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Quantification of Upper-Body Synergies: A Case Comparison for Stroke and Non-Stroke Victims

[+] Author Affiliations
Omid Heidari, John O. Roylance, Alba Perez-Gracia, Eydie Kendall

Idaho State University, Pocatello, ID

Paper No. DETC2016-59314, pp. V05AT07A032; 10 pages
  • ASME 2016 International Design Engineering Technical Conferences and Computers and Information in Engineering Conference
  • Volume 5A: 40th Mechanisms and Robotics Conference
  • Charlotte, North Carolina, USA, August 21–24, 2016
  • Conference Sponsors: Design Engineering Division, Computers and Information in Engineering Division
  • ISBN: 978-0-7918-5015-2
  • Copyright © 2016 by ASME


Motion synergies are principal components of the movement, obtained as combinations of joint degrees of freedom, that account for common postures of the human body. These synergies are usually obtained by capturing the motion of the human joints and reducing the dimensionality of the joint space with techniques such as principal component analysis. In this work, an experimental procedure to investigate the synergies of the upper body is developed and the results of the pilot study are shown.

The upper-limb kinematics includes the joint complexes of the hand, wrist, forearm, elbow, and shoulder. The different kinematic models in the literature have been reviewed, and a serial chain is considered from the upper arm. A three degree of freedom (3-DOF) linkage containing two revolute joints and one prismatic joint has been chosen to simulate the shoulder motion. A spherical joint represents the Glenohumeral (GH) joint; the elbow and ulna-radius rotations are represented by two revolute joints and the wrist is modeled with two revolute joints. The hand has a tree structure and branches into the individual phalanges, with a 2-dof MCP joint and single R joints for the rest of the phalangeal joints.

The data are collected using motion capture and the joint angles are calculated using a combination of dimensional synthesis and inverse kinematics. Principal component analysis can be used to extract the synergies for a set of previously-selected motions. The motions are performed by healthy subjects and subjects who have suffered stroke, in order to see the changes in the motion primitives. It is expected that this study will help quantify and classify some of the loss of motion due to stroke.

Copyright © 2016 by ASME



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