AboutDownloadsDocumentsForumsIssuesNews
Modeling and analysis
These files contain CSV files of inverse kinematics results, combined with experimental electromyography data and estimated exoskeleton torque profiles. Code for data-driven modeling and analysis are included.
Initial dataset and code submission
Jun 19, 2020

This is the initial submission of code and datasets for data-driven modeling and analysis of gait with passive exoskeletons.  View License

Download Links

Jun 19, 2020
156 KB
Any
Data/images/video
This document summarizes the datasets (CSV files) for each participant, containing joint kinematics, muscle activity, and exoskeleton torque profiles. The document also contains descriptions of data-driven modeling and analysis code.

Jun 19, 2020
25 MB
Any
Data/images/video
P01 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
25 MB
Any
Data/images/video
P02 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
25 MB
Any
Data/images/video
P03 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
25 MB
Any
Data/images/video
P04 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
25 MB
Any
Data/images/video
P05 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
25 MB
Any
Data/images/video
P06 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
25 MB
Any
Data/images/video
P09 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
25 MB
Any
Data/images/video
P07 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
25 MB
Any
Data/images/video
P08 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
25 MB
Any
Data/images/video
P10 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
25 MB
Any
Data/images/video
P11 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
25 MB
Any
Data/images/video
P12 - Datasets containing CSV files of kinematics, electromyography, and exoskeleton torque profiles for each exoskeleton condition. Files identifying initial contact events for each condition are included.

Jun 19, 2020
191 MB
Any
Data/images/video
Data-driven model prediction accuracy results and sample predictions. These files are used in the Statistical Analysis code package.

Jun 19, 2020
338 KB
Any
Data/images/video
Python code used to generate data-driven prediction models of gait with exoskeletons.

Jun 19, 2020
42 KB
Any
Data/images/video
MATLAB code used to generate figures and run statistical analyses of data-driven model predictions.

Aug 25, 2020
598
Any
Data/images/video
Information about participants and the exoskeleton stiffness levels.

PLEASE CITE THESE PAPERS

Rosenberg Michael C., Banjanin Bora S., Burden Samuel A. and Steele Katherine M. 2020 Predicting walking response to ankle exoskeletons using data-driven models. J. R. Soc. Interface.1720200487. (2020) View


Simulation datasets
Datasets from the manuscript: Rosenberg MC, et al., "Predicting walking response to ankle exoskeletons using data-driven models," Submitted to: Journal of the Royal Society Interface, 2020.
Initial dataset submission
Jun 19, 2020

Initial submission of datasetsNotes  View License

Download Links

Jun 19, 2020
71 MB
Any
Data/images/video
P04 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

Jun 19, 2020
80 KB
Any
Data/images/video
Contains descriptions of the musculoskeletal models and associated datasets.

Jun 19, 2020
743 KB
Any
Data/images/video
A generic musculoskeletal model with the marker set used in scaling and inverse kinematics.

Jun 19, 2020
71 MB
Any
Data/images/video
P01 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

Jun 19, 2020
63 MB
Any
Data/images/video
P02 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

Jun 19, 2020
70 MB
Any
Data/images/video
P03 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

Jun 19, 2020
69 MB
Any
Data/images/video
P05 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

Jun 19, 2020
71 MB
Any
Data/images/video
P06 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

Jun 19, 2020
70 MB
Any
Data/images/video
P07 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

Jun 19, 2020
70 MB
Any
Data/images/video
P08 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

Jun 19, 2020
69 MB
Any
Data/images/video
P09 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

Jun 19, 2020
69 MB
Any
Data/images/video
P11 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

Jun 19, 2020
70 MB
Any
Data/images/video
P10 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

Jun 19, 2020
70 MB
Any
Data/images/video
P12 - Dataset including a scaled model, marker trajectories, ground reaction forces, and setup files for scaling and inverse kinematics.

ADDITIONAL PAPERS

Predicting walking response to ankle exoskeletons using data-driven models Michael C. Rosenberg, Bora S. Banjanin, Samuel A. Burden, Katherine M. Steele bioRxiv 2020.06.18.105163; doi: https://doi.org/10.1101/2020.06.18.105163 (2020) View


Template Signatures code
This package contains MATLAB-based code package to identify hybrid Template Signatures of center-of-mass dynamics during walking with ankle exoskeletons. Modeling, analysis, and plotting code sets are included. Some functions are unmodified from: Mangan NM, Kutz JN, Brunton SL, Proctor JL. Model selection for dynamical systems via sparse regression and information criteria. Proceedings of the Royal Society A: Mathematical, Physical and Engineering Sciences. 2017 Aug 31;473(2204):20170009.
Hybrid-SINDy modeling code
Jun 16, 2022

This code package contains code to run and analyze template-like gait dynamics with ankle exoskeletons. The package also contains a synthetic spring-loaded inverted pendulum walker used to implement the Hybrid-SINDy algorithm for gait.  View License

Download Links

Jun 16, 2022
149 MB
Any
Data/images/video
This code package enables rapid identification of data-driven whole-leg gait dynamics during walking. The code is applied to gait with exoskeletons and can be tested on the data provided in the Template Signatures Dataset.


Template Signatures datasets
This package contains CSV files of center-of-mass kinematics, and foot position estimates from OpenSim 3.3 for 12 unimpaired adults and one adult with post-stroke hemiparesis during walking with and without ankle exoskeletons. Participant demographics are also included. A sample synthetic dataset of a spring-loaded inverted pendulum walker is included for validation of the Hybrid-SINDy algorithm.
Initial Release
Jan 21, 2022

This is the initial release  View License

Download Links

Jan 21, 2022
3 MB
Any
Data/images/video
Results files from the Hybrid-SINDy analysis, used to generate figures for human walking in shoes only and with bilateral passive ankle exoskeletons. Exoskeleton conditions were zero-stiffness and high-stiffness (5 Nm/deg). Results are included for analyses using a logarithmic range of Gaussian noise levels added to the position measurements. Results contain indices for hybrid regimes (single and double-limb support) and template signatures.

Jan 20, 2022
650 KB
Any
Data/images/video
Results files from the Hybrid-SINDy analysis, used to generate manuscript figures for the synthetic datasets of a simulated spring-loaded inverted pendulum walker. Results are included for analyses using a logarithmic range of Gaussian noise levels added to the position measurements.

Jun 13, 2022
511 MB
Any
Data/images/video
Datasets containing MAT files of center-of-mass and foot kinematics, and ground reaction forces for 13 adults walking with and without passive ankle exoskeletons. A synthetic dataset of a spring-loaded inverted pendulum is included for algorithm validation.


Feedback