Human-robot coupling modeling and analysis for upper limb rehabilitation robots

2020 ◽  
pp. 1-15
Author(s):  
Qiaolian Xie ◽  
Qiaoling Meng ◽  
Yue Dai ◽  
Qingxin Zeng ◽  
Yuanjie Fan ◽  
...  
Keyword(s):  
Upper Limb ◽  
Dynamic Control ◽  
Human Robot Interaction ◽  
Rehabilitation Robot ◽  
Robot Interaction ◽  
Upper Limb Rehabilitation ◽  
Modeling And Analysis ◽  
Rehabilitation Robots ◽  
Human Arm ◽  
Limb Rehabilitation

BACKGROUND: Upper limb rehabilitation robots have become an important piece of equipment in stroke rehabilitation. Human-robot coupling (HRC) dynamics play a key role in the control of rehabilitation robots to improve human-robot interaction. OBJECTIVE: This study aims to study the methods of modeling and analysis of HRC dynamics to realize more accurate dynamic control of upper limb rehabilitation robots. METHODS: By the analysis of force interaction between the human arm and the upper limb rehabilitation robot, the HRC torque is achieved by summing up the robot torque and the human arm torque. The HRC torque and robot torque of a 2-DOF upper limb rehabilitation robot (FLEXO-Arm) are solved by Lagrangian equation and step-by-step dynamic parameters identification method. RESULTS: The root mean square (RMS) is used to evaluate the accuracy of the HRC torque and the robot torque calculated by the parameter identification, and the error of both is about 10%. Moreover, the HRC torque and the robot torque are compared with the actual torque measured by torque sensors. The error of the robot torque is more than twice the HRC. Therefore, the HRC torque is more accurate than the actual torque. CONCLUSIONS: The proposed HRC dynamics effectively achieves more accurate dynamic control of upper limb rehabilitation robots.

Kinematic dexterity analysis of human-robot interaction of an upper limb rehabilitation robot

2020 ◽  
pp. 1-17
Author(s):  
Qing Sun ◽  
Shuai Guo ◽  
Leigang Zhang
Keyword(s):  
Upper Limb ◽  
Constraint Equation ◽  
Human Robot Interaction ◽  
Rehabilitation Robot ◽  
Connecting Rod ◽  
Robot Interaction ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Training ◽  
Limb Rehabilitation ◽  
Training Trajectory

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.

scholarly journals Design and Analysis of a Wearable Upper Limb Rehabilitation Robot with Characteristics of Tension Mechanism

2020 ◽  
Vol 10 (6) ◽  
pp. 2101 ◽  
Author(s):  
Zaixiang Pang ◽  
Tongyu Wang ◽  
Zhanli Wang ◽  
Junzhi Yu ◽  
Zhongbo Sun ◽  
...  
Keyword(s):  
Upper Limb ◽  
Human Body ◽  
Wrist Joint ◽  
Traction Force ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
Freedom Of Movement ◽  
Human Arm ◽  
Toothed Belt ◽  
Limb Rehabilitation

Nowadays, patients with mild and moderate upper limb paralysis caused by cerebral apoplexy are uncomfortable with autonomous rehabilitation. In this paper, according to the “rope + toothed belt” generalized rope drive design scheme, we design a utility model for a wearable upper limb rehabilitation robot with a tension mechanism. Owing to study of the human upper extremity anatomy, movement mechanisms, and the ranges of motion, it can determine the range of motion angles of the human arm joints, and design the shoulder joint, elbow joint, and wrist joint separately under the principle of ensuring the minimum driving torque. Then, the kinematics, workspace and dynamics analysis of each structure are performed. Finally, the control system of the rehabilitation robot is designed. The experimental results show that the structure is convenient to wear on the human body, and the robot’s freedom of movement matches well with the freedom of movement of the human body. It can effectively support and traction the front and rear arms of the affected limb, and accurately transmit the applied traction force to the upper limb of the joints. The rationality of the wearable upper limb rehabilitation robot design is verified, which can help patients achieve rehabilitation training and provide an effective rehabilitation equipment for patients with hemiplegia caused by stroke.

scholarly journals A Human-Robot Cooperative and Personalized Compliant Joint Controller for Upper-Limb Rehabilitation Robots: The Elbow Joint Validation

2021 ◽  
Author(s):  
Stefano Dalla Gasperina ◽  
Valeria Longatelli ◽  
Francesco Braghin ◽  
Alessandra Laura Giulia Pedrocchi ◽  
Marta Gandolla
Keyword(s):  
Upper Limb ◽  
Human Robot Interaction ◽  
Control Law ◽  
Robot Interaction ◽  
Activation Patterns ◽  
Upper Limb Rehabilitation ◽  
Control Framework ◽  
High Level ◽  
Limb Rehabilitation ◽  
Muscular Activation

Abstract Background: Appropriate training modalities for post-stroke upper-limb rehabilitation are key features for effective recovery after the acute event. This work presents a novel human-robot cooperative control framework that promotes compliant motion and renders different high-level human-robot interaction rehabilitation modalities under a unified low-level control scheme. Methods: The presented control law is based on a loadcell-based impedance controller provided with positive-feedback compensation terms for disturbances rejection and dynamics compensation. We developed an elbow flexion-extension experimental setup, and we conducted experiments to evaluate the controller performances. Seven high-level modalities, characterized by different levels of (i) impedance-based corrective assistance, (ii) weight counterbalance assistance, and (iii) resistance, have been defined and tested with 14 healthy volunteers.Results: The unified controller demonstrated suitability to promote good transparency and render compliant and high-impedance behavior at the joint. Superficial electromyography results showed different muscular activation patterns according to the rehabilitation modalities. Results suggested to avoid weight counterbalance assistance, since it could induce different motor relearning with respect to purely impedance-based corrective strategies. Conclusion: We proved that the proposed control framework could implement different physical human-robot interaction modalities and promote the assist-as-needed paradigm, helping the user to accomplish the task, while maintaining physiological muscular activation patterns. Future insights involve the extension to multiple degrees of freedom robots and the investigation of an adaptation control law that makes the controller learn and adapt in a therapist-like manner.

scholarly journals Configuration Design of an Upper Limb Rehabilitation Robot with a Generalized Shoulder Joint

2021 ◽  
Vol 11 (5) ◽  
pp. 2080
Author(s):  
Hao Yan ◽  
Hongbo Wang ◽  
Peng Chen ◽  
Jianye Niu ◽  
Yuansheng Ning ◽  
...  
Keyword(s):  
Upper Limb ◽  
Shoulder Joint ◽  
Configuration Model ◽  
Configuration Design ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Robots ◽  
Closed Chain ◽  
Limb Rehabilitation ◽  
Human Upper Limb

For stroke patients with upper limb motor dysfunction, rehabilitation training with the help of rehabilitation robots is a social development trend. Existing upper limb rehabilitation robots have difficulty fully fitting the complex motion of the human shoulder joint and have poor human–robot compatibility. In this paper, based on the anatomical structure of the human upper limb, an equivalent mechanism model of the human upper limb is established. The configuration synthesis of the upper limb rehabilitation mechanism was carried out, a variety of shoulder joint man–machine closed-chain Θs and shoulder elbow human–machine closed-chain Θse configuration combinations were synthesized, and the configuration model with compatibility and reduced moment conduction attenuation was selected from them. Two configurations, 2Pa1P3Ra and 5Ra1P, are proposed for the generalized shoulder joint mechanism of the robot. The closed-chain kinematic models of the two configurations are established, and the velocity Jacobian matrix is obtained. Motion performance analysis, condition reciprocal analysis and operability ellipsoid analysis of different configuration design schemes were carried out in different operation planes. The results show that in the normal upper limb posture of the human body, the 5Ra1P configuration of the shoulder joint has better kinematic performance. Finally, on this basis, an upper limb rehabilitation robot prototype with good human–computer compatibility is developed, and its moving space was verified.

scholarly journals Sensorless force estimation of end-effect upper limb rehabilitation robot system with friction compensation

2019 ◽  
Vol 16 (4) ◽  
pp. 172988141985613
Author(s):  
Xiangxing Liu ◽  
Guokun Zuo ◽  
Jiaji Zhang ◽  
Jiajin Wang
Keyword(s):  
Friction Force ◽  
Disturbance Observer ◽  
Human Robot Interaction ◽  
Rehabilitation Robot ◽  
End Effect ◽  
Force Estimation ◽  
Robot System ◽  
Robot Interaction ◽  
Upper Limb Rehabilitation ◽  
Limb Rehabilitation

In human robot interaction systems, human intent detection plays an important role to improve the interactive performances and then the rehabilitation effects. A study is proposed to estimate the interactive forces that indirectly detect the human motion intent. A disturbance observer is designed to estimate interactive torques and friction forces without force sensors, and then a friction force model is constructed to estimate the friction force in the robot system. To detect the human–robot interaction force, we subtract the friction force from disturbance observer estimation result. Several experiments were performed to test the performances of the proposed methods. Those methods were applied in an end-effect upper limb rehabilitation robot system. The results show that the precision of the estimated sensor force can increase 5% than the force sensor. The senseless force estimation method we proposed in this article can be an alternative option in force control tasks when force sensors are not suitable.

Analytical Inverse Kinematic Resolution of a Redundant Exoskeleton for Upper-Limb Rehabilitation

2016 ◽  
Vol 13 (03) ◽  
pp. 1550042 ◽  
Author(s):  
Qing-Cong Wu ◽  
Xing-Song Wang ◽  
Feng-Po Du
Keyword(s):  
Upper Limb ◽  
Inverse Kinematic ◽  
Human Robot Interaction ◽  
Additional Parameter ◽  
Redundancy Resolution ◽  
Upper Limb Rehabilitation ◽  
Human Arm ◽  
Swivel Angle ◽  
Limb Rehabilitation ◽  
Mean Square Errors

Robot-assisted therapy has played a significant role in helping the disabled patients to restore motor functions. In this paper, a redundant exoskeleton is developed for upper-limb rehabilitation. An analytical methodology for obtaining the inverse kinematic solution of the exoskeleton is presented to provide synchronized movement with patients and ensure natural human–robot interaction. To mathematically express the redundancy problem, the swivel angle of elbow is introduced as an additional parameter to specify the human arm congratulation with a predefined wrist location. A kinematic criterion is proposed to determine the swivel angle by imitating the natural reflexive reaction of human arm. The effectiveness of the proposed strategy is experimentally evaluated via four representative types of upper-limb motion tasks. During the experiments, the actual kinematic data of human arm is collected by utilizing an articulated motion capture system integrated with inertial sensors and, after that, compared to the estimation results generated by the proposed redundancy resolution. The experimental results indicate that the kinematic criterion of swivel angle is suitable to describe the free reaching movement without additional constraints. Moreover, with the estimated swivel angles, the root mean square errors between the actual and calculated joint angles are normally less than 8[Formula: see text].

scholarly journals Developing a Robot-Guided Interactive Simon Game for Physical and Cognitive Training

2019 ◽  
Vol 16 (01) ◽  
pp. 1950003
Author(s):  
Mısra Turp ◽  
José Carlos González ◽  
José Carlos Pulido ◽  
Fernando Fernández
Keyword(s):  
Upper Limb ◽  
Human Robot Interaction ◽  
Robot Interaction ◽  
Planning Techniques ◽  
Upper Limb Rehabilitation ◽  
Nao Robot ◽  
Therapeutic Benefits ◽  
Humanoid Nao ◽  
Limb Rehabilitation ◽  
Robotic Architecture

Enveloping cognitive or physical rehabilitation into a game highly increases the patients’ commitment with their treatment. Specially with children, keeping them motivated is a very time-consuming work, so therapists are demanding tools to help them with this task. NAOTherapist is a generic robotic architecture that uses Automated Planning techniques to autonomously drive noncontact upper-limb rehabilitation sessions for children with a humanoid NAO robot. Our aim is to develop more robotic games for this platform to enrich its variability and possibilities of interaction. The goal of this work is to present our first attempt to develop a different, more complex game that reuses the previous architecture. We contribute with the design description of a novel robotic Simon game that employs upper-limb poses instead of colors and could qualify as a cognitive and physical training. Statistics of evaluation tests with 14 adults and 56 children are displayed and the outcomes are analyzed in terms of human–robot interaction (HRI) quality. The results demonstrate the application-domain generalization capabilities of the NAOTherapist architecture and give an insight to further analyze the therapeutic benefits of the new developed Simon game.

Upper-limb Rehabilitation Robot Based on Motor Imagery EEG

ROBOT ◽  
2011 ◽  
Vol 33 (3) ◽  
pp. 307-313 ◽  
Author(s):  
Baoguo XU ◽  
Si PENG ◽  
Aiguo SONG
Keyword(s):  
Motor Imagery ◽  
Upper Limb ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
Limb Rehabilitation
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