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.

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.

Control System Design of Upper Limb Rehabilitation Robot

2013 ◽  
Vol 310 ◽  
pp. 477-480 ◽  
Author(s):  
Gang Yu ◽  
Jin Wu Qian ◽  
Lin Yong Shen ◽  
Ya Nan Zhang
Keyword(s):  
Control System ◽  
Upper Limb ◽  
Impedance Control ◽  
Medical Personnel ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Training ◽  
Simulation And Experiment ◽  
Limb Rehabilitation ◽  
Active Training

In traditional iatrical method, the patients with hemiplegia were assisted mainly by medical personnel to complete rehabilitation training. To make the medical personnel work easily and improve the effect of rehabilitation training, the rehabilitation robot was adopted. And the control system of a four DOF upper limb rehabilitation robot was designed based on impedance control to assist the patients with hemiplegia to complete rehabilitation training after the kinematic and kinetic analysis was finished. Then finished the analysis, simulation, and experiment of monarticular movement and multiarticulate movement after the analyzing the algorithm to tested the control system. The control system based on impedance control of the upper limb rehabilitation robot can realize the passive training which followed the planning trajectory, and active training which followed patients’ awareness of movement.

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.

Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation

2018 ◽  
pp. 1267-1287
Author(s):  
Wei Wei
Keyword(s):  
Virtual Reality ◽  
Virtual Environment ◽  
Upper Limb ◽  
Haptic Device ◽  
Rehabilitation Robot ◽  
Robot System ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Training ◽  
Rehabilitation System ◽  
Limb Rehabilitation

This chapter mainly introduced the virtual reality as many benefits of robots involved in disability rehabilitation. According to the vision feedback and force feedback, the therapist can adjust his operation. Virtual reality technology can provide repeated practice, performance feedback and motivation techniques for rehabilitation training. Patients can learn motor skills in a virtual environment, and then transfer the skills to the real world. It is hopeful to achieve satisfactory outcome in the field of rehabilitation in the future. VR is mainly used for the upper-limb rehabilitation robot system in this article. The objective of robotic systems for disability rehabilitation are explored to divide the whole rehabilitation training process into three parts, earliest rehabilitation training, medium-term rehabilitation training and late rehabilitation training, respectively. Accordingly, brain-computer training modes, the master-slave training modes and the electromyogram (EMG) signals training modes are developed to be used in rehabilitation training to help stroke patients with hemiplegia to restore the motor function of upper limb. Aimed at the rehabilitation goal, three generations of VR rehabilitation system has designed. The first generation of VR rehabilitation system includes haptic device (PHANTOM Omni), an advanced inertial sensor (MTx) and a computer. The impaired hand grip the stylus of haptic device, the intact hand can control the impaired hand's motion based on the virtual reality scene. The second generation of the VR rehabilitation system is the exoskeleton robots structure. Two virtual upper limbs are portrayed in the virtual environment, simulated the impaired hand and the intact hand, respectively. The third generation is a novel VR-based upper limb rehabilitation robot system. In the system, the realization of virtual reality environment is implemented, which can potentially motivate patients to exercise for longer periods of time. Not only virtual images but also position and force information are sent to the doctors. The development of this system can be a promising approach for further research in the field of tele-rehabilitation science.

Virtual Reality Enhanced Robotic Systems for Disability Rehabilitation

2016 ◽  
pp. 48-68
Author(s):  
Wei Wei
Keyword(s):  
Virtual Reality ◽  
Virtual Environment ◽  
Upper Limb ◽  
Haptic Device ◽  
Rehabilitation Robot ◽  
Robot System ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Training ◽  
Rehabilitation System ◽  
Limb Rehabilitation

This chapter mainly introduced the virtual reality as many benefits of robots involved in disability rehabilitation. According to the vision feedback and force feedback, the therapist can adjust his operation. Virtual reality technology can provide repeated practice, performance feedback and motivation techniques for rehabilitation training. Patients can learn motor skills in a virtual environment, and then transfer the skills to the real world. It is hopeful to achieve satisfactory outcome in the field of rehabilitation in the future. VR is mainly used for the upper-limb rehabilitation robot system in this article. The objective of robotic systems for disability rehabilitation are explored to divide the whole rehabilitation training process into three parts, earliest rehabilitation training, medium-term rehabilitation training and late rehabilitation training, respectively. Accordingly, brain-computer training modes, the master-slave training modes and the electromyogram (EMG) signals training modes are developed to be used in rehabilitation training to help stroke patients with hemiplegia to restore the motor function of upper limb. Aimed at the rehabilitation goal, three generations of VR rehabilitation system has designed. The first generation of VR rehabilitation system includes haptic device (PHANTOM Omni), an advanced inertial sensor (MTx) and a computer. The impaired hand grip the stylus of haptic device, the intact hand can control the impaired hand's motion based on the virtual reality scene. The second generation of the VR rehabilitation system is the exoskeleton robots structure. Two virtual upper limbs are portrayed in the virtual environment, simulated the impaired hand and the intact hand, respectively. The third generation is a novel VR-based upper limb rehabilitation robot system. In the system, the realization of virtual reality environment is implemented, which can potentially motivate patients to exercise for longer periods of time. Not only virtual images but also position and force information are sent to the doctors. The development of this system can be a promising approach for further research in the field of tele-rehablitation science.

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.

scholarly journals Development and Assist-As-Needed Control of an End-Effector Upper Limb Rehabilitation Robot

2020 ◽  
Vol 10 (19) ◽  
pp. 6684 ◽  
Author(s):  
Leigang Zhang ◽  
Shuai Guo ◽  
Qing Sun
Keyword(s):  
Upper Limb ◽  
Healthy Male Subject ◽  
Motor Dysfunction ◽  
Virtual Channel ◽  
Rehabilitation Robot ◽  
End Effector ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Therapy ◽  
Rehabilitation Training ◽  
Limb Rehabilitation

Robot-assisted rehabilitation therapy has been proven to effectively improve upper limb motor function and daily behavior of patients with motor dysfunction, and the demand has increased at every stage of the rehabilitation recovery. According to the motor relearning program theory, upper limb motor dysfunction can be restored by a certain amount of repetitive training. Robotics devices can be an approach to accelerate the rehabilitation process by maximizing the patients’ training intensity. This paper develops a new end-effector upper limb rehabilitation robot (EULRR) first and then presents a controller that is suitable for the assist-as-needed (AAN) training of the patients when performing the rehabilitation training. The AAN controller is a strategy that helps the patient’s arm to stay close to the given trajectory while allowing for spatial freedom. This controller enables the patient’s arm to have spatial freedom by constructing a virtual channel around the predetermined training trajectory. Patients could move their arm freely in the allowed virtual channel during rehabilitation training while the robot provides assistance when deviating from the virtual channel. The AAN controller is preliminarily tested with a healthy male subject in different conditions based on the EULRR. The experimental results demonstrate that the proposed AAN controller could provide assistance when moving out of the virtual channel and provide no assistance when moving along the trajectory within the virtual channel. In the close future, the controller is planned to be used in elderly volunteers and help to increase the intensity of the rehabilitation therapy by assisting the arm movement and by provoking active participation.

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