Limb Rehabilitation Exoskeleton Research Articles

Non-linear active disturbance rejection control for upper limb rehabilitation exoskeleton

Trajectory tracking in upper limb rehabilitation exercises is utilized for repeatability of joint movement to improve the patient’s recovery in the early stages of rehabilitation. In this article, non-linear active disturbance rejection control as a combination of non-linear extended-state observer and non-linear state error feedback is used for the sinusoidal trajectory tracking control of the two-link model of an upper limb rehabilitation exoskeleton. The two links represent movements like flexion/extension for both the shoulder joint and the elbow joint in the sagittal plane. The Euler–Lagrange method was employed to acquire a dynamic model of an upper limb rehabilitation exoskeleton. To examine the efficacy and robustness of the proposed method, four disturbances cases in simulation studies with 20% parameter variation were applied. It was found that the non-linear active disturbance rejection control is robust against disturbances and achieves better tracking as compared to proportional–integral–derivative and existing conventional active disturbance rejection control method.

Development a multi-loop modulation method on the servo drives for lower limb rehabilitation exoskeleton

This paper proposed a multi-loop modulation method (MMM; 3M) on the servo drives applied for the lower limb rehabilitation exoskeleton (LLRE). This proposed 3M included the current, speed and position 3-loop with the auto-tuning, inertia identifier and external load torque observer. The controller gains by searching the optimal bandwidth and by identifying the inertia of the LLRE system were derived from the 3-loop auto-tuning. The controller gains could be instantly adjusted according to the system's oscillation during the LLRE gait motion. In particular, a concept of the phase margin (PM) was introduced in the calculation of the controller gain to ensure system stability. The proposed method could avoid system turbulence due to the excessive bandwidth. On the other hand, a torque observer and inertia identifier were adopted to compensate the external load. Compared the traditional parameter design method and traditional auto-tuning method with this proposed 3M in terms of tracking error and root mean square error (RMSE), the result showed that this proposed 3M provided better response and stability for gait tracking. Also, this proposed 3M could be adapted to variations in different loads.

An Adaptive Sliding Mode Variable Admittance Control Method for Lower Limb Rehabilitation Exoskeleton Robot

As passive rehabilitation training with fixed trajectory ignores the active participation of patients, in order to increase the active participation of patients and improve the effect of rehabilitation training, this paper proposes an innovative adaptive sliding mode variable admittance (ASMVA) controller for the Lower Limb Rehabilitation Exoskeleton Robot. The ASMVA controller consists of an outer loop with variable admittance controller and an inner loop with an adaptive sliding mode controller. It estimates the wearer’s active muscle strength and movement intention by judging the deviation between the actual and standard interaction force of the wearer’s leg and the exoskeleton, thereby adaptively changing admittance controller parameters to alter training intensity. Three healthy volunteers engaged in further experimental studies, including trajectory tracking experiments with no admittance, fixed admittance, and variable admittance adjustment. The experimental results show that the proposed ASMVA control scheme has high control accuracy. Besides, the ASMVA can not only increase training intensity according to the active muscle strength of the patient during positive movement intention (so as to increase active participation of the patient), but also increase the amount of trajectory adjustment during negative movement intention to ensure the safety of the patient.

Development of MMG sensors using PVDF piezoelectric electrospinning for lower limb rehabilitation exoskeleton

In this study, a new type of fiber-based mechanomyography (MMG) sensor was developed and used as a motion on/off trigger sensor for a lower limb rehabilitation exoskeleton (LLRE). Piezoelectric material, polyvinylidene difluoride (PVDF), was applied to fabricate a MMG sensor, using the near-field electrospinning technology to electrically spin PVDF fibers to ∼5-10 μm in diameter. PVDF fibers attached on an interdigitated (IDT) electrode with different pole pairs and interspaces were packaged into a MMG sensor. This MMG sensor was stuck on the thigh muscles to detect and acquire human motion intention signal, then trigger the controller and actuate the LLRE. The LLRE multi-axis control system included a master and four slave controllers. The master controller released the command signal to control the slave controllers via controller area network (CAN). A multi-axis control system was developed to actuate the joints of hips and knees of both legs by the LLRE. In the study, commercial electromyography (EMG) sensors were also to compare with the as-made MMG sensors. Results showed that the maximum signal amplitude of the commercail EMG sensor was about ∼0.2 V, whereas the MMG sensor was about ∼2.8 V. The signal-to-noise ratio (SNR) of EMG was about ∼4, while that of MMG was about ∼25. From physiological signals captured from the MMG sensor for the human walking with the LLRE, this new sensor improved the sensitivity in driving the LLRE.

Output Feedback Repetitive Learning Control of an Electrohydraulic Actuator of a Lower Limb Rehabilitation Exoskeleton

This paper addresses the output feedback repetitive learning control of an electrohydraulic actuator of a lower limb rehabilitation exoskeleton. A repetitive learning extended state observer (RLESO) is proposed to estimate the unmeasurable system states, mismatched modeling uncertainties, and repetitive unknowns. Based on the backstepping technique and RLESO, an output feedback repetitive controller (OFRC) is developed to improve the tracking performance. Both the convergence of the RLESO and the stability of the closed-loop system are proved in a Lyapunov way. The efficiencies of the proposed RLESO and OFRC are verified via simulation. It is worthwhile to highlight that the repetitive learning scheme is integrated into both the observer and controller design parts. In this way, the remarkable performances of the output tracking via OFRC and the estimations of unmeasurable states via RLESO can be ensured.

Fall preventive gait trajectory planning of a lower limb rehabilitation exoskeleton based on capture point theory

We study the balance problem caused by forward leaning of the wearer’s upper body during rehabilitation training with a lower limb rehabilitation exoskeleton. The instantaneous capture point is obtained by modeling the human-exoskeleton system and using the capture point theory. By comparing the stability region with instantaneous capture points of different gait phases, the balancing characteristics of different gait phases and changes to the equilibrium state in the gait process are analyzed. Based on a model of the human-exoskeleton system and the condition of balance of different phases, a trajectory correction strategy is proposed for the instability of the human-exoskeleton system caused by forward leaning of the wearer’s upper body. Finally, the reliability of the trajectory correction strategy is verified by carrying out experiments on the Zhejiang University Lower Extremity Exoskeleton. The proposed trajectory correction strategy can respond to forward leaning of the upper body in a timely manner. Additionally, in the process of the center of gravity transferred from a double-support phase to a single-support phase, the ratio of gait cycle to zero moment point transfer is reduced correspondingly, and the gait stability is improved.

Strength Analysis of Polymer Conical Gear Wheel Made with 3D Printing Technique

Abstract The article deals with the problem of designing conical gears with a curved line contour. The contour of the tooth flank is described by means of a helix and involutions. In the work, a conical gear designed to drive of the lower limb rehabilitation exoskeleton has analysed. Parameters of the conical gearbox have been adapted to design requirements of the exoskeleton. Gear wheels were made with ABS material using 3D printing technique. The article presents the results of strength calculations obtained using the method classical design of the gear wheals described in the norm ISO 6336-1996. In the strength calculations, bending and contact stresses were taken into account. Creating the contour of gears was aided through the gearbox wizard available in Inventor program. The work contains the results of a static tensile test of the material from which the gear wheels were made. In experimental and numerical studies, the orthotropy of the material used was taken into account. The orthogonal values of the Young’s modulus, the Poisson’s ratio and the Kirchhoff’s modulus were determined. The publication also includes partial results of fatigue tests in the area of normal stresses. In the research used to finite element method (FEM), determine of internal loads in the gear. A structure of the FEM model is described in detail. Maximum values of contact pressures determined by use to FEM models have been compared with the results obtained on the basis of Hertz’s formulas. The article presents basic geometrical and strength parameters of the designed gear. The work demonstrates the validity of the material models used. Limitations in the application of the classic method of calculating conical gears made of orthotropic materials have been indicated. The results of analytical and numerical calculations are presented in tabular and graphical form.

Inverse kinematic analysis and trajectory planning of a modular upper limb rehabilitation exoskeleton.

BACKGROUND: Stroke is the most prevalent neurological disease and often leads to disability. Stroke can affect a person’s daily life, for example, its typical feature is the decline in the patient’s upper limbs. In order to reduce the sports injury of stroke patients, the best method is to carry out certain rehabilitation training.OBJECTIVE: In this paper, inverse kinematic analysis and trajectory planning of a modular upper limb rehabilitation exoskeleton are proposed.METHODS: The reverse coordinate system method is applied to solve inverse kinematics of the exoskeleton with a non-spherical joint in the wrist. For verifying the effectiveness of the algorithms, the smooth round-trip trajectory movement in joint place is designed and simulated.RESULTS: The reverse coordinate system method can simplify the calculation process compared with the normal coordinate system. Smooth round-trip trajectory planning is simulated to generate a smooth trajectory curve.CONCLUSIONS: The developed inverse kinematics algorithm and trajectory planning method are effective.

A Simplified Inverse Dynamics Modelling Method for a Novel Rehabilitation Exoskeleton with Parallel Joints and Its Application to Trajectory Tracking

In this paper, a new modular upper limb rehabilitation exoskeleton, which is actuated by a parallel mechanical structure, is designed to help stroke patients. For analysing the relationship between motor torque and joint torque of the novel exoskeleton, a conversion algorithm mapping motor motion to joint motion is developed here. Then, to simplify the dynamics model of exoskeleton with parallel actuated joints, the serial equivalence configuration dynamics of the exoskeleton is established to be equivalent to the parallel joints dynamics. Afterwards, a torque controller used for our exoskeleton is designed based on the proposed conversion algorithm and the inverse dynamics of exoskeleton. It should be noted that the controller mentioned above combines both conversion algorithm and joint position decoupling. At last, for verifying the effectiveness of the proposed algorithms, a trajectory tracking simulation is given, and the simulated results show the proposed algorithms are valid.

SMA Based Elbow Exoskeleton for Rehabilitation Therapy and Patient Evaluation

A large number of musculoskeletal and neurological disorders can affect the upper limb limiting the subject’s ability to perform activities of daily living. In recent years, rehabilitation therapies based on robotics have been proposed as complement to the work of therapists. This paper introduces a prototype of exoskeleton for the evaluation and rehabilitation therapy of the elbow joint in flexion extension and pronation-supination. The main novelty is the use of bioinspired actuators based on shape memory alloys (for the first time) in an upper limb rehabilitation exoskeleton. Because of this, the device presents a light weight, less than 1 kg, and noiseless operation, both characteristics are very beneficial for rehabilitation therapies. In addition, the prototype has been designed with low-cost electronics and materials, and the result is a wearable, comfortable, and cheap rehabilitation exoskeleton for the elbow joint. The exoskeleton can generate the joint torque (active mode) or it can be used as a passive tool. (The patient performs therapy by itself, carrying the device while it collects relevant movement data for evaluation.) The simulations and experimental tests validate the solution in the first phases of rehabilitation therapies when slow and repetitive movements are required.

Enhanced neural network control of lower limb rehabilitation exoskeleton by add-on repetitive learning

Abstract This paper addresses neural network (NN) control of a lower limb exoskeleton for rehabilitation. Two control schemes are presented for exoskeleton to conduct trajectory tracking tasks, in the presence of unmodeled dynamics of exoskeleton, interaction between human and exoskeleton, as well as additional disturbances. The first controller is purely NN-based, and a combined error factor (CEF), which consists of the weighted sum of tracking error and its derivative, is adopted to enhance the human safety by improved transient response. The second controller is developed based on a combined scheme of repetitive learning control (RLC) and NN, where the add-on RLC is used to learn periodic uncertainties that attribute to the repetitive motion of the exoskeleton leg. Stabilities of the controllers are proved rigorously in a Lyapunov way. It is worthwhile to highlight that although the pure NN controller can deal with periodic and non-periodic uncertainties simultaneously, the main feature of exoskeleton motion during rehabilitation therapy, namely, the repetitiveness, is fully ignored, thus could degrade the tracking performance. Compared simulation reveals that, the proposed control method has achieved a significant control effect with remarkable transient performance.

Structural design and modal analysis of exoskeleton robot for rehabilitation of lower limb

According to the actual needs of rehabilitation training after knee joint replacement surgery, and based on ergonomics, the idea of personification design and the basic design idea of force transfer between human body and exoskeleton are discussed, objective to develop a rehabilitation exoskeleton robot for leg rehabilitation after knee joint replacement surgery. The robot can detect the movement trend of the human body, judge the motion intention in use, and promote the movement of the hind leg, so as to achieve the purpose of rehabilitation training of the knee joint. The modal analysis of the lower limb rehabilitation exoskeleton robot is carried out, and the first six order natural frequencies and vibration modes are obtained.

Development of an RBFN-based neural-fuzzy adaptive control strategy for an upper limb rehabilitation exoskeleton

The patients of paralysis with motion impairment problems require extensive rehabilitation programs to regain motor functions. The great labor intensity and limited therapeutic effect of traditional human-based manual treatment have recently boosted the development of robot-assisted rehabilitation therapy. In the present work, a neural-fuzzy adaptive controller (NFAC) based on radial basis function network (RBFN) is developed for a rehabilitation exoskeleton to provide human arm movement assistance. A comprehensive overview is presented to describe the mechanical structure and electrical real-time control system of the therapeutic robot, which provides seven actuated degrees of freedom (DOFs) and achieves natural ranges of upper extremity movement. For the purpose of supporting the disable patients to perform repetitive passive rehabilitation training, the RBFN-based NFAC algorithm is proposed to guarantee trajectory tracking accuracy with parametric uncertainties and environmental disturbances. The stability of the proposed control scheme is demonstrated through Lyapunov stability theory. Further experimental investigation, involving the position tracking experiment and the frequency response experiment, are conducted to compare the control performance of the proposed method to those of cascaded proportional-integral-derivative controller (CPID) and fuzzy sliding mode controller (FSMC). The comparison results indicate that the proposed RBFN-based NFAC algorithm is capable of obtaining lower position tracking error and better frequency response characteristic.

A motion intention-based upper limb rehabilitation training system to stimulate motor nerve through virtual reality

Motor rehabilitation strategies for treating motor deficits after stroke are based on the understanding of the neural plasticity. In recent years, various upper limb rehabilitation robots have been proposed for the stroke survivors to provide relearning of motor skills by stimulating the motor nerve. However, several aspects including costing, human–robot interaction, and effective stimulation of motor nerve still remain as major issues. In this article, a new upper limb rehabilitation training system named as motion intention-based virtual reality training system is developed to close the aforementioned issues. The system identifies the user’s motion intention via force sensors mounted on the rehabilitation robot to conduct therapeutic exercises and stimulates the user’s motor nerve by introducing the illusion of immersion in virtual reality environment. The illusion of immersion is developed by creating Virtual Exoskeleton Robot model which is driven by user’s motion intention and reflecting the motion states in real time. The users can be present to the training exercises by themselves and fully engage in the virtual reality environment, so that they can relax, move, and recreate motor neuro-pathways. As preliminary phase, six healthy subjects were invited to participate in experiments. The experimental results showed that the motion intention-based virtual reality training system is effective for the upper limb rehabilitation exoskeleton and the evaluations of the developed system showed a significant reduction of the performance error in the training task.

Design and kinematic analysis of a novel upper limb exoskeleton for rehabilitation of stroke patients.

This paper details the design process and features of a novel upper limb rehabilitation exoskeleton named CLEVER (Compact, Low-weight, Ergonomic, Virtual/Augmented Reality Enhanced Rehabilitation) ARM. The research effort is focused on designing a lightweight and ergonomic upper-limb rehabilitation exoskeleton capable of producing diverse and perceptually rich training scenarios. To this end, the knowledge available in the literature of rehabilitation robotics is used along with formal conceptual design techniques. This paper briefly reviews the systematic approach used for design of the exoskeleton, and elaborates on the specific details of the proposed design concept and its advantages over other design possibilities. The kinematic structure of CLEVER ARM has eight degrees of freedom supporting the motion of shoulder girdle, glenohumeral joint, elbow and wrist. Six degrees of freedom of the exoskeleton are active, and the two degrees of freedom supporting the wrist motion are passive. Kinematics of the proposed design is studied analytically and experimentally with the aid of a 3D printed prototype. The paper is concluded by some remarks on the optimization of the design, motorization of device, and the fabrication challenges.

Passive and Active Control Strategies of a Leg Rehabilitation Exoskeleton Powered by Pneumatic Artificial Muscles

Nerve injury can cause lower limb paralysis and gait disorder. Currently lower limb rehabilitation exoskeleton robots used in the hospitals need more power to correct abnormal motor patterns of stroke patients’ legs. These gait rehabilitation robots are powered by cumbersome and bulky electric motors, which provides a poor user experience. A newly developed gait rehabilitation exoskeleton robot actuated by low-cost and lightweight pneumatic artificial muscles (PAMs) is presented in this research. A model-free proxy-based sliding mode control (PSMC) strategy and a model-based chattering mitigation robust variable control (CRVC) strategy were developed and first applied in rehabilitation trainings, respectively. As the dynamic response of PAM due to the compressed air is low, an innovative intention identification control strategy was taken in active trainings by the use of the subject’s intention indirectly through the estimation of the interaction force between the subject’s leg and the exoskeleton. The proposed intention identification strategy was verified by treadmill-based gait training experiments.

Active disturbance rejection control based human gait tracking for lower extremity rehabilitation exoskeleton

This paper presents an active disturbance rejection control (ADRC) based strategy, which is applied to track the human gait trajectory for a lower limb rehabilitation exoskeleton. The desired human gait trajectory is derived from the Clinical Gait Analysis (CGA). In ADRC, the total external disturbance can be estimated by the extended state observer (ESO) and canceled by the designed control law. The observer bandwidth and the controller bandwidth are determined by the practical principles. We simulated the proposed methodology in MATLAB. The numerical simulation shows the tracking error comparison and the estimated errors of the extended state observer. Two experimental tests were carried out to prove the performance of the algorithm presented in this paper. The experiment results show that the proposed ADRC behaves a better performance than the regular proportional integral derivative (PID) controller. With the proposed ADRC, the rehabilitation system is capable of tracking the target gait more accurately.

Development of a lower limb rehabilitation exoskeleton based on real-time gait detection and gait tracking

Hemiplegia, apoplexia, or traffic accidents often lead to unilateral lower limb movement disorders. Traditional lower limb rehabilitation equipments usually execute walk training based on fixed gait trajectory; however, this type is unsuitable for unilateral lower limb disorders because they still have athletic ability and initiative walking intention on the healthy side. This article describes a wearable lower limb rehabilitation exoskeleton with a walk-assisting platform for safety and anti-gravity support. The exoskeleton detects and tracks the motion of the healthy leg, which is then used as the control input of the dyskinetic leg with half a gate-cycle delay. The patient can undergo walk training on his own intention, including individual walking habit, stride length, and stride frequency, which likely contribute to the training initiative. The series elastic actuator is chosen for the exoskeleton because the torque output can be accurately detected and used to calculate the assisted torque on the dyskinetic leg. This parameter corresponds to the recovery level of a patient’s muscle force. Finally, the walk-assisting experiments reveal that the rehabilitation exoskeleton in this article can provide the necessary assisting torques on the dyskinetic leg, which can be accurately monitored in real time to evaluate a patient’s rehabilitation status.

A passively safe cable driven upper limb rehabilitation exoskeleton.

When using upper limb exoskeletons that assist the movement of physically weak people, safety should be the most important index. In this paper, a passively safe, cable-driven upper limb exoskeleton with parallel actuated joints, which perfectly mimics human motions, is proposed. Compared with the existing upper limb exoskeletons which are mostly designed only considering the realization of functional properties, and having poor wearabity, a passively safe prototype for motion assistance based on human anatomy structure has been developed in our design. This design is based on the prior exoskeleton structure with the adoption of a gravity balanced device. The gravity balanced mechanism was confirmed in theory and simulation, showing it has a positive effect on balance.

Kinematics and Workspace Analysis of Parallel Lower Limb Rehabilitation Exoskeleton

In view of the lower paralysis patients,a new type of 3-DOF parallel lower limb exoskeleton mechanism is designed as the foundation for research,the forward and inverse position solution of the mechanism are analyzed with product of exponentials(POE)formulation,in the meanwhile,the Jacobian matrix and motion singularity of mechanism are also analyzed.Taking the maximum workspace as the objective function,the chief factors influencing the workspace of the parallel mechanism such as the workspace restriction of the length of linkage,the angle of motion pair and the human body's joint angle have been taken into account.The boundary of workspace is determined with the help of boundary search method,and the area of workspace is calculated.The influence of various parameters of the mechanism on the workspace is analyzed.On the basis of kinematics analysis,in order to satisfy the demand of hip's angle and knee's angle range of motion of normal human walking,to improve the mechanism kinematic performance as the goal,optimize the value of structural parameters.Preliminary analysis shows that the kinematical performance can been improved with optimizing the value of the structural parameters.The mechanism can be used to lower limb paralysis patients in rehabilitation training.The study paves the way for the design and analysis of the parallel mechanisms.