A Fractional-Order Ultra-Local Model-Based Adaptive Neural Network Sliding Mode Control of n-DOF Upper-Limb Exoskeleton With Input Deadzone

This paper proposes an adaptive neural network sliding mode control based on fractional-order ultra-local model for n-DOF upper-limb exoskeleton in presence of uncertainties,external disturbances and input deadzone.Considering the model complexity and input deadzone,a fractional-order ultra-local model is proposed to formulate the original dynamic system for simple controller design.Firstly,the control gain of ultra-local model is considered as a constant.The fractional-order sliding mode technique is designed to stabilize the closed-loop system,while fractional-order time-delay estimation is combined with neural network to estimate the lumped disturbance.Correspondingly,a fractional-order ultra-local model-based neural network sliding mode controller(FO-NNSMC) is proposed.Secondly,to avoid disadvantageous effect of improper gain selection on the control performance,the control gain of ultra-local model is considered as an unknown parameter.Then,the Nussbaum technique is introduced into the FO-NNSMC to deal with the stability problem with unknown gain.Correspondingly,a fractional-order ultra-local model-based adaptive neural network sliding mode controller(FO-ANNSMC) is proposed.Moreover,the stability analysis of the closed-loop system with the proposed method is presented by using the Lyapunov theory.Finally,with the co-simulations on virtual prototype of 7-DOF iReHave upper-limb exoskeleton and experiments on 2-DOF upper-limb exoskeleton,the obtained compared results illustrate the effectiveness and superiority of the proposed method.

Design and Implementation of a Rehabilitation Upper-limb Exoskeleton Robot Controlled by Cognitive and Physical Interfaces

This paper presents an upper limb exoskeleton that allows cognitive(through electromyography signals)and physical user interaction(through load cells sensors)for passive and active exercises that can activate neuroplasticity in the rehabilitation process of people who suffer from a neurological injury.For the exoskeleton to be easily accepted by patients who suffer from a neurological injury,we used the ISO9241-210:2010 as a methodology design process.As the first steps of the design process,design requirements were collected from previous usability tests and literature.Then,as a second step,a technological solution is proposed,and as a third step,the system was evaluated through performance and user testing.As part of the technological solution and to allow patient participation during the rehabilitation process,we have proposed a hybrid admittance control whose input is load cell or electromyography signals.The hybrid admittance control is intended for active therapy exercises,is easily implemented,and does not need musculoskeletal modeling to work.Furthermore,electromyography signals classification models and features were evaluated to identify the best settings for the cognitive human–robot interaction.

Analysis of a passive ankle exoskeleton for reduction of metabolic costs during walking

Modern conflicts demand substantial physical and psychological exertion,often resulting in fatigue and diminished combat or operational readiness.Several exoskeletons have been developed recently to address these challenges,presenting various limitations that affect their operational or everyday usability.This article evaluates the performance of a dual-purpose passive ankle exoskeleton developed for the reduction of metabolic costs during walking,seeking to identify a force element that could be applied to the target population.Based on the 6-min walk test,twenty-nine subjects participated in the study using three different force elements.The results indicate that it is possible to reduce metabolic expenditure while using the developed exoskeleton.Additionally,the comfort and range of motion results verify the exoskeleton's suitability for use in uneven terrain and during extended periods.Nevertheless,the choice of the force element should be tailored to each user,and the control system should be adjustable to optimise the exoskeleton's performance.

Model Parameters Identification and Backstepping Control of Lower Limb Exoskeleton Based on Enhanced Whale Algorithm

Exoskeletons generally require accurate dynamic models to design the model-based controller conveniently under the human-robot interaction condition.However,due to unknown model parameters such as the mass,moment of inertia and mechanical size,the dynamic model of exoskeletons is difficult to construct.Hence,an enhanced whale optimization algorithm(EWOA)is proposed to identify the exoskeleton model parameters.Meanwhile,the periodic excitation trajectories are designed by finite Fourier series to input the desired position demand of exoskeletons with mechanical physical constraints.Then a backstepping controller based on the identified model is adopted to improve the human-robot wearable comfortable performance under cooperative motion.Finally,the proposed Model parameters identification and control are verified by a two-DOF exoskeletons platform.The knee joint motion achieves a steady-state response after 0.5 s.Meanwhile,the position error of hip joint response is less than 0.03 rad after 0.9 s.In addition,the steady-state human-robot interaction torque of the two joints is constrained within 15 N·m.This research proposes a whale optimization algorithm to optimize the excitation trajectory and identify model parameters.Furthermore,an enhanced mutation strategy is adopted to avoid whale evolution’s unsatisfactory local optimal value.

Neural Network Robust Control Based on Computed Torque for Lower Limb Exoskeleton

The lower limb exoskeletons are used to assist wearers in various scenarios such as medical and industrial settings.Complex modeling errors of the exoskeleton in different application scenarios pose challenges to the robustness and stability of its control algorithm.The Radial Basis Function(RBF)neural network is used widely to compensate for modeling errors.In order to solve the problem that the current RBF neural network controllers cannot guarantee the asymptotic stability,a neural network robust control algorithm based on computed torque method is proposed in this paper,focusing on trajectory tracking.It innovatively incorporates the robust adaptive term while introducing the RBF neural network term,improving the compensation ability for modeling errors.The stability of the algorithm is proved by Lyapunov method,and the effectiveness of the robust adaptive term is verified by the simulation.Experiments wearing the exoskeleton under different walking speeds and scenarios were carried out,and the results show that the absolute value of tracking errors of the hip and knee joints of the exoskeleton are consistently less than 1.5°and 2.5°,respectively.The proposed control algorithm effectively compensates for modeling errors and exhibits high robustness.

Adaptive Robust Control with Leakage-Type Control Law for Trajectory Tracking of Exoskeleton Robots

This paper investigates the trajectory following problem of exoskeleton robots with numerous constraints. However, as a typical nonlinear system with variability and parameter uncertainty, it is difficult to accurately achieve the trajectory tracking control for exoskeletons. In this paper, we present a robust control of trajectory tracking control based on servo constraints. Firstly, we consider the uncertainties (e.g., modelling errors, initial condition deviations, structural vibrations, and other unknown external disturbances) in the exoskeleton system, which are time-varying and bounded. Secondly, we establish the dynamic model and formulate a close-loop connection between the dynamic model and the real world. Then, the trajectory tracking issue is regarded as a servo constraint problem, and an adaptive robust control with leakage-type adaptive law is proposed with the guaranteed Lyapunov stability. Finally, we conduct numerical simulations to verify the performance of the proposed controller.

肌电生物反馈疗法与脊髓损伤患者运动功能的恢复

背景:肌电生物反馈技术具有非侵入性、实时反馈、个性化治疗和促进神经可塑性等独特优势,加速了脊髓损伤患者的功能恢复。目的:综述肌电生物反馈联合运动疗法、外骨骼机器人以及虚拟现实技术在脊髓损伤运动功能恢复中的应用现状及治疗效果。方法:应用计算机检索中国知网、PubMed数据库建库至2024年5月期间的相关文献,英文检索词为“Spinal cord injury,EMG biofeedback,physical therapy,robotic exoskeleton,VR,motor function,exercise”,中文检索词为“脊髓损伤,肌电生物反馈,运动疗法,外骨骼机器人,虚拟现实,运动功能,运动”,最终纳入71篇文献进行综述。结果与结论:肌电生物反馈疗法促进脊髓损伤康复的机制包括促进神经可塑性变化、增强神经肌肉连接和改善运动模式。肌电生物反馈作为新兴的技术手段,通常与运动疗法、外骨骼机器人以及虚拟现实联合用于脊髓损伤后运动功能的恢复,综合治疗效果得到明显提升。然而目前仍存在一些问题和挑战,例如缺乏机制的详细解析、缺少为结合疗效提供有力证据的大规模试验、技术适应性有限等。未来的研究可以集中在这些方面:提高肌电生物反馈的个性化和精准性;可以探索将肌电生物反馈与更先进的技术或工学设备相结合开发新型康复设备,扩大应用领域;将肌电生物反馈应用到步态训练系统、呼吸训练系统以及四肢联动康复系统中,提高反馈的准确性和个性化治疗方案的效果,同时提高设备的易用性和舒适性。

人工智能在脊髓神经损伤与修复领域研究热点的可视化分析

背景:近年来人工智能逐渐兴起,在多方面应用于脊髓神经损伤与修复领域,对临床治疗也有诸多积极影响。目的:研究人工智能在脊髓神经损伤与修复领域的诊断、治疗和康复中的应用进展,明确该领域的研究热点和不足,为今后研究工作提供建议。方法:在Web of Science核心集数据库检索建库至2023年收录的人工智能在脊髓神经损伤与修复领域相关文献,使用CiteSpace 6.1.R6和VOSviewer 1.6.19软件对文献数据进行一般文献学分析、文献共被引、期刊共被引、期刊双图叠加及关键词聚类等可视化分析。结果与结论:①共筛选出1713篇文章,此领域年发文量呈波动上升趋势,其中美国占据主导地位,Kadone Hideki是发文量最多的作者,《ARCH PHYS MED REHAB》是被引用次数最多的期刊。②关键词共现和聚类分析显示,去除与检索词相近的关键词后,主要关键词被分为3个主要集群:外骨骼与运动康复(为最大核心热点)、机器学习和神经可塑性、机器人和康复训练。③关键词爆发分析显示,深度学习和人工智能在过去5年中已成为突发术语。④文献共被引和高被引文献分析结果显示,人工智能在脊髓神经损伤与修复领域热点集中于动力外骨骼(powered exoskeleton)、步态(gait)、神经电刺激(electrical nerve stimulation)、皮质内脑机接口(intracortical brain-computer interface,IBCI)、机器人(robot)、高分子生物材料(polymer biomaterials)及神经干细胞(neural stem cell)等内容。⑤人工智能在脊髓神经损伤与修复领域的研究近年来呈现上升趋势,该领域的关注点从外骨骼、电刺激等单一的治疗手段,逐渐向智能化、精准化和个性化等方向转变。⑥该领域存在一些局限性,例如数据缺失或不平衡的后果、数据准确性和可重复性低以及伦理问题(如隐私、研究透明度和临床可靠性等),未来的研究应该解决数据收集的问题,需要大样本、高质量的临床数据集来建立有效的人工智能模型;同时该领域的基因组学等机制研究十分薄弱,未来可利用类脑芯片等多种机器学习技术,运用基因编辑治疗及单细胞空间转录组等方法,进行再生相关基因上调和轴突生长结构蛋白产生等基础机制研究。

A Review on Lower Limb Rehabilitation Exoskeleton Robots

Lower limb rehabilitation exoskeleton robots integrate sensing, control, and other technologies and exhibit the characteristics of bionics, robotics, information and control science, medicine, and other interdisciplinary areas. In this review, the typical products and prototypes of lower limb exoskeleton rehabilitation robots are introduced and stateof-the-art techniques are analyzed and summarized. Because the goal of rehabilitation training is to recover patients’ sporting ability to the normal level, studying the human gait is the foundation of lower limb exoskeleton rehabilitation robot research. Therefore, this review critically evaluates research progress in human gait analysis and systematically summarizes developments in the mechanical design and control of lower limb rehabilitation exoskeleton robots. From the performance of typical prototypes, it can be deduced that these robots can be connected to human limbs as wearable forms;further, it is possible to control robot movement at each joint to simulate normal gait and drive the patient’s limb to realize robot-assisted rehabilitation training. Therefore human–robot integration is one of the most important research directions, and in this context, rigid-flexible-soft hybrid structure design, customized personalized gait generation, and multimodal information fusion are three key technologies.

Proceeding of Human Exoskeleton Technology and Discussions on Future Research

After more than half a century of intense efforts, the development of exoskeleton has seen major advances, and several remarkable achievements have been made. Reviews of developing history of exoskeleton are presented, both in active and passive categories. Major models are introduced, and typical technologies are commented on. Difficulties in control algorithm, driver system, power source, and man-machine interface are discussed. Current researching routes and major developing methods are mapped and critically analyzed, and in the process, some key problems are revealed. First, the exoskeleton is totally different from biped robot, and relative studies based on the robot technologies are considerably incorrect. Second, biomechanical studies are only used to track the motion of the human body, the interaction between human and machines are seldom studied. Third, the traditional developing ways which focused on servo-controlling have inborn deficiency from making portable systems. Research attention should be shifted to the human side of the coupling system, and the human ability to learn and adapt should play a more significant role in the control algorithms Having summarized the major difficulties, possible future works are discussed. It is argued that, since a distinct boundary cannot be drawn in such strong-coupling human-exoskeleton system, the more complex the control system gets, the more difficult it is for the user to learn to use. It is suggested that the exoskeleton should be treated as a simple wearable tool, and downgrading its automatic level may be a change toward a brighter research outlook. This effort at simplification is definitely not easy, as it necessitates theoretical supports from fields such as biomechanics, ergonomics, and bionics.

Development of a Hand Exoskeleton System for Index Finger Rehabilitation

In order to overcome the drawbacks of traditional rehabilitation method,the robot-aided rehabilitation has been widely investigated for the recent years.And the hand rehabilitation robot,as one of the hot research fields,remains many challenging issues to be investigated.This paper presents a new hand exoskeleton system with some novel characteristics.Firstly,both active and passive rehabilitative motions are realized.Secondly,the device is elaborately designed and brings advantages in many aspects.For example,joint motion is accomplished by a parallelogram mechanism and high level motion control is therefore made very simple without the need of complicated kinematics.The adjustable joint limit design ensures that the actual joint angles don＇t exceed the joint range of motion（ROM） and thus the patient safety is guaranteed.This design can fit to the different patients with different joint ROM as well as to the dynamically changing ROM for individual patient.The device can also accommodate to some extent variety of hand sizes.Thirdly,the proposed control strategy simultaneously realizes the position control and force control with the motor driver which only works in force control mode.Meanwhile,the system resistance compensation is preliminary realized and the resisting force is effectively reduced.Some experiments were conducted to verify the proposed system.Experimentally collected data show that the achieved ROM is close to that of a healthy hand and the range of phalange length（ROPL） covers the size of a typical hand,satisfying the size need of regular hand rehabilitation.In order to evaluate the performance when it works as a haptic device in active mode,the equivalent moment of inertia（MOI） of the device was calculated.The results prove that the device has low inertia which is critical in order to obtain good backdrivability.The experiments also show that in the active mode the virtual interactive force is successfully feedback to the finger and the resistance is reduced by one-third;for the passive control mode,the desired trajectory is realized satisfactorily.

Structure Design of Lower Limb Exoskeletons for Gait Training

Due to the close physical interaction between human and machine in process of gait training, lower limb exoskeletons should be safe, comfortable and able to smoothly transfer desired driving force/moments to the patients. Correlatively, in kinematics the exoskeletons are required to be compatible with human lower limbs and thereby to avoid the uncontrollable interactional loads at the human-machine interfaces. Such requirement makes the structure design of exoskeletons very difficult because the human-machine closed chains are complicated. In addition, both the axis misalignments and the kinematic character difference between the exoskeleton and human joints should be taken into account. By analyzing the DOF（degree of freedom） of the whole human-machine closed chain, the human-machine kinematic incompatibility of lower limb exoskeletons is studied. An effective method for the structure design of lower limb exoskeletons, which are kinematically compatible with human lower limb, is proposed. Applying this method, the structure synthesis of the lower limb exoskeletons containing only one-DOF revolute and prismatic joints is investigated; the feasible basic structures of exoskeletons are developed and classified into three different categories. With the consideration of quasi-anthropopathic feature, structural simplicity and wearable comfort of lower limb exoskeletons, a joint replacement and structure comparison based approach to select the ideal structures of lower limb exoskeletons is proposed, by which three optimal exoskeleton structures are obtained. This paper indicates that the human-machine closed chain formed by the exoskeleton and human lower limb should be an even-constrained kinematic system in order to avoid the uncontrollable human-machine interactional loads. The presented method for the structure design of lower limb exoskeletons is universal and simple, and hence can be applied to other kinds of wearable exoskeletons.

NOVEL 6-DOF WEARABLE EXOSKELETON ARM WITH PNEUMATIC FORCE-FEEDBACK FOR BILATERAL TELEOPERATION

A particular emphasis is put on a novel wearable exoskeleton arm, ZJUESA, with 6 degrees of freedom, which is used for the robot teleoperation with the force-feedback in the unknown environment. In this external structure mechanism, the 3-revolution-prismatic-spherical （3RPS） parallel mechanism is devised from the concept of the human upper-limb anatomy and applied for the shoulder 3-DOF joint. Meanwhile, the orthogonal experiment design method is introduced for its optimal design. Aiming at enhancing the performance of teleoperation, the force feedback is employed by the pneumatic system on ZJUESA to produce the vivid feeling in addition to the soft control interface. Due to the compressibility and nonlinearity of the pneumatic force feedback system, a novel hybrid fuzzy controller for the precise force control is proposed and realized based on the Mega8 microcontroller units as the units of the distributed control system on ZJUESA. With the results of several experiments for master-slave control with force feedback, the feasibility of ZJUESA system and the effect of its hybrid fuzzy controller are verified.

Robotic exoskeletons: The current pros and cons

Robotic exoskeletons have emerged as rehabilitation tool that may ameliorate several of the existing healthrelated consequences after spinal cord injury(SCI).However,evidence to support its clinical application is still lacking considering their prohibitive cost.The current mini-review is written to highlight the main limitations and potential benefits of using exoskeletons in the rehabilitation of persons with SCI.We have recognized two main areas relevant to the design of exoskeletons and to their applications on major health consequences after SCI.The design prospective refers to safety concerns,fitting time and speed of exoskeletons.The health prospective refers to factors similar to body weight,physical activity,pressure injuries and bone health.Clinical trials are currently underway to address some of these limitations and to maximize the benefits in rehabilitation settings.Future directions highlight the need to use exoskeletons in conjunction with other existing and emerging technologies similar to functional electrical stimulation and brain-computer interface to address major limitations.Exoskeletons have the potential to revolutionize rehabilitation following SCI;however,it is still premature to make solid recommendations about their clinical use after SCI.

Design of a Passive Gait‑based Ankle‑foot Exoskeleton with Self‑adaptive Capability

Propulsion during push-off is the key to realizing human locomotion.Humans have evolved a way of walking with high energy utilization,but it can be further improved.Drawing inspiration from the muscle-tendon unit,a passive spring-actuated ankle-foot exoskeleton is designed to assist with human walking and to lengthen walking duration by mechanically enhancing walking efficiency.Detection of the gait events is realized using a smart clutch,which is designed to detect the contact states between the shoe sole and the ground,and automatically switch its working state.The engagement of a suspended spring behind the human calf muscles is hence controlled and is in synchrony with gait.The device is completely passive and contains no external power source.Energy is stored and returned passively using the clutch.In our walking trials,the soleus electromyography activity is reduced by as much as 72.2%when the proposed ankle-foot exoskeleton is worn on the human body.The influence of the exoskeleton on walking habits is also studied.The results show the potential use of the exoskeleton in humans’daily life.

Neural-Network-Based Nonlinear Model Predictive Tracking Control of a Pneumatic Muscle Actuator-Driven Exoskeleton

Pneumatic muscle actuators(PMAs)are compliant and suitable for robotic devices that have been shown to be effective in assisting patients with neurologic injuries,such as strokes,spinal cord injuries,etc.,to accomplish rehabilitation tasks.However,because PMAs have nonlinearities,hysteresis,and uncertainties,etc.,complex mechanisms are rarely involved in the study of PMA-driven robotic systems.In this paper,we use nonlinear model predictive control(NMPC)and an extension of the echo state network called an echo state Gaussian process(ESGP)to design a tracking controller for a PMA-driven lower limb exoskeleton.The dynamics of the system include the PMA actuation and mechanism of the leg orthoses;thus,the system is represented by two nonlinear uncertain subsystems.To facilitate the design of the controller,joint angles of leg orthoses are forecasted based on the universal approximation ability of the ESGP.A gradient descent algorithm is employed to solve the optimization problem and generate the control signal.The stability of the closed-loop system is guaranteed when the ESGP is capable of approximating system dynamics.Simulations and experiments are conducted to verify the approximation ability of the ESGP and achieve gait pattern training with four healthy subjects.

WALK-ASSISTING BALANCE SYSTEM OF THE EXOSKELETON ROBOT FOR DISABLED PEOPLE

A novel methodology for a walk-assisting balance system of the exoskeleton robot for dis-abled people is presented. The experiment on the walk-assisting balance system is implemented using amini-type ropewalker robot. The mechanism of the ropewalker robot is designed, its dynamic model isbuilt, and its control system based on PWM is developed. The emulations in Matlab and the results ofexperiments prove that this methodology is effective.

One Novel Hydraulic Actuating System for the Lower-Body Exoskeleton

The hydraulic exoskeleton is one research hotspot in the field of robotics,which can take heavy load due to the high power density of the hydraulic system.However,the traditional hydraulic system is normally centralized,inefficient,and bulky during application,which limits its development in the exoskeleton.For improving the robot's performance,its hydraulic actuating system should be optimized further.In this paper a novel hydraulic actuating system(HAS)based on electric-hydrostatic actuator is proposed,which is applied to hip and knee joints.Each HAS integrates an electric servo motor,a high-speed micro pump,a specific tank,and other components into a module.The specific parameters are obtained through relevant simulation according to human motion data and load requirements.The dynamic models of the HAS are built,and validated by the system identification.Experiments of trajectory tracking and human-exoskeleton interaction are carried out,which demonstrate the proposed HAS has the ability to be applied to the exoskeleton.Compared with the previous prototype,the total weight of the HAS in the robot is reduced by about 40%,and the power density is increased by almost 1.6 times.

Control and Implementation of 2-DOF Lower Limb Exoskeleton Experiment Platform

In this study,a humanoid prototype of 2-DOF(degrees of freedom)lower limb exoskeleton is introduced to evaluate the wearable comfortable effect between person and exoskeleton.To improve the detection accuracy of the humanrobot interaction torque,a BPNN(backpropagation neural networks)is proposed to estimate this interaction force and to compensate for the measurement error of the 3D-force/torque sensor.Meanwhile,the backstepping controller is designed to realize the exoskeleton's passive position control,which means that the person passively adapts to the exoskeleton.On the other hand,a variable admittance controller is used to implement the exoskeleton's active followup control,which means that the person's motion is motivated by his/her intention and the exoskeleton control tries best to improve the human-robot wearable comfortable performance.To improve the wearable comfortable effect,serval regular gait tasks with different admittance parameters and step frequencies are statistically performed to obtain the optimal admittance control parameters.Finally,the BPNN compensation algorithm and two controllers are verified by the experimental exoskeleton prototype with human-robot cooperative motion.

Human-machine compatibility and dynamic analysis of a novel unpowered and self-adaptive shoulder rehabilitation exoskeleton

To reduce the complexity of the configuration and control strategy for shoulder rehabilitation exoskeleton,a 2R1R1P2R serial of shoulder exoskeleton based on gravity balance is proposed.Based on three basic rotatory shoulder joints,an exact kinematic constraint system can be formed between the exoskeleton and the upper arm by introducing a passive sliding pair and a center of glenohumeral(CGH)unpowered compensation mechanism,which realizes the human-machine kinematic compatibility.Gravity balance is used in the CGH compensation mechanism to provide shoulder joint support.Meanwhile,the motion of the compensation mechanism is pulled by doing reverse leading through the arm to realize the kinematic self-adaptive,which decreases control complexity.Besides,a simple and intuitive spring adjustment strategy is proposed to ensure the gravity balance of any prescribed quality.Furthermore,according to the influencing factors analysis of the scapulohumeral rhythm,the kinematic analysis of CGH mechanism is performed,which shows that the mechanism can fit the trajectory of CGH under various conditions.Finally,the dynamic simulation of the mechanism is carried out.Results indicate that the compensation torques are reduced to below 0.22 N·m,and the feasibility of the mechanism is also verified.