Musculoskeletal Analysis of Upper Limb Rehabilitation Robot Prototype

2016 ◽  
Vol 833 ◽  
pp. 196-201 ◽  
Author(s):  
Shahrol Mohamaddan ◽  
Annisa Jamali ◽  
Noor Aliah Abd Majid ◽  
Mohamad Syazwan Zafwan Mohamad Suffian
Keyword(s):  
Upper Limb ◽  
Vertical Movement ◽  
Human Model ◽  
Rehabilitation Robot ◽  
Upper Limb Rehabilitation ◽  
The Third ◽  
Hardware Development ◽  
Limb Rehabilitation ◽  
Human Upper Limb ◽  
Rehabilitation Exercise

Stroke is the third largest cause of death in Malaysia. Different approaches including hardware development and simulation were conducted to support the conventional rehabilitation courses. New upper limb rehabilitation robot prototype was developed for this research. The prototype consists of horizontal and vertical movement exercise. The prototype was modeled and simulated using ergonomics optimization software known as AnyBody. This paper presents the analysis of human upper limb muscles during rehabilitation exercise using virtual human model. The result shows that eleven muscle areas were affected during the rehabilitation exercise using new prototype.

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.

Mechanism Design and Kinematics Positive Solution of the Exoskeleton Upper Limb Rehabilitation Robot with 6-DOF

2013 ◽  
Vol 744 ◽  
pp. 74-77 ◽  
Author(s):  
Hui Zhang ◽  
Yong Xing Wang ◽  
Sheng Ze Wang
Keyword(s):  
Positive Solution ◽  
Upper Limb ◽  
Shoulder Joint ◽  
Rehabilitation Medicine ◽  
Rehabilitation Robot ◽  
Joint Motion ◽  
Guide Rail ◽  
Upper Limb Rehabilitation ◽  
Limb Rehabilitation ◽  
Human Upper Limb

According to the clinical rehabilitation medicine theory and the characteristics of human upper limb rehabilitation robot, a dexterous rehabilitation mechanical arm with 6-DOF is designed to satisfy the need of rehabilitation in this paper. By analyzing the six cases of the 3-DOF serial distribution and the kinematic relation of the shoulder joint, the spherical joint motion of the shoulder joint is achieved by using the circular arc guide rail. Two serial mechanism approaches of the shoulder joint using PRR and RRP type are provided. After comparing these designs, the PRR type is selected, the kinematics positive solution of this type is given.

DEVELOPMENT AND ANALYSIS OF A BILATERAL END-EFFECTER UPPER LIMB REHABILITATION ROBOT

2021 ◽  
pp. 2150032
Author(s):  
LEIGANG ZHANG ◽  
SHUAI GUO ◽  
QING SUN
Keyword(s):  
Upper Limb ◽  
Rehabilitation Robot ◽  
Healthy Human Subject ◽  
Unaffected Side ◽  
Healthy Human ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Training ◽  
Limb Rehabilitation ◽  
Human Upper Limb ◽  
Training Protocol

Studies have shown that rehabilitation training with the unaffected side guiding affected side is more consistent with the natural movement pattern of human upper limb compared with unilateral rehabilitation training, which is conducive to improve rehabilitation effect of the affected limb motor function. In this paper, a bilateral end-effector upper limb rehabilitation robot (BEULRR) based on two modern commercial manipulators is developed first, then the kinematics, reachability, and dexterity analysis of BEULRR are performed, respectively. Finally, a bilateral symmetric training protocol with the unaffected side guiding the affected side is proposed and evaluated through healthy human subject experiment testing based on BEULRR. The simulation results show that the developed BEULRR could perform spatial rehabilitation training and its rehabilitation training workspace can fully cover the physiological workspace of human upper limb. The preliminary experiment results from the healthy human subject show that the BEULRR system could provide reliable bilateral symmetric training protocol. These simulation and experiment results demonstrated that the developed BEULRR system could be used in bilateral rehabilitation training application, and also show that the BEULRR system has the potential to be applied to clinical rehabilitation training in the further step. In the close future, the proposed BEULRR and bilateral symmetric training protocol are planned to be applied in elderly volunteers and patients with upper limb motor dysfunction for further evaluating.

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.

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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