scholarly journals Using proposed optimization algorithm for solving inverse kinematics of human upper limb applying in rehabilitation robotic

2021 ◽  
Author(s):  
Trung Nguyen ◽  
Tam Bui ◽  
Ha Pham
Keyword(s):  
Upper Limb ◽  
Inverse Kinematics ◽  
Search Space ◽  
Human Motion ◽  
Robot Arm ◽  
Upper Limb Rehabilitation ◽  
Rehabilitation Robots ◽  
Inverse Kinematics Problem ◽  
Limb Rehabilitation ◽  
Human Upper Limb

AbstractThe requirement to solve the problem of Inverse Kinetics (IK) plays a very important role in the robotics field in general, and especially in the field of rehabilitation robots, in particular. If the solutions of this problem are not suitable, it can cause undesirable damage to the patient when exercising. Normally, the problem of Inverse Kinematics in the robotics field, as well as the natural field, especially for redundant driven systems, often requires the application of a lot of techniques. The redundancy in Degree of Freedom (DoF), the nonlinearity of the system leads to solve inverse kinematics problem more challenge. In this study, we proposed to apply the self-adaptive control parameters in Differential Evolution with search space improvement (Pro-ISADE) to solve the problem for the human upper limb, which is a very typical redundancy model in nature. First of all, the angles of the joints were measured by a proposed Exoskeleton type Human Motion Capture System (E-HMCS) when the wearer performs some Activities of Daily Living (ADL) and athletic activities. The values of these measured angles joints then were put into the forward kinematics model to find the end effector trajectories. After having these orbits, they were re-fed into the proposed Pro-ISADE algorithm mentioned above to process the IK problem and obtain the predicted joints angular values. The experimental results showed that the predicted joints’ values closely follow the measured joints’ values. That demonstrates the ability to apply the Pro-ISADE algorithm to solve the problem of Inverse Kinetics of the human upper limb as well as the upper limb rehabilitation robot arm.

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.

Improved Artificial Potential Field Method Manipulator Inverse Kinematics

2013 ◽  
Vol 273 ◽  
pp. 119-123
Author(s):  
Ding Jin Huang ◽  
Teng Liu
Keyword(s):  
Potential Field ◽  
Inverse Kinematics ◽  
Search Space ◽  
Field Method ◽  
Robotic Arm ◽  
Artificial Potential Field ◽  
Robot Arm ◽  
Potential Field Method ◽  
Inverse Kinematics Problem ◽  
Artificial Potential Field Method

The use of traditional analytical method for manipulator inverse kinematics is able to get a display solution with the limitations of the application, only when the robotic arm has a specific structure. In view of the insufficient, this paper presents an improved artificial potential field method to solve the inverse kinematics problem of the manipulator which does not have a special structure. Firstly, establish the standard DH model for the robot arm. Then the strategy that improves search space of artificial potential field method and motion control standard is presented by combining artificial potential field method with the manipulator. Finally, the simulation results show that the proposed method is effective.

A Study of the Control method of a Robot for Human Upper Limb Rehabilitation

2002 ◽  
Vol 2002.40 (0) ◽  
pp. 425-426
Author(s):  
Yuzuru ITO ◽  
Yoshihiro KAI ◽  
Yoshio INOUE ◽  
Tetsuya TANIOKA ◽  
Kenichi SUGAWARA
Keyword(s):  
Upper Limb ◽  
Control Method ◽  
Upper Limb Rehabilitation ◽  
Limb Rehabilitation ◽  
Human Upper Limb

Kinematic Design Consideration Based on Actuator Placement of Five-Bar Planar Robot for Arm Rehabilitation

2014 ◽  
Vol 625 ◽  
pp. 638-643 ◽  
Author(s):  
Jung Hyun Choi ◽  
Dong Hwan Shin ◽  
Tae Sang Park ◽  
Choong Pyo Jeong ◽  
Jeon Il Moon ◽  
...  
Keyword(s):  
Upper Limb ◽  
Point Of View ◽  
Planar Mechanisms ◽  
Upper Limb Rehabilitation ◽  
Kinematic Design ◽  
Rehabilitation Robots ◽  
Arm Rehabilitation ◽  
Critical Issues ◽  
Limb Rehabilitation ◽  
Actuator Placement

In the design of upper limb rehabilitation robots, critical issues to be considered are large workspace with minimum singularities to cover enough patients’ upper limb range of motion and higher manipulability for the patients to easily and freely move their arm with applying almost the same force to every direction in a given posture. This paper presents an analysis of the suggested kinematic design considerations of five-bar planar mechanism according to the actuator locations. A comparison between two different five-bar linkage types is given. Finally, several open challenges for the applicability of five-bar planar mechanisms are discussed from the kinematic point of view to upper limb rehabilitation robots.

scholarly journals Fusion Learning for sEMG Recognition of Multiple Upper-Limb Rehabilitation Movements

Sensors ◽  
2021 ◽  
Vol 21 (16) ◽  
pp. 5385
Author(s):  
Tianyang Zhong ◽  
Donglin Li ◽  
Jianhui Wang ◽  
Jiacan Xu ◽  
Zida An ◽  
...  
Keyword(s):  
Feature Extraction ◽  
Upper Limb ◽  
Classification Accuracy ◽  
Human Motion ◽  
Identification Accuracy ◽  
Classification Model ◽  
Upper Limb Rehabilitation ◽  
Time Frequency ◽  
Limb Rehabilitation ◽  
Semg Signals

Surface electromyogram (sEMG) signals have been used in human motion intention recognition, which has significant application prospects in the fields of rehabilitation medicine and cognitive science. However, some valuable dynamic information on upper-limb motions is lost in the process of feature extraction for sEMG signals, and there exists the fact that only a small variety of rehabilitation movements can be distinguished, and the classification accuracy is easily affected. To solve these dilemmas, first, a multiscale time–frequency information fusion representation method (MTFIFR) is proposed to obtain the time–frequency features of multichannel sEMG signals. Then, this paper designs the multiple feature fusion network (MFFN), which aims at strengthening the ability of feature extraction. Finally, a deep belief network (DBN) was introduced as the classification model of the MFFN to boost the generalization performance for more types of upper-limb movements. In the experiments, 12 kinds of upper-limb rehabilitation actions were recognized utilizing four sEMG sensors. The maximum identification accuracy was 86.10% and the average classification accuracy of the proposed MFFN was 73.49%, indicating that the time–frequency representation approach combined with the MFFN is superior to the traditional machine learning and convolutional neural network.

scholarly journals A Review on Upper Limb Rehabilitation Robots

2020 ◽  
Vol 10 (19) ◽  
pp. 6976
Author(s):  
Hassan M. Qassim ◽  
W. Z. Wan Hasan
Keyword(s):  
Upper Limb ◽  
Rehabilitation Process ◽  
Upper Limb Rehabilitation ◽  
Post Stroke ◽  
Rehabilitation Robots ◽  
The Common ◽  
Limb Rehabilitation

Rehabilitation is the process of treating post-stroke consequences. Impaired limbs are considered the common outcomes of stroke, which require a professional therapist to rehabilitate the impaired limbs and restore fully or partially its function. Due to the shortage in the number of therapists and other considerations, researchers have been working on developing robots that have the ability to perform the rehabilitation process. During the last two decades, different robots were invented to help in rehabilitation procedures. This paper explains the types of rehabilitation treatments and robot classifications. In addition, a few examples of well-known rehabilitation robots will be explained in terms of their efficiency and controlling mechanisms.

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