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

2020 ◽  
Vol 10 (7) ◽  
pp. 2536
Author(s):  
Yao Tu ◽  
Aibin Zhu ◽  
Jiyuan Song ◽  
Huang Shen ◽  
Zhitao Shen ◽  
...  
Keyword(s):  
Lower Limb ◽  
Sliding Mode ◽  
Active Participation ◽  
Training Intensity ◽  
Active Muscle ◽  
Adaptive Sliding Mode ◽  
Exoskeleton Robot ◽  
Limb Rehabilitation ◽  
Movement Intention ◽  
Lower Limb Rehabilitation

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.

Impedance Control Based Sliding Mode for Lower Limb Rehabilitation Robot

2014 ◽  
Vol 672-674 ◽  
pp. 1770-1773 ◽  
Author(s):  
Fu Cheng Cao ◽  
Li Min Du
Keyword(s):  
Dynamic Response ◽  
Sliding Mode Control ◽  
Lower Limb ◽  
Control Method ◽  
Sliding Mode ◽  
Impedance Control ◽  
Rehabilitation Robot ◽  
Active Rehabilitation ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

Aimed at improving the dynamic response of the lower limb for patients, an impedance control method based on sliding mode was presented to implement an active rehabilitation. Impedance control can achieve a target-reaching training without the help of a therapist and sliding mode control has a robustness to system uncertainty and vary limb strength. Simulations demonstrate the efficacy of the proposed method for lower limb rehabilitation.

Human-Like Robust Adaptive PD Based Human Gait Tracking for Exoskeleton Robot

2021 ◽  
Vol 33 (1) ◽  
pp. 88-96
Author(s):  
Aihui Wang ◽  
Ningning Hu ◽  
Jun Yu ◽  
Junlan Lu ◽  
Yifei Ge ◽  
...  
Keyword(s):  
Control Strategy ◽  
Lower Limb ◽  
Structural Parameters ◽  
Human Gait ◽  
Pd Control ◽  
Rehabilitation Training ◽  
Exoskeleton Robot ◽  
Robust Adaptive ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

For patients with dyskinesias caused by central nervous system diseases such as stroke, in the early stage of rehabilitation training, lower limb rehabilitation robots are used to provide passive rehabilitation training. This paper proposed a human-like robust adaptive PD control strategy of the exoskeleton robot based on healthy human gait data. When the error disturbance is bounded, a human-like robust adaptive PD control strategy is designed, which not only enables the rehabilitation exoskeleton robot to quickly track the human gait trajectory obtained through the 3D NOKOV motion capture system, but also can well identify the structural parameters of the system and avoid excessively initial output torque for the robot. MATLAB simulation verifies that the proposed method has a better performance to realize tracking the experimental trajectory of human movement and anti-interference ability under the condition of ensuring global stability for a lower limb rehabilitation exoskeleton robot.

scholarly journals Lower limb rehabilitation exoskeleton robot: A review

2021 ◽  
Vol 13 (4) ◽  
pp. 168781402110118
Author(s):  
Jinman Zhou ◽  
Shuo Yang ◽  
Qiang Xue
Keyword(s):  
Lower Limb ◽  
Physical Status ◽  
Positive Role ◽  
Advantages And Disadvantages ◽  
Exoskeleton Robot ◽  
Human Kinematics ◽  
Patient Groups ◽  
Limb Rehabilitation ◽  
Movement Rules ◽  
Lower Limb Rehabilitation

Lower limb rehabilitation exoskeleton robots (LLRERs) play a positive role in lower limb rehabilitation and assistance for patients with lower limb disorders, and they are helpful to improve patients’ physical status. More and more experiments pay more attention to the kinematic and dynamic data characteristics of different patient groups. However, it is not clear whether these devices have broad adaptability and their clinical significance, so it is necessary to summarize and analyze these research results. This paper summarizes the LLRERs prototype and product in recent years, also compares the advantages and disadvantages of the theory and technology used in these research, and compares the functional characteristics of the devices, finally summarizes the aspects of the LLRERs to be improved. These devices apply advanced theories, techniques or structures, as well as human kinematics and dynamics data. However, due to the complexity of human body characteristics and movement rules, the theory or technology applied in the study design of LLRERs remains to be further studied, which can be improved in many aspects, such as improve the human-computer cooperation of equipment or carry out clinical trials. This paper can provide reference for researchers and designers in the future study, as well as understanding and selecting LLRERs for all kinds of therapist and patients.

scholarly journals A Self-Adaptive-Coefficient-Double-Power Sliding Mode Control Method for Lower Limb Rehabilitation Exoskeleton Robot

2021 ◽  
Vol 11 (21) ◽  
pp. 10329
Author(s):  
Yuepeng Zhang ◽  
Guangzhong Cao ◽  
Wenzhou Li ◽  
Jiangcheng Chen ◽  
Linglong Li ◽  
...  
Keyword(s):  
Environmental Factors ◽  
Sliding Mode Control ◽  
Lower Limb ◽  
Control Method ◽  
Sliding Mode ◽  
Control Law ◽  
Mode Control ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation ◽  
Self Adaptive

Lower limb rehabilitation exoskeleton robots have the characteristics of nonlinearity and strong coupling, and they are easily disturbed during operation by environmental factors. Thus, an accurate dynamic model of the robot is difficult to obtain, and achieving trajectory tracking control of the robot is also difficult. In this article, a self-adaptive-coefficient double-power sliding mode control method is proposed to overcome the difficulty of tracking the robot trajectory. The method combines an estimated dynamic model with sliding mode control. A nonlinear control law was designed based on the robot dynamics model and computational torque method, and a compensation term of control law based on double-power reaching law was introduced to reduce the disturbance from model error and environmental factors. The self-adaptive coefficient of the compensation term of the control law was designed to adaptively adjust the compensation term to improve the anti-interference ability of the robot. The simulation and experiment results show that the proposed method effectively improves the trajectory tracking accuracy and anti-interference ability of the robot. Compared with the traditional computed torque method, the proposed method decreases the tracking error by more than 71.77%. The maximum absolute error of the hip joint and knee joint remained below 0.55° and 1.65°, respectively, in the wearable experiment of the robot.

scholarly journals Human Intention Recognition for Lower Limb Rehabilitation Exoskeleton Robot

2021 ◽  
Author(s):  
Jing Chen ◽  
Zhiyuan Yu ◽  
Xiaorong Zhu ◽  
Longfei Jia ◽  
Yuping Huang
Keyword(s):  
Lower Limb ◽  
Cooperative Control ◽  
Surface Emg ◽  
Semg Signal ◽  
Exoskeleton Robot ◽  
Intention Recognition ◽  
Increasing Demand ◽  
Hidden Layer ◽  
Limb Rehabilitation ◽  
Lower Limb Rehabilitation

Abstract With the increasing aging of the population, the contradiction between the increasing demand for rehabilitation and the insufficient rehabilitation medical resources of the patients with moderate limb disorders in stroke is increasingly prominent. As a new means of rehabilitation, rehabilitation exoskeleton robot has gradually become a research hotspot in recent years. The rapid and accurate recognition of human lower limb movement intentions is very important for the control system of lower limb rehabilitation exoskeleton robots, this paper innovatively proposes an adaptive inertial weighted improved particle swarm optimization LSTM algorithm (IPSO-LSTM), which not only characterizes the mapping relationship between the surface EMG (sEMG) signal and the joint angle of the lower extremity in continuous motion, but also solves the values random setting problems of iterations number, learning rate and hidden layer number. More importantly, the optimization algorithm solves the network over fitting problem and further improves the predict accuracy of the model. Finally, based on the complex system of lower limb rehabilitation exoskeleton robot, the algorithm is applied to the human-machine cooperative control experiment of active rehabilitation training, the experiment verifies that the IPSO-LSTM algorithm model can meet the requirements of real-time and accuracy of active intention recognition.

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