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.

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.

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.

A new structure of end-effector traction upper limb rehabilitation robot

2021 ◽  
Author(s):  
Liaoyuan Li ◽  
Jianhai Han ◽  
Xiangpan Li ◽  
Bingjing Guo ◽  
Pengpeng Xia ◽  
...  
Keyword(s):  
Upper Limb ◽  
Rehabilitation Robot ◽  
End Effector ◽  
Upper Limb Rehabilitation ◽  
Limb Rehabilitation

scholarly journals Development and Implementation of an End-Effector Upper Limb Rehabilitation Robot for Hemiplegic Patients with Line and Circle Tracking Training

2017 ◽  
Vol 2017 ◽  
pp. 1-11 ◽  
Author(s):  
Yali Liu ◽  
Chong Li ◽  
Linhong Ji ◽  
Sheng Bi ◽  
Xuemin Zhang ◽  
...  
Keyword(s):  
Upper Limb ◽  
Functional Ability ◽  
Degrees Of Freedom ◽  
Muscle Activation ◽  
Movement Pattern ◽  
Interaction Force ◽  
Rehabilitation Robot ◽  
End Effector ◽  
Upper Limb Rehabilitation ◽  
Limb Rehabilitation

Numerous robots have been widely used to deliver rehabilitative training for hemiplegic patients to improve their functional ability. Because of the complexity and diversity of upper limb motion, customization of training patterns is one key factor during upper limb rehabilitation training. Most of the current rehabilitation robots cannot intelligently provide adaptive training parameters, and they have not been widely used in clinical rehabilitation. This article proposes a new end-effector upper limb rehabilitation robot, which is a two-link robotic arm with two active degrees of freedom. This work investigated the kinematics and dynamics of the robot system, the control system, and the realization of different rehabilitation therapies. We also explored the influence of constraint in rehabilitation therapies on interaction force and muscle activation. The deviation of the trajectory of the end effector and the required trajectory was less than 1 mm during the tasks, which demonstrated the movement accuracy of the robot. Besides, results also demonstrated the constraint exerted by the robot provided benefits for hemiplegic patients by changing muscle activation in the way similar to the movement pattern of the healthy subjects, which indicated that the robot can improve the patient’s functional ability by training the normal movement pattern.

scholarly journals Upper Limb Action Identification Based on Physiological Signals and Its Application in Limb Rehabilitation Training

2021 ◽  
Vol 38 (6) ◽  
pp. 1887-1894
Author(s):  
Chao Zhang ◽  
Ji Zou ◽  
Zhongjing Ma ◽  
Qian Wu ◽  
Zhaogang Sheng ◽  
...  
Keyword(s):  
Frequency Domain ◽  
Upper Limb ◽  
Motor Dysfunction ◽  
Physiological Signals ◽  
Joint Analysis ◽  
Action Identification ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Training ◽  
Time Frequency ◽  
Limb Rehabilitation

pper limb motor dysfunction brings huge pain and burden to patients with brain trauma, stroke, and cerebral palsy, as well as their relatives. Physiological signals are closely related to the recovery of patients with limb dysfunction. The joint analysis of two key physiological signals, namely, surface electromyographic (sEMG) signal and acceleration signal, enables the scientific and effective evaluation of upper limb rehabilitation. However, the existing indices of upper limb rehabilitation are incomplete, and the current evaluation approaches are not sufficiently objective or quantifiable. To solve the problems, this paper explores upper limb action identification based on physiological signals, and tries to apply the approach to limb rehabilitation training. Specifically, the upper limb action features during limb rehabilitation training were extracted and identified by time-domain feature method, frequency-domain feature method, time-frequency domain feature method, and entropy feature method. Then, the evaluation flow of upper limb rehabilitation, plus the relevant evaluation indices, were given. Experimental results demonstrate the effectiveness of the proposed composite feature identification of upper limb actions, and the proposed evaluation method for limb rehabilitation.

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.

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