This article illustrates the development of a passive back-support exoskeleton to assist individuals with manual material handling tasks. The exoskeleton hardware is primarily composed of the differential clutches, variable-stiffness gravity compensators, walking assistance mechanisms, and back and thigh modules. With the designed mechanisms, this exoskeleton can automatically switch between the walking and lifting modes and provide an assistive torque that can well match with the torque required by the wearers. The modeling of the variable-stiffness gravity compensator and walking assistance mechanism is presented. Experimental results demonstrate that the exoskeleton has the potential to assist the individuals with load-lifting and weight-bearing walking tasks. Specifically, during the stoop lifting of a 10-kg object, reductions of 26.40% in average thoracic erector spinae activity, 28.73% in lumbar erector spinae activity, and 18.50% in biceps femoris activity are observed. Additionally, during walking while carrying a 10-kg object, a reduction of 14.74% in average rectus femoris activity is recorded.

This paper presents a robotic upper-limb rehabilitation exoskeleton for individuals with upper-limb motor impairments in the middle-to-late stages of rehabilitation. The exoskeleton features a metamorphic mechanical architecture capable of switching among four metamorphic configurations: shoulder adduction/abduction (SA/A), shoulder flexion/extension (SF/E), elbow flexion/extension (EF/E), and forearm pronation/supination (FP/S). For hierarchical assistance, a termite life cycle optimizer-tuned support vector machine (TLCO-SVM) is developed for metamorphic-configuration recognition, and a TLCO-optimized long short-term memory network (TLCO-LSTM) is proposed to predict the desired jointangle trajectory. Based on the recognized configuration and the predicted desired joint-angle trajectory, a deep deterministic policy gradient-based adaptive impedance controller is developed to generate assistive torques and support compliant physical human-robot interaction. Experiments were conducted to evaluate the proposed recognition, prediction, and control framework. The TLCO-SVM achieves an average classification accuracy of 98.10%. The TLCO-LSTM achieves root mean square errors (RMSEs) of 2.71° (SA/A), 2.41° (SF/E), 3.47° (EF/E), and 5.19° (FP/S), respectively. Assistive-torque tracking RMSEs are 0.2497 Nm, 0.2252 Nm, 0.1130 Nm, and 0.3423 Nm for SA/A, SF/E, EF/E, and FP/S, respectively.

Frequent and high-load manual material handling (MMH) tasks often cause back injuries to the workers, and backsupport exoskeletons are developed for individuals with MMH tasks. However, these exoskeletons usually cannot adapt well to the movements of the wearer's spine. This paper introduces a new bio-inspired 5-DOF origami, and via mechanical design, a unique rigid-flexible coupled bio-inspired origami mechanism is proposed. This origami mechanism is compact and lightweight, and it has stable kinematic behaviors. With the designed origami mechanisms, a novel active origami-based robotic spine assistive exoskeleton (OSAE) is developed to assist individuals with MMH tasks during the symmetric and asymmetric lifting. The OSAE is actuated by a cable-driven module through an under-actuated spine module that consists of seven origami mechanisms. With the designed spine module, the OSAE can adapt well to the wearer's spine motions during MMH tasks. Modeling of the 5- DOF origami is described, and an adaptive control strategy is proposed for the exoskeleton to adapt to different lifting methods and objects with different weights. The experimental results demonstrate the effectiveness of the proposed OSAE. During the symmetric lifting of a 10-kg object, a reduction of 41.28% of the average muscle activity of the wearer's lumbar erector spinae muscle (LES) is observed, and reductions of 30.15% and 39.54% of the average muscle activities of the wearer's left and right LES are observed, respectively, during the asymmetric lifting of a 10- kg object.

The number of patients with hand dysfunction is increasing worldwide, and their activities of daily living (ADLs) are seriously affected. Robotic medical devices such as robotic hand exoskeletons have been investigated to help restore and improve the hand functions of these patients. In comparison with the traditional therapies, robotic hand exoskeletons have the advantages of providing a controllable assistive force/torque, recording the wearer's motion data, and improving the wearer's voluntary participation and motivation in the rehabilitation, which can improve the hand rehabilitation efficiency. Currently, there is a lack of systematic reviews of robotic hand exoskeletons. This paper presents a systematic review of robotic hand exoskeletons. Six electronic databases are searched using the same keywords, and a total of 86 papers that meet the inclusion criteria are selected for this review. The biomechanics of a human hand is introduced. The design concepts of robotic hand exoskeletons are also proposed, which include the actuator design and configuration, human-machine kinematic compatibility, and design of degrees-of-freedom (DOFs). Additionally, the control strategies of robotic hand exoskeletons are described. Finally, the limitations of the currently available robotic hand exoskeletons and their possible future research and development directions are discussed. The significance of this review is to provide useful information for the engineers and researchers to develop robotic hand exoskeletons with practical and plausible applications.

Frequent and high-load manual material handling (MMH) tasks often cause back injuries to the workers, and back-support exoskeletons are developed for individuals with MMH tasks. However, these exoskeletons usually cannot adapt well to the movements of the wearer's spine. This article introduces a new bioinspired five degree of freedom (DOF) origami, and via mechanical design, a unique rigid-flexible coupled bioinspired origami mechanism is proposed. This origami mechanism is compact and lightweight, and it has stable kinematic behaviors. With the designed origami mechanisms, a novel active origami-based robotic spine assistive exoskeleton (OSAE) is developed to assist individuals with MMH tasks during the symmetric and asymmetric lifting. The OSAE is actuated by a cable-driven module through an underactuated spine module that consists of seven origami mechanisms. With the designed spine module, the OSAE can adapt well to the wearer's spine motions during MMH tasks. Modeling of the five-DOF origami is described, and an adaptive control strategy is proposed for the exoskeleton to adapt to different lifting methods and objects with different weights. The experimental results demonstrate the effectiveness of the proposed OSAE. During the symmetric lifting of a 10-kg object, a reduction of 41.28% of the average muscle activity of the wearer's lumbar erector spinae muscle (LES) is observed, and reductions of 30.15% and 39.54% of the average muscle activities of the wearer's left and right LES are observed, respectively, during the asymmetric lifting of a 10-kg object.

Based on the Chebyshev polynomial method (CPM) and interval theory, this article establishes the relationship between uncertain parameters and the dynamic response of a new cable-driven parallel robot (CDPR). Meanwhile, the time-varying characteristic of uncertain parameters in the dynamic uncertainty analysis of the model is considered in this article, effectively enhancing the accuracy of the dynamic response. The mechanical design and kinematic modeling are conducted, and the dynamic model is established based on the Lagrangian method. Thus, uncertain parameters including the length of the lifting arm L, the angle of the lifting arm rotation on the support plate alpha, and the length of the payload l are defined as interval variables, and the dynamic equilibrium equation with interval variables is derived. Numerical examples show that the CPM has a higher accuracy than the first-order interval perturbation method (FOIPM), and a higher efficiency than the Monte Carlo method (MCM) when it comes to solve the dynamic response of the CDPR with uncertain parameters. Experimental results demonstrate the effectiveness of dynamic modeling and the CPM in achieving efficient dynamic response and show that the largest relative error between the theoretical and experimental values for the dynamic response of the CDPR with uncertain parameter L is 1.466%; the largest relative error with uncertain parameter alpha is 0.783%; the largest relative error with uncertain parameter l is 0.857%; and the largest relative error with multiple uncertain parameters is 1.513%.

This paper illustrates the design and testing of an upper-body exoskeleton for the assistance of individuals with load-lifting and load-carrying tasks, and the provided assistive force can well match with the force required by the human. First, the biomechanics of the human lumbar during the squat lifting of an object is described. Next, the modeling of the exoskeleton is introduced. Additionally, the hardware design of the exoskeleton is presented. The exoskeleton is mainly composed of a back-assist mechanism and an upper extremity labor-saving mechanism, which can assist the wearer’s lumbar during the squat lifting of an object and assist the wearer’s arms to carry an object during walking, respectively. Finally, experiments are conducted to evaluate the performance of the developed upper-body exoskeleton. The experimental results demonstrate that the exoskeleton has the potential to provide assistance for individuals with manual handling tasks. An average assistive force of 44.8 N can be provided for the wearer to lift a 10-kg object. During the squat lifting of the 10-kg object, reductions of 31.86% and 28.30% of the average muscle activities of the wearer’s lumbar erector spinae and thoracic erector spinae are observed, respectively. In addition, a reduction of 23.78% of the average muscle activity of the wearer’s biceps brachii is observed during walking while carrying the 10-kg object.

The development of rehabilitation robots has long been an issue of increasing interest in a wide range of fields. An important aspect of the ongoing research field is applying flexible components to rehabilitation equipment to enhance human-machine interaction. Another major challenge is to accurately estimate the individual's intention to achieve safe operation and efficient training. In this article, a robotic knee-ankle orthosis (KAO) with shape memory alloy (SMA) actuators is developed, and the estimation method is proposed to determine the joint torque. First, based on the analysis of human lower limb structure and walking patterns, the mechanical design of the KAO that can achieve various rehabilitation training modes is detailed. Next, the dynamic model of the hybrid-driven KAO is established using the thermodynamic constitutive equation and Lagrange formalism. In addition, the joint torque estimation is realized by the nonlinear Kalman filter method. Finally, the prototype and human subject experiments are conducted, and the experimental results demonstrate that the KAO can assist lower limb movements. In the three experimental scenarios, reductions of 59.1%, 16.5%, and 73% of the torque estimation error during the knee joint movement are observed, respectively.

This article presents the design and control of a robotic knee exoskeleton for gait rehabilitation of patients with knee joint impairments. First, the hardware design of the exoskeleton is presented, including the mechanical structure, actuator design and configuration, and electronic system. Based on the nonlinear characteristics of human muscles, a nonlinear variable stiffness actuator (NLVSA) is designed for the actuation system of the exoskeleton. Next, the modeling of the NLVSA is described. In addition, an adaptive admittance control strategy comprising a sparrow search optimization algorithm-based long short-term memory neural network model and an adaptive admittance control algorithm based on the radial basis function neural network (RBFAAC) is proposed for the exoskeleton. Finally, a pilot study is conducted to demonstrate the effectiveness of the robotic knee exoskeleton. The experimental results validate the effectiveness of the designed NLVSA, and the exoskeleton has the potential for human knee rehabilitation by providing effective assistance with the proposed control strategy. With the proposed RBFAAC algorithm, the average root mean square error between the reference and actual knee joint angles is 1.24 degrees at different walking speeds.

Individuals with a drop-foot generally have issues of foot-slap and toe-drag, and ankle-foot orthoses (AFOs) have been developed for them to address the drop-foot gait. However, the currently available active AFOs usually have heavier mass, larger volume, and additional power sources, and almost all of the passive AFOs can achieve dorsiflexion assistance at the cost of making plantarflexion more difficult, which increases the wearer's metabolic cost of walking. This paper illustrates the development and validation of a passive AFO for walking propulsion and drop-foot prevention of individuals with a drop-foot gait. The AFO is primarily composed of a propulsion module, a drop-foot prevention module, and a support module. The propulsion module can detect the wearer's gait stages, and it can control the energy storage and release of an energy storage spring-A by switching the state of a clutch-A mechanism. The drop-foot prevention module is designed to correct the abnormal gait of individuals with a drop-foot gait during the swing phase. Experiments are conducted to evaluate the performance of the developed AFO. The experimental results demonstrate that during a gait cycle, reductions of 7.74%, 6.72%, and 16.36% of the average muscle activities of the gastrocnemius, soleus, and tibialis anterior are observed, respectively. The significance of this study is the development of a portable passive AFO that has the potential to provide plantarflexion assistance and dorsiflexion assistance for the wearers during the late stance phase and swing phase, respectively.

Abstract This paper presents the development of a robotic ankle exoskeleton for human walking assistance. First, the biomechanical properties of a human ankle joint during walking are presented. Next, design of the robotic ankle exoskeleton is introduced. The exoskeleton is actuated by a novel parallel nonlinear elastic actuator. The cam-spring mechanism in the actuator can function as a parallel nonlinear spring with an adjustable stiffness, and the design of the cam profile curve is described. Additionally, an adaptive controller is proposed for the exoskeleton to generate a desired assistive torque according to the wearer's total weight. Finally, experiments are conducted to validate the effectiveness of the developed robotic ankle exoskeleton. The experimental results demonstrate that during a gait cycle, reductions of 42.7% and 40.1% of the peak and average currents of the driving motor in the actuator are observed, respectively, with the designed cam-spring mechanism. A peak assistive torque of 23.9 Nm can be provided for the wearers by the exoskeleton during walking. With the assistance provided by the exoskeleton, the average and peak soleus activities of the wearers during a gait cycle are decreased by 25.42% and 31.94%, respectively.

In this paper, a hybrid driven knee orthosis using Shape Memory Alloy (SMA) actuator is proposed. First, the mechanical design of the actuator system is presented. The device mainly consists of the DC motor module and the SMA spring actuator module, and the two independent operating actuators realize the hybrid drive through the electromagnetic clutch connection. Then, the constitutive model for SMA spring and mathematical model for DC motor system are established respectively to describe the output characteristics of the actuator. Finally, a series of numerical simulations are implemented on SMA springs and the DC motor to determine the changing parameters of the SMA actuator during the heating phase transition and the load characteristics of the motor.

Cable-driven parallel robots (CDPRs) have been widely used in engineering fields because of their significant advantages including high load-bearing capacity, large workspace, and low inertia. However, the impact of convergence speed and solution accuracy of optimization approaches on optimal performances can become a key issue when it comes to the optimal design of CDPR applied to large storage space. An adaptive adjustment inertia weight particle swarm optimization (AAIWPSO) algorithm is proposed for the multi-objective optimal design of CDPR. The kinematic and static models of CDPR are established based on the principle of virtual work. Subsequently, two performance indices including workspace and dexterity are derived. A multi-objective optimization model is established based on performance indices. The AAIWPSO algorithm introduces an adaptive adjustment inertia weight to improve the convergence efficiency and accuracy of traditional particle swarm optimization (PSO) algorithm. Numerical examples demonstrate that final convergence values of the objective function by the AAIWPSO algorithm can almost be 14 & SIM;20% and 19 & SIM;40% higher than those by the PSO algorithm and genetic algorithm (GA) for the optimal design of CDPR with different configurations and masses of end-effectors, respectively.

This paper illustrates the design and testing of a lower limb exoskeleton for walking assistance. First, the biomechanics of the human knee and ankle joints during walking and the strategy of energy recycling and releasing are introduced. Next, the hardware design of the exoskeleton is described. The exoskeleton is primarily composed of a waist module, a knee module, and an ankle module. Two clutch mechanisms are designed for one-way motion transmission, and an energy storage spring is designed to store the energy recycled from the human knee motion. Additionally, the modeling of the human-exoskeleton system is presented. Finally, experiments are conducted to verify the effectiveness of the developed exoskeleton. The experimental results demonstrate that the exoskeleton has the potential to recycle the negative work from the wearer's knee flexion during the late stance phase and knee extension during the swing phase to assist the wearer's ankle plantarflexion during the stance phase. During a gait cycle, reductions of 11.6% and 15.6% of the average muscle activities of the gastrocnemius and soleus are observed, respectively. In addition, the peak gastrocnemius and soleus activities during the push-off stage are reduced by 16.9% and 42.6%, respectively.

AbstractIn 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.

The increasing requirement of powering portable electronic devices can be potentially met by recycling the biomechanical energy generated during the human joint motion through a knee-ankle exoskeleton. In this paper, a knee-ankle exoskeleton is designed to recycle the negative work from the wearer’s knee extension and ankle dorsiflexion. The exoskeleton can convert the mechanical energy into electrical energy for energy harvesting and assist the knee flexion and ankle plantarflexion to reduce the wearer’s metabolic cost during walking. It is mainly composed of two torsion springs, two one-way transmission mechanisms, a gear train, and a generator. The torsion springs can store the elastic energy when the wearer’s ankle and knee joints do negative work and release it to assist walking when positive work is required. The one-way transmission mechanisms are employed to filter the knee flexion and ankle plantarflexion and to convert the knee extension and ankle dorsiflexion into the one-way rotation of the generator by symmetrically arranging the gear train. Finally, experiments are conducted to evaluate the performance of the developed knee-ankle exoskeleton. The experimental results indicate that the exoskeleton can generate an average electrical power of 0.49 W and a maximum instantaneous electrical power of 1.8 W at a walking speed of 5.5 km h −1 during a gait cycle, and reductions of 3.48% ± 0.33%, 9.50% ± 0.29%, and 4.54% ± 0.47% of the average muscle activities of the semitendinosus, soleus, and gastrocnemius during a gait cycle are observed, respectively.

Patients with knee impairments caused by neurological or orthopedic diseases such as a stroke, spinal cord injury, or physical injury are at a high risk of secondary complications, which include muscular dystrophy and hemiplegia. This seriously affect the quality of life of these patients. Therefore, it is necessary to assist these patients to regain the ability to perform activities of daily living. Robotic knee exoskeletons are wearable humane-machine cooperative systems, which can provide effective gait training by generating controllable torque at the wearer’s knee joint. This paper presents the design and simulation of a robotic knee exoskeleton with a variable stiffness actuator (VSA). First, a brief description of the human knee biomechanics during walking is introduced. Next, design of the robotic knee exoskeleton with the VSA is proposed. In the designed VSA, a disk-type torsion spring is employed as the compliant element in the actuator, which can absorb perturbations and guarantee a low system output impedance and stable torque control. Then, the dynamic model of the VSA is established and simulations are conducted. The simulation results indicate that the application of the VSA in the robotic knee exoskeleton has good torque tracking performance and stability.

In this paper, a robotic ankle-foot orthosis (AFO) is developed for individuals with a paretic ankle, and an impedance-based assist-as-needed controller is designed for the robotic AFO to provide adaptive assistance. First, a description of the robotic AFO hardware design is presented. Next, the design of the finite state machine is introduced, followed by an introduction to the modeling of the robotic AFO. Additionally, the control of the robotic AFO is presented. An impedance-based high-level controller that is composed of an ankle impedance based torque generation controller and an impedance controller is designed for the high-level control. A compensated low-level controller that is composed of a braking controller and a proportional-derivative controller with a compensation part is designed for the low-level control. Finally, a pilot study with eight healthy participants is conducted, and the experimental results demonstrate that with the proposed control algorithm, the robotic AFO has the potential for ankle rehabilitation by providing adaptive assistance. In the assisted condition with a high level of assistance, reductions of 8% and 20.1% of the root mean square of the tibialis anterior and lateral soleus activities are observed, respectively.

This paper illustrates the development and experimental validation of a robotic ankle–foot orthosis (AFO) with a series elastic actuator (SEA) and a magneto-rheological (MR) brake. First, the biomechanics of a human ankle joint during walking is explained. Next, the hardware design of the robotic AFO is introduced, including its mechanical structure, actuator design and configuration, and electronic system. The SEA is primarily composed of an electric motor, a planetary gearbox, a torsion spring, and a pair of bevel gears. The MR brake can modulate the viscosity of the robotic AFO and generate a large braking torque of 21.8 Nm with a low power of 8.8 W. Additionally, the modeling of the robotic AFO is presented, followed by an introduction to its control; several gait evaluation indices are proposed as well. Finally, a pilot study is conducted to verify the effectiveness of the developed robotic AFO. The experimental results demonstrate that the robotic AFO has the potential to provide dorsiflexion assistance, thus preventing foot slap and toe drag, in addition to plantarflexion assistance for the forward propulsion of the body. During a gait cycle, an average power of 0.23 W is harvested, and an 8% improvement in the system energy efficiency is achieved.

In this paper, a waist and lower limbs cable-driven parallel rehabilitation robot is designed to perform waist and lower limbs rehabilitation simultaneously and separately. It is designed based on the analysis of the human biomechanics and can reduce the cost, meet the needs of more patients and reduce the weight of the robot. The mechanism design is firstly proposed in this paper. The rehabilitation robot is mainly composed of four motor driven parallel motion platform, which can provide active motion to realize the waist rehabilitation in three degrees of freedom (DOF). It also includes a lower limbs adjustable mechanism to realize the hip, knee and ankle rehabilitation training. In addition, the kinematic analysis and numerical simulation of the robot are presented. The simulation results demonstrate that the designed rehabilitation robot is effective and safe with a good kinematic performance.