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Towards Virtual Assessment of Human Factors: A Concept for Data Driven Prediction and Analysis of Physical User-product Interactions

Part of: User-Centred Design

Published online by Cambridge University Press:  26 July 2019

Alexander Wolf ,
Nicole Binder ,
Jörg Miehling  and
Sandro Wartzack

Abstract

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The early consideration of human factors in product development hugely favours the development of products, which excel with a positive user experience. The virtual environment of product development however, still has significant gaps in the virtual assessment and simulation of human factors, especially for user-product interactions composed of human movements. This motivates us to introduce a concept for data-driven prediction and analysis of user-product interactions. Heart of the concept is a predictive component that models the interaction between the user, represented by a musculoskeletal model, and the product, represented by product characteristics. We describe the implementation of this concept based on a pilot study for a lifting task. Motion capturing was performed to build a database and compare the results of our novel approach. The resulting kinematic and dynamic quantities show similar curve profiles with a small constant offset to the measured data. This indicates that the concept enables the virtual comparison of different designs or concepts regarding human factors.

Keywords

User centred designSimulationEarly design phasesUser-product interactionData-driven movement prediction
Type
Article
Information
Proceedings of the Design Society: International Conference on Engineering Design , Volume 1 , Issue 1 , July 2019 , pp. 4029 - 4038
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
© The Author(s) 2019

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