Back to Search Start Over

AddBiomechanics Dataset: Capturing the Physics of Human Motion at Scale

Authors :
Werling, Keenon
Kaneda, Janelle
Tan, Alan
Agarwal, Rishi
Skov, Six
Van Wouwe, Tom
Uhlrich, Scott
Bianco, Nicholas
Ong, Carmichael
Falisse, Antoine
Sapkota, Shardul
Chandra, Aidan
Carter, Joshua
Preatoni, Ezio
Fregly, Benjamin
Hicks, Jennifer
Delp, Scott
Liu, C. Karen
Publication Year :
2024

Abstract

While reconstructing human poses in 3D from inexpensive sensors has advanced significantly in recent years, quantifying the dynamics of human motion, including the muscle-generated joint torques and external forces, remains a challenge. Prior attempts to estimate physics from reconstructed human poses have been hampered by a lack of datasets with high-quality pose and force data for a variety of movements. We present the AddBiomechanics Dataset 1.0, which includes physically accurate human dynamics of 273 human subjects, over 70 hours of motion and force plate data, totaling more than 24 million frames. To construct this dataset, novel analytical methods were required, which are also reported here. We propose a benchmark for estimating human dynamics from motion using this dataset, and present several baseline results. The AddBiomechanics Dataset is publicly available at https://addbiomechanics.org/download_data.html.<br />Comment: 15 pages, 6 figures, 4 tables

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2406.18537
Document Type :
Working Paper