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Best-Practice Approach for a Solution-Oriented Technology Assessment: Ethical, Legal, and Social Issues in the Context of Human-Robot Collaboration Read chapter Read first chapter

2017 | OriginalPaper | Chapter

Joint Angle Depending Representation of Maximum Forces in Digital Human Models: Investigating Multivariate Joint-Torque Polynomials for Elbow Flexion and Elbow Extension

Authors : André Kaiser, Michael Spitzhirn, Angelika C. Bullinger

Published in: Advances in Ergonomic Design of Systems, Products and Processes

Publisher: Springer Berlin Heidelberg

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Abstract

Joint angle-dependent calculations of human action forces constitute a significant advantage of digital human models, but further knowledge of maximum allowable joint torques has to be acquired. This paper describes a method to calculate polynomials (functions) for maximum torque of elbow flexion and extension that depend on various joints of elbow and shoulder to increase the quality of prediction.
First, the anatomical influences are described to explain which joint angles affect the determination of elbow flexion torques and elbow extension torques. Following, the used experimental design with 948 measurements and the procedure to conduct the polynomials is shown in detail. Here, different ways to determine polynomials are investigated. The results are polynomials for elbow flexion and extension torques which depend on the elbow-flexion angle (EF), the elbow-rotation angle (ER), the shoulder-flexion angle (SF), the shoulder-abduction angle (SA) and the shoulder-rotation angle (SR). The polynomials explain 81.5 % of the variance of the measured values for flexion and 76.5 % of the variance for extension, respectively. Overall, the developed model gives an accurate prediction for maximum flexion and extension torques in regard to the described joint angles. It can therefore help to improve the quality of ergonomic planning using digital human models.

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previous chapter Man-Robot Collaboration in the Context of Industry 4.0: Approach-Avoidance Tendencies as an Indicator for the Affective Quality of Interaction?
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Metadata
Title
Joint Angle Depending Representation of Maximum Forces in Digital Human Models: Investigating Multivariate Joint-Torque Polynomials for Elbow Flexion and Elbow Extension
Authors
André Kaiser
Michael Spitzhirn
Angelika C. Bullinger
Copyright Year
2017
Publisher
Springer Berlin Heidelberg
Book
Advances in Ergonomic Design of Systems, Products and Processes

Print ISBN: 978-3-662-53304-8

Electronic ISBN: 978-3-662-53305-5

Copyright Year: 2017

DOI
https://doi.org/10.1007/978-3-662-53305-5_25

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