SimTK: OpenArm: Volumetric & Time Series Models of Muscle Deformation: Project Home

OpenArm: Volumetric & Time Series Models of Muscle Deformation

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The OpenArm data sets are designed to enable study of force- and kinematic-induced muscle deformation for applications in biomechanics research, computer graphics, and assistive device development.

**NEW:** The OpenArm Multisensor 2.0 data set contains new time series of ultrasound-measured brachioradialis deformation, surface electromyography (sEMG)-measured activation, force, and goal trajectory data, for various force-, deformation-, and activation-based trajectory tracking tasks, under refined conditions from those of the 1.0 data set. Also included are all analysis, real-time muscle deformation tracking, and display code.

The OpenArm Multisensor 1.0 data set contains time series cross-sectional ultrasound scans of the brachioradialis muscle under variable elbow loading, alongside corresponding surface electromyography (sEMG), acoustic myography (AMG), and force data.

The OpenArm 1.0 and 2.0 data sets encompass factorial sets of volumetric scans of the arm, generated using ultrasound and motion capture, that allow for analysis of both force- and configuration-associated muscle deformation.

We invite anyone in the research community to use the OpenArm and OpenArm Multisensor data sets to validate existing muscle deformation models or to devise new ones.

Full details can be found in the following papers:

Laura A. Hallock, Bhavna Sud, Chris Mitchell, Eric Hu, Fayyaz Ahamed, Akash Velu, Amanda Schwartz, and Ruzena Bajcsy. "Toward Real-Time Muscle Force Inference and Device Control via Optical-Flow-Tracked Muscle Deformation." In IEEE Transactions on Neural Systems and Rehabilitation Engineering (TNSRE). IEEE, 2021. (Under review.)

Laura Hallock, Akash Velu, Amanda Schwartz, and Ruzena Bajcsy. "Muscle deformation correlates with output force during isometric contraction." In IEEE RAS/EMBS International Conference on Biomedical Robotics & Biomechatronics (BioRob). IEEE, 2020. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/hallock2020biorob.)

Yonatan Nozik*, Laura A. Hallock*, Daniel Ho, Sai Mandava, Chris Mitchell, Thomas Hui Li, and Ruzena Bajcsy, "OpenArm 2.0: Automated Segmentation of 3D Tissue Structures for Multi-Subject Study of Muscle Deformation Dynamics," in International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), IEEE, 2019. *Equal contribution. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/nozikhallock2019embc.)

Laura Hallock, Akira Kato, and Ruzena Bajcsy. "Empirical quantification and modeling of muscle deformation: Toward ultrasound-driven assistive device control." In IEEE International Conference on Robotics and Automation (ICRA). IEEE, 2018. (Available at https://people.eecs.berkeley.edu/~lhallock/publication/hallock2018icra.)

This project is currently in development in the Human-Assistive Robotic Technologies (HART) Lab at the University of California, Berkeley (http://hart.berkeley.edu).