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In this paper, the design and experimental validation of a knee exoskeleton are presented. The exoskeleton can capture the negative work from the wearer's knee motion while decreasing the muscle activities of the wearer. First, the human knee biomechanics during the normal walking is described. Then, the design of the exoskeleton is presented. The exoskeleton mainly includes a left one-way transmission mechanism, a right one-way transmission mechanism, and a front transmission mechanism. The left and right one-way transmission mechanisms are designed to capture the negative work from the wearer's knee motion in the stance and swing phases, respectively. The front transmission mechanism is designed to transform the bidirectional rotation of the wearer's knee joint into the generator unidirectional rotation. Additionally, the modeling and analysis of the energy harvesting of the exoskeleton is described. Finally, walking experiments are performed to validate the effectiveness of the proposed knee exoskeleton. The testing results verify that the developed knee exoskeleton can output a maximum power of 5.68 ± 0.23 W and an average power of 1.45 ± 0.13 W at a speed of 4.5 km/h in a gait cycle. The average rectus femoris and semitendinosus activities of the wearers in a gait cycle are decreased by 3.68% and 3.40%, respectively. [ABSTRACT FROM AUTHOR]

Wearable robots, sometimes known as exoskeletons, are incredible devices for improving human strength, reducing fatigue, and restoring impaired mobility. The control of powered exoskeletons, on the other hand, is still a challenge. This necessitates the development of a technique to simulate exoskeleton–wearer interaction. This study uses a two-dimensional human skeletal model with a powered knee exoskeleton to predict the optimal lifting motion and assistive torque. For lifting motion prediction, an inverse dynamics optimization formulation is utilized. In addition, the electromechanical dynamics of the exoskeleton DC motor are modeled in the lifting optimization formulation. The design variables are human joint angle profiles and exoskeleton motor current profiles. The human joint torque square is minimized subject to physical and lifting task constraints. Then, the lifting optimization problem is solved by the gradient-based sparse nonlinear optimizer (SNOPT). Furthermore, the optimal exoskeleton torque is implemented through a two-phase control strategy to provide optimal assistance in lifting. Experimental validations of the optimal control with 6 Nm and 16 Nm maximum assistive torque are presented. Both 6 Nm and 16 Nm maximum optimal assistance of the exoskeletons reduce the mean values of vastus lateralis, biceps femoris, and latissimus dorsi muscle activations compared to the lifting without the exoskeleton. However, the mean value of the vastus medialis activation is increased by a small amount for the exoskeleton case, although its peak value is reduced. Finally, the experimental results demonstrate that the proposed lifting optimization formulation and control strategy are promising for powered knee exoskeleton for lifting tasks. [ABSTRACT FROM AUTHOR]

In an unstructured environment, the arm can perform complicated tasks with rapidity, flexibility, and robustness. It is difficult to configure multiple artificial muscles similar to an arm in the compact space of a robotic arm. When muscle tension is transferred, mechanisms like tendon-sheath/tendon-pulley may be installed in a compact space to develop musculoskeletal robots that are closer to the arm. However, handling variable frictional nonlinearity and elastic cable deformation is necessary for transmission stability. In this study, the modular artificial muscle system (MAMS), including motor cable artificial muscle and tendon sheath–pulley system (TSPS), that can be installed remotely and transmit muscle tension in narrow paths, is designed. The feed-forward multi-layer neural network (FF-MNN) approach is utilized to discuss the relationship between the measurable input tension of TSPS and the unmeasurable output tension and cable elongation. Subsequently, the lightweight musculoskeletal arm (LM-Arm) is built to verify the validity of MAMS. Through trials, the experiments of MAMS after friction compensating and the LM-Arm's end-point 3D trajectory tracking are investigated. The results show that average errors of the active and passive muscles tension are 3.87 N and 3.51 N, respectively, under conditions of larger load and higher contraction velocity. The average muscle length error of trajectory tracking is 0.00078 m (0.72%). The suggested MAMS may successfully build a musculoskeletal robot that has similar flexibility and morphology to the arm. It can also be utilized to power various pieces of machinery, such as rescue robot, invasive surgical robots, dexterous hands, and wearable exoskeletons. [ABSTRACT FROM AUTHOR]

Exoskeleton robot can assist people and reduce energy consumption when they walk with heavy weight, so as to protect their health and travel longer distances. This work analyzes the cross gait during walking and designs a dual-drive four joint time-sharing assistance exoskeleton system, which controls the four joints through two motors to realize the assistance to the wearer's movement process. The control curve and adaptive control algorithm are designed to help different people with various walking gaits and speeds, the effectiveness of exoskeleton system is proved by testing metabolism. When the exoskeleton wearer carries 25 kg weight (load equal to 36% of body mass) and travels at the average speed of 5 km/h, the metabolic rate of the exoskeleton wearers decreases by an average of 7.79%, the reduction magnitude is comparable to the effect of taking off 7.33 kg during walking. [ABSTRACT FROM AUTHOR]

With the excellent characteristic of intrinsic compliance, pneumatic artificial muscle can improve the interaction comfort of wearable robotic devices. This paper resolves the safety tracking control problem of a pneumatically actuated lower limb exoskeleton system. A single-parameter adaptive fuzzy control strategy is proposed with high control precision and full state constraints for the safe gait training tasks. Based on the barrier Lyapunov function, all signals in the closed-loop system can be bounded in finite time, which guarantees the deviation of the exoskeleton's moving trajectory within a bounded range. Furthermore, with the proposed single-parameter adaptive law, the computational burden and the complexity of the control are reduced significantly. Finally, numerical simulations, no-load tracking experiments, and passive and active gait training experiments with healthy subjects validate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The lower extremity rehabilitation exoskeleton is mainly used to help patients with movement disorders complete rehabilitation training. For the human-machine interaction problem of the lower limb rehabilitation exoskeleton, a fuzzy radial-based impedance (RBF-FVI) controller is proposed in this study. A six degree of freedom (DOF) lower extremity rehabilitation exoskeleton was developed, and the human-machine coupling dynamics model was established. To realize the compliance control of the human-machine coupling system, a novel RBF-FVI controller is designed, which includes an inner-loop fuzzy position control module and an outer-loop impedance control module. The inner-loop fuzzy position control module is mainly used to achieve the tracking control of the desired training trajectory and position adjustment amount. The outer-loop impedance control module regulates the impedance parameters and compensates for the uncertainty terms. The superiority of the proposed controller in trajectory following is verified through simulation and comparison tests. The hardware test of the human-machine coupling system was carried out, and the test results showed that the subject and the exoskeleton system could realize a coordinated and smooth movement. [ABSTRACT FROM AUTHOR]

Aiming at problems of low optimization accuracy and slow convergence speed in the gait optimization algorithm of lower limb exoskeleton robot, a novel gait multi-objectives optimization strategy based on beetle swarm optimization (BSO)-elite opposition-based learning (EOL) levy flight foraging (LFF) algorithm was proposed. In order to avoid the algorithm from falling into the local optimum, the EOL strategy with global search capability, the LFF strategy with local search capability and the dynamic mutation strategy with high population diversity were introduced to improve optimization performance. The optimization was performed by establishing a multi-objectives optimization function with the robot's gait zero moment point (ZMP) stability margin and driving energy consumption. The joint comparative tests were carried out in SolidWorks, ADAMS and MATLAB software. The simulation results showed that compared with the particle swarm optimization algorithm and the BSO algorithm, the ZMP stability margin obtained by the BSO-EOLLFF algorithm was increased, and the average driving energy consumption was reduced by 25.82% and 17.26%, respectively. The human-machine experiments were conducted to verify the effectiveness and superiority. The robot could realize stable and smooth walking with less energy consumption. This research will provide support for the application of exoskeleton robot. [ABSTRACT FROM AUTHOR]

Stroke has a considerable incidence in the world population and would cause sequelae in the upper limbs. One way to increase the efficiency in the rehabilitation process of patients with these sequelae is through robot-assisted therapy. The present study developed a portable robotic orthosis called Pinotti Portable Robotic Exoskeleton (PPRE) and validated its functioning in clinical tests. The static and dynamic parts of the device modules are described. Design issues, such as heavyweight and engine positioning, have been optimized. The implementation of control was through a smartphone application that communicates with a microcontroller to perform desired movements. Four individuals with motor impairment of the upper limbs due to stroke performed clinical tests to validate the device. Participants did not mention pain, discomfort, tingling, and paresthesia. The robotic device showed the ability to perform the flexion and extension movements of the fingers and elbow. The PPRE was confirmed to be adequate and functional at different levels of motor impairment assessed. The orthosis presented advantages over the currently existing devices, concerning its biomechanical functioning, portability, comfort, and versatility. Thus, the apparatus has the great innovative potential to become a device for home use, serving as an aid to the therapist and facilitating the rehabilitation of patients after an injury. In a larger sample, future studies are needed to assess the effect of a robotic orthosis on the level of rehabilitation in individuals with upper limb impairment. [ABSTRACT FROM AUTHOR]

As one of the research hotspots in the field of rehabilitation robotics, the upper limb exoskeleton robot has been widely used in the field of rehabilitation. However, the existing methods cannot comprehensively and accurately reflect the motion state of patients, which may lead to overtraining and secondary injury of patients in the process of rehabilitation training. In this paper, an upper limb exoskeleton control method based on mixed perception model of motion intention and intensity is proposed, which is based on the 6 degree-of-freedom upper limb rehabilitation exoskeleton in the laboratory. First, the kinematic information and heart rate information in the rehabilitation process of patients are collected, corresponding to patients' motion intention and motion intensity, and fused to obtain the mixed perception vector. Second, the motion perception model based on long short-term memory neural network is established to realize the prediction of upper limb motion trajectory of patients and compared with back-propagation neural network to prove its effectiveness. Finally, the control system is built, and both offline and online test of the control method proposed are implemented. The experimental results show that the method can achieve comprehensive motion state perception of patients, realize real-time and accurate prediction trajectory according to human motion intention and intensity. The average prediction accuracy is 95.3%, and predicted joint angle error is less than 5 degrees. Therefore, the control method based on mixed perception model has good robustness and universality, which provides a new method for the active control of upper limb exoskeleton. [ABSTRACT FROM AUTHOR]

With diverse areas of applications, wearable robotic exoskeleton devices have gained attention in the past decade. These devices cover one or more human limbs/joints and have been presented for rehabilitation, strength augmentation and interaction with virtual reality. This research is focused towards design, modeling and control of a novel series elastic actuation (SEA) based index finger exoskeleton with a targeted torque rendering capability of 0.3 Nm and a force control bandwidth of 3 Hz. The proposed design preserves the natural range of motion of the finger by incorporating five passive and two actively actuated joints and provides active control of metacarpophalangeal and proximal interphalangeal joints. Forward and inverse kinematics for both position and velocity have been solved using closed loop vector analysis by including human finger as an integral part of the system. For accurate force control, a cascaded control structure has been presented. Force controlled trajectories have been proposed to guide the finger along preprogrammed virtual paths. Such trajectories serve to gently guide the finger towards the correct rehabilitation protocol, thus acting as an effective replacement of intervention by a human therapist. Extensive computer simulations have been performed before fabricating a prototype and performing experimental validation. Results show accurate modeling and control of the proposed design. [ABSTRACT FROM AUTHOR]

Summary: The knee joint plays a significant role in ground clearness, which is a crucial subtask of normal walking and avoiding falls. While post-stroke survivors are often faced with muscle weakness during walking, which leads to inadequate knee flexion. The lack of ground clearance caused by inadequate knee flexion will severely impede walking, increase metabolic exertion, and increase the risk of falls. A compliant exoskeleton robot possesses more favorable edges than other rigid ones in lightweight, safety, sense of comfort, and so on. We developed a new type of soft exoskeleton robot to assist the knee joint to achieve desired movements with Bowden cable transmitting force and torque. With the agonist–antagonist driving method, like a group of muscles working, we have explored dual-motors structure to realize the knee flexion function. It has built a standard dynamic model to analyze stability and realize the control law. We have conducted simulation and prototype experiments to verify the feasibility and usefulness of our method. The results show that the device can compensate for the lack of the knee joint driving force and realize the reference movement. Finally, we concluded that our method is a desirable way, and the scheme could improve the knee flexion ability and clearing ground. [ABSTRACT FROM AUTHOR]

In order to assist patients with lower limb disabilities in normal walking, a new trajectory learning scheme of limb exoskeleton robot based on dynamic movement primitives (DMP) combined with reinforcement learning (RL) was proposed. The developed exoskeleton robot has six degrees of freedom (DOFs). The hip and knee of each artificial leg can provide two electric-powered DOFs for flexion/extension. And two passive-installed DOFs of the ankle were used to achieve the motion of inversion/eversion and plantarflexion/dorsiflexion. The five-point segmented gait planning strategy is proposed to generate gait trajectories. The gait Zero Moment Point stability margin is used as a parameter to construct a stability criteria to ensure the stability of human-exoskeleton system. Based on the segmented gait trajectory planning formation strategy, the multiple-DMP sequences were proposed to model the generation trajectories. Meanwhile, in order to eliminate the effect of uncertainties in joint space, the RL was adopted to learn the trajectories. The experiment demonstrated that the proposed scheme can effectively remove interferences and uncertainties. [ABSTRACT FROM AUTHOR]

Efficient and high-precision identification of dynamic parameters is the basis of model-based robot control. Firstly, this paper designed the structure and control system of the developed lower extremity exoskeleton robot. The dynamics modeling of the exoskeleton robot is performed. The minimum parameter set of the identified parameters is determined. The dynamic model is linearized based on the parallel axis theory. Based on the beetle antennae search algorithm (BAS) and particle swarm optimization (PSO), the beetle swarm optimization algorithm (BSO) was designed and applied to the identification of dynamic parameters. The update rule of each particle originates from BAS, and there is an individual's judgment on the environment space in each iteration. This method does not rely on the historical best solution in the PSO and the current global optimal solution of the individual particle, thereby reducing the number of iterations and improving the search speed and accuracy. Four groups of test functions with different characteristics were used to verify the performance of the proposed algorithm. Experimental results show that the BSO algorithm has a good balance between exploration and exploitation capabilities to promote the beetle to move to the global optimum. Besides, the test was carried out on the exoskeleton dynamics model. This method can obtain independent dynamic parameters and achieve ideal identification accuracy. The prediction result of torque based on the identification method is in good agreement with the ideal torque of the robot control. [ABSTRACT FROM AUTHOR]

Lower-body exoskeleton control that adapts to users and provides assistance-as-needed can increase user participation and motor learning and allow for more effective gait rehabilitation. Adaptive model-based control methods have previously been developed to consider a user's interaction with an exoskeleton; however, the predefined dynamics models required are challenging to define accurately, due to the complex dynamics and nonlinearities of the human-exoskeleton interaction. Model-free deep reinforcement learning (DRL) approaches can provide accurate and robust control in robotics applications and have shown potential for lower-body exoskeletons. In this paper, we present a new model-free DRL method for end-to-end learning of desired gait patterns for over-ground gait rehabilitation with an exoskeleton. This control technique is the first to accurately track any gait pattern desired in physiotherapy without requiring a predefined dynamics model and is robust to varying post-stroke individuals' baseline gait patterns and their interactions and perturbations. Simulated experiments of an exoskeleton paired to a musculoskeletal model show that the DRL method is robust to different post-stroke users and is able to accurately track desired gait pattern trajectories both seen and unseen in training. [ABSTRACT FROM AUTHOR]

We present a method to drastically reduce the required number of degrees-of-freedom (DOFs) needed for walking for each leg of bipedal robots and lower-limb exoskeletons. This approach releases more legs DOFs in the null space to do other tasks, instead of unnecessarily constraining them. It uses relative reference frames to control relative motion between the two feet, instead of the usual method of controlling foot movement with respect to fixed reference frames. In its basic form, it controls the bipedal walking holistically using two controllers: (1) world space control using relative feet motion and (2) null-space control of the legs posture. [ABSTRACT FROM AUTHOR]

By recognizing the motion of the healthy side, the lower limb exoskeleton robot can provide therapy to the affected side of stroke patients. To improve the accuracy of motion intention recognition based on sensor data, the research based on deep learning was carried out. Eighty healthy subjects performed gait experiments under five different gait environments (flat ground, 10 ${}^\circ$ upslope and downslope, and upstairs and downstairs) by simulating stroke patients. To facilitate the training and classification of the neural network, this paper presents template processing schemes to adapt to different data formats. The novel algorithm model of a hybrid network model based on convolutional neural network (CNN) and Long–short-term memory (LSTM) model is constructed. To mitigate the data-sparse problem, a spatial–temporal-embedded LSTM model (SQLSTM) combining spatial–temporal influence with the LSTM model is proposed. The proposed CNN-SQLSTM model is evaluated on a real trajectory dataset, and the results demonstrate the effectiveness of the proposed model. The proposed method will be used to guide the control strategy design of robot system for active rehabilitation training. [ABSTRACT FROM AUTHOR]

The design and development of an upper limb exoskeleton are being discussed for the tele-operation in order to control the KUKA KR5 industrial robot. When sufficient resolution is not provided by the visual feedback, feedback of haptic provides a qualitative understanding of changes in the remote conditions. This also provides tactile feedback from the virtual and real environment. Peg in a hole operation using exoskeleton works as the master for tele-operation in order to control the robot using immersive environment as visual feedback for the operator. The application of this work can be implemented as a nuclear power generation plant. [ABSTRACT FROM AUTHOR]

In order to improve the working performance of the lower limb rehabilitation robot and the safety of the trained object, the mechanical characteristics of a cable-driven lower limb rehabilitation robot (CDLR) are studied. The dynamic model of the designed CDLR was established. Four kinds of cable tension optimization algorithms were proposed to obtain a good rehabilitation training effect, and the quality of the feasible workspace of the CDLR was analyzed. Finally, a real-time evaluation index of the cable tension optimization algorithms was given to measure the calculation speed of the optimization algorithms. The numerical research results were provided to confirm the characteristics of the four kinds of the optimization algorithms. The research results provide a basis for the follow-up research on the safety and compliance control strategy of the CDLR system. [ABSTRACT FROM AUTHOR]

With the widespread development of leg exoskeletons to provide external force-based repetitive training for gait rehabilitation, the prospect of undesired movement adaptation due to applied forces and imposed constraints require adequate investigation. A cable-driven leg exoskeleton, CDLE, presents a lightweight, flexible, and redundantly actuated architecture that enables the possibility of system parameters modulation to alter human–robot interaction while applying the desired forces. In this work, multi-joint stiffness performance of CDLE is formulated to systematically analyze human–CDLE interaction. Further, potential alterations in CDLE architecture are presented to tune human–CDLE interaction that favors the desired human leg movement during a gait rehabilitation paradigm. [ABSTRACT FROM AUTHOR]

SUMMARY: Over the past decade, research on human–robot collaboration has grown exponentially, motivated by appealing applications to improve the daily life of patients/operators. A primary requirement in many applications is to implement highly "transparent" control laws to reduce the robot impact on human movement. This impact may be quantified through relevant motor control indices. In this paper, we show that control laws based on careful identification procedures improve transparency compared to classical closed-loop position control laws. A new performance index based on the ratio between electromyographic activity and limb acceleration is also introduced to assess the quality of human exoskeleton interaction. [ABSTRACT FROM AUTHOR]

SUMMARY: It was reported that about 10% of people suffer from painful knee arthritis, and a quarter of them were severely disabled. The core activities of daily living were severely limited by knee osteoarthritis (KOA). In order to reduce knee pain and prolong the life of the knee joint, there has been an increasing demand on the development of exoskeletons, for prevention and treatment. The course of KOA was closely related to the biomechanics of knee joint, and the pathogenesis was summarized based on the biomechanics of knee joint. For the prevention and clinical treatment, exoskeletons are classified into three categories: prevention, treatment, and rehabilitation after the operation. Furthermore, the design concepts, actuators, sensors, control strategies, and evaluation criteria were presented. Finally, the shortcomings and limitations were summarized. It is useful for researchers to develop suitable exoskeletons in the future. [ABSTRACT FROM AUTHOR]

SUMMARY: Accurate torque control is a critical issue in the compliant human–robot interaction scenario, which is, however, challenging due to the ever-changing human intentions, input delay, and various disturbances. Even worse, the performances of existing control strategies are limited on account of the compromise between precision and stability. To this end, this paper presents a novel high-performance torque control scheme without compromise. In this scheme, a new nonlinear disturbance observer incorporated with equivalent control concept is proposed, where the faster convergence and stronger anti-noise capability can be obtained simultaneously. Meanwhile, a continuous fractional power control law is designed with an iteration method to address the matched/unmatched disturbance rejection and global finite-time convergence. Moreover, the finite-time stability proof and prescribed control performance are guaranteed using constructed Lyapunov function with adding power integrator technique. Both the simulation and experiments demonstrate enhanced control accuracy, faster convergence rate, perfect disturbance rejection capability, and stronger robustness of the proposed control scheme. Furthermore, the evaluated assistance effects present improved gait patterns and reduced muscle efforts during walking and upstair activity. [ABSTRACT FROM AUTHOR]

SUMMARY: In this paper, hybrid control of central pattern generators (CPGs), along with an adaptive supper-twisting sliding mode (ASTSM) control based on supper-twisting state observer, is proposed to guard against disturbances and uncertainties. Rhythmic and coordinated signals are generated using CPGs. In addition, to overcome the chattering of conventional sliding mode, supper-twisting sliding mode has been applied. The ASTSM method triggers sliding variables, and its derivatives tend to zero continuously in the presence of the uncertainties. Moreover, to acquire maximum stability, the desired trajectory of the upper limb based on zero moment point criterion is designed. [ABSTRACT FROM AUTHOR]

SUMMARY: The robotic intervention has great potential in the rehabilitation of post-stroke patients to regain their lost mobility. In this paper, firstly, we present a design of a novel, 7 degree-of-freedom (DOF) upper limb robotic exoskeleton (u-Rob) that features shoulder scapulohumeral rhythm with a wide range of motions (ROM) compared to other existing exoskeletons. An ergonomic shoulder mechanism with two passive DOF was included in the proposed exoskeleton to provide scapulohumeral motion with corresponding full ROM. Also, the joints of u-Rob have more range of motions compared to its existing counterparts. Secondly, we propose a fractional sliding mode control (FSMC) to control u-Rob. Applying the Lyapunov theory to the proposed control algorithm, we showed the stability of it. To control u-Rob, FSMC has shown effectiveness to handle unmodeled dynamics (e.g. friction, disturbance, etc.) in terms of better tracking and chatter compared to traditional SMC. [ABSTRACT FROM AUTHOR]

Summary: Wearable devices are fast evolving to address mobility and autonomy needs of elderly people who would benefit from physical assistance. Recent developments in soft robotics provide important opportunities to develop soft exoskeletons (also called exosuits) to enable both physical assistance and improved usability and acceptance for users. The XoSoft EU project has developed a modular soft lower limb exoskeleton to assist people with low mobility impairments. In this paper, we present the design of a soft modular lower limb exoskeleton to improve person's mobility, contributing to independence and enhancing quality of life. The novelty of this work is the integration of quasi-passive elements in a soft exoskeleton. The exoskeleton provides mechanical assistance for subjects with low mobility impairments reducing energy requirements between 10% and 20%. Investigation of different control strategies based on gait segmentation and actuation elements is presented. A first hip–knee unilateral prototype is described, developed, and its performance assessed on a post-stroke patient for straight walking. The study presents an analysis of the human–exoskeleton energy patterns by way of the task-based biological power generation. The resultant assistance, in terms of power, was 10.9% ± 2.2% for hip actuation and 9.3% ± 3.5% for knee actuation. The control strategy improved the gait and postural patterns by increasing joint angles and foot clearance at specific phases of the walking cycle. [ABSTRACT FROM AUTHOR]

Summary: Using wearable robots is an effective means of rehabilitation for stroke survivors, and effective recognition of human motion intentions is a key premise in controlling wearable robots. In this paper, we propose an inertial measurement unit (IMU)-based gait phase detection system. The system consists of two IMUs that are tied on the thigh and on the shank, respectively, for collecting acceleration and angular velocity. Features were extracted using a sliding window of 150 ms in length, which was then fed into a quadratic discriminant analysis (QDA) classifier for classification. We recruited five stroke survivors to test our system. They walked at their own preferred speed on the level ground. Experimental results show that our proposed system has the ability of recognizing the gait phase of stroke survivors. All recognition accuracy results are above 96.5%, and detections are about 5–15 ms in advance of time. In addition, using only one IMU can also give reliable recognition results. This paper proposes an idea about the further research on human–computer interaction for the control of wearable robots. [ABSTRACT FROM AUTHOR]

Summary: This paper studies the problem of optimizing the kinematic structure of an eight degree-of-freedom upper-limb rehabilitation exoskeleton. The objective of optimization is achieving minimum volume and maximum dexterity in the workspace of daily activities specified by a set of upper-arm configurations. To formulate the problem, a new index is proposed for effective characterization of kinematic dexterity for wearable robots. Additionally, a set of constraints are defined to ensure that the optimal design can cover the desired workspace of the exoskeleton, while singular configurations and physical interferences are avoided. The formulated multi-objective optimization problem is solved using an evolutionary algorithm (Non-dominated Sorting Genetic Algorithm II) and the weighted sum approach. Among the resulted optimal points, the point with least sensitivity with respect to the variations of design variables is chosen as the final design. [ABSTRACT FROM AUTHOR]

Summary: Exoskeleton robots have been widely used in many fields at present. When wearing the exoskeleton to operate, the wearer may be unconscious of the position of exoskeleton or affected by the surrounding environment, causing collision between two arms of exoskeleton or between arms and environment. The collision may result in the exoskeleton destroyed or even the wearer injured. This paper proposes a hierarchical safety control strategy for exoskeleton robots based on maximum correntropy Kalman filter and bounding box to ensure safe operation. Accurate joint angle prediction can be obtained by filtering out non-Gaussian impulsive noise using maximum correntropy criterion as evaluation criterion. Relative position relationship of the arms can be derived based on bounding box to realize hierarchical safe control. Enough experiments have been carried out, and the results validated the feasibility of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a novel three-degree of freedom (DOF) sensorized remote-center-of-motion (RCM) ankle module for a military-purpose lower-limb exoskeleton. A military-purpose exoskeleton should assist and follow the fast and dexterous motion of a soldier in rough terrain environments. Among the lower-limb joints, the ankle joint plays an important role in stabilizing walking motion during the stance phase. Thus, aligning the rotation center of the ankle module with the center of the wearer's ankle is very important to reduce potential risks and fatigue of a soldier. To this end, the ankle exoskeleton was designed using two spherical chains. The two spherical chains were designed such that the intersection of all revolute pairs, which consist of the spherical chains, is located close to the rotation center of the wearer's ankle. In addition, three encoders are attached to each of the three revolute pairs of a spherical chain to measure the three-DOF orientation of the ankle mechanism. For the design, the required range of motion is analyzed via gait analysis in three environment conditions. Forward and inverse kinematic relations are derived, and the workspace of the ankle is analyzed. For the prototype ankle mechanism, the range of motion and measurement performance are verified by a static experiment. In addition, comparative studies between the proposed RCM ankle and an ankle mechanism with offset rotation center are performed for three walking conditions: level walking, ascending and descending stairs, and a vertical slope. Via comparative study, it is confirmed that, compared to the ankle mechanism with offset center of rotation, the proposed RCM ankle is advantageous for sensing wearer's ankle motion and reducing mechanical interference to wearer's natural ankle motion. [ABSTRACT FROM AUTHOR]

Summary: In this paper, we present a passive lower extremity exoskeleton with a simple structure and a light weight. The exoskeleton does not require any external energy source and can achieve energy transfer only by human body's own gravity. The exoskeleton is self-adaptive to human gait to achieve basic matching therewith. During walking, pulling forces are generated through Bowden cables by pressing plantar power output devices by feet, and the forces are transmitted to the exoskeleton through a crank-slider mechanism to enable the exoskeleton to provide torques for the ankle and knee joints as required by the human body during the stance phase and the swing phase. Our self-developed gait detection system is used to perform experiments on kinematics, dynamics and metabolic cost during walking of the human body wearing the exoskeleton in different states. The experimental results show that the exoskeleton has the greatest influence on motion of the ankle joint and has the least influence on hip joint. With the increase in elastic coefficient of the spring, the torques generated at the joints by the exoskeleton increase. When walking with wearing k3EF exoskeleton at a speed of 0.5 m/s, it can save the most metabolic cost, reaching 13.63%. [ABSTRACT FROM AUTHOR]

Summary: This study investigates the effectiveness of a robot-mediated strategy aimed at promoting balance recovery after multidirectional slippages. Six older adults were asked to manage anteroposterior and mediolateral slippages while donning an active pelvis orthosis (APO). The APO was set up either to assist volunteers during balance loss or to be transparent. The margin of stability, in sagittal and frontal planes, was the main metric to assess the effectiveness of balance recovery. Results showed that the assistive strategy is effective at promoting balance recovery in the sagittal plane, for both perturbing paradigms; however, it is not effective at controlling stability in the frontal plane. [ABSTRACT FROM AUTHOR]

Summary: This paper presents a lower-limb exoskeleton that is actuated by pneumatic muscle actuators (PMAs). This exoskeleton system is composed of the mechanical structures, a treadmill, and a weight support system. With the cooperative work of the three parts, the system aims to assist either the elderly for muscle strengthening by conducting walking activities or the stroke patients during a rehabilitation training program. A mechanism is developed to separate the PMAs from the wearer's legs to reduce the subject's physical exertion. Furthermore, considering the difficulty in the modeling of proposed PMAs-driven exoskeleton, a safe and model-free control strategy called proxy-based sliding mode control (PSMC) is used to ensure proper control of the exoskeleton. However, the favorable performances are strongly dependent on the appropriate control parameters, which may be difficult to obtain with blind tuning. Therefore, we propose a global parameters optimization algorithm called switch-mode firefly algorithm (SMFA) to automatically calculate the pre-defined object function and attain the most applicable parameters. Experimental studies are conducted, and the results show the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Summary: In this work we present NEUROExos, a novel generation of upper-limb exoskeletons developed in recent years at The BioRobotics Institute of Scuola Superiore Sant'Anna (Italy). Specifically, we present our attempts to progressively (i) improve the ergonomics and safety (ii) reduce the encumbrance and weight, and (iii) develop more intuitive human–robot cognitive interfaces. Our latest prototype, described here for the first time, extends the field of application to assistance in activities of daily living, thanks to its compact and portable design. The experimental studies carried out on these devices are summarized, and a perspective on future developments is presented. [ABSTRACT FROM AUTHOR]

While initially conceived for human motion augmentation, wearable robots have gradually evolved as technological aids in motion assistance and rehabilitation. There are increasing real-world applications in industrial and medical scenarios. Though efforts have been made on wearable robotic systems, e.g. robotic prostheses and exoskeletons, there are still several challenges in kinematics and actuation solutions, dynamic analysis and control of human-robot systems, neuro-control and human-robot interfaces; ergonomics and human-in-the-loop optimization. Meanwhile, real-world applications in industrial or medical scenarios are facing difficulties considering effectiveness. [ABSTRACT FROM AUTHOR]

In this paper, we introduce a lower extremity exoskeleton CUHK-EXO that is developed to help paraplegic patients, who have lost the motor and sensory functions of their lower limbs to perform basic daily life motions. Since the sit-to-stand and stand-to-sit (STS) motion is the first step for paraplegic patients toward walking, analysis of the exoskeleton's applicability to the STS motion assistance is performed. First, the human-exoskeleton system (HES) is modeled as a five-link model during the STS motion, and the center of pressure (COP) on the ground and center of gravity of the whole system are calculated. Then, a description of the CUHK-EXO hardware design is presented, including the mechatronics design and actuator selection. The COP position is an important factor indicating system balance and wearer's comfort. Based on the COP position, a trajectory online modification algorithm (TOMA) is proposed for CUHK-EXO to counteract disturbances, stabilize system balance, and improve the wearer's comfort in the STS motion. The results of STS motion tests conducted with a paraplegic patient demonstrate that CUHK-EXO can provide a normal reference pattern and proper assistive torque to support the patient's STS motion. In addition, a pilot study is conducted with a healthy subject to verify the effectiveness of the proposed TOMA under external disturbances before future clinical trials. The testing results verify that CUHK-EXO can counteract disturbances, and help the wearer perform the STS motion safely and comfortably. [ABSTRACT FROM AUTHOR]

Variable stiffness can improve the capability of human-robot interacting. Based on the mechanism of a flexible rack and gear, a rotational joint actuator named vsaFGR is proposed to regulate the joint stiffness. The flexible gear rack can be regarded as a combination of a non-linear elastic element and a linear adjusting mechanism, providing benefits of compactness. The joint stiffness is in the range of 217-3527 N.m/rad, and it is inversely proportional to the 4th-order of the gear displacement, and nearly independent from the joint angular deflection, providing benefits of quick stiffness regulation in a short displacement of 20 mm. The gear displacement with respect to the flexible gear rack is perpendicular to the joint loading force, so the power required for stiffness regulating is as low as 14.4 W, providing benefits of energy saving. The working principles of vsaFGR are elaborated, followed by presentation on the mechanics model and the prototype. The high compactness, great stiffness range and low power cost of vsaFGR are proved by simulations and experiments. [ABSTRACT FROM AUTHOR]

Assist-as-needed control is underlain by the aim of replacing skillful therapists with rehabilitation robots. The objective of this research was to introduce a smart assist-as-needed control system for the elderly or partially paralyzed individuals. The main function of the proposed system is to assist the patients just in the required sub phases of the motion. To ensure that a smart and compliant system is developed, the target admittance gains of the controller was adapted according to the concept of energy The admittance gains were modified so that an exoskeleton reduces interaction energy in cases wherein users have sufficient strength for task execution and maximizes the interaction energy in the required subphases. The results of simulations and an experimental investigation on a novel exoskeleton showed that the proposed adaptive admittance control improves performance to a level substantially higher than that achieved with constant impedance control. [ABSTRACT FROM AUTHOR]

We propose a novel class of unsupervised learning-based algorithms that extend the conditional restricted Boltzmann machine to predict, in real-time, a lower limb exoskeleton wearer's intended movement type and future trajectory. During training, our algorithm automatically clusters unlabeled exoskeletal measurement data into movement types. Our predictor then takes as input a short time series of measurements, and outputs in real-time both the movement type and the forward trajectory time series. Physical experiments with a prototype exoskeleton demonstrate that our method more accurately and stably predicts both movement type and the forward trajectory compared to existing methods. [ABSTRACT FROM AUTHOR]

In this paper, we study the problem of adaptive position tracking for a multi-link robot driven by two opposing pneumatic muscle groups with additive disturbances. In contrast to widely used sliding mode control methods, the proposed controller is continuous and able to prevent chattering. All physical parameters of the robot and the pneumatic muscles, including pneumatic muscle coefficients, link lengths and moments of inertia are unknown and can be time-varying and the unknown additive disturbances can be discontinuous. Under these conditions, we prove that closed-loop trajectories of all of the joint positions can track any C1 joint reference signal. The joint errors will be within a prescribed error bound in a finite time. The adaptive controller only uses the reference signal, not its derivative. The continuous adaptive gain is one-dimensional. Simulations including a two-link robot arm with friction and realistic muscle models are presented to demonstrate the robustness of the adaptive control under severe changes of the system parameters. In all simulations, the joint positions can track C1 trajectories and all errors are within the prescribed error bound in the same time frame, even though the muscle parameters are vastly different. [ABSTRACT FROM AUTHOR]

Redundancy in motion, and synergy in neuromuscular coordination provides significant versatility to the human fingers while performing coordinated grasping and manipulation tasks in several ways. This paper explores how humans may resolve the redundancy in their thumb, index and middle fingers when these digits flex to cooperatively translate a small object toward the palm. It is observed that humans actively employ a secondary subtask of maximizing instantaneous manipulability that helps determine all intermediate finger configurations when performing the primary subtask of following a tip trajectory. This behavior is accurately captured by an inverse kinematic model based on a redundancy parameter. The joint angles get determined unambiguously though the redundancy parameter is shown to depend on the instantaneous finger configurations and also, to attain negative values. Further, this parameter is noted to vary significantly across subjects performing the same kinematic task. The findings, that are based on the experimental finger motion data garnered from 12 subjects, are reckoned to be of significant importance, especially in reference to the challenges in design and control of finger exoskeletons for cooperative manipulation. [ABSTRACT FROM PUBLISHER]

A multimodal actuator was proposed to achieve a more agile power-assisted exoskeleton in uncertain complex walking environments. A power-assisted knee exoskeleton prototype based on a multimodal actuator was constructed. With this multimodal actuator, several modes of operation in the power-assisted knee exoskeleton during a motion cycle are actuated, including series elastic actuation, stiff position control, and energy storage and release. Also, a control strategy for power-assisted knee exoskeleton motion control based on a state machine is developed. The ability of the power-assisted knee exoskeleton to follow human motion was tested, and the results showed that the angle error of the knee exoskeleton followed the human motion is not more than 0.4˚, and the response time error of the knee exoskeleton followed the human motion is not more than 0.2 s. [ABSTRACT FROM PUBLISHER]

In accordance with strict requirements of portability, cheapness, and modularity, an innovative assistive device for hand disabilities has been developed and validated. This robotic orthosis is designed to be a low-cost, portable hand exoskeleton to assist people with physical disabilities in their everyday lives. Referring to hand opening disabilities, the authors have developed a methodology which, by starting from the geometrical characteristics of the patient's hand, defines the novel kinematic mechanism that better fits to the finger trajectories. The authors have validated the proposed novel mechanism by carrying out a Hand Exoskeleton System (HES) prototype, based on a single-phalanx mechanism, cable driven. The testing phase of the real prototype with a patient is currently on going. [ABSTRACT FROM PUBLISHER]

Exoskeleton robots, which can be worn on human limbs to improve or to rehabilitate their function, are currently of great importance. When these robots are used in rehabilitation, one aspect that must be fulfilled is their capacity to adapt to different patients without significantly varying their performance. This paper describes the application of a relatively new control technique called virtual decomposition control (VDC) to a seven degrees-of-freedom (DOF) exoskeleton robot arm, named ETS-MARSE. The VDC approach mainly involves decomposing complex systems into subsystems, and using the resulting simpler dynamics to conduct control computation, while strictly ensuring global stability and having the subsystem dynamics interactions rigorously managed and maintained by means of virtual power flow. This approach is used to deal with different masses, joint stiffness and biomechanical variations of diverse subjects, allowing the control technique to naturally adapt to the variances involved and to maintain a successful control task. The results obtained in real time on a 7DOF exoskeleton robot arm show the effectiveness of the approach. [ABSTRACT FROM AUTHOR]

This paper addresses attention to a design for a low-cost exoskeleton with fairly simple construction, lightweight, easy to wear and to adapt to human legs. The design core is focused on a cam-mechanism implementation at the ankle joint level of the leg exoskeleton. The engineering feasibility of the proposed design is characterized by numerical simulations for the design process. [ABSTRACT FROM PUBLISHER]