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1 – 10 of 209Rohollah Hasanzadeh Fereydooni, Hassan Siahkali, Heidar Ali Shayanfar and Amir Houshang Mazinan
This paper aims to propose an innovative adaptive control method for lower-limb rehabilitation robots.
Abstract
Purpose
This paper aims to propose an innovative adaptive control method for lower-limb rehabilitation robots.
Design/methodology/approach
Despite carrying out various studies on the subject of rehabilitation robots, the flexibility and stability of the closed-loop control system is still a challenging problem. In the proposed method, surface electromyography (sEMG) and human force-based dual closed-loop control strategy is designed to adaptively control the rehabilitation robots. A motion analysis of human lower limbs is performed by using a wavelet neural network (WNN) to obtain the desired trajectory of patients. In the outer loop, the reference trajectory of the robot is modified by a variable impedance controller (VIC) on the basis of the sEMG and human force. Thenceforward, in the inner loop, a model reference adaptive controller with parameter updating laws based on the Lyapunov stability theory forces the rehabilitation robot to track the reference trajectory.
Findings
The experiment results confirm that the trajectory tracking error is efficiently decreased by the VIC and adaptively correct the reference trajectory synchronizing with the patients’ motion intention; the model reference controller is able to outstandingly force the rehabilitation robot to track the reference trajectory. The method proposed in this paper can better the functioning of the rehabilitation robot system and is expandable to other applications of the rehabilitation field.
Originality/value
The proposed approach is interesting for the design of an intelligent control of rehabilitation robots. The main contributions of this paper are: using a WNN to obtain the desired trajectory of patients based on sEMG signal, modifying the reference trajectory by the VIC and using model reference control to force rehabilitation robot to track the reference trajectory.
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Wei Meng, Quan Liu, Zude Zhou and Qingsong Ai
The purpose of this paper is to propose a seamless active interaction control method integrating electromyography (EMG)-triggered assistance and the adaptive impedance control…
Abstract
Purpose
The purpose of this paper is to propose a seamless active interaction control method integrating electromyography (EMG)-triggered assistance and the adaptive impedance control scheme for parallel robot-assisted lower limb rehabilitation and training.
Design/methodology/approach
An active interaction control strategy based on EMG motion recognition and adaptive impedance model is implemented on a six-degrees of freedom parallel robot for lower limb rehabilitation. The autoregressive coefficients of EMG signals integrating with a support vector machine classifier are utilized to predict the movement intention and trigger the robot assistance. An adaptive impedance controller is adopted to influence the robot velocity during the exercise, and in the meantime, the user’s muscle activity level is evaluated online and the robot impedance is adapted in accordance with the recovery conditions.
Findings
Experiments on healthy subjects demonstrated that the proposed method was able to drive the robot according to the user’s intention, and the robot impedance can be updated with the muscle conditions. Within the movement sessions, there was a distinct increase in the muscle activity levels for all subjects with the active mode in comparison to the EMG-triggered mode.
Originality/value
Both users’ movement intention and voluntary participation are considered, not only triggering the robot when people attempt to move but also changing the robot movement in accordance with user’s efforts. The impedance model here responds directly to velocity changes, and thus allows the exercise along a physiological trajectory. Moreover, the muscle activity level depends on both the normalized EMG signals and the weight coefficients of involved muscles.
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Jian Li, Diansheng Chen, Chunjing Tao and Hui Li
Many studies have shown that rehabilitation robots are crucial for lower limb dysfunction, but application of many robotics have yet to be seen to actual use in China. This study…
Abstract
Purpose
Many studies have shown that rehabilitation robots are crucial for lower limb dysfunction, but application of many robotics have yet to be seen to actual use in China. This study aimed to improve a lower limb rehabilitation robot by details improving and practical design.
Design/methodology/approach
Structures and control system of a lower limb rehabilitation robot are improved in detail, including joint calculations, comfort analysis and feedback logic creation, and prototype experiments on healthy individuals and patients are conducted in a hospital.
Findings
All participating subjects did not experience any problems. The experiment shows detail improving is reasonable, and feasibility of the robot was confirmed, which has potential for overcoming difficulties and problems in practical application.
Research limitations/implications
Therapeutic effects need to be evaluated in the future. Also, more details should be improved continuously based on the actual demand.
Originality/value
The improved robot could assist the lower limb during standing or walking, which has significance for practical application and patients in China.
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Gaoxin Cheng, Linsen Xu, Jiajun Xu, Jinfu Liu, Jia Shi, Shouqi Chen, Lei Liu, Xingcan Liang and Yang Liu
This paper aims to develop a robotic mirror therapy system for lower limb rehabilitation, which is applicable for different patients with individual movement disability levels.
Abstract
Purpose
This paper aims to develop a robotic mirror therapy system for lower limb rehabilitation, which is applicable for different patients with individual movement disability levels.
Design/methodology/approach
This paper puts forward a novel system that includes a four-degree-of-freedom sitting/lying lower limb rehabilitation robot and a wireless motion data acquisition system based on mirror therapy principle. The magnetorheological (MR) actuators are designed and manufactured, whose characteristics are detected theoretically and experimentally. The passive training control strategy is proposed, and the trajectory tracking experiments verify its feasibility. Also, the active training controller that is adapt to the human motor ability is designed and evaluated by the comparison experiments.
Findings
The MR actuators produce continuously variable and compliant torque for robotic joints by adjusting excitation current. The reference limb joint position data collected by the wireless motion data acquisition system can be used as the motion trajectory of the robot to drive the affected limb. The passive training strategy based on proportional-integral control proves to have great trajectory tracking performance through experiments. In the active training mode, by comparing the real-time parameters adjustment in two phases, it is certified that the proposed fuzzy-based regulated impedance controller can adjust assistance torque according to the motor ability of the affected limb.
Originality/value
The system developed in this paper fulfills the needs of robot-assisted mirror therapy for hemiplegic patients.
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This research was to understand people's perceptions and trends in wearable robots and the research questions were as follows: (1) investigating key terms related to wearable…
Abstract
Purpose
This research was to understand people's perceptions and trends in wearable robots and the research questions were as follows: (1) investigating key terms related to wearable robots that were frequently used by and exposed to people and (2) analyzing relationships among those key terms.
Design/methodology/approach
Textom, a big data collection and analysis software system, was used to collect data using the keyword – wearable robot.
Findings
The frequency-inverse document frequency, term frequency and central analyses were investigated, and the major key terms related to wearable robots and their connectivity were identified. After performing network analysis and convergence of iterated correlations analyses using UCINET and NetDraw programs, the major key term categories were identified.
Originality/value
It is important to understand how people think and perceive about wearable robots before developing wearable robots. The results of the research are expected to be helpful to better understand how people perceive and what key terms are mainly discussed by people in both countries and ultimately help when developing wearable robots with better market targeting approach methods.
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Vahab Khoshdel and Alireza Akbarzadeh
This paper aims to present an application of design of experiments techniques to determine the optimized parameters of artificial neural networks (ANNs), which are used to…
Abstract
Purpose
This paper aims to present an application of design of experiments techniques to determine the optimized parameters of artificial neural networks (ANNs), which are used to estimate human force from Electromyogram (sEMG) signals for rehabilitation robotics. Physiotherapists believe, to make a precise therapeutic exercise, we need to design and perform therapeutic exercise base on patient muscle activity. Therefore, sEMG signals are the best tool for using in therapeutic robots because they are related to the muscle activity. Using sEMG signals as input for therapeutic robots need precise human force estimation from sEMG. Furthermore, the ANN estimator performance is highly dependent on the accuracy of the target date and setting parameters.
Design/methodology/approach
In the previous studies, the force data, which are collected from the force sensors or dynameters, has widely been used as target data in the training phase of learning ANN. However, force sensors or dynameters could measure only contact force. Therefore, the authors consider the contact force, limb’s dynamic and time in target data to increase the accuracy of target data.
Findings
There are plenty of algorithms that are used to obtain optimal ANN settings. However, to the best of our knowledge, they do not use regression analysis to model the effect of each parameter, as well as present the contribution percentage and significance level of the ANN parameters for force estimation.
Originality/value
In this paper, a new model to estimate the force from sEMG signals is presented. In this method, the sum of the limb’s dynamics and the contact force is used as target data in the training phase. To determine the limb’s dynamics, the patient’s body and the rehabilitation robot are modeled in OpenSim. Furthermore, in this paper, sEMG experimental data are collected and the ANN parameters based on an orthogonal array design table are regulated to train the ANN. Taguchi is used to find the optimal parameters settings. Next, analysis of variance technique is used to obtain significance level, as well as contribution percentage of each parameter, to optimize ANN’s modeling in human force estimation. The results indicate that the presented model can precisely estimate human force from sEMG signals.
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Wujun Tang, Jiwon Chung and Sumin Koo
This study aims to conduct text mining and semantic network analysis of muscle-supportive and posture-corrective wearable robots for the elderly to understand key terms related to…
Abstract
Purpose
This study aims to conduct text mining and semantic network analysis of muscle-supportive and posture-corrective wearable robots for the elderly to understand key terms related to the topic and to identify considerations for developing these types of clothing.
Design/methodology/approach
The authors searched and identified the key terms wearable robot, muscle-supportive, posture correction and elderly using the text-mining software Textom to extract terms as well as the network analysis software UCINET 6 to process and visualize the relationships among the terms. The authors compared and analyzed the term frequency (TF), the TF-inverse document frequency and the degree centrality of the terms, and the authors visualized and summarized the terms using NetDraw.
Findings
The key terms and their relationships in 3–4 groups were identified: wearable robot, muscle-supportive, posture correction and elderly. The authors identified the aspects of designing muscle-supportive and posture-corrective wearable robots for the elderly.
Originality/value
This study contributes to the field of muscle-supportive clothing and wearable robotics by deriving insights into what people are discussing and interested in, and by offering recommendations when developing these types of clothing for the elderly.
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Kaixin Li, Ye He, Kuan Li and Chengguo Liu
With the increasing demands of industrial applications, it is imperative for robots to accomplish good contact-interaction with dynamic environments. Hence, the purpose of this…
Abstract
Purpose
With the increasing demands of industrial applications, it is imperative for robots to accomplish good contact-interaction with dynamic environments. Hence, the purpose of this research is to propose an adaptive fractional-order admittance control scheme to realize a robot–environment contact with high accuracy, small overshoot and fast response.
Design/methodology/approach
Fractional calculus is introduced to reconstruct the classical admittance model in this control scheme, which can more accurately describe the complex physical relationship between position and force in the interaction process of the robot–environment. In this control scheme, the pre-PID controller and fuzzy controller are adopted to improve the system force tracking performance in highly dynamic unknown environments, and the fuzzy controller is used to improve the trajectory, transient and steady-state response by adjusting the pre-PID integration gain online. Furthermore, the stability and robustness of this control algorithm are theoretically and experimentally demonstrated.
Findings
The excellent force tracking performance of the proposed control algorithm is verified by constructing highly dynamic unstructured environments through simulations and experiments. In simulations and experiments, the proposed control algorithm shows satisfactory force tracking performance with the advantages of fast response speed, little overshoot and strong robustness.
Practical implications
The control scheme is practical and simple in the actual industrial and medical scenarios, which requires accurate force control by the robot.
Originality/value
A new fractional-order admittance controller is proposed and verified by experiments in this research, which achieves excellent force tracking performance in dynamic unknown environments.
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Chengguo Liu, Ye He, Xiaoan Chen and Hongli Cao
As more and more robots are used in industry, it is necessary for robots to interact with high dynamic environments. For this reason, the purpose of this research is to form an…
Abstract
Purpose
As more and more robots are used in industry, it is necessary for robots to interact with high dynamic environments. For this reason, the purpose of this research is to form an excellent force controller by considering the transient contact force response, overshoot and steady-state force-tracking accuracy.
Design/methodology/approach
Combining the active disturbance rejection control (ADRC) and the adaptive fuzzy PD controller, an enhanced admittance force-tracking controller framework and a well-designed control scheme are proposed. Tracking differentiator balances the contradiction between inertia and jump control signal of the control object. Kalman filter and extended state observer are introduced to obtain purer feedback force signal and uncertainty compensation. Adaptive fuzzy PD controller is introduced to account for transient and steady state performance of the system.
Findings
The proposed controller has achieved successful results through simulation and actual test of 6-axis robot with minimum error.
Practical implications
The controller is simple and practical in real industrial scenarios, where force control by robots is required.
Originality/value
In this research, a new practical force control algorithm is proposed to guarantee the performance of the force controller for robots interacting with high dynamic environments.
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To improve the position tracking efficiency of the upper-limb rehabilitation robot for stroke hemiplegia patients, the optimization Learning rate of the membership function based…
Abstract
Purpose
To improve the position tracking efficiency of the upper-limb rehabilitation robot for stroke hemiplegia patients, the optimization Learning rate of the membership function based on the fuzzy impedance controller of the rehabilitation robot is propose.
Design/methodology/approach
First, the impaired limb’s damping and stiffness parameters for evaluating its physical recovery condition are online estimated by using weighted least squares method based on recursive algorithm. Second, the fuzzy impedance control with the rule has been designed with the optimal impedance parameters. Finally, the membership function learning rate online optimization strategy based on Takagi-Sugeno (TS) fuzzy impedance model was proposed to improve the position tracking speed of fuzzy impedance control.
Findings
This method provides a solution for improving the membership function learning rate of the fuzzy impedance controller of the upper limb rehabilitation robot. Compared with traditional TS fuzzy impedance controller in position control, the improved TS fuzzy impedance controller has reduced the overshoot stability time by 0.025 s, and the position error caused by simulating the thrust interference of the impaired limb has been reduced by 8.4%. This fact is verified by simulation and test.
Originality/value
The TS fuzzy impedance controller based on membership function online optimization learning strategy can effectively optimize control parameters and improve the position tracking speed of upper limb rehabilitation robots. This controller improves the auxiliary rehabilitation efficiency of the upper limb rehabilitation robot and ensures the stability of auxiliary rehabilitation training.
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