scholarly journals Multi-Domain Dynamic Modelling of a Low-Cost Upper Limb Rehabilitation Robot

Robotics ◽  
2021 ◽  
Vol 10 (4) ◽  
pp. 134
Author(s):  
Adam G. Metcalf ◽  
Justin F. Gallagher ◽  
Andrew E. Jackson ◽  
Martin C. Levesley

Tracking patient progress through a course of robotic tele-rehabilitation requires constant position data logging and comparison, alongside periodic testing with no powered assistance. The test data must be compared with previous test attempts and an ideal baseline, for which a good understanding of the dynamics of the robot is required. The traditional dynamic modelling techniques for serial chain robotics, which involve forming and solving equations of motion, do not adequately describe the multi-domain phenomena that affect the movement of the rehabilitation robot. In this study, a multi-domain dynamic model for an upper limb rehabilitation robot is described. The model, built using a combination of MATLAB, SimScape, and SimScape Multibody, comprises the mechanical electro-mechanical and control domains. The performance of the model was validated against the performance of the robot when unloaded and when loaded with a human arm proxy. It is shown that this combination of software is appropriate for building a dynamic model of the robot and provides advantages over the traditional modelling approach. It is demonstrated that the responses of the model match the responses of the robot with acceptable accuracy, though the inability to model backlash was a limitation.

2017 ◽  
Vol 2017 ◽  
pp. 1-15 ◽  
Author(s):  
Xikai Tu ◽  
Hualin Han ◽  
Jian Huang ◽  
Jian Li ◽  
Chen Su ◽  
...  

The reach-to-grasp activities play an important role in our daily lives. The developed RUPERT for stroke patients with high stiffness in arm flexor muscles is a low-cost lightweight portable exoskeleton rehabilitation robot whose joints are unidirectionally actuated by pneumatic artificial muscles (PAMs). In order to expand the useful range of RUPERT especially for patients with flaccid paralysis, functional electrical stimulation (FES) is taken to activate paralyzed arm muscles. As both the exoskeleton robot driven by PAMs and the neuromuscular skeletal system under FES possess the highly nonlinear and time-varying characteristics, iterative learning control (ILC) is studied and is taken to control this newly designed hybrid rehabilitation system for reaching trainings. Hand function rehabilitation refers to grasping. Because of tiny finger muscles, grasping and releasing are realized by FES array electrodes and matrix scan method. By using the surface electromyography (EMG) technique, the subject’s active intent is identified. The upper limb rehabilitation robot powered by PAMs cooperates with FES arrays to realize active reach-to-grasp trainings, which was verified through experiments.


2019 ◽  
Vol 9 (15) ◽  
pp. 3106 ◽  
Author(s):  
Hyung Seok Nam ◽  
Nhayoung Hong ◽  
Minwoo Cho ◽  
Chiwon Lee ◽  
Han Gil Seo ◽  
...  

In the context of stroke rehabilitation, simple structures and user-intent driven actuation are relevant features to facilitate neuroplasticity as well as deliver a sufficient number of repetitions during a single therapy session. A novel robotic treatment device for distal upper limb rehabilitation in stroke patients was developed, and a usability test was performed to assess its clinical feasibility. The rehabilitation robot was designed as a two-axis exoskeleton actuated by electric motors, consisting of forearm supination/pronation and hand grasp/release, which were selected based on a kinematic analysis of essential daily activities. A vision-assisted algorithm was utilized for user-intent extraction in a human-in-the-loop concept. A usability test was performed on six physiatrists, five biomedical engineers, five rehabilitation therapists, two chronic stroke patients, and two caregivers of the patients. After sufficient instruction, all subjects tested the robot for a minimum of 10 min and completed the evaluation form using a 7-point Likert scale. The participants found the device interesting (5.7 ± 1.2), motivating (5.8 ± 0.9), and as having less possibility of causing injury or safety issues (6.1 ± 1.1); however, the appropriateness of difficulty (4.8 ± 1.9) and comfort level (4.9 ± 1.3) were found to be relatively low. Further development of the current device would provide a good treatment option as a simple, low-cost, and clinically feasible rehabilitation robot for stroke.


ROBOT ◽  
2011 ◽  
Vol 33 (3) ◽  
pp. 307-313 ◽  
Author(s):  
Baoguo XU ◽  
Si PENG ◽  
Aiguo SONG

ROBOT ◽  
2012 ◽  
Vol 34 (5) ◽  
pp. 539 ◽  
Author(s):  
Lizheng PAN ◽  
Aiguo SONG ◽  
Guozheng XU ◽  
Huijun LI ◽  
Baoguo XU

2020 ◽  
pp. 1-17
Author(s):  
Qing Sun ◽  
Shuai Guo ◽  
Leigang Zhang

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.


2016 ◽  
Vol 16 (02) ◽  
pp. 1650008 ◽  
Author(s):  
PIN-CHENG KUNG ◽  
CHOU-CHING K. LIN ◽  
SHU-MIN CHEN ◽  
MING-SHAUNG JU

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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