The Analysis and Control of Exoskeleton Upper-Limb Rehabilitation Robot

2013 ◽  
Vol 572 ◽  
pp. 619-623 ◽  
Author(s):  
Lan Wang ◽  
Zheng Qian Yin ◽  
Yuan Hang Sun
Keyword(s):  
Upper Limb ◽  
Shoulder Abduction ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
Upper Limb Exoskeleton ◽  
Revolute Joints ◽  
Shoulder Flexion ◽  
Flexion Extension ◽  
Active Rehabilitation ◽  
Limb Rehabilitation

Based on the analysis of the methods for upper limb rehabilitation training, an anthropomorphic upper-limb exoskeleton was developed. Anatomical and physiological characteristics and upper limb joint ranges of motion are also considered. The rehabilitation robot is achieved by 4 single-axis revolute joints which are shoulder abduction-adduction (abd-add), shoulder flexion-extension (flx-ext), elbow flx-ext and wrist flx-ext. Kinematics and dynamics analysis of the rehabilitation robot are made. The passive rehabilitation mode and active rehabilitation mode are researched, and the result of experenment is shown that the robot can finish the rehabilitation task well.

scholarly journals Design and evaluation of a novel upper limb rehabilitation robot with space training based on an end effector

2021 ◽  
Vol 12 (1) ◽  
pp. 639-648
Author(s):  
Qiaoling Meng ◽  
Zongqi Jiao ◽  
Hongliu Yu ◽  
Weisheng Zhang
Keyword(s):  
Upper Limb ◽  
Degrees Of Freedom ◽  
Elbow Flexion ◽  
Rehabilitation Robot ◽  
End Effector ◽  
Upper Limb Rehabilitation ◽  
Flexion Extension ◽  
Robot Configuration ◽  
Limb Rehabilitation ◽  
Equivalent Mechanism

Abstract. The target of this paper is to design a lightweight upper limb rehabilitation robot with space training based on end-effector configuration and to evaluate the performance of the proposed mechanism. In order to implement this purpose, an equivalent mechanism to the human being upper limb is proposed before the design. Then, a 4 degrees of freedom (DOF) end-effector-based upper limb rehabilitation robot configuration is designed to help stroke patients perform space rehabilitation training of the shoulder flexion/extension and adduction/abduction and elbow flexion/extension. Thereafter, its kinematical model is established together with the proposed equivalent upper limb mechanism. The Monte Carlo method is employed to establish their workspace. The results show that the overlap of the workspace between the proposed mechanism and the equivalent mechanism is 96.61 %. In addition, this paper also constructs a human–machine closed-chain mechanism to analyze the flexibility of the mechanism. According to the relative manipulability and manipulability ellipsoid, the highly flexible area of the mechanism accounts for 67.6 %, and the mechanism is far away from the singularity on the drinking trajectory. In the end, the single-joint training experiments and a drinking water training trajectory planning experiment are developed and the prototype is manufactured to verify it.

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

Upper-limb Rehabilitation Robot Motion Control Based on Dynamic Interpolation

ROBOT ◽  
2012 ◽  
Vol 34 (5) ◽  
pp. 539 ◽  
Author(s):  
Lizheng PAN ◽  
Aiguo SONG ◽  
Guozheng XU ◽  
Huijun LI ◽  
Baoguo XU
Keyword(s):  
Motion Control ◽  
Upper Limb ◽  
Robot Motion ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
Limb Rehabilitation

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.

Configuration Design and Simulation of Exoskeleton for Upper Limb Rehabilitation Train

2014 ◽  
Vol 701-702 ◽  
pp. 654-658 ◽  
Author(s):  
Yuan Zhang ◽  
Qiang Liu ◽  
Ji Liang Jiang ◽  
Li Yuan Zhang ◽  
Rui Rui Shen
Keyword(s):  
Upper Limb ◽  
Simulation Analysis ◽  
Motion Simulation ◽  
Upper Limb Rehabilitation ◽  
Motion Data ◽  
Upper Limb Exoskeleton ◽  
Movement Data ◽  
Kinematics Simulation ◽  
Motion Process ◽  
Limb Rehabilitation

A new upper limb exoskeleton mechanical structure for rehabilitation train and electric putters were used to drive the upper limb exoskeleton and kinematics simulation was carried. According to the characteristics of upper limb exoskeleton, program control and master - slave control two different ways were presented. Motion simulation analysis had been done by Pro/E Mechanism, the motion data of electric putter and major joints had been extracted. Based on the analysis of the movement data it can effectively guide the electric putter control and analysis upper limb exoskeleton motion process.

CONTROL OF FOREARM MODULE IN UPPER-LIMB REHABILITATION ROBOT FOR REDUCTION AND BIOMECHANICAL ASSESSMENT OF PRONATOR HYPERTONIA OF STROKE PATIENTS

2016 ◽  
Vol 16 (02) ◽  
pp. 1650008 ◽  
Author(s):  
PIN-CHENG KUNG ◽  
CHOU-CHING K. LIN ◽  
SHU-MIN CHEN ◽  
MING-SHAUNG JU
Keyword(s):  
Upper Limb ◽  
Position Control ◽  
Biomechanical Properties ◽  
Torque Control ◽  
Rehabilitation Robot ◽  
Stroke Patients ◽  
Upper Limb Rehabilitation ◽  
Biomechanical Assessment ◽  
Custom Made ◽  
Limb Rehabilitation

Spastic hypertonia causes loss of range of motion (ROM) and contractures in patients with post-stroke hemiparesis. The pronation/supination of the forearm is an essential functional movement in daily activities. We developed a special module for a shoulder-elbow rehabilitation robot for the reduction and biomechanical assessment of pronator/supinator hypertonia of the forearm. The module consisted of a rotational drum driven by an AC servo motor and equipped with an encoder and a custom-made torque sensor. By properly switching the control algorithm between position control and torque control, a hybrid controller able to mimic a therapist’s manual stretching movements was designed. Nine stroke patients were recruited to validate the functions of the module. The results showed that the affected forearms had significant increases in the ROM after five cycles of stretching. Both the passive ROM and the average stiffness were highly correlated to the spasticity of the forearm flexor muscles as measured using the Modified Ashworth Scale (MAS). With the custom-made module and controller, this upper-limb rehabilitation robot may be able to aid physical therapists to reduce hypertonia and quantify biomechanical properties of the muscles for forearm rotation in stroke patients.

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