Joint Exoskeleton Research Articles

Design and Evaluation of a Novel Variable Stiffness Hip Joint Exoskeleton.

An exoskeleton is a wearable device with human-machine interaction characteristics. An ideal exoskeleton should have kinematic and kinetic characteristics similar to those of the wearer. Most traditional exoskeletons are driven by rigid actuators based on joint torque or position control algorithms. In order to achieve better human-robot interaction, flexible actuators have been introduced into exoskeletons. However, exoskeletons with fixed stiffness cannot adapt to changing stiffness requirements during assistance. In order to achieve collaborative control of stiffness and torque, a bionic variable stiffness hip joint exoskeleton (BVS-HJE) is designed in this article. The exoskeleton proposed in this article is inspired by the muscles that come in agonist-antagonist pairs, whose actuators are arranged in an antagonistic form on both sides of the hip joint. Compared with other exoskeletons, it has antagonistic actuators with variable stiffness mechanisms, which allow the stiffness control of the exoskeleton joint independent of force (or position) control. A BVS-HJE model was established to study its variable stiffness and static characteristics. Based on the characteristics of the BVS-HJE, a control strategy is proposed that can achieve independent adjustment of joint torque and joint stiffness. In addition, the variable stiffness mechanism can estimate the output force based on the established mathematical model through an encoder, thus eliminating the additional force sensors in the control process. Finally, the variable stiffness properties of the actuator and the controllability of joint stiffness and joint torque were verified through experiments.

Variable Admittance Control of High Compatibility Exoskeleton Based on Human–Robotic Interaction Force

The wearable exoskeleton system is a typical strongly coupled human–robotic system. Human–robotic is the environment for each other. The two support each other and compete with each other. Achieving high human–robotic compatibility is the most critical technology for wearable systems. Full structural compatibility can improve the intrinsic safety of the exoskeleton, and precise intention understanding and motion control can improve the comfort of the exoskeleton. This paper first designs a physiologically functional bionic lower limb exoskeleton based on the study of bone and joint functional anatomy and analyzes the drive mapping model of the dual closed-loop four-link knee joint. Secondly, an exoskeleton dual closed-loop controller composed of a position inner loop and a force outer loop is designed. The inner loop of the controller adopts the PID control algorithm, and the outer loop adopts the adaptive admittance control algorithm based on human–robot interaction force (HRI). The controller can adaptively adjust the admittance parameters according to the HRI to respond to dynamic changes in the mechanical and physical parameters of the human–robot system, thereby improving control compliance and the wearing comfort of the exoskeleton system. Finally, we built a joint simulation experiment platform based on SolidWorks/Simulink to conduct virtual prototype simulation experiments and recruited volunteers to wear rehabilitation exoskeletons to conduct related control experiments. Experimental results show that the designed physiologically functional bionic exoskeleton and adaptive admittance controller can significantly improve the accuracy of human–robotic joint motion tracking, effectively reducing human–machine interaction forces and improving the comfort and safety of the wearer. This paper proposes a dual-closed loop four-link knee joint exoskeleton and a variable admittance control method based on HRI, which provides a new method for the design and control of exoskeletons with high compatibility.

Pneumatic Exoskeleton Joint With a Self-Supporting Air Tank and Stiffness Modulation: Design, Modeling, and Experimental Evaluation

Pneumatic Exoskeleton Joint With a Self-Supporting Air Tank and Stiffness Modulation: Design, Modeling, and Experimental Evaluation

Eight-Bar Elbow Joint Exoskeleton Mechanism

This paper deals with the design and kinematic analysis of a novel mechanism for the elbow joint of an upper-limb exoskeleton, with the aim of helping operators, in terms of effort and physical resistance, in carrying out heavy operations. In particular, the proposed eight-bar elbow joint exoskeleton mechanism consists of a motorized Watt I six-bar linkage and a suitable RP dyad, which connects mechanically the external parts of the human arm with the corresponding forearm by hook and loop velcro, thus helping their closing relative motion for lifting objects during repetitive and heavy operations. This relative motion is not a pure rotation, and thus the upper part of the exoskeleton is fastened to the arm, while the lower part is not rigidly connected to the forearm but through a prismatic pair that allows both rotation and sliding along the forearm axis. Instead, the human arm is sketched by means of a crossed four-bar linkage, which coupler link is considered as attached to the glyph of the prismatic pair, which is fastened to the forearm. Therefore, the kinematic analysis of the whole ten-bar mechanism, which is obtained by joining the Watt I six-bar linkage and the RP dyad to the crossed four-bar linkage, is formulated to investigate the main kinematic performance and for design purposes. The proposed algorithm has given several numerical and graphical results. Finally, a double-parallelogram linkage, as in the particular case of the Watt I six-bar linkage, was considered in combination with the RP dyad and the crossed four-bar linkage by giving a first mechanical design and a 3D-printed prototype.

Development and Analysis of a Novel Bio-syncretic Parallel Hip Exoskeleton Based on Torque Requirements

Abstract This paper presents a novel bio-syncretic parallel hip exoskeleton (BsPH-Exo) to address the rehabilitation exercise needs of individuals with lower limb motor dysfunction. BsPH-Exo has six degrees of freedom and can generate all three kinds of rotations that the hip joint can naturally realize. BsPH-Exo effectively solves the problem of misalignment between human and exoskeleton joints, eliminating the need for patients to perform any alignment operations. Considering the varying maximum torque requirements for hip joint rehabilitation in different directions, the limbs of BsPH-Exo are specially arranged to ensure that the maximum torque provided by BsPH-Exo in each direction follows the same law as that of the required torque. As a result, BsPH-Exo exhibits excellent output torque performance, specifically in the flexion/extension direction. Moreover, BsPH-Exo demonstrates weak coupling characteristics in the flexion/extension direction and decoupling characteristics in the adduction/abduction direction, which reduces the difficulty in its control. Compared to currently available parallel hip exoskeletons, BsPH-Exo has several distinct advantages that make it particularly well-suited for rehabilitation applications.

Research on exoskeleton compliance control strategy based on dual interaction torque split phase control method.

Human gait pattern recognition and compliance control are key technologies for achieving high coordination and assistance between exoskeleton robots and human movements. In order to improve the adaptability of exoskeleton robots to the human body, this paper proposes an exoskeleton compliance control strategy based on dual interaction torque phase separation control method. A support phase swing phase split control strategy based on dual interaction torque is proposed. Utilize the interaction force of human joints and adopt a model-based method to control the support phase. By utilizing the interaction force of exoskeleton joints and using a torque closed-loop method to control the swing phase, a multi-state control method of motion is achieved. A lower limb exoskeleton knee joint testing platform is built to verify the proposed human gait recognition The effectiveness of human-machine interaction force identification and human-machine coupling system compliance control technology. The proposed control method can effectively adjust joint torque, enabling the exoskeleton robot to maintain balance and stability during the entire walking phase.

A Cable-Driven Parallel Hip Exoskeleton for High-Performance Walking Assistance

Misalignment between human and exoskeleton joints is a common issue in exoskeletons of rigid structure, as it can lead to discomfort or even injuries. Cable-driven exoskeletons, by using human skeletal joints, remove misalignment as a potential issue. However, large parasitic forces due to cable pulling endure as a shortcoming of cable-driven exoskeletons. To address the problem, this paper proposes a novel cable-driven hip exoskeleton of parallel structures for assisted walking with eliminated parasitic force. The parasitic force potentially caused by either the misalignment or direct pulling can be removed mechanically. The new exoskeleton, conceptually different compared to existing anthropomorphic exoskeletons or soft exoskeletons, can conjugate flexibility and kinematic redundancy in flexion/extension and ab/adduction for self-alignment with anatomical joints. The unique design enables internal/external rotation for versatile walking gaits. In the work, the misalignment between the mechanical and biological hip joints is quantified both theoretically and experimentally. Moreover, an adaptive robust controller (ARC) is designed to provide desired force during assisted walking. Experimental results demonstrate the performance of the proposed cable-driven exoskeleton system and improved wearing comfort with parasitic forces eliminated.

Powered single hip joint exoskeletons for gait rehabilitation: a systematic review and Meta-analysis.

Gait disorders and as a consequence, robotic rehabilitation techniques are becoming increasingly prevalent as the population ages. In the area of rehabilitation robotics, using lightweight single hip joint exoskeletons are of significance. Considering no prior systematic review article on clinical outcomes, we aim to systematically review powered hip exoskeletons in terms of gait parameters and metabolic expenditure effects. Three databases of PubMed, Scopus, and Web of science were searched for clinical articles comparing outcomes of gait rehabilitation using hip motorized exoskeleton with conventional methods, on patients with gait disorder or healthy individuals. Of total number of 37 reviewed articles, 14 trials were quantitatively analyzed. Analyses performed in terms of gait spatiotemporal parameters like speed (self-speed and maximum speed), step length, stride length, cadence, and oxygen consumption. Improved clinical outcomes of gait spatiotemporal parameters with hip joint exoskeletons are what our review's findings show. In terms of gait values, meta-analysis indicates that rehabilitation with single hip joint exoskeleton enhanced parameters of maximum speed by 0.13 m/s (0.10-0.17) and step length by 0.06 m (0.05-0.07). For the remaining investigated gait parameters, no statistically significant difference was observed. Regarding metabolic parameters, oxygen consumption was lower in individuals treated with hip exoskeleton (- 1.23 ml/min/kg; range - 2.13 to - 0.32). Although the analysis demonstrated improvement with just specific gait measures utilizing powered hip exoskeletons, the lack of improvement in all parameters is likely caused by the high patient condition heterogeneity among the evaluated articles. We also noted in patients who rehabilitated with the hip exoskeleton, the oxygen cost was lower. More randomized controlled trials are needed to verify both the short- and long-term clinical outcomes, including patient-reported measures. Level I (systematic review and meta-analysis).

Magnetorheological Damper with Variable Displacement Permanent Magnet for Assisting the Transfer of Load in Lower Limb Exoskeleton.

Magnetorheological (MR) fluid exhibits the ability to modulate its shear state through variations in magnetic field intensity, and is widely used for applications requiring damping. Traditional MR dampers use the current in the coil to adjust the magnetic field strength, but the accumulated heat can cause the magnetic field strength to decay if it works for a long time. In order to deal with this shortcoming, a novel MR damper is proposed in this paper, which is based on a variable displacement permanent magnet to adjust the output resistance torque and applied to an exoskeleton joint for human load transfer assistance. A finite element model is used to determine the size parameters of the magnet and separator, so that the maximum output torque is optimal and the torque is uniformly distributed with the magnet displacement. The MR damper was characterized and calibrated on the experimental bench to make it controllable. The novel design enables the torque mass density of the MR damper to reach 8.83Nmm/g, the torque volume density to reach 48.7N/mm2, and has stability for long-term operation. Based on the torque control method proposed, a preliminary human experiment is conducted. The ground reaction force (GRF) data of the subjects is analyzed here, which represents the effect of load transfer to the exoskeleton. Compared with no exoskeleton, the GRF with exoskeleton is significantly reduced: the peak GRF in early stance phase is reduced by 24.14%, and in late stance phase is reduced by 19.77%. Based on our net load benefit (NLB) and net force benefit (NFB) evaluation indicators, the effectiveness of the proposed MR damper exoskeleton for human weight bearing assistance is established.

MODEL PREDICTIVE CONTROL OF EXOSKELETON JOINT ANGLES

Lower limb exoskeletons are used for rehabilitation purposes, so their precise control is an important issue. Classical controllers are often unable to provide high accuracy and speed, which can lead to errors in exoskeleton operation. Complexities associated with lower limb exoskeleton control systems arise from the dynamic and nonlinear nature of human locomotion. Solving these complexities involves designing modern control systems. One of the modern approaches is Model Predictive Control, which, predicting future deviations of system state variables, performs optimization calculations and selects such input signals, in which case the error will tend to the minimum value. This controller is widely used for controlling nonlinear dynamic systems with constraints. Considering this fact, it was proposed to develop a controller with a predictive model for controlling the angles of the exoskeleton joints. Control with a predictive model assumes that the dynamic equations of the control object are known, so a nonlinear mathematical model of the lower limb exoskeleton was firstly designed, taking into account the mechanical and electromechanical components. An examination of the exoskeleton state variables and control input constraints, which were taken into account during the design of the controller, was performed, and a reduction function was defined, according to which the controller with a predictive model should perform an optimization calculation, thereby enabling the reduction of errors or inaccuracies. Simulations performed in the MATLAB/Simulink environment validate the effectiveness and accuracy of the developed controller, showing small deviations between the desired and actual joint angles during dynamic motions. Future efforts will focus on improving control quality and validating results through empirical studies, thereby strengthening the role of model predictive controllers for the design of exoskeleton control systems.

Research on Human Machine Interaction of Exoskeleton

In the exoskeleton system, the interaction force between the exoskeleton and the human body is one of the important factors determining the efficiency of exoskeleton assistance, and the constraints generated by the positional deviation between the exoskeleton and the human body can affect the human-machine interaction force. Therefore, this article first focuses on the mechanical characteristics of the relative position deviation of the external skeleton binding point, and obtains the constraint characteristics in different directions through experiments. Secondly, different exoskeleton mechanical models are established in the support phase and swing phase, and the magnitude of human-machine interaction forces is calculated based on the constraints generated by weight bearing gravity, human-machine deviation, and the inertia force generated by exoskeleton motion at each joint. Then, we analysed the impact of driving torque on human-machine interaction forces during active assistance at the hip and knee joints of the exoskeleton. When 100% assistance is provided to the hip and knee joints of the exoskeleton, the human-machine interaction force is the smallest and the assistance effect is the most obvious. Finally, a human-machine coupled motion model was established in Adams, and the mechanical factors of the exoskeleton model were added through constraints and driving functions. Simulation experiments were conducted on the impact of active assistance at the exoskeleton joints on human-machine interaction forces. Verified the accuracy of theoretical research results on the impact of exoskeleton joint matching on the relative position deviation of the binding position and active joint assistance on human-machine interaction force.

Design of a Lower Limb Exoskeleton: Robust Control, Simulation and Experimental Results

This paper presents the development of a robust control algorithm to be applied in a knee and ankle joint exoskeleton designed for rehabilitation of flexion/extension movements. The goal of the control law is to follow the trajectory of a straight leg extension routine in a sitting position. This routine is commonly used to rehabilitate an injury on an Anterior Cruciate Ligament (ACL) and it is applied to the knee and ankle joints. Moreover, the paper presents the development and implementation of the robotic structure of the ankle joint to integrate it into an exoskeleton for gait rehabilitation. The development of the dynamic model and the implementation of the control algorithm in simulation and experimental tests are presented, showing that the proposed control guarantees the convergence of the tracking error.

Rehabilitation exoskeleton torque control based on PSO-RBFNN optimization.

Exoskeletons are widely used in the field of medical rehabilitation, however imprecise exoskeleton control may lead to accidents during patient rehabilitation, so improving the control performance of exoskeletons has become crucial. Nevertheless, improving the control performance of exoskeletons is extremely difficult, the nonlinear nature of the exoskeleton model makes control particularly difficult, and external interference when the patient wears an exoskeleton can also affect the control effect. In order to solve the above problems, a method based on particle swarm optimization (PSO) and RBF neural network to optimize exoskeleton torque control is proposed to study the motion trajectory of nonlinear exoskeleton joints in this paper, and it is found that exoskeleton torque control optimized by PSO-RBFNN has faster control speed, better stability, more accurate control results and stronger anti-interference, and the optimized exoskeleton can effectively solve the problem of difficult control of nonlinear exoskeleton and the interference problem when the patient wears the exoskeleton.

Output Constrained Control of Lower Limb Exoskeleton Based on Knee Motion Probabilistic Model With Finite-Time Extended State Observer

Due to randomness and uncertainty of individual walking gait, this study uses the sparse Gaussian process (SGP) to construct a knee motion probabilistic model related to its corresponding hip motion. Since the SGP can quantify output uncertainty, a time-varying constrained boundary of knee position is presented to guarantee the operator's safety and comfort in human-exoskeleton cooperative motion. First, a low-cost gait acquisition system (called CJD-1) composed of inertial measurement unit is constructed to collect the operator's gait information. Then, a virtual interaction torque field and an output-dependent universal barrier function are designed to realize the coordinated transformation of the time-varying constrained boundary generated by the SGP. Hence, the exoskeleton joint position is constrained by the desired output constrained boundary, which is complied with the operator's gait law. Then, a backstepping controller with a finite-time extended state observer is proposed to estimate and compensate unmeasured joint velocity and lumped uncertainty. The effectiveness of the proposed control scheme is verified by both simulations and experimental results of human-exoskeleton cooperative motion.

Nonlinear-Observer-Based Neural Fault-Tolerant Control for a Rehabilitation Exoskeleton Joint with Electro-Hydraulic Actuator and Error Constraint

The rehabilitation exoskeleton is an effective piece of equipment for stroke patients and the aged. However, this complex human–robot system incurs many problems, such as modeling uncertainties, unknown human–robot interaction, external disturbance, and actuator fault. This paper addresses the adaptive fault-tolerant tracking control for a lower limb rehabilitation exoskeleton joint driven by an electro-hydraulic actuator (EHA). First, the model of the exoskeleton joint is built by considering the principle of the hydraulic cylinder and the servo valve. Then, a novel disturbance-observer-based neural fault-tolerant control scheme is proposed, where the neural network and disturbance observer are incorporated to reduce the influence of the the nonlinear uncertainties and disturbance. Meanwhile, a barrier Lyapunov function is constructed to ensure the stability of the closed-loop system. Finally, comparative simulations on an exoskeleton joint validate the effect of the proposed control scheme.

Feasibility Study of Joint Exoskeleton Device Without Bowden Cables Based on Highly Integrated Wireless Fluxgate Sensor

Feasibility Study of Joint Exoskeleton Device Without Bowden Cables Based on Highly Integrated Wireless Fluxgate Sensor

Design and Analysis of a Novel Shoulder Exoskeleton Based on a Parallel Mechanism

Power-assisted upper-limb exoskeletons are primarily used to improve the handling efficiency and load capacity. However, kinematic mismatch between the kinematics and biological joints is a major problem in most existing exoskeletons, because it reduces the boosting effect and causes pain and long-term joint damage in humans. In this study, a shoulder augmentation exoskeleton was designed based on a parallel mechanism that solves the shoulder dislocation problem using the upper arm as a passive limb. Consequently, the human–machine synergy and wearability of the exoskeleton system were improved without increasing the volume and weight of the system. A parallel mechanism was used as the structural body of the shoulder joint exoskeleton, and its workspace, dexterity, and stiffness were analyzed. Additionally, an ergonomic model was developed using the principle of virtual work, and a case analysis was performed considering the lifting of heavy objects. The results show that the upper arm reduces the driving force requirement in coordinated motion, enhances the load capacity of the system, and achieves excellent assistance.

Human–Exoskeleton Interaction Force Estimation in Indego Exoskeleton

Accurate interaction force estimation can play an important role in optimizing human–robot interaction in an exoskeleton. In this work, we propose a novel approach for the system identification of exoskeleton dynamics in the presence of interaction forces as a whole multibody system without imposing any constraints on the exoskeleton dynamics. We hung the exoskeleton through a linear spring and excited the exoskeleton joints with chirp commands while measuring the exoskeleton–environment interaction force. Several structures of neural networks were trained to model the exoskeleton passive dynamics and estimate the interaction force. Our testing results indicated that a deep neural network with 250 neurons and 10 time–delays could obtain a sufficiently accurate estimation of the interaction force, resulting in an RMSE of 1.23 on Z–normalized applied torques and an adjusted R2 of 0.89.

Human Compatible Stiffness Modulation of a Novel VSA for Physical Human-Robot Interaction

Due to intensive human-robot interaction in exoskeletons, it is desirable to design and control the exoskeletons with behavior compatible to human limbs to achieve natural and energy-efficient motion assistance. This requires both novel variable stiffness actuators and also technologies able to detect human muscle stiffness, upon which exoskeleton joint stiffness can be tuned. In this paper, a novel stiffness modulation method is proposed to achieve variable stiffness with respect to human status. The method is developed upon a novel actuator of nonlinear variable stiffness. Moreover, human joint stiffness is estimated innovatively from Force Myography (FMG) signals. The correlation between the recorded FMG and human joint stiffness is established with Machine Learning methods, which is further used for online estimation. An elbow joint exoskeleton is finally developed and tested. The results validate experimentally the methods for bionic compatible stiffness modulation.

Novel Design and Control of a Crank-Slider Series Elastic Actuated Knee Exoskeleton for Compliant Human–Robot Interaction

The lower-limb assist exoskeleton plays the role of torque assiting and compliant tracking for wearers to perform tasks. Accurate torque generation, backdrivability performance, low output impedance, and hardware compactness are essential factors for lower-limb exoskeleton to achieve better compliant physical interaction. This research studies a crank-slider series elastic actuator (CS-SEA) that can be used as a compact exoskeleton joint module. The device has a unique crank slider mechanism, and a set of linear springs are equipped inside the slider to guarantee the nonlinear stiffness of its physical impedance so that the torque effect can be improved and a high level of transparency can be achieved. The RBF-based sliding mode controller is chosen as the output torque controller of the exoskeleton, and the adaptive neuro-fuzzy sliding mode control law is designed and its stability is verified. The precise output force control performance of CS-SEA is verified by experiments. The actuator is incorporated into a knee exoskeleton prototype and was worn by the subjects. The experimental results demonstrate the precision of the compliant transparent and torque assisting control while interacting with the human wearer.