Occupational exoskeletons have the potential to prevent work-related musculoskeletal disorders. Their widespread adoption should be promoted by investigating their long-term innocuity, sustained effectiveness, and practicability. This article presents a six-months longitudinal study exploring effects of an arm support exoskeleton (ASE) on six male workers, examining potential side effects, ASE's effectiveness, and its integration into daily work practices. Monthly clinical visits were scheduled to monitor workers’ health. Effectiveness, usability and acceptance metrics were collected at the beginning of the study and after six months. No side effects were found in clinical metrics during the study. Significant reductions, consistent overtime, were observed in shoulder muscle activity (up to 30%) and in effort perception-related metrics (up to 2.4 out of 10 points). Usage time settled around 10% of the monthly work-shift and gradually decreased possibly due to external factors (e.g., social, motivational, and seasonal factors) beyond researchers' control. Results encourage the continuation of similar investigations to strengthen these findings and promote the use of occupational exoskeletons.

Most individuals who experience a stroke exhibit several sensorimotor impairments that limit their independence in everyday activities. Hemiparetic gait is frequently characterized by reduced knee flexion in swing due to knee stiffness or muscle weakness and knee hyperextension or knee buckling in the stance phase. Recently, unilateral-powered orthoses have been designed to overcome the limitations of the passive knee-ankle-foot orthoses. This study presents a unilateral Active Knee Orthosis Exoskeleton, AKO-$\beta$, endowed with a series elastic actuator and designed to assist the knee in flexion and extension movements. The paper describes the system mechatronic design and its characterization on the bench, the control system, and pilot experiments with three post-stroke participants. The device has a weight of 1.78 kg on the user's leg, with a lateral encumbrance of 76 mm. The pilot experiments aimed to verify the effects of the exoskeleton assistance in hemiparetic gait patterns. When walking with the device, participants on average increased the knee flexion on the paretic side by 18.70 deg (+44.9%) during swing and decreased knee hyperextension in stance by 4.50 deg, compared to walking without it. Overall, when walking with the exoskeleton, subjects showed improved Gait Variable Score of the paretic knee profile by 37.5% compared to walking without it. The temporal and spatial gait symmetry indexes did not show clear changes, although an improvement in symmetry was observed in two of the three participants. These preliminary results suggest the potential benefits of the unilateral Active Knee Orthosis exoskeleton to enhance and restore mobility in individuals with hemiparetic gait.

Robotic lower limb prostheses have the power to revolutionize mobility by enhancing gait efficiency and facilitating movement. While several design approaches have been explored to create lightweight and energy-efficient devices, the potential of underactuation remains largely untapped in lower limb prosthetics. Taking inspiration from the natural harmony of walking, in this article, we have developed an innovative active transfemoral prosthesis. By incorporating underactuation, our design uses a single power actuator placed near the knee joint and connected to a differential mechanism to drive both the knee and ankle joints. We conduct comprehensive benchtop tests and evaluate the prosthesis with three individuals who have above-knee amputations, assessing its performance in walking, stair climbing, and transitions between sitting and standing. Our evaluation focuses on gathering position and torque data recorded from sensors integrated into the prosthesis and comparing these measurements to biomechanical data of able-bodied locomotion. Our findings highlight the promise of underactuation in advancing lower limb prosthetics and demonstrate the feasibility of our knee–ankle underactuated design in various tasks, showcasing its ability to replicate natural movement.

Lower-limb exoskeletons are wearable devices whose main purposes are human rehabilitation and bilateral locomotion assistance. In particular, there is a growing interest for their use to symmetrize the gait of hemiparetic patients. This often consists in using the kinematics of the less affected side as a reference for the most affected one. In this work, we followed this approach to design a symmetrization algorithm using the formalism of motor primitives, i.e. a low-dimensional set of signals that provide the desired assistance through their combination. The amount of variables to be stored in memory is thus intrinsically limited, and this framework is particularly adapted to include other modes of assistance and/or transitions between locomotion tasks. In this paper, we report the preliminary validation of this newly developed algorithm with a hip exoskeleton and a single participant replicating hemiparetic walking. Results show that the algorithm effectively managed to reduce both temporal and spatial gait asymmetry.

Lower-limb exoskeletons are robotic devices that can provide assistance to human locomotion. Since they are expected to be used in ecological environments, their control strategy should handle different kinds of daily-life situations. Taking inspiration from the human neuromuscular system - and particularly from the socalled motor primitives - may help in adapting the type of delivered assistance to different locomotion tasks. In this work, we validated the combination of simplified primitives and a musculoskeletal model for assisting healthy subjects with a hip exoskeleton. This framework showed adaptation to the user's gait for different slope inclinations, although its effects on the subject's speed and their perceived effort showed no significant improvement compared to wearing the device in transparent mode.

For a lower limb exoskeleton, accurate and continuous estimation of the gait phase in real time is a fundamental requirement to provide a well-tailored assistive action at the proper time in the gait cycle (GC). This article presents a new gait phase estimator for a portable hip exoskeleton based on discrete wavelet transform (DWT) and adaptive oscillators. The algorithm is capable of continuously tracking the gait phase and identifying the relevant biomechanical gait events online, i.e., heel strike (HS) and toe-off (TO). The proposed method exploits only the hip joint angle signals measured by hip encoders, avoiding the need to use additional sensors to those already built in the exoskeleton. The novel phase estimator has been benchmarked against a state-of-the-art method, based on the maximum flexion angle (MFA), with pressure-sensitive insoles used as the reference ground truth for the event detection. To validate the method, two experimental activities were carried out. Experiments conducted with eight healthy subjects walking on a treadmill at different speeds, with and without hip assistance, demonstrated that the DWT-based method outperformed the MFA method in all operative conditions, reducing the rms of the phase reset error by 64.0% in assistive mode, and identifying the HS and TO events with low delay (0.4% and 1.1% GC, respectively, for HS and TO). Experiments carried out with three transfemoral amputees showed similar performance, paving the way for clinical applications of the method.

The papers in this special section focus on the development and applications supported by wearable robots. Wearable powered robots may be used for functional substitution in patients suffering from motor disorders, rehabilitation, assistance, and strength augmentation. Despite recent technological and scientific achievements, more research is needed to realize the promise of intuitive, easy-to-wear, safe, and effective wearable robots

Dynamic control of robotic exoskeletons is paramount to ensuring safe, synergistic assistive action of functional benefit to users. To date, exoskeleton controllers have excelled in rhythmic and quasi-rhythmic tasks, whereas control methods for assisting discrete movements remain limited by their task-specificity. Inspired by neurophysiological dynamic movement primitives (DMPs), we formulated a novel controller that facilitated a variety of lifting movements using a singleadaptiveDMP (aDMP), for wearable robotic assistance of discrete movements. For a variety of load lifting tasks, we first benchmarked our method's trajectory prediction accuracy against the state-of-the-art DMP using passively recorded exoskeleton sensor data (offline), followed by a functional validation of online aDMP trajectory estimates. Finally, we assessed the functional effects of aDMP-based exoskeletal assistance on joint kinematics and muscular activity during repetitive lifting. The new aDMP method accurately predicted and smoothly synchronized robotic assistance with variable movement trajectories, resulting in reduced muscular activation of the erector spinae muscles (up to 47.6%) while preserving lower-limb joint kinematics and reducing the extension time by 15.5% compared to unassisted conditions. This method holds promise for use in a wide range of wearable robotic applications, including both clinical rehabilitation and user assistance in activities of daily living and/or manual labor.

In this paper we present the design and characterization of a novel Passive Variable Stiffness Joint (pVSJ). pVSJ is the proof of concept of a passive revolute joint with controllable variable stiffness. The current design is intended to be a bench-test for future development towards applications in haptic teleoperation purposed exoskeletons. The main feature of the pVSJ is its capability of varying the stiffness with infinite range based on a simple mechanical system. Moreover, the joint can rotate freely at the zero stiffness case without any limitation. The stiffness varying mechanism consists of two torsional springs, mounted with an offset from the pVSJ rotation center and coupled with the joint shaft by an idle roller. The position of the roller between the pVSJ rotation center and the spring's center is controlled by a linear sliding actuator fitted on the chassis of the joint. The variation of the output stiffness is obtained by changing the distance from the roller-springs contact point to the joint rotation center (effective arm). If this effective arm is null, the stiffness of the joint will be zero. The stiffness increases to reach high stiffness values when the effective arm approaches its maximum value, bringing the roller close to the torsional springs' center. The experimental results matched with the physical-based modeling of the pVSJ in terms of stiffness variation curve, stiffness dependency upon the springs' elasticity, joint deflection and the spring's deflection.

Variable stiffness actuators (VSA) are fostered in robotics for their capability to address physical interaction with a physically adjustable compliance, being advantageous in terms of efficiency, safety and adaptability to unknown environments. Here we introduce the concept of a switching VSA (sVSA), in which a single actuator is used to control the position or the stiffness of a robotic joint according to a mechanical switch. Despite not allowing simultaneous control of both quantities, this architecture has the potential to make the design lighter, requiring one continuously powered actuator, controllable in position, and one additional switch, activated only occasionally between two limit stages: the advantages are the separation of the motors power requirements and a simpler control. A first prototype of a 1-DoF revolute variable-stiffness joint has been built, based on the vsaUT-II developed at the University of Twente, with a novel clutch mechanism allowing continuous and efficient switching. The prototype proved functionality and feasibility of the sVSA concept.

This paper presents a realtime locomotion mode recognition method for an active pelvis orthosis. Five locomotion modes, including sitting, standing still, level-ground walking, ascending stairs, and descending stairs, are taken into consideration. The recognition is performed with locomotion information measured by the onboard hip angle sensors and the pressure insoles. These five modes are firstly divided into static modes and dynamic modes, and the two kinds are classified by monitoring the variation of the relative hip angles of the two legs within a pre-defined period. Static states are further classified into sitting and standing still based on the absolute hip angle. As for dynamic modes, a fuzzy-logic based method is proposed for the recognition. Two event-based locomotion features, including the hip joint angle at the first foot-strike and the center of foot pressure at the first foot-strike are used to calculate the membership of different modes based on the membership function, and the mode with the maximal membership is selected as the target mode. Experimental results with three subjects achieve an average recognition accuracy of 99.87% and average recognition delay of 18.12% of one gait cycle.

The field of wearable robotics is gaining momentum thanks to its potential application in rehabilitation engineering, assistive robotics, and power augmentation. These devices are designed to be used in direct contact with the user to aid with movement or increase the power of specific skeletal joints. The design of the so-called physical human-robot interface is critical, since it determines not only the efficacy of the robot but the kinematic compatibility of the device with the human skeleton and the degree of adaptation to different anthropometries as well. Failing to deal with these problems causes misalignments between the robot and the user joint. Axes misalignment leads to the impossibility of controlling the torque effectively transmitted to the user joint and causes undesired loading forces on articulations and soft tissues. In this paper, we propose a general analytical method for the design of exoskeletons able to assist human joints without being subjected to misalignment effects. This method is based on a kinetostatic analysis of a coupled mechanism (robot-human skeleton) and can be applied in the design of self-aligning mechanisms. The method is exemplified in the design of an assistive robotic chain for a two-degree-of-freedom (DOF) human articulation.

Estimation of the temporal derivatives of a noisy position signal is a ubiquitous problem in industrial and robotics engineering. Here, we propose a new approach to get velocity and acceleration estimates of cyclical/periodic signals near to steady-state regime, by using adaptive oscillators. Our method combines the advantages of introducing no delay, and filtering out the high-frequency noise. We expect this method to be useful in control applications requiring undelayed but smooth estimates of velocity and acceleration (e.g., velocity control and inverse dynamics) of quasi-periodic tasks (e.g., active vibration compensation, robot locomotion, and lower-limb movement assistance).

This paper presents the design and experimental testing of the robotic elbow exoskeleton NEUROBOTICS Elbow Exoskeleton (NEUROExos). The design of NEUROExos focused on three solutions that enable its use for poststroke physical rehabilitation. First, double-shelled links allow an ergonomic physical human-robot interface and, consequently, a comfortable interaction. Second, a four-degree-of-freedom passive mechanism, embedded in the link, allows the user's elbow and robot axes to be constantly aligned during movement. The robot axis can passively rotate on the frontal and horizontal planes 30° and 40°, respectively, and translate on the horizontal plane 30 mm. Finally, a variable impedance antagonistic actuation system allows NEUROExos to be controlled with two alternative strategies: independent control of the joint position and stiffness, for robot-in-charge rehabilitation mode, and near-zero impedance torque control, for patient-in-charge rehabilitation mode. In robot-in-charge mode, the passive joint stiffness can be changed in the range of 24-56 N·m/rad. In patient-in-charge mode, NEUROExos output impedance ranges from 1 N·m/rad, for 0.3 Hz motion, to 10 N·m/rad, for 3.2 Hz motion.

Inferring temporal derivatives (like velocity and acceleration) from a noisy position signal is a well-known challenge in control engineering, due to the intrinsic trade-off between noise filtering and estimation bandwidth. To tackle this problem, in this paper we propose a new approach specifically designed for periodic movements. This approach uses an adaptive oscillator as fundamental building block. It is a tool capable of synchronizing to a periodic input while learning its features (frequency, amplitude, ...) in dedicated state variables. Since the oscillator's input and output are perfectly synchronized during steady-state regime, a non-delayed estimate of the input temporal derivatives can be obtained simply by deriving the output analytical form. Pending a (quasi-)periodic input signal, these temporal derivatives are thus synchronized with the actual kinematics, while the signal bandwidth can be arbitrarily tuned by the intrinsic dynamics of the oscillator. We further validate this approach by developing an impedance-based strategy for assisting human walking in the LOPES lower-limb exoskeleton. Preliminary results with a single participant give rise to three main conclusions. First, our method indeed provides velocity and acceleration estimates of the participant's joint kinematics which are smoother and less delayed with respect to the actual kinematics than using a standard Kalman filter. Second, closing the human-robot loop with a high-gain impedance field depending on the acceleration is not possible with a Kalman filter approach, due to unstable dynamics. In contrast, our approach tolerates high gains (up to 70% of the nominal walking torque), showing its intrinsic stability. Finally, no clear benefit of the acceleration-dependent field with respect to a simpler position-dependent field is visible regarding the reduction of metabolic cost. This last result illustrates the challenge of designing sound assistive strategies for complex tasks like walking.

This paper introduces NEUROExos, an elbow powered exoskeleton for rehabilitation. The NEUROExos is provided with three novel characteristics which address the major problems arising in rehabilitation robotics. A double shell link structure allows for a comfortable human-robot interaction, while a 4-DOF passive mechanism gives a perfect kinematic compatibility with the user. Moreover, NEUROExos is powered by a variable impedance antagonistic actuator, which provides the exoskeleton with a software-controllable passive compliance. We present the main characteristics of the exoskeleton, with a focus on the actuation and control of the platform. Additionally, results on a healthy subject show the relevance of this design during a prototypical rehabilitation task.

This paper introduces a novel exoskeleton device (HANDEXOS) for the rehabilitation of the hand for post-stroke patients. The nature of the impaired hand can be summarized in a limited extension, abduction and adduction leaving the fingers in a flexed position, so the exoskeleton goal is to train a safe extension motion from the typical closed position of the impaired hand. The mechanical design of HANDEXOS offers the possibility to overcome the exoskeleton limits often related to the general high level of complexity of the structure, mechanism and actuation. We describe the mechanical design of the index finger module, the dynamic model and some preliminary experimental results.

This paper presents the development of new transmission components and position controller of the NEURARM hydraulic actuation unit as critical components of a novel robotic arm specifically designed to perform joint experiments between neuroscience and robotics. NEURARM replicates the main functions and characteristics of the human arm during the execution of planar movements like reaching and catching, and it was used to investigate human motion control theories, to develop and evaluate models of control, of learning and of sensory-motor interaction.

We present an incremental approach to the migration of non decomposable COBOL applications to a Web-enabled multi-tier architecture. The relevant software components of the target architecture, namely the communication middleware and the generator of graphical user interfaces, are developed once for all in order to reduce the migration effort. An Eclipse plug-in has also been developed to support the software engineer in the migration of the graphical user interface and in the restructuring and wrapping of the original legacy code. A pilot project on a COBOL legacy system evolved during the last thirty years has been used to experiment the migration strategy and the plug-in