Real-Time Continuous Locomotion Mode Recognition and Transition Prediction for Human With Lower Limb Exoskeleton.

Real-time continuous locomotion mode recognition and seamless timely transition detection is critical for the exoskeleton robot. This study aims to present a comprehensive and innovative framework for locomotion mode recognition and transition prediction, exclusively utilizing inertial measurement unit (IMU) signals from the exoskeleton. In this framework, a CNN-BiLSTM model was developed and trained to be the classifier and a novel majority filter was designed to reduce the transition misjudgment rate. Moreover, a comprehensive evaluation system encompassing eight dimensions for the classifier, incorporating evaluation metrics specifically for transition misjudgment, was proposed. We collected locomotion motion data from six subjects wearing a rigid exoskeleton robot using six IMU sensors on the exoskeleton. The proposed method achieves a high level of recognition accuracy, with an overall average of 99.58% for the five steady locomotion modes (level ground walking (LG), stair ascent/descent (SA/SD), and ramp ascent/descent (RA/RD)) across six subjects following the transition decision. All transitions are recognizable, and the majority can be predicted in advance, with an average prediction time of 353ms. Furthermore, the implementation of majority filter resulted in an average 87.04% reduction in the transition misjudgment rate among six subjects, thereby decreasing the average transition misjudgment rate to 4.82%. Finally, the model was tested on a Jetson Nano to verify its real-time performance. The results presented above were obtained under the condition where either leg could function as the first transition leg and revealed that the developed system was capable of achieving precise locomotion mode recognition and timely transition prediction, with high real-time performance.

Soft Robotics to Enhance Upper Limb Endurance in Individuals with Multiple Sclerosis.

Multiple sclerosis (MS) is a chronic autoimmune disorder that affects the central nervous system and can result in various symptoms, including muscle weakness, spasticity, and fatigue, ultimately leading to the deterioration of the musculoskeletal system. However, in recent years, exosuits have emerged as a game-changing solution to assist individuals with MS during their daily activities. These lightweight and affordable wearable robotic devices have gained immense popularity. In our study, we assessed the performance of an elbow exosuit on eight individuals with MS using high-density electromyography to measure biceps muscle activity. The results demonstrated that our prototype significantly reduced muscle effort during both dynamic and isometric tasks while increasing the elbow range of motion. In addition, the exosuit effectively delayed the onset of muscle fatigue, enhancing endurance for people with MS and enabling them to perform heavy duty tasks for a longer period.

Improving Walking Assistance Efficiency in Real-World Scenarios with Soft Exosuits Using Locomotion Mode Detection.

The use of portable and lightweight wearable assistive devices can improve wearer locomotion efficiency by reducing the metabolic cost of walking. To achieve this goal, assistive technologies must adapt to different locomotion modes to optimize walking assistance. In this work, we developed a novel control strategy for an underactuated soft exosuit featuring a single actuator to assist bilateral hip flexion, which utilized inertial measurement units (IMUs) to discriminate between three different locomotion modes: walking up/down stairs or on level ground. Walking assistance was adjusted in real-time to maximize the assistance provided to the user. In order to preliminary test the effectiveness of this control strategy, four healthy subjects performed a walking task with the exosuit disabled (Exo Off) and enabled (Exo On). Results showed that the kinematics-based IMU classification strategy achieved an overall accuracy exceeding 95% across the three-movement patterns. Subjects were able to save an average of 10.1% on walking energy expenditure with assistance from the wearable device. This work contributes to the development of compact, high-performance lower limb assistive technologies and their development in practical applications.

A robot-aided visuomotor wrist training induces motor and proprioceptive learning that transfers to the untrained ipsilateral elbow.

BACKGROUND: Learning of a visuomotor task not only leads to changes in motor performance but also improves proprioceptive function of the trained joint/limb system. Such sensorimotor learning may show intra-joint transfer that is observable at a previously untrained degrees of freedom of the trained joint. OBJECTIVE: Here, we examined if and to what extent such learning transfers to neighboring joints of the same limb and whether such transfer is observable in the motor as well as in the proprioceptive domain. Documenting such intra-limb transfer of sensorimotor learning holds promise for the neurorehabilitation of an impaired joint by training the neighboring joints. METHODS: Using a robotic exoskeleton, 15 healthy young adults (18-35 years) underwent a visuomotor training that required them to make continuous, increasingly precise, small amplitude wrist movements. Wrist and elbow position sense just-noticeable-difference (JND) thresholds and spatial movement accuracy error (MAE) at wrist and elbow in an untrained pointing task were assessed before and immediately after, as well as 24 h after training. RESULTS: First, all participants showed evidence of proprioceptive and motor learning in both trained and untrained joints. The mean JND threshold decreased significantly by 30% in trained wrist (M: 1.26° to 0.88°) and by 35% in untrained elbow (M: 1.96° to 1.28°). Second, mean MAE in untrained pointing task reduced by 20% in trained wrist and the untrained elbow. Third, after 24 h the gains in proprioceptive learning persisted at both joints, while transferred motor learning gains had decayed to such extent that they were no longer significant at the group level. CONCLUSION: Our findings document that a one-time sensorimotor training induces rapid learning gains in proprioceptive acuity and untrained sensorimotor performance at the practiced joint. Importantly, these gains transfer almost fully to the neighboring, proximal joint/limb system.

Bimanual Motor Strategies and Handedness Role in Human-Robot Haptic Interaction.

Bimanual object manipulation involves using both hands to interact with objects in the environment, and the process requires the central nervous system to process sensory feedback and translate it into motor commands. Although there have been significant advancements in haptics and robotics, the kinematic strategies involved in bimanual coupled tasks are still not fully understood. This study aimed to investigate the dynamic interaction between hands during the manipulation of a shared object using two impedance-controlled exoskeletons programmed to simulate bimanual coupled manipulation of virtual objects. Twenty-six participants (right-handed and left-handed) were asked to use both hands to grab and place simulated objects in specific locations. The virtual objects were rendered with four different dynamic properties, affecting the manipulation strategies used to complete the tasks. The results showed that force asymmetries were related to movement direction and handedness preference, with right-handers exhibiting asymmetries related to movement direction and left-handers showing better control of the force applied between their hands. This is possibly due to their constant exposure to objects designed for right-handed use. Additionally, the haptic properties of the virtual objects influenced task performance in terms of timing and failure for all participants. This study demonstrates the potential of advanced technologies to provide realistic simulations of multi-joint movements involving the entire upper extremities. The findings have implications for the development of training programs for bimanual object manipulation tasks and the design of virtual environments that can enhance the learning process.

A Comprehensive Framework for the Modelling of Cartesian Force Output in Human Limbs.

Neuromuscular functional electrical stimulation represents a valid technique for functional rehabilitation or, in the form of a neuroprosthesis, for the assistance of neurological patients. However, the selected stimulation of single muscles through surface electrodes remains challenging particularly for the upper extremity. In this paper, we present the MyoCeption, a comprehensive setup, which enables intuitive modeling of the user's musculoskeletal system, as well as proportional stimulation of the muscles with 16-bit resolution through up to 10 channels. The system can be used to provide open-loop force control, which, if coupled with an adequate body tracking system, can be used to implement an impedance control where the control loop is closed around the body posture. The system is completely self-contained and can be used in a wide array of scenarios, from rehabilitation to VR to teleoperation. Here, the MyoCeption's control environment has been experimentally validated through comparison with a third-party simulation suite. The results indicate that the musculoskeletal model used for the MyoCeption provides muscle geometries that are qualitatively similar to those computed in the baseline model.

Adaptive Hybrid FES-Force Controller for Arm Exosuit.

Patients suffering from neuromuscular diseases experience motor disabilities which hinder their independence during activities of daily living (ADLs). For such impaired subjects, robotic devices and Functional Electrical Stimulation (FES) are technologies commonly used to rehabilitate lost functions. Nevertheless, both systems present some limitations, and merging FES and robots in Hybrid Robotic Rehabilitation Systems allows to overcome these boundaries. Here we propose for the first time a hybrid cooperative controller involving FES and a soft wearable upper arm exosuit to rehabilitate elbow movements. We tested the designed hybrid controller on six healthy participants. The results showed how the proposed hybrid controller allowed the wearers to perform flexion movements with no significant decrease in accuracy and precision with respect to the exosuit alone, while significantly decreasing the fatigue level by about 63% and delaying its onset with respect to the FES action alone.

Rendering Immersive Haptic Force Feedback via Neuromuscular Electrical Stimulation.

Haptic feedback is the sensory modality to enhance the so-called "immersion", meant as the extent to which senses are engaged by the mediated environment during virtual reality applications. However, it can be challenging to meet this requirement using conventional robotic design approaches that rely on rigid mechanical systems with limited workspace and bandwidth. An alternative solution can be seen in the adoption of lightweight wearable systems equipped with Neuromuscular Electrical Stimulation (NMES): in fact, NMES offers a wide range of different forces and qualities of haptic feedback. In this study, we present an experimental setup able to enrich the virtual reality experience by employing NMES to create in the antagonists' muscles the haptic sensation of being loaded. We developed a subject-specific biomechanical model that estimated elbow torque during object lifting to deliver suitable electrical muscle stimulations. We experimentally tested our system by exploring the differences between the implemented NMES-based haptic feedback (NMES condition), a physical lifted object (Physical condition), and a condition without haptic feedback (Visual condition) in terms of kinematic response, metabolic effort, and participants' perception of fatigue. Our results showed that both in terms of metabolic consumption and user fatigue perception, the condition with electrical stimulation and the condition with the real weight differed significantly from the condition without any load: the implemented feedback was able to faithfully reproduce interactions with objects, suggesting its possible application in different areas such as gaming, work risk assessment simulation, and education.

Soft, Lightweight Wearable Robots to Support the Upper Limb in Activities of Daily Living: A Feasibility Study on Chronic Stroke Patients.

Stroke can be a devastating condition that impairs the upper limb and reduces mobility. Wearable robots can aid impaired users by supporting performance of Activities of Daily Living (ADLs). In the past decade, soft devices have become popular due to their inherent malleable and low-weight properties that makes them generally safer and more ergonomic. In this study, we present an improved version of our previously developed gravity-compensating upper limb exosuit and introduce a novel hand exoskeleton. The latter uses 3D-printed structures that are attached to the back of the fingers which prevent undesired hyperextension of joints. We explored the feasibility of using this integrated system in a sample of 10 chronic stroke patients who performed 10 ADLs. We observed a significant reduction of 30.3 ± 3.5% (mean ± standard error), 31.2 ± 3.2% and 14.0 ± 5.1% in the mean muscular activity of the Biceps Brachii (BB), Anterior Deltoid (AD) and Extensor Digitorum Communis muscles, respectively. Additionally, we observed a reduction of 14.0 ± 11.5%, 14.7 ± 6.9% and 12.8 ± 4.4% in the coactivation of the pairs of muscles BB and Triceps Brachii (TB), BB and AD, and TB and Pectoralis Major (PM), respectively, typically associated to pathological muscular synergies, without significant degradation of healthy muscular coactivation. There was also a significant increase of elbow flexion angle ( 12.1±1.5° ). These results further cement the potential of using lightweight wearable devices to assist impaired users.

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.

Efficacy of wrist robot-aided orthopedic rehabilitation: a randomized controlled trial.

BACKGROUND: In recent years, many studies focused on the use of robotic devices for both the assessment and the neuro-motor reeducation of upper limb in subjects after stroke, spinal cord injuries or affected by neurological disorders. Contrarily, it is still hard to find examples of robot-aided assessment and rehabilitation after traumatic injuries in the orthopedic field. However, those benefits related to the use of robotic devices are expected also in orthopedic functional reeducation. METHODS: After a wrist injury occurred at their workplace, wrist functionality of twenty-three subjects was evaluated through a robot-based assessment and clinical measures (Patient Rated Wrist Evaluation, Jebsen-Taylor and Jamar Test), before and after a 3-week long rehabilitative treatment. Subjects were randomized in two groups: while the control group (n = 13) underwent a traditional rehabilitative protocol, the experimental group (n = 10) was treated replacing traditional exercises with robot-aided ones. RESULTS: Functionality, assessed through the function subscale of PRWE scale, improved in both groups (experimental p = 0.016; control p < 0.001) and was comparable between groups, both pre (U = 45.5, p = 0.355) and post (U = 47, p = 0.597) treatment. Additionally, even though groups' performance during the robotic assessment was comparable before the treatment (U = 36, p = 0.077), after rehabilitation the experimental group presented better results than the control one (U = 26, p = 0.015). CONCLUSIONS: This work can be considered a starting point for introducing the use of robotic devices in the orthopedic field. The robot-aided rehabilitative treatment was effective and comparable to the traditional one. Preserving efficacy and safety conditions, a systematic use of these devices could lead to decrease human therapists' effort, increase repeatability and accuracy of assessments, and promote subject's engagement and voluntary participation. Trial Registration ClinicalTrial.gov ID: NCT04739644. Registered on February 4, 2021-Retrospectively registered, https://www.clinicaltrials.gov/ct2/show/study/NCT04739644 .

Effects of a robot-aided somatosensory training on proprioception and motor function in stroke survivors.

BACKGROUND: Proprioceptive deficits after stroke are associated with poor upper limb function, slower motor recovery, and decreased self-care ability. Improving proprioception should enhance motor control in stroke survivors, but current evidence is inconclusive. Thus, this study examined whether a robot-aided somatosensory-based training requiring increasingly accurate active wrist movements improves proprioceptive acuity as well as motor performance in chronic stroke. METHODS: Twelve adults with chronic stroke completed a 2-day training (age range: 42-74 years; median time-after-stroke: 12 months; median Fugl-Meyer UE: 65). Retention was assessed at Day 5. Grasping the handle of a wrist-robotic exoskeleton, participants trained to roll a virtual ball to a target through continuous wrist adduction/abduction movements. During training vision was occluded, but participants received real-time, vibro-tactile feedback on their forearm about ball position and speed. Primary outcome was the just-noticeable-difference (JND) wrist position sense threshold as a measure of proprioceptive acuity. Secondary outcomes were spatial error in an untrained wrist tracing task and somatosensory-evoked potentials (SEP) as a neural correlate of proprioceptive function. Ten neurologically-intact adults were recruited to serve as non-stroke controls for matched age, gender and hand dominance (age range: 44 to 79 years; 6 women, 4 men). RESULTS: Participants significantly reduced JND thresholds at posttest and retention (Stroke group: pretest: mean: 1.77° [SD: 0.54°] to posttest mean: 1.38° [0.34°]; Control group: 1.50° [0.46°] to posttest mean: 1.45° [SD: 0.54°]; F[2,37] = 4.54, p = 0.017, ηp2 = 0.20) in both groups. A higher pretest JND threshold was associated with a higher threshold reduction at posttest and retention (r = - 0.86, - 0.90, p ≤ 0.001) among the stroke participants. Error in the untrained tracing task was reduced by 22 % at posttest, yielding an effect size of w = 0.13. Stroke participants exhibited significantly reduced P27-N30 peak-to-peak SEP amplitude at pretest (U = 11, p = 0.03) compared to the non-stroke group. SEP measures did not change systematically with training. CONCLUSIONS: This study provides proof-of-concept that non-visual, proprioceptive training can induce fast, measurable improvements in proprioceptive function in chronic stroke survivors. There is encouraging but inconclusive evidence that such somatosensory learning transfers to untrained motor tasks. Trial registration Clinicaltrials.gov; Registration ID: NCT02565407; Date of registration: 01/10/2015; URL: https://clinicaltrials.gov/ct2/show/NCT02565407 .

A robot-aided visuomotor wrist training induces gains in proprioceptive and movement accuracy in the contralateral wrist.

Proprioceptive training is a neurorehabilitation approach known to improve proprioceptive acuity and motor performance of a joint/limb system. Here, we examined if such learning transfers to the contralateral joints. Using a robotic exoskeleton, 15 healthy, right-handed adults (18-35 years) trained a visuomotor task that required making increasingly small wrist movements challenging proprioceptive function. Wrist position sense just-noticeable-difference thresholds (JND) and spatial movement accuracy error (MAE) in a wrist-pointing task that was not trained were assessed before and immediately as well as 24 h after training. The main results are: first, training reduced JND thresholds (- 27%) and MAE (- 33%) in the trained right wrist. Sensory and motor gains were observable 24 h after training. Second, in the untrained left wrist, mean JND significantly decreased (- 32%) at posttest. However, at retention the effect was no longer significant. Third, motor error at the untrained wrist declined slowly. Gains were not significant at posttest, but MAE was significantly reduced (- 27%) at retention. This study provides first evidence that proprioceptive-focused visuomotor training can induce proprioceptive and motor gains not only in the trained joint but also in the contralateral, homologous joint. We discuss the possible neurophysiological mechanism behind such sensorimotor transfer and its implications for neurorehabilitation.

Robotic Assessment of Wrist Proprioception During Kinaesthetic Perturbations: A Neuroergonomic Approach.

Position sense refers to an aspect of proprioception crucial for motor control and learning. The onset of neurological diseases can damage such sensory afference, with consequent motor disorders dramatically reducing the associated recovery process. In regular clinical practice, assessment of proprioceptive deficits is run by means of clinical scales which do not provide quantitative measurements. However, existing robotic solutions usually do not involve multi-joint movements but are mostly applied to a single proximal or distal joint. The present work provides a testing paradigm for assessing proprioception during coordinated multi-joint distal movements and in presence of kinaesthetic perturbations: we evaluated healthy subjects' ability to match proprioceptive targets along two of the three wrist's degrees of freedom, flexion/extension and abduction/adduction. By introducing rotations along the pronation/supination axis not involved in the matching task, we tested two experimental conditions, which differed in terms of the temporal imposition of the external perturbation: in the first one, the disturbance was provided after the presentation of the proprioceptive target, while in the second one, the rotation of the pronation/ supination axis was imposed during the proprioceptive target presentation. We investigated if (i) the amplitude of the perturbation along the pronation/supination would lead to proprioceptive miscalibration; (ii) the encoding of proprioceptive target, would be influenced by the presentation sequence between the target itself and the rotational disturbance. Eighteen participants were tested by means of a haptic neuroergonomic wrist device: our findings provided evidence that the order of disturbance presentation does not alter proprioceptive acuity. Yet, a further effect has been noticed: proprioception is highly anisotropic and dependent on perturbation amplitude. Unexpectedly, the configuration of the forearm highly influences sensory feedbacks, and significantly alters subjects' performance in matching the proprioceptive targets, defining portions of the wrist workspace where kinaesthetic and proprioceptive acuity are more sensitive. This finding may suggest solutions and applications in multiple fields: from general haptics where, knowing how wrist configuration influences proprioception, might suggest new neuroergonomic solutions in device design, to clinical evaluation after neurological damage, where accurately assessing proprioceptive deficits can dramatically complement regular therapy for a better prediction of the recovery path.

A soft, synergy-based robotic glove for grasping assistance.

This paper presents a soft, tendon-driven, robotic glove designed to augment grasp capability and provide rehabilitation assistance for postspinal cord injury patients. The basis of the design is an underactuation approach utilizing postural synergies of the hand to support a large variety of grasps with a single actuator. The glove is lightweight, easy to don, and generates sufficient hand closing force to assist with activities of daily living. Device efficiency was examined through a characterization of the power transmission elements, and output force production was observed to be linear in both cylindrical and pinch grasp configurations. We further show that, as a result of the synergy-inspired actuation strategy, the glove only slightly alters the distribution of forces across the fingers, compared to a natural, unassisted grasping pattern. Finally, a preliminary case study was conducted using a participant suffering from an incomplete spinal cord injury (C7). It was found that through the use of the glove, the participant was able to achieve a 50% performance improvement (from four to six blocks) in a standard Box and Block test.

Relationship Between Muscular Activity and Assistance Magnitude for a Myoelectric Model Based Controlled Exosuit.

The growing field of soft wearable exosuits, is gradually gaining terrain and proposing new complementary solutions in assistive technology, with several advantages in terms of portability, kinematic transparency, ergonomics, and metabolic efficiency. Those are palatable benefits that can be exploited in several applications, ranging from strength and resistance augmentation in industrial scenarios, to assistance or rehabilitation for people with motor impairments. To be effective, however, an exosuit needs to synergistically work with the human and matching specific requirements in terms of both movements kinematics and dynamics: an accurate and timely intention-detection strategy is the paramount aspect which assume a fundamental importance for acceptance and usability of such technology. We previously proposed to tackle this challenge by means of a model-based myoelectric controller, treating the exosuit as an external muscular layer in parallel to the human biomechanics and as such, controlled by the same efferent motor commands of biological muscles. However, previous studies that used classical control methods, demonstrated that the level of device's intervention and effectiveness of task completion are not linearly related: therefore, using a newly implemented EMG-driven controller, we isolated and characterized the relationship between assistance magnitude and muscular benefits, with the goal to find a range of assistance which could make the controller versatile for both dynamic and static tasks. Ten healthy participants performed the experiment resembling functional daily activities living in separate assistance conditions: without the device's active support and with different levels of intervention by the exosuit. Higher assistance levels resulted in larger reductions in the activity of the muscles augmented by the suit actuation and a good performance in motion accuracy, despite involving a decrease of the movement velocities, with respect to the no assistance condition. Moreover, increasing torque magnitude by the exosuit resulted in a significant reduction in the biological torque at the elbow joint and in a progressive effective delay in the onset of muscular fatigue. Thus, contrarily to classical force and proportional myoelectric schemes, the implementation of an opportunely tailored EMG-driven model based controller affords to naturally match user's intention detection and provide an assistance level working symbiotically with the human biomechanics.

An Assistive Soft Wrist Exosuit for Flexion Movements With an Ergonomic Reinforced Glove.

Soft exosuits are a promising solution for the assistance and augmentation of human motor abilities in the industrial field, where the use of more symbiotic wearable robots can avoid excessive worker fatigue and improve the quality of the work. One of the challenges in the design of soft exosuits is the choice of the right amount of softness to balance load transfer, ergonomics, and weight. This article presents a cable-driven based soft wrist exosuit for flexion assistance with the use of an ergonomic reinforced glove. The flexible and highly compliant three-dimensional (3D)-printed plastic structure that is sewn on the glove allows an optimal force transfer from the remotely located motor to the wrist articulation and to preserve a high level of comfort for the user during assistance. The device is shown to reduce fatigue and the muscular effort required for holding and lifting loads in healthy subjects for weights up to 3 kg.

Assessment of human wrist rigidity and pain in post-traumatic patients.

The aim of this work is to present a novel robot-based method to assess the sources of a lack of functionality in patients with recent traumatic wrist injuries. Post-traumatic patients experience limited range of motion as well as strength and proprioceptive deficits. These dysfunctions are related to different complications that usually follow the injuries: pain, increased rigidity, lack of movement fluency and loss of stability could arise differently, according to the severity, site and kind of lesion. Their quantitative evaluation could be essential to target rehabilitation treatments to the specific problem and to optimize and speed up the functional recovery. The use of robotic devices for assessment not only ensures objectivity and repeatability, but could also help to estimate the goodness of the evaluation itself, in terms of reliability and patient's engagement. Ten subjects with different types of wrist injuries were enrolled in this study and required to perform passive robot-guided reaching movements. Forces and angular positions were used to evaluate subject's range of motion, rigidity and pain that, considered together, allowed a comprehensive characterization of the level of healing and functionality achieved by each subject.

On the edge between soft and rigid: an assistive shoulder exoskeleton with hyper-redundant kinematics.

In this paper, we present a prototype of an innovative portable shoulder exoskeleton for human assistance and augmentation. The device provides torques to flexion/extension movements of the shoulder, compensating for gravitational forces, and is passively compliant along the remaining degrees of freedom letting the shoulder moving along them. The novelty of our system is a flexible link, made of a hyper-redundant passive structure, that avoids joint misalignment by adapting to the complex movements of the humerus head, similarly to a soft component. The flexible link is compliant to rotations around one axis but rigid around the other two axes, allowing transmission of flexion/extension torque but kinematically transparent along the remaining degrees of freedom. The device is light weight and allows to cover around the 82% of the shoulder flexion/extension range of motion. The exoskeleton was tested on a cohort of 5 healthy subjects, monitoring shoulder kinematics, interaction forces and acquiring the electromyography of three major muscles contributing to shoulder flexion. During both static postures and dynamic movements, assistance from the exoskeleton resulted in a significant reduction of muscular effort in the anterior (-32.2% in static, -25.3% in dynamic) and medial deltoid (56.9% in static, -49.6% in dynamic) and an average reduction of the biceps brachii.