to examine P-value-dependent stochastic dynamics of the model for small D-values. The simulation results demonstrated that introduction of the nonlinear controllers in the model determined the fractal features of gait for a wide range of the P-values, provided that the model operates near the edge of stability. In other words, neither the model stabilized only by pure impedance control even at the edge of linear stability, nor the model stabilized by specific nonlinear controllers, but with P-values far inside the stability region, could induce gait fractality. Although only limited types of controllers were examined, we suggest that the impulsive nonlinear controllers and criticality could be major mechanisms for the genesis of gait fractality.

Preliminary results on a dual balancing task

Balancing a stick on the fingertip while standing upright is a dual balancing task that requires the integration of two independent control systems. This is a completely novel experimental paradigm for attempting to understand how the brain deals with equilibrium in a general way. Preliminary results are presented and interpreted in the framework of an intermittent control policy extended to include a dual balancing task. In particular the study reveals that the upright standing (the less critical task) is modified in an adaptive way, in order to facilitate the more critical task, i.e. stick balancing.

Strategy preference in complex dynamical tasks: preliminary results

Many complex activities of daily living are characterized by instabilities. From a motor control point of view, there are two alternative stabilization mechanisms that require to integrate multi-joint coordination aspects: stiffness and positional stabilization strategies. The aim of this work is to understand how the central nervous system can switch between the two control paradigms, depending on the dynamic properties of the environment. This study reports the performance of healthy participants trained to master both strategies and, in particular, it shows how it is possible to quantitatively assess the individual strategy preference when specific environmental factors are introduced.

Tactile and proprioceptive dysfunction differentiates cervical dystonia with and without tremor

Objective

To determine whether different phenotypes of cervical dystonia (CD) express different types and levels of somatosensory impairment.

Methods

We assessed somatosensory function in patients with CD with and without tremor (n = 12 each) and in healthy age-matched controls (n = 22) by measuring tactile temporal discrimination thresholds of the nondystonic forearm and proprioceptive acuity in both the dystonic (head/neck) and nondystonic body segments (forearm/hand) using a joint position‐matching task. The head or the wrist was passively displaced along different axes to distinct joint positions by the experimenter or through a robotic exoskeleton. Participants actively reproduced the experienced joint position, and the absolute joint position‐matching error between the target and the reproduced positions served as a marker of proprioceptive acuity.

Results

Tactile temporal discrimination thresholds were significantly elevated in both CD subgroups compared to controls. Proprioceptive acuity of both the dystonic and nondystonic body segments was elevated in patients with CD and tremor with respect to both healthy controls and patients with CD without tremor. That is, tactile abnormalities were a shared dysfunction of both CD phenotypes, while proprioceptive dysfunction was observed in patients with CD with tremor.

Conclusions

Our findings suggest that the pathophysiology in CD can be characterized by 2 abnormal neural processes: a dysfunctional somatosensory gating mechanism involving the basal ganglia that triggers involuntary muscle spasms and abnormal processing of proprioceptive information within a defective corticocerebellar loop, likely affecting the feedback and feedforward control of head positioning. This dysfunction is expressed mainly in CD with tremor.

Interaction between position sense and force control in bimanual tasks

Background

Several daily living activities require people to coordinate the motion and the force produced by both arms, using their position sense and sense of effort. However, to date, the interaction in bimanual tasks has not been extensively investigated.

Methods

We focused on bimanual tasks where subjects were required:

(Experiment 1) to move their hands until reaching the same position – equal hand position implied identical arm configurations in joint space - under different loading conditions;

(Experiment 2) to produce the same amount of isometric force by pushing upward, with their hands placed in symmetric or asymmetric positions.

The arm motions and forces required for accomplishing these tasks were in the vertical direction. We enrolled a healthy population of 20 subjects for Experiment 1 and 25 for Experiment 2. Our primary outcome was the systematic difference between the two hands at the end of each trial in terms of position for Experiment 1 and force for Experiment 2. In both experiments using repeated measure ANOVA we evaluated the effect of each specific condition, namely loading in the former case and hand configuration in the latter.

Results

In the first experiment, the difference between the hands’ positions was greater when they were concurrently loaded with different weights. Conversely, in the second experiment, when subjects were asked to exert equal forces with both arms, the systematic difference between left and right force was not influenced by symmetric or asymmetric arm configurations, but by the position of the left hand, regardless of the right hand position. The performance was better when the left hand was in the higher position.

Conclusions

The experiments report the reciprocal interaction between position sense and sense of effort inbimanual tasks performed by healthy subjects. Apart for the intrinsic interest for a better understanding of basic sensorimotor processes, the results are also relevant to clinical applications, for defining functional evaluation and rehabilitative protocols for people with neurological diseases or conditions that impair the ability to sense and control concurrently position and force.

Neural correlates of proprioceptive upper limb position matching

Proprioceptive information allows humans to perform smooth coordinated movements by constantly updating one's mind with knowledge of the position of one's limbs in space. How this information is combined with other sensory modalities and centrally processed to form conscious perceptions of limb position remains relatively unknown. What has proven even more elusive is pinpointing the contribution of proprioception in cortical activity related to motion. This study addresses these gaps by examining electrocortical dynamics while participants performed an upper limb position matching task in two conditions, namely with proprioceptive feedback or with both visual and proprioceptive feedback. Specifically, we evaluated the reduction of the electroencephalographic power (desynchronization) in the μ frequency band (8-12 Hz), which is known to characterize the neural activation associated with motor control and behavior. We observed a stronger desynchronization in the left motor and somatosensory areas, contralateral to the moving limb while, parietal and occipital regions, identifying association and visual areas, respectively, exhibited a similar activation level in the two hemispheres. Pertaining to the influence of the two experimental conditions it affected only movement's offset, and precisely we found that when matching movements are performed relying only on proprioceptive information, a lower cortical activity is entailed. This effect was strongest in the visual and association areas, while there was a minor effect in the hand motor and somatosensory areas.

Movement related activity in the μ band of the human EEG during a robot-based proprioceptive task

Innovative research in the fields of prosthetic, neurorehabilitation, motor control and human physiology has been focusing on the study of proprioception, the sense through which we perceive the position and movement of our body, and great achievements have been obtained regarding its assessment and characterization. However, how proprioceptive signals are combined with other sensory modalities and processed by the central nervous system to form a conscious body image, is still unknown. Such a crucial question was addressed in this study, which involved 23 healthy subjects, by combining a robot-based proprioceptive test with a specific analysis of electroencephalographic activity (EEG) in the $\mu$ frequency band (8-12 Hz). We observed important activation in the motor area contralateral to the moving hand, and besides, a substantial bias in brain activation and proprioceptive acuity when visual feedback was provided in addition to the proprioceptive information during movement execution. In details, brain activation and proprioceptive acuity were both higher in case of movements performed with visual feedback. Remarkably, we also found a correlation between the level of activation in the brain motor area contralateral to the moving hand and the value of proprioceptive acuity.

Stabilization of a Cart Inverted Pendulum: Improving the Intermittent Feedback Strategy to Match the Limits of Human Performance

Stabilization of the CIP (Cart Inverted Pendulum) is an analogy to stick balancing on a finger and is an example of unstable tasks that humans face in everyday life. The difficulty of the task grows exponentially with the decrease of the length of the stick and a stick length of 32 cm is considered as a human limit even for well-trained subjects. Moreover, there is a cybernetic limit related to the delay of the multimodal sensory feedback (about 230 ms) that supports a feedback stabilization strategy. We previously demonstrated that an intermittent-feedback control paradigm, originally developed for modeling the stabilization of upright standing, can be applied with success also to the CIP system, but with values of the critical parameters far from the limiting ones (stick length 50 cm and feedback delay 100 ms). The intermittent control paradigm is based on the alternation of on-phases, driven by a proportional/derivative delayed feedback controller, and off-phases, where the feedback is switched off and the motion evolves according to the intrinsic dynamics of the CIP. In its standard formulation, the switching mechanism consists of a simple threshold operator: the feedback control is switched off if the current (delayed) state vector is closer to the stable than to the unstable manifold of the off-phase and is switched on in the opposite case. Although this simple formulation is effective for explaining upright standing as well as CIP balancing, it fails in the most challenging configuration of the CIP. In this work we propose a modification of the standard intermittent control policy that focuses on the explicit selection of switching times and is based on the phase reset of the estimated state vector at each switching time and on the simulation of an approximated internal model of CIP dynamics. We demonstrate, by simulating the modified intermittent control policy, that it can match the limits of human performance, while operating near the edge of instability.

Quiet standing: The Single Inverted Pendulum model is not so bad after all

In the study of balance and postural control the (Single) Inverted Pendulum model (SIP) has been taken for a long time as an acceptable paradigm, with the implicit assumption that only ankle rotations are relevant for describing and explaining sway movements. However, more recent kinematic analysis of quiet standing revealed that hip motion cannot be neglected at all and that ankle-hip oscillatory patterns are characterized by complex in-phase and anti-phase interactions, suggesting that the SIP model should be substituted by a DIP (Double Inverted Pendulum) model. It was also suggested that DIP control could be characterized as a kind of optimal bi-axial active controller whose goal is minimizing the acceleration of the global CoM (Center of Mass). We propose here an alternative where active feedback control is applied in an intermittent manner only to the ankle joint, whereas the hip joint is stabilized by a passive stiffness mechanism. The active control impulses are delivered to the ankle joint as a function of the delayed state vector (tilt rotation angle + tilt rotational speed) of a Virtual Inverted Pendulum (VIP), namely a pendulum that links the ankle to the CoM, embedded in the real DIP. Simulations of such DIP/VIP model, with the hybrid control mechanism, show that it can reproduce the in-phase/anti-phase interaction patterns of the two joints described by several experimental studies. Moreover, the simulations demonstrate that the DIP/VIP model can also reproduce the measured minimization of the CoM acceleration, as an indirect biomechanical consequence of the dynamic interaction between the active control of the ankle joint and the passive control of the hip joint. We suggest that although the SIP model is literally false, because it ignores the ankle-hip coordination, it is functionally correct and practically acceptable for experimental studies that focus on the postural oscillations of the CoM.

Muscle fatigue assessment during robot-mediated movements

BACKGROUND

Several neuromuscular disorders present muscle fatigue as a typical symptom. Therefore, a reliable method of fatigue assessment may be crucial for understanding how specific disease features evolve over time and for developing effective rehabilitation strategies. Unfortunately, despite its importance, a standardized, reliable and objective method for fatigue measurement is lacking in clinical practice and this work investigates a practical solution.

METHODS

40 healthy young adults performed a haptic reaching task, while holding a robotic manipulandum. Subjects were required to perform wrist flexion and extension movements in a resistive visco-elastic force field, as many times as possible, until the measured muscles (mainly flexor and extensor carpi radialis) exhibited signs of fatigue. In order to analyze the behavior and the characteristics of the two muscles, subjects were divided into two groups: in the first group, the resistive force was applied by the robot only during flexion movements, whereas, in the second group, the force was applied only during extension movements. Surface electromyographic signals (sEMG) of both flexor and extensor carpi radialis were acquired. A novel indicator to define the Onset of Fatigue (OF) was proposed and evaluated from the Mean Frequency of the sEMG signal. Furthermore, as measure of the subjects' effort throughout the task, the energy consumption was estimated.

RESULTS

From the beginning to the end of the task, as expected, all the subjects showed a decrement in Mean Frequency of the muscle involved in movements resisting the force. For the OF indicator, subjects were consistent in terms of timing of fatigue; moreover, extensor and flexor muscles presented similar OF times. The metabolic analysis showed a very low level of energy consumption and, from the behavioral point of view, the test was well tolerated by the subjects.

CONCLUSION

The robot-aided assessment test proposed in this study, proved to be an easy to administer, fast and reliable method for objectively measuring muscular fatigue in a healthy population. This work developed a framework for an evaluation that can be deployed in a clinical practice with patients presenting neuromuscular disorders. Considering the low metabolic demand, the requested effort would likely be well tolerated by clinical populations.

Social Cognition for Human-Robot Symbiosis-Challenges and Building Blocks

The next generation of robot companions or robot working partners will need to satisfy social requirements somehow similar to the famous laws of robotics envisaged by Isaac Asimov time ago (Asimov, 1942). The necessary technology has almost reached the required level, including sensors and actuators, but the cognitive organization is still in its infancy and is only partially supported by the current understanding of brain cognitive processes. The brain of symbiotic robots will certainly not be a “positronic” replica of the human brain: probably, the greatest part of it will be a set of interacting computational processes running in the cloud. In this article, we review the challenges that must be met in the design of a set of interacting computational processes as building blocks of a cognitive architecture that may give symbiotic capabilities to collaborative robots of the next decades: (1) an animated body-schema; (2) an imitation machinery; (3) a motor intentions machinery; (4) a set of physical interaction mechanisms; and (5) a shared memory system for incremental symbiotic development. We would like to stress that our approach is totally un-hierarchical: the five building blocks of the shared cognitive architecture are fully bi-directionally connected. For example, imitation and intentional processes require the “services” of the animated body schema which, on the other hand, can run its simulations if appropriately prompted by imitation and/or intention, with or without physical interaction. Successful experiences can leave a trace in the shared memory system and chunks of memory fragment may compete to participate to novel cooperative actions. And so on and so forth. At the heart of the system is lifelong training and learning but, different from the conventional learning paradigms in neural networks, where learning is somehow passively imposed by an external agent, in symbiotic robots there is an element of free choice of what is worth learning, driven by the interaction between the robot and the human partner. The proposed set of building blocks is certainly a rough approximation of what is needed by symbiotic robots but we believe it is a useful starting point for building a computational framework.

Dealing with instability in bimanual and collaborative tasks

In the context of unstable tasks, whenever the dynamics of the interaction are unknown, our ability to control an object depends on the predictability of the sensory feedback generated from the physical coupling at the interface with the object. In the case of physical human-human interaction, the haptic sensory feedback plays a primary role in the construction of a shared motor plan, being the channel for the mutual sharing of intentions. The present work addresses the issue of strategy selection in contexts in which instability is arising both from the environment, i.e. controlling a compliant object subject to nonlinear forces, and from the interaction with a partner, i.e. carrying out a bimanual balancing task in the presence of disturbing force-fields.

Codification mechanisms of wrist position sense

Proprioceptive signals from cutaneous, joint, tendon and muscle receptors create the basis for bodily perception and are known to be essential for motor control. However, which are the mechanisms underlying the proprioceptive signals and which are the variables that affect them is still a matter of debate. In particular, what is worth to investigate is, namely, the codification of proprioceptive information related to pointing movements of the wrist towards kinesthetic targets. In this work we asked 10 healthy adults to perform with their wrist a robot-aided proprioceptive matching task, in which the starting position of the matching movements was shifted forward or backward, in order to ascertain to which extent such shifts cause target over/under estimation and how important is movement's length on task performance. Results indicate that accuracy and precision of performance are highly correlated with the starting position and targets tended to be undershot when the active matching movements were longer. Moreover, further analysis revealed a consistent decrement of movement speed for shorter movements and conversely, faster displacement in case of backward of starting position.

A novel method for muscle fatigue assessment during robot-based tracking tasks

In this work we propose a novel method based on sEMG signals, easy and fast to perform, administered with a robotic device to maximize repeatability and objectivity. Muscle fatigue, which is frequently experienced by healthy subjects, can be a highly debilitating symptom in case of neuromuscular disorders. Its assessment provides crucial information on the progression of the disability itself, on patient's muscular function and on the efficacy of the eventual clinical intervention. Hence, a robust and objective protocol for fatigue assessment is fundamental in rehabilitation practice. Therefore, the aim of this work was twofold. Firstly, we aimed to test the proposed method and highlight its strengths and drawbacks for a future optimization and implementation in a clinical context. Secondly, we meant to identify which are the most sensitive and reliable measures of muscles' performance that can quickly and optimally predict subjects' behavior. sEMG signals were collected from right Extensor and Flexor Carpi Radialis of 9 healthy subjects during a flexion-extension robotic task consisting in a haptic tracking in a viscous field. Three indicators of fatigue (Mean Frequency, Dimitrov Index, Root Mean Square) were obtained and we proposed a novel sensitive parameter which determines the Onset of Fatigue.

Humanoid infers Archimedes' principle: understanding physical relations and object affordances through cumulative learning experiences

Emerging studies indicate that several species such as corvids, apes and children solve 'The Crow and the Pitcher' task (from Aesop's Fables) in diverse conditions. Hidden beneath this fascinating paradigm is a fundamental question: by cumulatively interacting with different objects, how can an agent abstract the underlying cause-effect relations to predict and creatively exploit potential affordances of novel objects in the context of sought goals? Re-enacting this Aesop's Fable task on a humanoid within an open-ended 'learning-prediction-abstraction' loop, we address this problem and (i) present a brain-guided neural framework that emulates rapid one-shot encoding of ongoing experiences into a long-term memory and (ii) propose four task-agnostic learning rules (elimination, growth, uncertainty and status quo) that correlate predictions from remembered past experiences with the unfolding present situation to gradually abstract the underlying causal relations. Driven by the proposed architecture, the ensuing robot behaviours illustrated causal learning and anticipation similar to natural agents. Results further demonstrate that by cumulatively interacting with few objects, the predictions of the robot in case of novel objects converge close to the physical law, i.e. the Archimedes principle: this being independent of both the objects explored during learning and the order of their cumulative exploration.

The Influence of External Forces on Wrist Proprioception

Proprioception combines information from cutaneous, joint, tendon, and muscle receptors for maintaining a reliable internal body image. However, it is still a matter of debate, in both neurophysiology and psychology, to what extent such body image is modified or distorted by a changing haptic environment. In particular, what is worth investigating is the contribution of external forces on our perception of body and joint configuration. The proprioceptive acuity of fifteen young participants was tested with a Joint Position Matching (JPM) task, performed with the dominant wrist under five different external forces, in order to understand to what extent they affect proprioceptive acuity. Results show that accuracy and precision in target matching do not change in a significant manner as a function of the loading condition, suggesting that the multi-sensory integration process is indeed capable of discriminating different sub-modalities of proprioception, namely the joint position sense and the sense of force. Furthermore, results indicate a preference for target undershooting when movements are performed in a viscous or high resistive force field, rather than passive or null fields in which subjects did not show any predominance for under/over estimation of their position.

Improving motor skill transfer during dyadic robot training through the modulation of the expert role

In daily life it is necessary to learn skills that can be applied in different tasks and different contexts. Usually these skills are acquired by observation or by direct physical training with another expert person. The critical point is to know which is the best possible way to achieve this knowledge acquisition. In this work we have proposed a collaborative environment where subjects with different levels of expertise have to interact through the use of a robotic platform. A motor skill learning algorithm has been designed in order to allow the less skilled subjects-naïves-to explore the virtual environment and to exploit the advantages of working with a skilled partner. Results show that the correct trade - off between exploration and exploitation, provided by the implemented algorithm applied during the dyadic training, allows a group of naive subjects to learn the task and generalize better the acquired skills respect to subjects trained without the proposed algorithm.

A fundamental study on how holding a helium-filled balloon affects stability in human standing

Various studies have been conducted in the field of the development/deterioration of standing and walking ability. In standing and walking control strategy, the relationship linking visual/somatosensory/vestibular-system information and physical movement is important. Researchers have previously sought to evaluate attitude control based on human sensory information. The authors have also reported that the body sway of a walking infant is mitigated when the subject holds a helium-filled balloon, with results suggesting that this approach can be applied to extend walking distance. This study was conducted to clarify how holding a balloon influences standing control strategy. A novel system was developed to quantitatively monitor and evaluate the standing state of subjects holding such a balloon. The results of the experiments conducted indicate that attitude control strategy changes in response to somatosensory information provided by the physical connection with the balloon.

The effects of age and amplitude on wrist proprioceptive acuity

This study examined wrist proprioception in a cross-sectional sample of 44 children aged between 8-to 14-years and a control group of 10 neurologically and physically healthy adults. Using a 3-degrees of freedom robotic device, participants performed an ipsilateral joint position matching task in which target amplitude (40% or 80% functional range of motion [fRoM]) and degrees-of-freedom (Flexion/Extension [FE], Radial/Ulnar deviation [RUD], Pronation/Supination [PS]) were manipulated. Results indicated that proprioceptive function became more accurate and consistent over the developmental spectrum, but that the ability to utilize proprioceptive feedback did not reach adult levels till the age of 10-11 years. Furthermore, proprioceptive acuity was influenced by target amplitude, such that movements were more accurate for the 80% fROM compared to the 40% fROM target for both the RUD and PS DoFs, independently of age. The present results provide critical information about the typical development of wrist proprioception that will enable clinicians to chart the course of development and dysfunction in neurological disorders in children, and help establish protocols for the robotic diagnosis and assessment of neurodevelopmental disorders.

The brain can mix different control strategies in a task-oriented and multi-referential manner: a simulation study

In everyday life the brain must adapt to variable situations that may require a mixture of approaches including anticipatory synergy formation, through an internal body schema, and different control strategies. Unstable tasks are particularly challenging because deteriorate the predictive power of internal models and further enhance the instability potential of delayed sensory feedback. We explore this issue by means of three simulation studies: A) The hybrid control of a double inverted pendulum model, B) The bimanual stabilization of a saddle-like instability, C) Whole-body focal-postural dynamics. The simulation results support the idea that the brain can mix different control strategies in a task-oriented and multi-referential manner.

Skill Learning and Skill Transfer Mediated by Cooperative Haptic Interaction

It is known that physical coupling between two subjects may be advantageous in joint tasks. However, little is known about how two people mutually exchange information to exploit the coupling. Therefore, we adopted a reversed, novel perspective to the standard one that focuses on the ability of physically coupled subjects to adapt to cooperative contexts that require negotiating a common plan: we investigated how training in pairs on a novel task affects the development of motor skills of each of the interacting partners. The task involved reaching movements in an unstable dynamic environment using a bilateral non-linear elastic tool that could be used bimanually or dyadically. The main result is that training with an expert leads to the greatest performance in the joint task. However, the performance in the individual test is strongly affected by the initial skill level of the partner. Moreover, practicing with a peer rather than an expert appears to be more advantageous for a naive; and motor skills can be transferred to a bimanual context, after training with an expert, only if the non-expert subject had prior experience of the dynamics of the novel task.

Transferring knowledge during dyadic interaction: The role of the expert in the learning process

Physical interaction between man and machines is increasing the interest of the research as well as the industrial community. It is known that physical coupling between active persons can be beneficial and increase the performance of the dyad compared to an individual. However, the factors that may result in performance benefits are still poorly understood. The aim of this work is to investigate how the different initial skill levels of the interacting partners influence the learning of a stabilization task. Twelve subjects, divided in two groups, trained in couples in a joint stabilization task. In the first group the couples were composed of two naive, while in the second a naive was trained together with an expert. Results show that training with an expert results in the greatest performance in the joint task. However, this benefit is not transferred to the individual when performing the same task bimanually.

Robot-aided developmental assessment of wrist proprioception in children

BACKGROUND

Several neurodevelopmental disorders and brain injuries in children have been associated with proprioceptive dysfunction that will negatively affect their movement. Unfortunately, there is lack of reliable and objective clinical examination protocols and our current knowledge of how proprioception evolves in typically developing children is still sparse.

METHODS

Using a robotic exoskeleton, we investigated proprioceptive acuity of the wrist in a group of 49 typically developing healthy children (8-15 years), and a group of 40 young adults. Without vision participants performed an ipsilateral wrist joint position matching task that required them to reproduce (match) a previously experienced target position. All three joint degrees-of-freedom of the wrist/hand complex were assessed. Accuracy and precision were evaluated as a measure of proprioceptive acuity. The cross-sectional data indicating the time course of development of acuity were then fitted by four models in order to determine which function best describes developmental changes in proprioception across age.

RESULTS

First, the robot-aided assessment proved to be an easy to administer method for objectively measuring proprioceptive acuity in both children and adult populations. Second, proprioceptive acuity continued to develop throughout middle childhood and early adolescence, improving by more than 50% with respect to the youngest group. Adult levels of performance were reached approximately by the age of 12 years. An inverse-root function best described the development of proprioceptive acuity across the age groups. Third, wrist/forearm proprioception is anisotropic across the three DoFs with the Abduction/Adduction exhibiting a higher level of acuity than those of Flexion/extension and Pronation/Supination. This anisotropy did not change across development.

CONCLUSIONS

Proprioceptive development for the wrist continues well into early adolescence. Our normative data obtained trough this novel robot-aided assessment method provide a basis against which proprioceptive function of pediatric population can be compared. This may aid the design of more effective sensorimotor intervention programs.

Wrist Proprioception: Amplitude or Position Coding?

This work examines physiological mechanisms underlying the position sense of the wrist, namely, the codification of proprioceptive information related to pointing movements of the wrist toward kinesthetic targets. Twenty-four healthy subjects participated to a robot-aided assessment of their wrist proprioceptive acuity to investigate if the sensorimotor transformation involved in matching targets located by proprioceptive receptors relies on amplitude or positional cues. A joint position matching test was performed in order to explore such dichotomy. In this test, the wrist of a blindfolded participant is passively moved by a robotic device to a preset target position and, after a removal movement from this position, the participant has to actively replicate and match it as accurately as possible. The test involved two separate conditions: in the first, the matching movements started from the same initial location; in the second one, the initial location was randomly assigned. Target matching accuracy, precision, and bias in the two conditions were then compared. Overall results showed a consistent higher performance in the former condition than in the latter, thus supporting the hypothesis that the joint position sense is based on vectorial or amplitude coding rather than positional.

Robot-Aided Mapping of Wrist Proprioceptive Acuity across a 3D Workspace

Proprioceptive signals from peripheral mechanoreceptors form the basis for bodily perception and are known to be essential for motor control. However we still have an incomplete understanding of how proprioception differs between joints, whether it differs among the various degrees-of-freedom (DoFs) within a particular joint, and how such differences affect motor control and learning. We here introduce a robot-aided method to objectively measure proprioceptive function: specifically, we systematically mapped wrist proprioceptive acuity across the three DoFs of the wrist/hand complex with the aim to characterize the wrist position sense. Thirty healthy young adults performed an ipsilateral active joint position matching task with their dominant wrist using a haptic robotic exoskeleton. Our results indicate that the active wrist position sense acuity is anisotropic across the joint, with the abduction/adduction DoF having the highest acuity (the error of acuity for flexion/extension is 4.64 ± 0.24°; abduction/adduction: 3.68 ± 0.32°; supination/pronation: 5.15 ± 0.37°) and they also revealed that proprioceptive acuity decreases for smaller joint displacements. We believe this knowledge is imperative in a clinical scenario when assessing proprioceptive deficits and for understanding how such sensory deficits relate to observable motor impairments.

Reinforcement learning for stabilizing an inverted pendulum naturally leads to intermittent feedback control as in human quiet standing

Intermittent feedback control for stabilizing human upright stance is a promising strategy, alternative to the standard time-continuous stiffness control. Here we show that such an intermittent controller can be established naturally through reinforcement learning. To this end, we used a single inverted pendulum model of the upright posture and a very simple reward function that gives a certain amount of punishments when the inverted pendulum falls or changes its position in the state space. We found that the acquired feedback controller exhibits hallmarks of the intermittent feedback control strategy, namely the action of the feedback controller is switched-off intermittently when the state of the pendulum is located near the stable manifold of the unstable saddle-type upright equilibrium of the inverted pendulum with no active control: this action provides an opportunity to exploit transiently converging dynamics toward the unstable upright position with no help of the active feedback control. We then speculate about a possible physiological mechanism of such reinforcement learning, and suggest that it may be related to the neural activity in the pedunculopontine tegmental nucleus (PPN) of the brainstem. This hypothesis is supported by recent evidence indicating that PPN might play critical roles for generation and regulation of postural tonus, reward prediction, as well as postural instability in patients with Parkinson's disease.

Testing proprioception in intrinsic and extrinsic coordinate systems: is there a difference?

An intact position sense is considered important for neuromotor recovery, but the available methods and protocols for its assessment are still limited. In the clinical practice it is generally tested trough a bimanual position matching test, that consists of replicating with one arm the angular positions of the other arm in space (intrinsic coordinates matching). However, the same test could be carried out by matching the hand location in space (extrinsic coordinates matching). Is there any difference between the procedures that may be relevant to the evaluation of position sense deficits? In this study we compared the performance of eight right handed subjects and two stroke survivors with left hemiparesis performing the test in the two conditions. A robotic manipulandum passively moved the left arm of the participants in twenty-four positions in the workspace. Subjects had to match the left arm position with their right arm either in intrinsic or extrinsic coordinates. The results show that all the subjects (impaired and controls) performed better when using the extrinsic paradigm.

An intermittent control model of flexible human gait using a stable manifold of saddle-type unstable limit cycle dynamics

Stability of human gait is the ability to maintain upright posture during walking against external perturbations. It is a complex process determined by a number of cross-related factors, including gait trajectory, joint impedance and neural control strategies. Here, we consider a control strategy that can achieve stable steady-state periodic gait while maintaining joint flexibility with the lowest possible joint impedance. To this end, we carried out a simulation study of a heel-toe footed biped model with hip, knee and ankle joints and a heavy head-arms-trunk element, working in the sagittal plane. For simplicity, the model assumes a periodic desired joint angle trajectory and joint torques generated by a set of feed-forward and proportional-derivative feedback controllers, whereby the joint impedance is parametrized by the feedback gains. We could show that a desired steady-state gait accompanied by the desired joint angle trajectory can be established as a stable limit cycle (LC) for the feedback controller with an appropriate set of large feedback gains. Moreover, as the feedback gains are decreased for lowering the joint stiffness, stability of the LC is lost only in a few dimensions, while leaving the remaining large number of dimensions quite stable: this means that the LC becomes saddle-type, with a low-dimensional unstable manifold and a high-dimensional stable manifold. Remarkably, the unstable manifold remains of low dimensionality even when the feedback gains are decreased far below the instability point. We then developed an intermittent neural feedback controller that is activated only for short periods of time at an optimal phase of each gait stride. We characterized the robustness of this design by showing that it can better stabilize the unstable LC with small feedback gains, leading to a flexible gait, and in particular we demonstrated that such an intermittent controller performs better if it drives the state point to the stable manifold, rather than directly to the LC. The proposed intermittent control strategy might have a high affinity for the inverted pendulum analogy of biped gait, providing a dynamic view of how the step-to-step transition from one pendular stance to the next can be achieved stably in a robust manner by a well-timed neural intervention that exploits the stable modes embedded in the unstable dynamics.

Motor control strategies in the bimanual stabilization of an unstable virtual tool

Previous works have shown that, when dealing with instabilities in a bimanual manipulation paradigm, humans modulate the stiffness of the arms according to feedforward or feedback mechanisms as a function of the dynamics of the task. The aim of this work is to complement these results getting insights on how the CNS controls the muscles to achieve the stabilization goal in the two aforementioned control strategies. Surface EMG was recorded from 13 muscles of each arm and trunk while three expert subjects performed bimanual balancing of a virtual underactuated tool immersed in an unstable force-field. Results suggest the existence of an intermittent muscle ensemble recruitment that follows two distinct activation patterns, namely synchronous co-contractions and independent activations. The observed EMG patterns were independent of the motor control strategy applied in the task. These findings therefore suggest the existence of separate control strategies for the tool stabilization and the control of hand movements at the muscular level during a bimanual postural task.

Non-actively controlled double-inverted-pendulum-like dynamics can minimize center of mass acceleration during human quiet standing

Multiple joint movements during human quiet standing exhibit characteristic inter-joint coordination, shortly referred to as reciprocal relationship, in which angular acceleration of the hip joint is linearly and negatively correlated with that of the ankle joint (antiphase coordination) and, moreover, acceleration of the center of mass (CoM) of the double-inverted-pendulum (DIP) model of the human body is close to zero constantly. A question considered in this study is whether the reciprocal relationship is established by active neural control of the posture, or rather it is a biomechanical consequence of non-actively controlled body dynamics. To answer this question, we consider a DIP model of quiet standing, and show that the reciprocal relationship always holds by Newton's second law applied to the DIP model with human anthropometric dimensions, regardless of passive and active joint torque patterns acting on the ankle and hip joints. We then show that characteristic frequencies included in experimental sway trajectories with the reciprocal relationship match with harmonics of the eigenfrequency of the stable antiphase eigenmode of the non-actively controlled DIP-like unstable body dynamics. The results suggest that non-actively controlled DIP-like mechanical dynamics is a major cause of the minimization of the CoM acceleration during quiet standing, which is consistent with a type of control strategy that allows switching off active neural control intermittently for suitable periods of time during quiet standing.