Hybrid wearable robotics, combining soft and rigid elements, offer a promising solution for upper limb assistance by balancing comfort and functionality. This study evaluates a hybrid soft-rigid elbow exosuit designed for elbow movement support in dynamic and endurance tasks, focusing on biomechanical impact, user perception, and ergonomics. A theoretical model guided the design, optimizing device dynamics and assistive force delivery. A generic interaction controller, combined with fixed system parameters, provided effective assistance across participants without the need for subject-specific tuning, simplifying deployment in practical settings. During dynamic tasks, the exosuit significantly reduced biceps muscle activity compared to the unassisted condition, with an average reduction of 28.40%. In endurance tasks, it reduced infraspinatus activity by an average of 44.55% and mitigated increased muscle activation during load-carrying. Subjective assessments indicated lower perceived physical demand, while the System Usability Scale confirmed high usability and acceptance. These findings highlight the exosuit's ability to reduce physical effort and improve muscle coordination while maintaining comfort. The robust mechatronic design enabled effective assistance through a generic controller, emphasizing the importance of hardware reliability.

Work-related musculoskeletal disorders (WMDs) affect a high percentage of operators performing repeated weight lifting and load carrying in industrial scenarios. Since upper limb muscles are affected in the process, the assistance provided by upper body exoskeletons is increasingly needed to prevent WMDs and their consequent cost to the health system. This paper presents the evaluation of Flexos, a portable, bilateral, shoulder exoskeleton prototype designed to assist logistic and industrial operators in performing occupational tasks. An in-lab assessment was conducted on twelve healthy subjects - 9 males, 3 females - to evaluate Flexos capability in assisting the user during the execution of isometric, dynamic, and carrying-load tasks. Different metrics were extracted from time-series signals to assess the effort related to five targeted muscles surrounding the shoulder complex. Despite the limited experimental size and the prototypal level of the device, Flexos managed to cover almost all the shoulders range of motion - 89.2% flexion/extension, and 88.4% internal/external rotation - and to globally decrease muscular activity in occupational activities, particularly when isometric contractions are required for a prolonged time, with average reductions of -27.2% for the static task, -18.6% for the dynamic task and -23.4% for the carrying-load task.

Passivity-based methods are widely used in tele-operation to guarantee stability, especially for the widely used Position-Force measured (PFm) architecture. Among them, Time Domain Passivity Approach (TDPA) achieves stability through passivation, generating a dissipation action that degrades the reference signals and thus, the performance of the system. Whereas passivization is necessary to ensure stability during contact, in free motion, it acts just as a disturb, without having a real impact on stability. In fact, during free motion the force feedback is zero, i.e. the teleoperation loop is not closed and thus, a stabilization action is not needed. Therefore, this paper proposes a formal demonstration that passivation is not needed during free motion. Accordingly, the paper introduces a new formulation of the TDPA to take into account the free motion condition. A one-degree-of-freedom case study is then proposed to provide a simple example to instantiate the formalism and to show the advantages of the proposed method, that achieve an almost total cancellation of the drift during free motion. Finally, the paper discusses the limitations of the method in real-case scenarios. In particular, how the inertia of tools mounted after the force sensors can affect the measurements and the perception of the system.

This paper presents a dynamic walking corridor generation (DWCG) algorithm designed to enhance navigation safety for visually impaired individuals in crowded pedestrian environments. Current physical human-robot interaction (pHRI) systems struggle with random pedestrian movements and interaction disturbances in such settings. To address these limitations, we propose a safety-critical framework that integrates Safe Flight Corridor concepts with pedestrian dynamics modeling. The method constructs time-varying Safe Walking Corridors (SWCs) through convex polyhedra decomposition, constrained by social force model predictions. Simulation experiments demonstrate a 100% success rate in moderate crowds (50 pedestrians or fewer) with 10.1 ms average computation time, and 86.3% success in high-density environments (100 pedestrians), establishing a foundation for reliable assistive navigation systems in complex urban settings.

This paper presents an automatic method for the design of Neural Networks (NNs) at the edge, enabling Machine Learning (ML) access even in privacy-sensitive Internet of Things (IoT) applications. The proposed method runs on IoT gateways and designs NNs for connected sensor nodes without sharing the collected data outside the local network, keeping the data in the site of collection. This approach has the potential to enable ML for Healthcare Internet of Things (HIoT) and Industrial Internet of Things (IIoT), designing hardware-friendly and custom NNs at the edge for personalized healthcare and advanced industrial services such as quality control, predictive maintenance, or fault diagnosis. By preventing data from being disclosed to cloud services, this method safeguards sensitive information, including industrial secrets and personal data. The outcomes of a thorough experimental session confirm that –on the Visual Wake Words dataset– the proposed approach can achieve state-of-the-art results by exploiting a search procedure that runs in less than 10 hours on the Raspberry Pi Zero 2.

The current trend of applying transfer learning from convolutional neural networks (CNNs) trained on large datasets can be an overkill when the target application is a custom and delimited problem, with enough data to train a network from scratch. On the other hand, the training of custom and lighter CNNs requires expertise, in the from-scratch case, and or high-end resources, as in the case of hardware-aware neural architecture search (HW NAS), limiting access to the technology by non-habitual NN developers. For this reason, we present ColabNAS, an affordable HW NAS technique for producing lightweight task-specific CNNs. Its novel derivative-free search strategy, inspired by Occam’s razor, allows to obtain state-of-the-art results on the Visual Wake Word dataset, a standard TinyML benchmark, in just 3.1 GPU hours using free online GPU services such as Google Colaboratory and Kaggle Kernel.

Haptic interaction often requires stabilizing controllers for safety. The Time-Domain Passivity Approach guarantees passivity (then stability) by observing and dissipating energy generated from active elements in a network. The dissipating action is performed by a Passivity Controller, whose action is commanded to the physically limited robot actuators. Thus, the controller stabilizing action should be in turn limited in order to command displayable references to the actuators. This problem is rarely taken into account in the literature and when it is, the limitation is neither directly related to the actuator power limits, nor to the robot's current configuration. The limits of the currently adopted strategies leave room for improvement. In this paper, a new strategy to limit the Passivity Controller action is proposed taking into account both the physical limits of the actuators and the robot configuration. This new strategy is experimentally tested against the classical one based on the sampling time. In the experiment, a human interacts with a virtual wall in a Virtual Environment through a haptic interface. The wall induces an unstable behavior passivated with the two limitation strategies. The results clearly state the benefits introduced by the proposed strategy in two relevant cases.

Robot-assisted rehabilitation often makes use of virtual environments to present the therapy tasks. Virtual reality has the ability of providing valuable visual feedback and enjoyable interaction to the patients; therefore, the way they are displayed to users becomes crucial. Is the monitor size an important feature that influences how the task is perceived and thus affects patients’ performance?This study on healthy participants investigates the influence of displays in perceiving haptic effects. The participants performed an experiment using an end-effector robot, where they followed a moving target around a trajectory while disturbed by a simulated perturbation and assisted by an adaptive algorithm. The experiment was presented on two different monitors to assess whether a different size affects their performance. Statistically significant results show that the performance achieved with the large monitor features lower error compared to the small monitor, implying that large monitors might be a better solution for rehabilitation with virtual tasks and assistive robots.

The accomplishment of a successful teleoperation task requires guaranteeing system stability and transparency. Communication delay (in particular variable time delay), quantization and discretization negatively affect system stability and might be overcome with Time Domain Passivity Approach (TDPA), a model-free and robust way to cope with energy injection due to communication delay. However, this method degrades the transparency of the teleoperation system and worsens tracking performance, introducing in particular position drift error at the slave side and high frequency vibration (jittering) at the master side. In this work, we propose a new joint passivity controller formulation for kinematically redundant manipulators. Our approach stabilizes the system guaranteeing minimal performance loss by privileging the dissipation of the observed energy in the Jacobian null-space. The residual energy (if any) is dissipated in an orthogonal subspace. This is achieved by the solution of an optimization problem with appropriately defined cost functions and constrained to dissipate the energy observed by the passivity observer, guaranteeing the stability of the system. The effectiveness of our algorithm is tested in simulation with both constant and variable time delays.

In interacting with stiff environments through teleoperated systems, time delays cause a mismatch between haptic feedback and the expected feedback by the operator. This mismatch causes artefacts in the feedback, which decrease transparency, but so does filtering these artefacts. Through modelling of operator stiffness and the expected feedback force with EMG, the artifacts can be selectively filtered without loss of transparency. We developed several feedback modulation techniques to bring the feedback force closer to the expected force: 1) the average between the modelled operator force and the feedback force, 2) a low pass filter and 3) a scaling modulation. To control for overdamping, a transparency check is included. We show that the averaging approach yields significantly better contacts than unmodulated feedback. None of the modulation algorithms differ significantly from the unmodulated feedback in transparency.

The intention-detection strategy used to drive an exosuit is fundamental to evaluate the effectiveness and acceptability of the device. Yet, current literature on wearable soft robotics lacks evidence on the comparative performance of different control approaches for online intention-detection. In the present work, we compare two different and complementary controllers on a wearable robotic suit, previously formulated and tested by our group; a model-based myoelectric control (myoprocessor), which estimates the joint torque from the activation of target muscles, and a force control that estimates human torques using an inverse dynamics model (dynamic arm). We test them on a cohort of healthy participants performing tasks replicating functional activities of daily living involving a wide range of dynamic movements. Our results suggest that both controllers are robust and effective in detecting human–motor interaction, and show comparable performance for augmenting muscular activity. In particular, the biceps brachii activity was reduced by up to 74% under the assistance of thedynamic armand up to 47% under themyoprocessor, compared to a no-suit condition. However, themyoprocessoroutperformed thedynamic armin promptness and assistance during movements that involve high dynamics. The exosuit work normalized with respect to the overall work was$68.84 \pm 3.81\%$when it was ran by themyoprocessor, compared to$45.29 \pm 7.71\%$during thedynamic armcondition. The reliability and accuracy of motor intention detection strategies in wearable device is paramount for both the efficacy and acceptability of this technology. In this article, we offer a detailed analysis of the two most widely used control approaches, trying to highlight their intrinsic structural differences and to discuss their different and complementary performance.

In this paper, we present a novel prototype of a flat and compact series elastic actuator (SEA) intended for use in assistive and portable upper limb exoskeletons. The elastic joint in series to the brushless motor is based on reliable and robust linear tension springs to achieve a high torque to weight ratio while keeping the design simple and cheap. A method to design the spring stiffness, based on the joint requirements, is proposed, and the torque controller for the device is presented. Characterization experiments have been carried out to verify the concept model and to tune and validate the torque estimator based on the elastic joint. The SEA exhibits suitable performance for the intended application: 39.7 Hz bandwidth in closed-loop torque control; about 0.2 Nm RMS torque in transparency operations; stability and acceptable torque tracking performance in compliant control mode.

Search and rescue robotics is becoming a relevant topic in the last years and the growing number of robotic platforms and dedicated projects is the evidence of the interest in this area. In this context, the possibility to drive a remote robot with an exoskeleton is a promising strategy to enhance dexterity, reduce operator effort and save time. However, the use of haptic feedback (bilateral teleoperation) may lead to instability in the presence of communication delay and more complex is the case of bimanual teleoperation where the two arms can exchange energy. In this work, we present a bimanual teleoperation system based on an exoskeletal master, where multi-degrees of freedom (multi-DoFs) and kinematically different devices are involved. In the implemented architecture the two slaves are managed in parallel and independently passivated using the Time Domain Passivity Approach (TDPA) extended for multi-DoFs devices. To investigate the stability of the architecture we designed two tasks highly related to real disaster scenarios: the first one was useful to verify the system behavior in case of small movements and constrained configurations, whereas the second experiment was designed to involve larger contact forces and movements. Moreover, we compared the effect of both delay and low control loop frequency on the stability of the system when TDPA was applied. From the results, it was evident that the overall system exhibited a stable behavior with the use of the TDPA, even passivating the two slaves independently, under simulated time delay and in presence of a low control loop frequency.

In this paper we propose a hybrid fiber optics sensor system, based on Fiber Bragg Gratings (FBG) and Raman distributed temperature sensing (RDTS), for monitoring essential sites within large railway infrastructures like bridges, viaducts and slopes potentially subject to landslides. The geometrical rail track condition is monitored in real-time using fiber optic sensors, providing early warning if pre-defined thresholds are exceeded in terms of longitudinal, horizontal and cross-level defects. The sensor reading units can be remotely located from the monitored zones, without requiring active elements on the tracks and ensuring high immunity to electromagnetic interference. The proposed technology has been first validated in railway laboratories and then in field trials confirming its capability to detect defects over pre-established thresholds and the absence of false alarms with regular train circulation.

The growing interest in wearable robots for assistance and rehabilitation purposes opens the challenge for developing intuitive and natural control strategies. Among several human-machine interaction approaches, myoelectric control consists in decoding the motor intention from muscular activity (or EMG signals) with the aim at moving the assistive robotic device accordingly, thus establishing an intimate human-machine connection. In this scenario, bio-inspired approaches, e.g. synergy-based controllers, are reveling to be the most robust.In this work, the authors presented an undercomplete autoencoder (AE) to extract muscles synergies for motion intention detection. The proposed AE topology has been validate with EMG signals acquired from the main upper limb muscles during planar isometric reaching tasks performed in a virtual environment while wearing an exoskeleton. The presented AE have shown promising results in muscle synergy extraction comparing its performance with the Non-Negative Matrix Factorization algorithm, i.e. the most used approach in literature. The synergy activations extracted with the AE have been then used for estimating the moment applied at the shoulder and elbow joints. Comparing such estimation with the results of other synergy-based techniques already proposed in literature, it emerged that the proposed method achieves comparable performance.

This paper proposes a size measurement system to be used in inspection tasks, based on the integration of fully immersive Virtual Reality visualization and haptic feedback at fingertip level. In particular, index finger and thumb are intuitively used to perform metric measurement on 3D point clouds visualized using a stereo vision Head Mounted Display. The haptic feedback consisting of contact transition and forces rendered at the fingertip is used to facilitate the user in the measurement task. Experimental results show similar performance of subjects in accomplishing the inspection task with and without the support of haptic feedback in terms of time and precision of measurements. However, qualitative questionnaire responses suggest a significant preference of subjects in using immersive environment enriched by haptic feedback.

Kinesthetic teaching is a viable solution for programming robots in the execution of new tasks thanks to the human-mediated mapping between the task objectives and the robot joint space. Redundant designs and differences from human kinematics pose challenges in the efficient execution of the teaching task. In this work we employ vibrotactile feedback letting operators understand specific kinematic constraints such as reaching joint limits and singularities. The experimentation with a Baxter robot and a four-motor vibrotactile bracelet is reported showing the effectiveness of the proposed enhancement to the kinesthetic teaching task.

This paper presents the development and the experimental validation of a controller for the simulation of the behavior of automotive automatic gearshifts. For this purpose a gearshift simulator was developed based on 2 DOF haptic interface to evaluate users qualitative judgment of automatic gearshifts response. In fact, many car manufacturers use vehicle and primary controls simulators to evaluate the characteristics of a new model before building physical mock-ups or even prototypes. A dedicated control law was designed in order to reproduce different experimentally measured force profiles during forward and backward run of the gearshift handle. The force feedback control law was based on an impedance model with different stiffness values along the path of the gearshift. A state machine selects the characteristics of the force feedback profile according to lever position and velocity. An additional state machine implements the hysteresis behavior of the force profiles by a transition function. The transition algorithm and constraints related to stability are discussed in this paper. The rendered force/position profiles were obtained from experimental data using a real gearshift. Several gearshift response profiles were tested and simulated and experimental results were compared and highlighted good fidelity in force reproduction.

Cardiopulmonary resuscitation (CPR) is a first-aid key survival technique used to stimulate breathing and keep blood flowing to the heart. Its effective administration can significantly increase the chances of survival in victims of cardiac arrest. In this paper, we propose a markerless system for quality CPR training based on RGB-D (RGB + Depth) sensors, called RELIVE. Then, we report the results of a series of experimental tests conducted to evaluate RELIVE tracking performance. The proposed system is able to accurately track the 3-D position of the hands performing CPR by means of RGB-D sensors to estimate the chest compression rate and depth, providing a real-time visual/audio feedback about the rescuer's performance. Finally, the system usability has been assessed by both healthcare professionals and lay people.

While research has demonstrated how vibrotactile devices can be effectively used to guide human behavior, efficient mappings of vibration patterns for spatial guidance in time-critical dynamical tasks have not yet been understood. In this paper, we contrast two types of action-dependent, haptic stimulus designs to demonstrate the different effects of vibrotactile feedback on the human control performance. A wireless bracelet is used to provide patterns of vibrotactile stimuli in real-time, representing either optimal hand velocity or acceleration for the stabilization of an inverted pendulum. The optimal control behavior is supplied by a linear quadratic regulator. The analyses of the participants' stabilization and learning behavior revealed a significant improvement caused by the additional velocity-dependent feedback. The results are consistent with previous research, which indicates that the human sensory-motor system is generally more sensitive to velocity than acceleration information. In summary, the present paper suggests how human-centric vibrotactile stimuli should be designed and how they can be effectively transmitted to the human user for time-critical behavioral guidance.

This paper presents a myoelectric control of an arm exoskeleton designed for rehabilitation. A four-muscles-based NeuroMusculoSkeletal (NMS) model was implemented and optimized using genetic algorithms to adapt the model to different subjects. The NMS model is able to predict the shoulder and elbow torques which are used by the control algorithm to ensure a minimal force of interaction. The accuracy of the method is assessed through validation experiments conducted with two healthy subjects performing free movements along the pseudo-sagittal plane. The experiments show promising results for our approach showing its potential for being introduced in a rehabilitation protocol.

A novel wearable haptic device for modulating skin stretch at the fingertip is presented. Rendering of skin stretch in 3 degrees of freedom (DoF), with contact - no contact capabilities, was implemented through rigid parallel kinematics. The novel asymmetrical three revolute-spherical-revolute (3-RSR) configuration allowed compact dimensions with minimum encumbrance of the hand workspace and minimum inter-finger interference. A differential method for solving the non-trivial inverse kinematics is proposed and implemented in real time for controlling the position of the skin tactor. Experiments involving the grasping of a virtual object were conducted using two devices (thumb and index fingers) in a group of 4 subjects: results showed that participants performed the grasping task more precisely and with grasping forces closer to the expected natural behavior when the proposed device provided haptic feedback.

Coming generations of robots will share physical space with humans, engaging in contact interactions (physical Human Robot Interaction, or pHRI) as they carry out cooperative tasks. This special issue turns a spotlight on the specific roles that crafted haptic interaction can play in cooperation and communication between a human and a robotic partner, from the viewpoints of human needs, capabilities, and expectations and of engineering implementation.

Walking mechanics has been studied for a long time, being essentially simple but nevertheless including quite tricky aspects. During walking, muscular forces are needed to support body weight and accelerate the body, thereby requiring a metabolic demand. In this paper, a new Constant Pushing Force Device (CPFD) is presented. Based on a novel actuation concept, the device is totally passive and is used to apply a constant force to the pelvis of a subject walking on a treadmill. The device is a serial manipulator featuring springs that provide gravity balancing to the device and exert a constant force regardless of the pelvis motion during walking. This is obtained using only two extension springs and no auxiliary links, unlike existing designs. A first experiment was carried out on a healthy subject to experimentally validate the device and assess the effect of the external force on gait kinematics and timing. Results show that the device was capable of exerting an approximately constant pushing force, whose action affected subject's cadence and the motion of the hip and ankle joints.

A non-invasive Brain Computer Interface (BCI) based on a Convolutional Neural Network (CNN) is presented as a novel approach for navigation in Virtual Environment (VE). The developed navigation control interface relies on Steady State Visually Evoked Potentials (SSVEP), whose features are discriminated in real time in the electroencephalographic (EEG) data by means of the CNN. The proposed approach has been evaluated through navigation by walking in an immersive and plausible virtual environment (VE), thus enhancing the involvement of the participant and his perception of the VE. Results show that the BCI based on a CNN can be profitably applied for decoding SSVEP features in navigation scenarios, where a reduced number of commands needs to be reliably and rapidly selected. The participant was able to accomplish a waypoint walking task within the VE, by controlling navigation through of the only brain activity.

This work presents the development and the preliminary experimental assessment of a novel EMG-driven robotic hand exoskeleton for bilateral active training of grasp motion in stroke. The system allows to control the grasping force required to lift a real object with an impaired hand, through the active guidance provided by a hand active exoskeleton, whose force is modulated by the EMG readings acquired on the opposite unimpaired arm. To estimate the grasping force, the system makes use of surface EMG recordings during grasping, developed on the opposite unimpaired arm, and of a neural network to classify the information. The design, integration and experimental characterization of the system during the grasp of two cylindrical objects is presented. The experimental results show that an optimal force tracking of the interaction force with the object can be achieved.

The combination of robotics and virtual reality seems promising for the rehabilitation of the upper limb by promoting intensive training on specific deficits with motor control and multimodal feedback in engaging game-like scenarios. In this paper we present the integration of a robotic system and virtual reality applications for the orthopedic rehabilitation of the arm, in terms of strengthening training and motion recovery. The system simulates the upper limb of the patient and their actions, and allows exhaustive exercising and motor control, giving visuomotor and haptic feedback and trajectory positioning guidance. The system allows assign specific tasks to perform within the virtual environments and aids to evaluate the mobility condition of the patient, to personalize the difficulty level of the therapy and provides kineseologic measures of the patient evolution. We present the results of a preliminary clinical assessment we are carried out on three patients in order to assess the usability and acceptance of the system.

This paper presents a health economic system for motor recovery in patients with the commonest cause of death in some countries, stroke. The system is based on immersive, real-time motion capture (MOCA) available for private use and at the bedside. An interactive virtual reality (VR) interface designed with auditory and visual feedback. It consists on two scenarios and a 3D character that follows the user's arm movements by using the first and third person view metaphors of interaction. Two easy and enjoyable games are proposed for each scenario. The system is designed to be adapted to several tasks with different index of difficulty (ID) for gradual motor recovery in patients with stroke. The experiments carried out on eight healthy neurologically interact volunteers have shown that our system is suitable to be used at home on training programs, giving good references for future applications on stroke arm recovery.

During typical robot-assisted training sessions, patients are required to execute tasks with the assistance of a robot while receiving feedback on a 2D display. Three-dimensional tasks of this sort require the adoption of stereoscopy to achieve correct visuo-motor-proprioceptive alignment. Stereoscopy often causes side-effects as sickness and tiredness, and it may affect the processes of recovery and cortical reorganization of the patients' brain in an unclear way. It follows that it is preferrable for a robot-assisted neurorehabilitation therapy to work in a real 3D setup containing real objects rather than using virtual reality. In this paper, we propose a new system for robot-assisted neurorehabilitation scenarios which allows patients to execute therapy by manipulating real, generic 3D objects. The proposed system is based on a new algorithm for identification and tracking of generic objects which makes efficient use of a Microsoft Kinect sensor. We discuss the results of several experiments conducted in order to test robustness, accuracy and speed of the tracking algorithm and the feasibility of the integrated system.

This paper presents the development of an interaction-torque control architecture for a rehabilitation exoskeleton (RehabExos) with flexible joints equipped with internal torque sensors. The architecture consists of an outer control loop, which is based on the kineto-statics of the RehabExos, and on four identical-independent inner full-state joint-torque controllers (IJTFC). The considered IJTFC demonstrate good stability, responsiveness and accuracy in tracking the desired torques generated by the outer controller. Comparison with other control strategies available from the literature is shown via analytical and experimental results, which highlight the improved performances of the proposed IJTFC method in controlling the RehabExos robot.

This paper proposes a new multimodal architecture for gaze-independent brain-computer interface (BCI)-driven control of a robotic upper limb exoskeleton for stroke rehabilitation to provide active assistance in the execution of reaching tasks in a real setting scenario. At the level of action plan, the patient's intention is decoded by means of an active vision system, through the combination of a Kinect-based vision system, which can online robustly identify and track 3-D objects, and an eye-tracking system for objects selection. At the level of action generation, a BCI is used to control the patient's intention to move his/her own arm, on the basis of brain activity analyzed during motor imagery. The main kinematic parameters of the reaching movement (i.e., speed, acceleration, and jerk) assisted by the robot are modulated by the output of the BCI classifier so that the robot-assisted movement is performed under a continuous control of patient's brain activity. The system was experimentally evaluated in a group of three healthy volunteers and four chronic stroke patients. Experimental results show that all subjects were able to operate the exoskeleton movement by BCI with a classification error rate of 89.4±5.0% in the robot-assisted condition, with no difference of the performance observed in stroke patients compared with healthy subjects. This indicates the high potential of the proposed gaze-BCI-driven robotic assistance for neurorehabilitation of patients with motor impairments after stroke since the earliest phase of recovery.

Eye-tracking systems are playing an increasingly important role in assistive robotics as hand-free interaction interfaces for motor impaired people, but no noticeable applications have been developed so far for enhancing the robotic assisted training in functional rehabilitation. In this paper we propose a new gaze-based control to provide active guidance to the upper limb movement, through a robotic exoskeleton, in the functional rehabilitation of pick and place tasks. Experimental results on healthy subjects demonstrate the feasibility of the proposed approach and the breakthrough that the system introduces in the field of eye-based rehabilitation systems.

Tangential skin displacement at the fingertip is an effective means of communicating direction or displaying static friction in haptic application. A tactile device capable of stretching the skin of the fingerpad can be mounted directly on the fingertip or embedded in haptic interfaces and hand-held devices. In both cases low weight and small dimensions are important requirements. We have developed a miniaturized tactile device capable of displaying tangential skin displacement in two directions. The actuation for the device is realized by SMA wires, in order to reduce bulk and weight, and the displacements are measured by optical sensors. The performance of the device has been verified experimentally.

Several manipulators or exoskeleton are characterized by having a concave workspace in the operational space due to mechanical limits. This article proposes an online trajectory planning method for performing visually guided assisted reaching through a rehabilitation robotic exoskeleton, the L-Exos, in its concave workspace. To evaluate the proposed methodology in a rehabilitation application, we set-up a computer vision based system that can automatically identify target objects in the workspace and generate a robot assisted movement to reach them through the L-Exos.

A linear-quadratic-Gaussian regulator is proposed for the torque control of flexible robotic joints with built-in torque sensor. The regulator requires the joint-torque sensor information only and features: (1) a Kalman filter that, beside reducing the noise and evaluating the derivative of the torque sensor measure, is able to estimate all the external and internal torques acting on the joint; 2) a controller that optimizes system stability, responsiveness, accuracy and effort. The regulator is implemented on a flexible joint of a rehabilitation exoskeleton. Simulation and experimental results are provided which demonstrate regulator performance and efficacy.

In this paper, we present the mechanical design of a new fMRI compatible haptic interface with 3DOFs, based on electrical DC actuation, for the study of brain mechanisms of human motor control. The 1DOF manipulator, which was evaluated successfully on the compatibility with fRMI environment in the preliminary experiments, was extended to the implementation of a 3DOFs parallel manipulator with 3- UPU kinematics. Kinematic properties were studied in different configurations to select the stroke of the prismatic joint and the radius difference between the moving platform and the base. Due to the dimensional constraints imposed by the fMRI environment, the choice of the dimensions and the adopted mechanical solution was a result of an optimization process presented in this work. A further optimization of the mechanical design was then conducted in order to reduce the torque requested to the actuators for gravity compensation and improve the mechanical stiffness with elastic compliance of the manipulator. The final design resulted in a system capable of satisfying all the environment and user requirements.

It is well-known that virtual reality (VR) is a powerful and promising computer-based technology for the motor recovery in stroke patients. The importance of using VR into arm rehabilitation has coined it as clinical VR; where its main sake is to improve the recovery process of post-stroke patients. In this regard, physical therapy and occupational therapy are provided by such technology. As we shall see into this contribution, interesting clinical VR applications have been designed for handling effectively the brain plasticity in chronic stroke patients. To this end, we use the so-called Light-Exoskeleton which has been presented for arm-robotic therapy such that it serves as the kinesthetic feedback stimulator for assisting the patient during the rehabilitation sessions.

Body awareness has important implications for the use of Virtual Reality (VR) and its effectiveness. This involves the senses of agency and body ownership. The possibility of producing the Rubber Hand Illusion (RHI) in VE (the sense of feeling a fake virtual body part seems like the one's own part), has been proven in the past, by giving the user synchronous 3D visual stimulation and passive tactile stimulation on the hidden real right hand. In this paper we present a VR system consisting on a low cost data-glove and a hand/arm model as a tool for study presence and body ownership in VE. We present also a novel study of the RHI within highly dynamic VE sessions with synchronous pure virtual vibrotactile stimulation of the fingers. The hand/arm participant's movements are realistically reproduced on the VE and tactile stimulations are self-inflicted by the participant through actively touching the virtual objects. The results of the proprioceptive drift and the response ratings of a questionnaire applied seem to reveal that the RHI is possible in active and fully multisensored VE sessions

While control theory for bilateral teleoperation systems under constant time communication delay is well developed, the research on time-varying communication delay systems is still ongoing. Most wave-based approaches proposed in literature to deal with time-varying delay appear too conservative resulting in high degradation from the constant time delay case. We have already proposed a bilateral control scheme with energy balance monitoring over packet switched communication networks. In the previous work, we dealt with a simplify situation where the time-varying was in the communication channel from master to the slave. However, we did not implement and test the system with a more complex scenario in which the delay was in both communication paths. The paper presents a complete bilateral teleoperation control scheme to compensate nonlinearity introduced by an Internet like communication channel. The system implements intelligent strategies to maintain the system passivity while it deals with position drift compensation, packets loss and blackouts management. Experimental results using the proposed control scheme are shown.

A new prototype of portable device for haptic interaction with virtual environments is presented. It is a lightweight interface for the fingertips, designed for providing cutaneous feedback and displaying the contact - non contact transition in highly immersive virtual environments. The second version of the interface features a force sensor for controlling the force on the fingertip during contact, assuring a better haptic feedback. In this paper the kinematics, the mechanical design and the improved control system are described. The device has been mounted on a kinesthetic haptic interface which tracks its position: in this configuration, the overall system can provide both cutaneous and kinesthetic feedback and improve the fidelity of the haptic interaction. Finally the performance of the cutaneous device in a task of contour following has been evaluated.

The required tasks in fixed-base exoskeletons demand a fast position/force controller; yet robust against unknown disturbances due to the application itself is tightly coupled with a human in a wide range of operational conditions, which give rise to human-exoskeleton interaction dynamics, high nonlinear uncertain exoskeleton dynamics, noisy sensors and other parametric uncertainties, such as environmental contacts. These factors do not allow to account on a precise dynamical model, thus model-based (regressor-based) controllers are difficult to implement. This paper deals with a regressor-free smooth PID-like fast force/position controller which guarantees finite-time convergence within second order sliding modes, thus ensuring inherent robustness. Experimental platform allows assessing its performance for rehabilitation tasks, which validates its functionality in practical implementation.

Any teleoperation system involving two distant devices is affected by communication delay due to the physical gap between the devices. Several approaches based on wave variables have already been proposed to deal with time-varying delay. However, these approaches are too conservative resulting in high degradation from the constant time delay case. In this paper, we propose a new control scheme for bilateral teleoperation under time-varying communication delay entirely developed in the wave variables domain. The proposed method minimizes the performance degradation from the constant time delay case. Experimental results show the validity of the proposed scheme.

Fixed-Base Exoskeleton applications have increased rapidly in the last few years, evidently as part of promising rehabilitation robotic programs of the robotics worldwide community, where in particular Human-Robot-Interaction (HRI) plays an important role in its design and control because they are tightly coupled to human-limbs. Exoskeletons embrace HRI as well as technological and theoretical challenges towards real and effective rehabilitation. In this realm, some questions arise, to name a few, what is the relationship between the exchanged energy between human and exoskeleton? How can we assess rehabilitation factors under HRI philosophy? This paper attempts to establish answers to these questions, which can be embodied into rehabilitation HRI using a Light-Exoskeleton. A compliant haptic guidance scheme for human arm subject to minimum-jerk-trajectories criterion is proposed. Preliminary experimental results provide further insight of a haptic guidance scheme taking into account decisive factors into the HRI such as human pose, haptic guidance control, reaching and tracking tasks, the complexity of the virtual environment, and muscles activity.

This paper presents the results of a clinical trial employing the PERCRO L-Exos (Light-Exoskeleton) system, which is a 5-DoF force-feedback exoskeleton for the right arm, for robotic-assisted rehabilitation. The device has demonstrated itself suitable for robotic arm rehabilitation therapy when integrated with a Virtual Reality (VR) system. Three different schemes of therapy in VR have been tested in the clinical evaluation trial, which was conducted at the Santa Chiara Hospital in Pisa with nine chronic stroke patients. The results of this clinical trial, both in terms of patients performance improvements in the proposed exercises and in terms of improvements in the standard clinical scales which have been used to monitor patients progresses will be reported and discussed throughout the paper. It is to be noted that statistically significant improvements have been demonstrated in terms of Fugl-Meyer scores, Ashworth scale and increments of active and passive ROMs on shoulder, elbow and wrist joints of the impaired limb.

This paper presents a novel method based on screw theory for the analysis of positioning accuracy in parallel manipulators with joint clearances. A general method is introduced, and a new analytical procedure is formulated which allows to determine analytically a sub-optimal estimation of the worst case condition for positioning accuracy. Moreover this procedure can determine exactly the worst-case angular accuracy in translating fully-parallel manipulators under the influence of joint clearances. The relevance of the method is demonstrated by two application examples, that clearly demonstrate how kinematic properties, such as kinematic isotropy, are strictly related to position accuracy in mechanisms with joint clearances.

Haptic interaction with virtual objects is typically tool mediated, or in alternative it constraints userpsilas body in someway, like it happens in exoskeletons that cannot be totally transparent. Encounter type haptic interfaces aim at hands free haptic interaction, that is more natural and can be applied in contexts in which the user moves in the space around the interface. This paper presents a system that allows a palm based haptic interaction in a large workspace using the principle of encountered haptics. The system is evaluated in a surface exploration task and compared against the same task performed with a standard haptic interface. In this type of task this type of interface is better suited, providing a smoother feedback to the hand during the movement over the surface.

In this paper the design and construction of a novel wireless Dataglove based on new flexible goniometric sensor technology is described. The device is characterized by a low cost and rugged construction and no requires calibration before its use. Indeed, the sensors used are purely goniometric, so they are not sensible to dimensions of the user's hand. The Dataglove can measure the angular displacement of the fingers hand using 11 sensors, each sensor has a resolution of 0.2 degrees, with 3 degree of accuracy in the worst case. The communication between the Dataglove and its computer Host is carried out using a 2,4 gigahertz wireless Bluetooth radio protocol, in a guaranteed range up to 10 meters with a refresh rate of 100 Hz.

This paper presents the synthesis and the analysis of the kinematics of a new robotic parallel wrist for laparoscopic surgery applications. The main properties of this new wrist are the wide singularity free orientation workspace and the capability of making large rotations of the end-effector with small rotation of the actuators. First, it is shown how these features suit the application of minimally invasive surgery. Secondly, the kinematics is described showing its working principle that allows the achievement of rotation multiplication. The forward kinematics problem is solved geometrically. Afterwards, a methodology based on screw theory for the solution of the differential kinematics is proposed. Finally a workspace representation is presented making a comparison with another known parallel wrist

The creation of applications of Virtual Reality enabled with Haptic interaction and dynamic simulation requires usually to cover many implementation details that increase the development time and the effectiveness of the application itself. This work presents one game application that has been developed using a Haptic toolkit for the rapid application development, that integrates 3D graphics,haptic feedback and dynamic simulation.The resulting application can be easily deployed on the Web directly to the final user.

One of the principal guidelines in the design of haptic devices is to provide a suitable mechanical design that can improve control performance and the force-feedback fidelity. Unfortunately these guidelines may conflict with other design objectives (reflected mass, balancing, dexterity) as well as with specifications given by users and applications. For haptic interfaces based on tendon driven actuation it is highly important to achieve an accurate model of friction losses in the transmission system, in order to be able to compensate for them through an active control. In this paper it is reported a method for modeling and control complex tendon transmissions used for driving haptic devices and robots. The presented approach can operate in realtime with very low complexity; it is applicable to all kinds of serial manipulators and provides enough flexibility to allow identification of parameters and modeling of distributed friction phenomena all along the transmission. The approach has been implemented and tested on a 4 DOF exoskeleton system, the PERCRO L-EXOS.

This paper presents a methodology for the evaluation of the performance of a given haptic display. The procedure can be carried out through the own proper sensors/actuators which equip the haptic display and allows to characterize the device from a static/dynamic point of view.

This article describes the architecture of the "Museum of Pure Form", a virtual reality system where the user can interact, through the senses of touch and sight, with digital models of 3D art forms and sculptures. Two different realizations of "Museum. of Pure Form" systems are currently being developed at PERCRO, Pisa, Italy. In one realization "The Museum of Pure Form" is conceived as a system placed inside several museums and art galleries around Europe and made available to people visiting such institutions. In the second realization the system will be placed and tested inside a CAVE environment. Considerations on technological aspects concerning the implementation of a virtual environment endowed with haptic feedback for cultural heritage applications are reported throughout the paper.

A 2-DOF force-feedback joystick was employed to simulate the force response of a manual gearshift of car during drive. The control law is based on an hybrid model. A state machine determines the active state of the system, according to the simulation, and changes the parameters of the dynamical model. The operator can move the gearshift lever whether such a movement would be allowed in an actual transmission under similar circumstances. The obtained performance was compared to the experimental data, measured on a real car. The simulated and experimental results match satisfactorily and the joystick gives a realistic feel of an actual manual transmission.

The hand force feedback system is an anthropomorphic haptic interface for the replication of the forces arising during grasping and fine manipulation operations. It is composed of four independent finger dorsal exoskeletons which wrap up four fingers of the human hand (the little finger is excluded). Each finger possesses three electrically actuated DOF placed in correspondence with the human finger flexion axes and a passive DOF allowing finger abduction movements. Each exoskeleton finger has three points of attachment to the operator's finger (two for the thumb) at the middle of the phalanges. Mechanical fixtures guarantee that just a force perpendicular to the finger and in its sagittal plane is exchanged at each point of attachment. Such force component is sensed and it is actively controlled in feedback. The paper illustrates the design and testing of the controller for the thumb exoskeleton. First the mechanical system is analyzed and the features which influence the controller design, such as the presence of unidirectional tendon transmission, are modeled. Then haptic controllers, i.e. feedback controllers aiming at improving the performance of the device when used as a haptic interface for virtual environments or telemanipulation, are designed and tested experimentally. Finally the experimental results are discussed.