A novel adaptive iterative learning control approach and human-in-the-loop control pattern for lower limb rehabilitation robot in disturbances environment

Sun, Zhongbo; Li, Feng; Duan, Xiaoqin; Jin, Long; Lian, Yufeng; Liu, Shuaishi; Liu, Keping

doi:10.1007/s10514-021-09988-3

Cited by 25 publications

(14 citation statements)

References 38 publications

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“…The series and parallel structures are rigid structures. The Lagrange method [47] and Newton-Euler method [48] can be used to establish dynamic models for rigid-body dynamics modelling, which is widely used in industrial robots. For the lower limb exoskeleton robot in a series Fig.…”

Section: Biological-signal-based Methodsmentioning

confidence: 99%

Review of human—robot coordination control for rehabilitation based on motor function evaluation

et al. 2022

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As a wearable and intelligent system, a lower limb exoskeleton rehabilitation robot can provide auxiliary rehabilitation training for patients with lower limb walking impairment/loss and address the existing problem of insufficient medical resources. One of the main elements of such a human—robot coupling system is a control system to ensure human—robot coordination. This review aims to summarise the development of human—robot coordination control and the associated research achievements and provide insight into the research challenges in promoting innovative design in such control systems. The patients’ functional disorders and clinical rehabilitation needs regarding lower limbs are analysed in detail, forming the basis for the human—robot coordination of lower limb rehabilitation robots. Then, human—robot coordination is discussed in terms of three aspects: modelling, perception and control. Based on the reviewed research, the demand for robotic rehabilitation, modelling for human—robot coupling systems with new structures and assessment methods with different etiologies based on multi-mode sensors are discussed in detail, suggesting development directions of human—robot coordination and providing a reference for relevant research.

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Section: Biological-signal-based Methodsmentioning

confidence: 99%

Review of human—robot coordination control for rehabilitation based on motor function evaluation

et al. 2022

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“…Eqn. (2) shows that the joint angles of each joint can be obtained from the position coordinates of the lower limb rehabilitation exoskeleton by inverse kinematics analysis. In general, the analysis of forward kinematics and inverse kinematics establishes the relationship between the joint angle variable of the lower limb exoskeleton robot and the position coordinate of the end of the connecting rod, and analyzes the motion process of the exoskeleton robot, which provides a theoretical basis for the design of the control method.…”

Section: Kinematics Modelmentioning

confidence: 99%

“…Among them, the lower limb rehabilitation exoskeleton robot introduces robot technology into the field of motor function rehabilitation training, which can help patients with lower limb dysfunction to achieve effective rehabilitation training under the guidance of rehabilitation medicine theory. It has certain advantages compared with traditional manual rehabilitation training [2][3][4]. However, so as to avoid secondary injury caused by rehabilitation robot in contact with patients, it is particularly important to design a well compliance control system.…”

Section: Introductionmentioning

confidence: 99%

Research on finite time stability of lower limb rehabilitation exoskeleton based on compliance control

Liu

et al. 2022

Preprint

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In this paper, in order to achieve safe, stable and efficient lower limb rehabilitation training, a PRR-NTSMIC(power reaching rate-nonsingular terminal sliding mode impedance controller, PRR-NTSMIC) for lower limb rehabilitation exoskeleton robot is proposed. Firstly, the kinemat-ics and dynamics models of the lower limb rehabilitation exoskeleton robot are established. On the basis of the model, PRR-NTSMIC is illustrated to ensure the compliance, comfort and robustness of the lower limb rehabilitation exoskeleton robot in the process of rehabilitation training, and the FTS(finite-time stability,FTS) of the system is verified by Lyapunov. Secondly, the superiority of the proposed control scheme is illustrated by designing a comparative simulation with the traditional PRR-SMIC(power reaching rate-sliding mode impedance controller, PRR-SMIC) and PRR-TSMIC(power reaching rate-terminal sliding mode impedance controller, PRR-TSMIC) algorithms. Then, in order to obtain better controller performance, through analyzing the influence of parameters values on control effect, numerical comparison simulations are designed to select the optimal controller 1 Springer Nature 2021 L A T E X template Article Title parameters values. Finally, the human bicycle motion data are collected as the system input for bicycle rehabilitation training based on lower limb rehabilitation exoskeleton robot to verify the proposed control method. The experimental results illustrate that the proposed controller has high tracking accuracy, effectiveness, robustness and FTS.

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“…While this method was found in some cases to increase the patient's participation [9], this manual tuning of impedance controllers may result in controllers that are too stiff or too compliant for different patients, depending on the severity of their injury. Lately, the neurological rehabilitation community turned more towards methods that can provide more personalised assistance [10]- [12]. To achieve a higher level of personalisation in rehabilitation, one approach that has been proposed is the use of iterative learning controllers [13]- [15].…”

Section: Introductionmentioning

confidence: 99%

Designing Personalised Rehabilitation Controllers using Offline Model-Based Optimisation

Christou

Gordon

Stouraitis

et al. 2022

2022 IEEE International Conference on Robotics and Biomimetics (ROBIO)

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The use of robotic assistance in rehabilitation is becoming more popular, yet delivering optimal assistance remains an open challenge. In order to accelerate a patient's recovery, assistance that is personalised to the needs of the patient is required. However, controllers of rehabilitation robots have traditionally been designed and tuned heuristically, through trial and error, with one set of parameters used across several patients. In this paper, we propose an offline model-based optimisation approach, which can be used to create personalised rehabilitation controllers. We formulate the process of designing and tuning a rehabilitation controller as a multi-objective optimisation problem, and we solve this problem using Bayesian optimisation. We evaluate our method with forward dynamics simulations and the results demonstrate that a set of controller parameters can be obtained that are both patient-specific and task-specific. Our approach could be used for the personalisation of controllers designed for rehabilitation, injury prevention and human augmentation.

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A novel adaptive iterative learning control approach and human-in-the-loop control pattern for lower limb rehabilitation robot in disturbances environment

Cited by 25 publications

References 38 publications

Review of human—robot coordination control for rehabilitation based on motor function evaluation

Review of human—robot coordination control for rehabilitation based on motor function evaluation

Research on finite time stability of lower limb rehabilitation exoskeleton based on compliance control

Designing Personalised Rehabilitation Controllers using Offline Model-Based Optimisation

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