Research Status on Ankle Rehabilitation Robot

2019 ◽  
Vol 12 (2) ◽  
pp. 104-124
Author(s):  
Jingang Jiang ◽  
Zhaowei Min ◽  
Zhiyuan Huang ◽  
Xuefeng Ma ◽  
Yihao Chen ◽  
...  

Background: Ankle is an important bearing joint in the human body. Unreasonable exercise patterns and exercise intensity can cause ankle injuries. This will seriously affect patients’ daily life. With the increase in the number of patients, the labor intensity of doctors is increasing. Ankle rehabilitation robot can help doctors free themselves from repetitive tasks, which is, of more practical value. Objective: To give a general summary of recent ankle rehabilitation robot and introduce the respective characteristics and development including structure type, drive type and rehabilitation training mode. Methods: This paper investigates various representative studies related to the ankle rehabilitation robot. The structure type, drive type, rehabilitation training mode and applications situation of these ankle rehabilitation robot are discussed. Results: The characteristics of different types of ankle rehabilitation robots are analyzed. This paper analyzes the main problems in its development. The solutions to the issues and the current and future research on ankle rehabilitation robot are discussed. Conclusion: The ankle rehabilitation robots are classified into motor drive type, pneumatic artificial muscle and pneumatic cylinder drive type and others. Further improvements are needed in the aspects of mechanical design, safety, virtual reality, brain-computer interface, control strategies and algorithm of bio-syncretic mechanism system of ankle rehabilitation robot. More related patents about ankle rehabilitation robot need to be developed.

Author(s):  
Mingjie Dong ◽  
Yu Zhou ◽  
Jianfeng Li ◽  
Xi Rong ◽  
Wenpei Fan ◽  
...  

Abstract Background The ankle joint complex (AJC) is of fundamental importance for balance, support, and propulsion. However, it is particularly susceptible to musculoskeletal and neurological injuries, especially neurological injuries such as drop foot following stroke. An important factor in ankle dysfunction is damage to the central nervous system (CNS). Correspondingly, the fundamental goal of rehabilitation training is to stimulate the reorganization and compensation of the CNS, and to promote the recovery of the motor system’s motor perception function. Therefore, an increasing number of ankle rehabilitation robots have been developed to provide long-term accurate and uniform rehabilitation training of the AJC, among which the parallel ankle rehabilitation robot (PARR) is the most studied. The aim of this study is to provide a systematic review of the state of the art in PARR technology, with consideration of the mechanism configurations, actuator types with different trajectory tracking control techniques, and rehabilitation training methods, thus facilitating the development of new and improved PARRs as a next step towards obtaining clinical proof of their rehabilitation benefits. Methods A literature search was conducted on PubMed, Scopus, IEEE Xplore, and Web of Science for articles related to the design and improvement of PARRs for ankle rehabilitation from each site’s respective inception from January 1999 to September 2020 using the keywords “ parallel”, “ ankle”, and “ robot”. Appropriate syntax using Boolean operators and wildcard symbols was utilized for each database to include a wider range of articles that may have used alternate spellings or synonyms, and the references listed in relevant publications were further screened according to the inclusion criteria and exclusion criteria. Results and discussion Ultimately, 65 articles representing 16 unique PARRs were selected for review, all of which have developed the prototypes with experiments designed to verify their usability and feasibility. From the comparison among these PARRs, we found that there are three main considerations for the mechanical design and mechanism optimization of PARRs, the choice of two actuator types including pneumatic and electrically driven control, the covering of the AJC’s motion space, and the optimization of the kinematic design, actuation design and structural design. The trajectory tracking accuracy and interactive control performance also need to be guaranteed to improve the effect of rehabilitation training and stimulate a patient’s active participation. In addition, the parameters of the reviewed 16 PARRs are summarized in detail with their differences compared by using figures and tables in the order they appeared, showing their differences in the two main actuator types, four exercise modes, fifteen control strategies, etc., which revealed the future research trends related to the improvement of the PARRs. Conclusion The selected studies showed the rapid development of PARRs in terms of their mechanical designs, control strategies, and rehabilitation training methods over the last two decades. However, the existing PARRs all have their own pros and cons, and few of the developed devices have been subjected to clinical trials. Designing a PARR with three degrees of freedom (DOFs) and whereby the mechanism’s rotation center coincides with the AJC rotation center is of vital importance in the mechanism design and optimization of PARRs. In addition, the design of actuators combining the advantages of the pneumatic-driven and electrically driven ones, as well as some new other actuators, will be a research hotspot for the development of PARRs. For the control strategy, compliance control with variable parameters should be further studied, with sEMG signal included to improve the real-time performance. Multimode rehabilitation training methods with multimodal motion intention recognition, real-time online detection and evaluation system should also be further developed to meet the needs of different ankle disability and rehabilitation stages. In addition, the clinical trials are in urgent need to help the PARRs be implementable as an intervention in clinical practice.


2016 ◽  
Vol 40 (2) ◽  
pp. 550-564 ◽  
Author(s):  
Mustafa Sinasi Ayas ◽  
Ismail Hakki Altas ◽  
Erdinc Sahin

Human–robot interaction is inherently available and used actively in ankle rehabilitation robots. This interaction causes disturbances to be counteracted on the rehabilitation robots in order to reduce the side effects. This paper presents a fractional order proportional–integral–derivative controller to improve the trajectory tracking ability of a developed 2-degree of freedom parallel ankle rehabilitation robot subject to external disturbances. The parameters of the controller are optimally tuned by using both the cuckoo search algorithm and the particle swarm optimization algorithm. A traditional proportional–integral–derivative controller, which is also tuned using both of the algorithms, is designed to test the performance of the fractional order proportional–integral–derivative controller. The experimental results show that the optimally tuned FOPID controller improves the tracking performance of the ankle rehabilitation robot subject to external disturbances significantly and decreases the steady-state tracking errors compared to the optimally tuned PID controller.


2020 ◽  
Vol 20 (09) ◽  
pp. 2040008 ◽  
Author(s):  
JUN ZHONG ◽  
DONGKAI HE ◽  
CHUN ZHAO ◽  
YUE ZHU ◽  
QIANZHUANG ZHANG

Rehabilitation robots are playing an important role in restoring movement ability of hemiplegic patients. However, most of these robots adopt motors as actuators. Considering human body is a flexible organism, rigid motors lack compliance when getting in touch with patients. This paper designs an ankle rehabilitation robot by employing pneumatic muscle actuators which are soft and have similar compliance with biological muscles. Analysis of motion characteristics of human ankle is performed, and relationship between angle and torque of human ankle acquired from experiment is studied. Driving mechanism using pneumatic muscle actuators is addressed carefully and ankle-rehabilitation robot is designed. Then, dynamics of the robot is established and structure optimization of the driving mechanism is performed. Consequently, prototype is manufactured and assembled.


2015 ◽  
Vol 72 (2) ◽  
Author(s):  
Khor Kang Xiang ◽  
Patrick Chin Jun Hua ◽  
Hisyam Abdul Rahman ◽  
Yeong Che Fai ◽  
Aqilah Leela T. Narayanan ◽  
...  

Rehabilitation robots are gradually becoming popular for stroke rehabilitation to improve motor recovery, as robotic technology can assist, enhance, and further quantify rehabilitation training for stroke patients.  However, most of the available rehabilitation robots are complex and involve multiple Degrees-Of-Freedoms (DOFs) causing it to be very expensive and huge in size. Rehabilitation robot needed to be useful but also should be cost-effective to be able to use in current rehabilitation process. This paper present the design of reconfigurable rehabilitation robot that able to adopt different training movement by changing the configuration of the device. The developed robotic system able to perform training for wrist, forearm and other functional rehabilitation training by using suitable modular units. Preliminary study with three stroke subject were presented to evaluate the functionality in different training modes for forearm and wrist rehabilitation training. 


Author(s):  
Jianfeng Li ◽  
Wenpei Fan ◽  
Mingjie Dong ◽  
Xi Rong

Purpose The purpose of this paper is to implement a passive compliance training strategy for our newly designed 2-UPS/RRR parallel ankle rehabilitation robot (PARR) to enhance its rehabilitation training safety. Design/methodology/approach First, a kinematic analysis of the PARR is introduced, and the mechanism ensures that the rotation centre of the ankle joint complex (AJC) coincides with robot’s rotation centre. Then, a passive compliance training strategy based on admittance control is described in detail and is implemented on our PARR. Findings Experiments involving healthy subjects were conducted, and the performance of trajectory tracking was quantitatively evaluated, with the results showing excellent compliance and trajectory tracking accuracy, which can ensure that a secondary injury to the AJC during passive rehabilitation training is avoided. The influence of different admittance parameters was also simulated and analysed, which can contribute to the development of adaptive parameter adjustment research. Originality/value The paper can be used to improve the effectiveness of ankle rehabilitation, to alleviate manual therapy problems in terms of labour intensiveness, precision and subjectivity and to ensure safety and comfort during rehabilitation sessions.


Author(s):  
Liang Zhou ◽  
Wei Meng ◽  
Charles Z. Lu ◽  
Quan Liu ◽  
Qingsong Ai ◽  
...  

Robotic rehabilitation for ankle injuries offers several advantages in terms of precision, force accuracy, and task-specific training. While the existing platform-based ankle rehabilitation robots tend to provide a rotation center that does not coincide with the actual ankle joint. In this paper, a novel bio-inspired ankle rehabilitation robot was designed, which is wearable and can keep the participant's shank be stationary. The robot is redundantly actuated by four motors in parallel to offer three ankle rotation degrees-of-freedom (DOFs) with sufficient range of motion (ROM) and force capacity. To control the robotic rehabilitation device operated in a repetitive trajectory training manner, a model-free robust control method in form of iterative feedback tuning (IFT) is proposed to tune the robot controller parameters. Experiments were performed on the parallel ankle rehabilitation platform to investigate the efficacy of the design and the robustness of the IFT technique under real-life rehabilitation scenarios.


2022 ◽  
Vol 9 ◽  
Author(s):  
Xiali Xue ◽  
Xinwei Yang ◽  
Zhongyi Deng ◽  
Huan Tu ◽  
Dezhi Kong ◽  
...  

Background: In recent years, with the development of medical science and artificial intelligence, research on rehabilitation robots has gained more and more attention, for nearly 10 years in the Web of Science database by journal of rehabilitation robot-related research literature analysis, to parse and track rehabilitation robot research hotspot and front, and provide some guidance for future research.Methods: This study employed computer retrieval of rehabilitation robot-related research published in the core data collection of the Web of Science database from 2010 to 2020, using CiteSpace 5.7 visualization software. The hotspots and frontiers of rehabilitation robot research are analyzed from the aspects of high-influence countries or regions, institutions, authors, high-frequency keywords, and emergent words.Results: A total of 3,194 articles were included. In recent years, the research on rehabilitation robots has been continuously hot, and the annual publication of relevant literature has shown a trend of steady growth. The United States ranked first with 819 papers, and China ranked second with 603 papers. Northwestern University ranked first with 161 publications. R. Riener, a professor at the University of Zurich, Switzerland, ranked as the first author with 48 articles. The Journal of Neural Engineering and Rehabilitation has the most published research, with 211 publications. In the past 10 years, research has focused on intelligent control, task analysis, and the learning, performance, and reliability of rehabilitation robots to realize the natural and precise interaction between humans and machines. Research on neural rehabilitation robots, brain–computer interface, virtual reality, flexible wearables, task analysis, and exoskeletons has attracted more and more attention.Conclusions: At present, the brain–computer interface, virtual reality, flexible wearables, task analysis, and exoskeleton rehabilitation robots are the research trends and hotspots. Future research should focus on the application of machine learning (ML), dimensionality reduction, and feature engineering technologies in the research and development of rehabilitation robots to improve the speed and accuracy of algorithms. To achieve wide application and commercialization, future rehabilitation robots should also develop toward mass production and low cost. We should pay attention to the functional needs of patients, strengthen multidisciplinary communication and cooperation, and promote rehabilitation robots to better serve the rehabilitation medical field.


Electronics ◽  
2021 ◽  
Vol 10 (10) ◽  
pp. 1147
Author(s):  
Xiaohong Cui ◽  
Binrui Wang ◽  
Han Lu ◽  
Jiayu Chen

In this paper, a rehabilitation robot driven by multifilament muscles is designed based on the rehabilitation robot motion model and a system elbow joint model. The passive training mode of rehabilitation robots were researched, and active disturbance rejection control (ADRC) leveraged to improve the tracking angle of robot joints. In the no-load motion simulation of rehabilitation robots, disturbances are added to the control variables to complete the ADRC and Proportional Integral Differential (PID) position control simulation. The simulation results indicate that the auto disturbance rejection control can quickly keep up the expected signal without overshoot, solve the contradiction between the system rapidity and overshoot. Moreover, it can better suppress the interference even if the external load changes. The upper limbs of the human body are used as the load on the robot body to complete the simulation of ADRC and PID position control objects of different weights. Finally, a passive rehabilitation training experiment was conducted to verify the safety of the rehabilitation robot, the rationality, comfort, and robustness of the mechanism design, and the effectiveness and feasibility of the ADRC.


2020 ◽  
pp. 1-17
Author(s):  
Qing Sun ◽  
Shuai Guo ◽  
Leigang Zhang

BACKGROUND: The definition of rehabilitation training trajectory is of great significance during rehabilitation training, and the dexterity of human-robot interaction motion provides a basis for selecting the trajectory of interaction motion. OBJECTIVE: Aimed at the kinematic dexterity of human-robot interaction, a velocity manipulability ellipsoid intersection volume (VMEIV) index is proposed for analysis, and the dexterity distribution cloud map is obtained with the human-robot cooperation space. METHOD: Firstly, the motion constraint equation of human-robot interaction is established, and the Jacobian matrix is obtained based on the speed of connecting rod. Then, the Monte Carlo method and the cell body segmentation method are used to obtain the collaborative space of human-robot interaction, and the VMEIV of human-robot interaction is solved in the cooperation space. Finally, taking the upper limb rehabilitation robot as the research object, the dexterity analysis of human-robot interaction is carried out by using the index of the approximate volume of the VMEIV. RESULTS: The results of the simulation and experiment have a certain consistency, which indicates that the VMEIV index is effective as an index of human-robot interaction kinematic dexterity. CONCLUSIONS: The VMEIV index can measure the kinematic dexterity of human-robot interaction, and provide a reference for the training trajectory selection of rehabilitation robot.


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