3D Body Twin: Improving Human Gait Visualizations Using Personalized Avatars

Zieger D, Güthlein F, Henningson JO, Jakob V, Gaßner H, Shanbhag J, Fleischmann S, Miehling J, Wartzack S, Eskofier B, Winkler J, Egger B, Stamminger M (2024)


Publication Type: Conference contribution

Publication year: 2024

Journal

Series: ShapeMI: International Workshop on Shape in Medical Imaging

Pages Range: 70-83

Conference Proceedings Title: ShapeMI 2024

Event location: Marrakesh MA

ISBN: 9783031752902

DOI: 10.1007/978-3-031-75291-9_6

Abstract

We propose an interactive visualization and reconstruction system for gait pattern analysis that creates a more realistic visualization of the patient than contemporary stick figure-like representations. It supports thorough gait pattern analysis, and enables unbiased inter- and intra-patient comparisons as well as longitudinal studies. Our system takes as input 3D motion capture data, but can be further constrained using readily available metadata or layman-accessible measurements. A statistical shape model is then fitted to the motion capture and personal metadata. The result is an immediate and interactive visualization of an animated 3D twin. Our system handles different marker setups and can thus be applied to already existing data. We further show that we can infer realistic body models with only a few of markers. A survey with medical experts confirms the clinical applicability of our method.

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How to cite

APA:

Zieger, D., Güthlein, F., Henningson, J.-O., Jakob, V., Gaßner, H., Shanbhag, J.,... Stamminger, M. (2024). 3D Body Twin: Improving Human Gait Visualizations Using Personalized Avatars. In ShapeMI 2024 (pp. 70-83). Marrakesh, MA.

MLA:

Zieger, Daniel, et al. "3D Body Twin: Improving Human Gait Visualizations Using Personalized Avatars." Proceedings of the Shape in Medical Imaging, Marrakesh 2024. 70-83.

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