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. 2020 Jul 10;10:11450. doi: 10.1038/s41598-020-68225-6

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© The Author(s) 2020

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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Human motion analysis using personalised biomechanical models, simulation, and data synthesis to estimate wearable system and marker performance. (A) Illustration of the personalised full body model, extended with motion sensor models at upper and lower body extremities. (B) Body kinematic simulation of the sensor-extended full body model with video motion-capture data. (C) Sensor data synthesis (here: acceleration) using a direct-link sensor-body attachment model. (D) Processing of synthesised acceleration data using gait marker estimation algorithms. (E) Analysis of individual movement effects on gait markers, sensor position on the body, and estimation algorithms. (F) Biomechanical models and video-motion data obtained from the public SimTK repository.