The central nervous system simplifies motor control by sending motor commands activating groups of muscles, known as synergies. Physiological locomotion can be described as a coordinated recruitment of four to five muscle synergies. The first studies on muscle synergies in patients affected by neurological diseases were on stroke survivors. They showed that synergies can be used as biomarkers for motor impairment as they vary in patients with respect to healthy people. Likewise, muscle synergy analysis has been applied to developmental diseases (DD). The need for a comprehensive view of the present findings is crucial for comparing results achieved so far and promote future directions in the field. In the present review, we screened three scientific databases and selected thirty-six papers investigating muscle synergies extracted from locomotion in children affected by DD. Thirty-one articles investigate how cerebral palsy (CP) influences motor control, the currently exploited method in studying motor control in CP and finally the effects of treatments in these patients in terms of synergies and biomechanics; two articles investigate how muscle synergies vary in Duchenne muscular dystrophy (DMD), and three other articles assess other developmental pathologies, such as chronic and acute neuropathic pain. For CP, most of the studies demonstrate that the number of synergies is lower and that the synergy composition varies in the affected children with respect to normal controls. Still, the predictability of treatment's effects and the etiology of muscle synergy variation are open questions, as it has been reported that treatments minimally modify synergies, even if they improve biomechanics. The application of different algorithms in extracting synergies might bring about more subtle differences. Considering DMD, no correlation was found between non-neural muscle weakness and muscle modules' variation, while in chronic pain a decreased number of synergies was observed as a possible consequence of plastic adaptations. Even if the potential of the synergistic approach for clinical and rehabilitation practices is recognized, there is not full consensus on protocols nor widely accepted guidelines for the systematic clinical adoption of the method in DD. We critically commented on the current findings, on the methodological issues and the relative open points, and on the clinical impact of muscle synergies in neurodevelopmental diseases to fill the gap for applying the method in clinical practice.

In clinical scenarios, the use of biomedical sensors, devices and multi-parameter assessments is fundamental to provide a comprehensive portrait of patients' state, in order to adapt and personalize rehabilitation interventions and support clinical decision-making. However, there is a huge gap between the potential of the multidomain techniques available and the limited practical use that is made in the clinical scenario. This paper reviews the current state-of-the-art and provides insights into future directions of multi-domain instrumental approaches in the clinical assessment of patients involved in neuromotor rehabilitation. We also summarize the main achievements and challenges of using multi-domain approaches in the assessment of rehabilitation for various neurological disorders affecting motor functions. Our results showed that multi-domain approaches combine information and measurements from different tools and biological signals, such as kinematics, electromyography (EMG), electroencephalography (EEG), near-infrared spectroscopy (NIRS), and clinical scales, to provide a comprehensive and objective evaluation of patients' state and recovery. This multi-domain approach permits the progress of research in clinical and rehabilitative practice and the understanding of the pathophysiological changes occurring during and after rehabilitation. We discuss the potential benefits and limitations of multi-domain approaches for clinical decision-making, personalized therapy, and prognosis. We conclude by highlighting the need for more standardized methods, validation studies, and the integration of multi-domain approaches in clinical practice and research.

Background: Stroke is becoming more and more a disease of chronically disabled patients, and new approaches are needed for better outcomes. An intervention based on robot fully assisted upper-limb functional movements is presented. Objectives: To test the immediate and sustained effects of the intervention in reducing impairment in chronic stroke and to preliminarily verify the effects on activity. Methodology: Nineteen patients with mild-to-severe impairment underwent 12 40-min rehabilitation sessions, 3 per week, of robot-assisted reaching and hand-to-mouth movements. The primary outcome measure was the Fugl-Meyer Assessment (FMA) at T1, immediately after treatment (n = 19), and at T2, at a 6-month follow-up (n = 10). A subgroup of 11 patients was also administered the Wolf Motor Function Test Time (WMFT TIME) and Functional Ability Scale (WMFT FAS) and Motor Activity Log (MAL) Amount Of Use (AOU), and Quality Of Movement (QOM). Results: All patients were compliant with the treatment. There was improvement on the FMA with a mean difference with respect to the baseline of 6.2 points at T1, after intervention (n = 19, 95% CI = 4.6-7.8, p < 0.0002), and 5.9 points at T2 (n = 10, 95% CI = 3.6-8.2, p < 0.005). Significant improvements were found at T1 on the WMFT FAS (n = 11, +0.3/5 points, 95% CI = 0.2-0.4, p < 0.004), on the MAL AOU (n = 11, +0.18/5, 95% CI = 0.07-0.29, p < 0.02), and the MAL QOM (n = 11, +0.14/5, 95% CI = 0.08-0.20, p < 0.02). Conclusions: Motor benefits were observed immediately after intervention and at a 6-month follow-up. Reduced impairment would appear to translate to increased activity. Although preliminary, the results are encouraging and lay the foundation for future studies to confirm the findings and define the optimal dose-response curve. Clinical Trial Registration: www.ClinicalTrials.gov, identifier: NCT03208634.

In recent years, several studies have investigated upper-limb motion in a variety of scenarios including motor control, physiology, rehabilitation and industry. Such applications assess people's kinematics and muscular performances, focusing on typical movements that simulate daily-life tasks. However, often only a limited interpretation of the EMG patterns is provided. In fact, rarely the assessments separate phasic (movement-related) and tonic (postural) EMG components, as well as the EMG in the acceleration and deceleration phases. With this paper, we provide a comprehensive and detailed characterization of the activity of upper-limb and trunk muscles in healthy people point-to-point upper limb movements. Our analysis includes in-depth muscle activation magnitude assessment, separation of phasic (movement-related) and tonic (postural) EMG activations, directional tuning, distinction between activations in the acceleration and deceleration phases. Results from our study highlight a predominant postural activity with respect to movement related muscular activity. The analysis based on the acceleration phase sheds light on finer motor control strategies, highlighting the role of each muscle in the acceleration and deceleration phase. The results of this study are applicable to several research fields, including physiology, rehabilitation, design of robots and assistive solutions, exoskeletons.

While multi-robot cells are being used more often in industry, the problem of work-piece position optimization is still solved using heuristics and the human experience and, in most industrial cases, even a feasible solution takes a considerable amount of trials to be found. Indeed, the optimization of a generic performance index along a path is complex, due to the dimension of the feasible-configuration space. This work faces this challenge by proposing an iterative layered-optimization method that integrates a Whale Optimization and an Ant Colony Optimization algorithm, the method allows the optimization of a user-defined objective function, along a working path, in order to achieve a quasi-optimal, collision free solution in the feasible-configuration space.

Manual labor is still strongly present in many industrial contexts (such as aerospace industry). Such operations commonly involve onerous tasks requiring to work in non-ergonomic conditions and to manipulate heavy parts. As a result, work-related musculoskeletal disorders are a major problem to tackle in workplace. In particular, back is one of the most affected regions. To solve such issue, many efforts have been made in the design and control of exoskeleton devices, relieving the human from the task load. Besides upper limbs and lower limbs exoskeletons, back-support exoskeletons have been also investigated, proposing both passive and active solutions. While passive solutions cannot empower the human's capabilities, common active devices are rigid, without the possibility to track the human's spine kinematics while executing the task. The here proposed paper describes a methodology to design an active back-support exoskeleton with backbone-based kinematics. On the basis of the (easily implementable) scissor hinge mechanism, a one-degree of freedom device has been designed. In particular, the resulting device allows tracking the motion of a reference vertebra, i.e., the vertebrae in the correspondence of the connection between the scissor hinge mechanism and the back of the operator. Therefore, the proposed device is capable to adapt to the human posture, guaranteeing the support while relieving the person from the task load. In addition, the proposed mechanism can be easily optimized and realized for different subjects, involving a subject-based design procedure, making possible to adapt its kinematics to track the spine motion of the specific user. A prototype of the proposed device has been 3D-printed to show the achieved kinematics. Preliminary tests for discomfort evaluation show the potential of the proposed methodology, foreseeing extensive subjects-based optimization, realization and testing of the device.

In the field of motion analysis, the gold standard devices are marker-based tracking systems. Despite being very accurate, their cost, stringent working environments, and long preparation time make them unsuitable for small clinics as well as for other scenarios such as industrial application. Since human-centered approaches have been promoted even outside clinical environments, the need for easy-to-use solutions to track human motion is topical. In this context, cost-effective devices, such as RGB-Depth (RBG-D) cameras have been proposed, aiming at a user-centered evaluation in rehabilitation or of workers in industry environment. In this paper, we aimed at comparing marker-based systems and RGB-D cameras for tracking human motion. We used a Vicon system (Vicon Motion Systems, Oxford, U.K.) as a gold standard for the analysis of accuracy and reliability of the Kinect V2 (Microsoft, Redmond, WA, USA) in a variety of gestures in the upper limb workspace--targeting rehabilitation and working applications. The comparison was performed on a group of 15 adult healthy subjects. Each subject had to perform two types of upper-limb movements (point-to-point and exploration) in three workspace sectors (central, right, and left) that might be explored in rehabilitation and industrial working scenarios. The protocol was conceived to test a wide range of the field of view of the RGB-D device. Our results, detailed in the paper, suggest that RGB-D sensors are adequate to track the upper limb for biomechanical assessments, even though relevant limitations can be found in the assessment and reliability of some specific degrees of freedom and gestures with respect to marker-based systems.

This letter proposes a procedure for the rapid prototyping and on-demand manufacturing of thin film flexible electro-adhesive devices (EADs) made with a commercial polyimide dielectric layer, inkjet printed interdigitated silver electrodes and blade coated silicone elastomer encapsulation backing. As a proof demonstration, flexible thin-film EADs featuring 9.6 cm active area, 315 ?m thickness and 0.7 g weight have been manufactured and tested over different adhering substrates showing peak adhesive shear stresses of up to 56.67 kPa, fast response time (11 ms for initial activation and 0.3 s for full electrification) and little energy requirements (from 1.3 mJ for initial activation to 20 mJ for full electrification and with a subsequent power consumption of about 1 mW for long-term grasp holding). Practical application of the manufactured EADs within a gripper for the grasping and handling of real objects that include a glass bottle, a hollow carbon fiber tube, a cardboard box, a box with thin polypropylene envelope and a polypropylene bottle is also demonstrated.

Industry 4.0 is taking human-robot collaboration at the center of the production environment. Collaborative robots enhance productivity and flexibility while reducing human's fatigue and the risk of injuries, exploiting advanced control methodologies. However, there is a lack of real-time model-based controllers accounting for the complex human-robot interaction dynamics. With this aim, this paper proposes a Model-Based Reinforcement Learning (MBRL) variable impedance controller to assist human operators in collaborative tasks. More in details, an ensemble of Artificial Neural Networks (ANNs) is used to learn a human-robot interaction dynamic model, capturing uncertainties. Such a learned model is kept updated during collaborative tasks execution. In addition, the learned model is used by a Model Predictive Controller (MPC) with Cross-Entropy Method (CEM). The aim of the MPC+CEM is to online optimize the stiffness and damping impedance control parameters minimizing the human effort (i.e, minimizing the human-robot interaction forces). The proposed approach has been validated through an experimental procedure. A lifting task has been considered as the reference validation application (weight of the manipulated part: 10 kg unknown to the robot controller). A KUKA LBR iiwa 14 R820 has been used as a test platform. Qualitative performance (i.e, questionnaire on perceived collaboration) have been evaluated. Achieved results have been compared with previous developed offline model-free optimized controllers and with the robot manual guidance controller. The proposed MBRL variable impedance controller shows improved human-robot collaboration. The proposed controller is capable to actively assist the human in the target task, compensating for the unknown part weight. The human-robot interaction dynamic model has been trained with a few initial experiments (30 initial experiments). In addition, the possibility to keep the learning of the human-robot interaction dynamics active allows accounting for the adaptation of human motor system.

Laser metal deposition (LMD) shows great promise for producing large components as well as thin-walled structures by additive manufacturing. Compared to the powder bed fusion (PBF) techniques, LMD can exploit further flexibility in terms of tool path programming. Layer-by-layer rastering commonly used in SLM is applicable also to the LMD process, where overhang structures remain a complex issue in the absence of support structures. Concerning thin-walled parts with a symmetry axis or those that evolve around an axis, more efficient strategies may be developed. Hence, this work discusses the use of different part programming strategies for thin-walled structures employing an LMD system based on a 6-axis anthropomorphic robot and a 2-axis rotary table. The work compares, layer-by-layer, continuous pathway, and oriented reference plane strategies, study of process parameters, build failure mechanisms, as well as geometric errors are discussed. Successful deposition of thin-walled organic and freeform tubular components in AISI 316L is demonstrated.

Human-robot cooperation is increasingly demanded in industrial applications. Many tasks require the robot to enhance the capabilities of humans. In this scenario, safety also plays an important role in avoiding any accident involving humans, robots, and the environment. With this aim, the paper proposes a cooperative fuzzy-impedance control with embedded safety rules to assist human operators in heavy industrial applications while manipulating unknown weight parts. The proposed methodology is composed by four main components: (i) an inner Cartesian impedance controller (to achieve the compliant robot behavior), (ii) an outer fuzzy controller (to provide the assistance to the human operator), (iii) embedded safety rules (to limit force/velocity during the human-robot interaction enhancing safety), and (iv) a neural network approach (to optimize the control parameters for the human-robot collaboration on the basis of the target indexes of assistance performance defined for this purpose). The main achieved result refers to the capability of the controller to deal with uncertain payloads while assisting and empowering the human operator, both embedding in the controller safety features at force and velocity levels and minimizing the proposed performance indexes. The effectiveness of the proposed approach is verified with a KUKA iiwa 14 R820 manipulator in an experimental procedure where human subjects evaluate the robot performance in a collaborative lifting task of a 10 kg part.

Variable Stiffness Actuators (VSAs) are actuators that allow the regulation, in a controlled manner, both of the equilibrium configuration and of the mechanical stiffness of the load, so as to modify its mechanical characteristics in the interaction with the humans and the environment.

This paper presents the principle of operation of a variable stiffness joint with a circular flexural spring. The mechanism is characterized by an unlimited ration angle, a limited energy consumption, and a decoupled control of position and stiffness.

Background: Recently, muscle synergy analysis has become a standard methodology for extracting coordination patterns from electromyographic (EMG) signals, and for the evaluation of motor control strategies in many contexts. Most previous studies have characterized upper-limb muscle synergies across a limited set of reaching movements. With the aim of future uses in motor control, rehabilitation and other fields, this study provides a comprehensive characterization of muscle synergies in a large set of upperlimb tasks and also considers inter-individual and environmental variability. Methods: Sixteen healthy subjects performed upper-limb hand exploration movements for a comprehensive mapping of the upper-limb workspace, which was divided into several sectors (Frontal, Right, Left, Horizontal, and Up). EMGs from representative upper-limb muscles and kinematics were recorded to extract muscle synergies and explore the composition, repeatability and similarity of spatial synergies across subjects and movement directions, in a context of high variability of motion. Results: Even in a context of high variability, a reduced set of muscle synergies may reconstruct the original EMG envelopes. Composition, repeatability and similarity of synergies were found to be shared across subjects and sectors, even if at a lower extent than previously reported. Conclusion: Extending the results of previous studies, which were performed on a smaller set of conditions, a limited number of muscle synergies underlie the execution of a large variety of upper-limb tasks. However, the considered spatial domain and the variability seem to influence the number and composition of muscle synergies. Such detailed characterization of the modular organization of the muscle patterns for upperlimb control in a large variety of tasks may provide a useful reference for studies on motor control, rehabilitation, industrial applications, and sports

This paper presents the control architecture of a novel wheelchair simulator to support the training phase in a controlled and safe environment. It is composed by a virtual reality system and a parallel mechatronic platform, in order to provide proper vestibular and haptic feedbacks to the patient. The system allows to simulate both electronic and manual wheelchair, by the use of a couple of sensorized and motorized haptic wheels.

This paper presents the control architecture of a novel wheelchair simulator to support the training phase in a controlled and safe environment. It is composed of a virtual reality system and a parallel mechatronic platform, in order to provide proper vestibular and haptic feedbacks to the patient. The system allows to simulate both electronic and manual wheelchair, by the use of a couple of sensorized and motorized haptic wheels.

Variable-Stiffness Actuators are continuously increasing in importance due to their characteristics that can be beneficial in various applications. It is undisputed that several one-degree-of-freedom (DoF) solutions have been developed thus far. The aim of this work is to introduce an original two-DoF planar variable-stiffness mechanism, characterized by an orthogonal arrangement of the actuation units to favor the isotropy. This device combines the concepts forming the basis of a one-DoF agonist-antagonist variable-stiffness mechanism and the rigid planar parallel and orthogonal kinematic one. In this paper, the kinematics and the operation principles are set out in detail, together with the analysis of the mechanism stiffness.

Since the release of the first Kinect in 2011, low-cost technologies for upper-limb evaluation has been employed frequently for rehabilitation purposes. However, a limited number of studies have assessed the potential of the Kinect V2 for motor evaluations. In this paper, a simple biomechanical protocol has been developed, in order to assess the performances of healthy people and patients, during daily-life reaching movements, with focus on some of the patients' common compensatory strategies. The assessment considers shoulder range of motion, elbow range of motion, trunk compensatory strategies, and movement smoothness. Seventy-seven healthy people and twenty post-stroke patients participated to test the biomechanical assessment. The testing protocol included four different experimental conditions: (1) dominant limb and (2) non-dominant limb of 77 healthy people, and (3) the more impaired limb of 20 post-stroke hemiparetic patients, and (4) the less-impaired limb of 11 patients (subgroup of the original 20). Biomechanical performances of the four groups were compared. Results showed that the dominant and non-dominant limbs of healthy people had comparable performances (p > 0.05). On the contrary, condition (3) showed statistically significant differences between the healthy dominant/non-dominant limb and the less-affected limb in hemiparetic patients, for all parameters of assessment (p < 0.001). In some cases, the less-affected limb of the patients also showed statistical differences (p < 0.05), with respect to the healthy people. Such results suggest that Kinect V2 has the potential for being employed at home, laboratory or clinical environment, for the evaluation of patients' motor performances.

In questo deliverable si descrive lo stato di avanzamento nello sviluppo del Prototipo I, ossia l'implementazione su piattaforma GRAIL dell'ambiente virtuale dedicato alla guida della sedia a rotelle in uno scenario outdoor (AV1). Congiuntamente allo stato di avanzamento del Prototipo I, si descrivono anche gli avanzamenti fatti per lo sviluppo di AV1 con Unity 3D, ossia dello sviluppo dell'ambiente di training che sarà effettivamente sviluppato per funzionare con visore immersivo e la piattaforma meccatronica.

Upper-limb paresis is a main disabling condition in stroke and neurological diseases and rehabilitation is essential for recovering/maintaining function. Upper-limb weight support may help/enable these patients performing movements against gravity thus allowing for task oriented interventions. In this framework, an exoskeleton for upper-limb weight support was developed. In this preliminary study the system was tested in a small group of neurological patients (N=12) to verify the overall usability and its efficacy in assisting patients during functional movements against gravity. Patients performed some functional tasks of the ARAT test both with and without the exoskeleton. The system seems effective as it enabled even the most impaired patients performing the tasks. All patients could wear the exoskeleton and complete the tasks. Usability of the system was assessed as adequate for a use inside a clinical study. Future work will focus on verifying the efficacy of task-oriented intervention performed using the exoskeleton