scholarly journals The kinematical model of the elbow joint with one degree of freedom

2019 ◽  
Keyword(s):  
Elbow Joint ◽  
Degree Of Freedom ◽  
Kinematical Model

Design of Bio-Exoskeleton for Elbow Rehabilitation

2020 ◽  
Author(s):  
Pablo Delgado ◽  
Thisath Attampola Arachchige Don ◽  
Jesus Gomez ◽  
Virgil Miranda ◽  
Yimesker Yihun
Keyword(s):  
Motion Capture ◽  
Elbow Joint ◽  
Synthesis Method ◽  
Elbow Flexion ◽  
Degree Of Freedom ◽  
Motion Capture System ◽  
Research Topics ◽  
End Effector ◽  
Joint Injuries ◽  
And Task

Abstract In this study, a methodology for designing a task-based exoskeleton which can recreate the end-effector trajectory of a given limb during a rehablitation task/movement is presented. The exoskeleton provides an option to replace traditional jointbased exoskeleton joints, which often have alignment issues with the biological joint. The proper fit of the exoskeleton to the user and task are research topics to reduce pain or joint injuries as well as for the execution of the task. The proposed task-based synthesis method was successfully applied to generate the 3D motions of the elbow flexion and extensions using a one degree of freedom (DOF), spatial four-bar mechanism. The elbow joint is analyzed through motion capture system to develop the bio-exoskeleton. The resulted exoskeleton does not need to align with the corresponding limb joint to generate the desired anatomical motion.

Approximating power for significance tests with one degree of freedom.

1997 ◽  
Vol 2 (2) ◽  
pp. 186-191 ◽  
Author(s):  
William P. Dunlap ◽  
Leann Myers
Keyword(s):  
Degree Of Freedom ◽  
Significance Tests

Performance analysis of global local mean square error criterion of stochastic linearization for nonlinear oscillator

2019 ◽  
Author(s):  
Nguyen Cao Thang ◽  
Luu Xuan Hung
Keyword(s):  
Performance Analysis ◽  
Mean Square Error ◽  
Nonlinear Oscillators ◽  
Degree Of Freedom ◽  
Equivalent Linearization ◽  
Mean Square ◽  
Error Criterion ◽  
Stochastic Linearization ◽  
Local Mean ◽  
Mean Square Error Criterion

The paper presents a performance analysis of global-local mean square error criterion of stochastic linearization for some nonlinear oscillators. This criterion of stochastic linearization for nonlinear oscillators bases on dual conception to the local mean square error criterion (LOMSEC). The algorithm is generally built to multi degree of freedom (MDOF) nonlinear oscillators. Then, the performance analysis is carried out for two applications which comprise a rolling ship oscillation and two degree of freedom one. The improvement on accuracy of the proposed criterion has been shown in comparison with the conventional Gaussian equivalent linearization (GEL).

Sign in / Sign up

Export Citation Format

Share Document