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This page contains links to two types of data set packages: 1) the OpenArm Multisensor data set, which contains 2D time series ultrasound data (with muscle contour tracking code) alongside surface electromyography (sEMG), acoustic myography (AMG), and force data, and 2) the OpenArm 1.0 and 2.0 data sets, each of which contain full 3D data of the human arm under multiple conditions, alongside ground-truth and CNN-generated annotations of select tissue structures for select scans. All code and neural network models used in tissue annotation are also provided under a separate package. See each package for details.
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OpenArm Multisensor 2.0
This folder contains the second iteration of the OpenArm Multisensor data set and associated muscle contour tracking code. Included are 1) a multi-subject data set of ultrasound-based time series deformation data of the brachioradialis muscle alongside surface electromyography (sEMG), force, and goal trajectory data, and 2) all code used in analyzing deformation across subjects and optical flow tracking of muscle deformation over time.
OpenArm Multisensor 2.0
Jul 10, 2021

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ADDITIONAL 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) (2021)


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OpenArm Multisensor 1.0
This folder contains the first iteration of the OpenArm Multisensor data set and associated muscle contour tracking code. Included are 1) a multi-subject data set of ultrasound-based time series deformation data of the brachioradialis muscle alongside surface electromyography (sEMG), acoustic myography (AMG), and force data, and 2) all code used in analyzing deformation across subjects and optical flow tracking of muscle deformation over time.
OpenArm Multisensor 1.0
Jul 17, 2020

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PLEASE CITE THESE PAPERS

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. (2020) View


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OpenArm 2.0
This package contains the second iteration of the OpenArm data set, a multi-subject set of full volumetric scans of the human arm collected using ultrasound and motion capture. Data are factorial under multiple elbow angles and loading conditions, and thus allow for separable analysis of force- and configuration-associated muscle deformation. Improvements from OpenArm 1.0 include improved data collection procedures allowing for more explicit comparison of force conditions across angles, more subjects, and partial annotations for all subjects enabled by neural-network-based segmentation.
OpenArm 2.0
Apr 24, 2019

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PLEASE CITE THESE PAPERS

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. (2019) View


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OpenArm 1.0
This package contains the first iteration of the OpenArm data set, a set of full volumetric scans of the human arm collected using ultrasound and motion capture. Data are factorial under multiple elbow angles and loading conditions, and thus allow for separable analysis of force- and configuration-associated muscle deformation.
OpenArm 1.0
Nov 28, 2018

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PLEASE CITE THESE PAPERS

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. (2018) View


Annotation Source Code
This package contains source code and neural network models for both registration and CNN-based automated annotation of the biceps and humerus, first used to generate the OpenArm 2.0 data set.
Segmentation Code & Network Models
Jul 12, 2019

This release contains all code and neural network models used to generate tissue segmentations for the OpenArm 2.0 data set, using both convolutional neural networks and classical image registration. Code and models used in network training, prediction, analysis, and data augmentation are included.  View License

PLEASE CITE THESE PAPERS

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. (2019) View


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