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Rehabilitation Dataset Directory: Dataset Profile

Dataset: Medical University of South Carolina Stroke Data (ARRA)

Basic Information
Dataset Full Name Medical University of South Carolina Stroke Data
Dataset Acronym ARRA

The Medical University of South Carolina Stroke Data (ARRA*) was a NIH funded study conducted in 2011-12. It was designed to delineate the cause/effect relationship between neural output and the biomechanical functions executed in walking. Subjects included 27 post-stroke patients (at least 6 months post-stroke) and 17 healthy controls.

Each subject walked on a treadmill at their self-selected walking speed as well as completing a randomized set of four steady-state mobility capability tasks: walking at maximum speed, and walking at self-selected speed with maximum cadence, maximum step length, and maximum step height. Kinematic, kinetic, and electromyography (EMG) data were collected.  The data collected allow scientists interested in EMG analyses of hemiparetic walking to have a test set for their analyses.

The data collected includes demographics, clinical assessments, kinetic (from treadmill force plates), kinematic (from active markers), EMG and Over-ground spatial temporal measures (GaitRite Platinum Walkway).

* Documentation refers to the study as ARRA: American Recovery and Reinvestment Act 

Key Terms

Stroke, Post-stroke, Mobility, Gait, Walking, Kinematic, Kinetic, Electromyography (EMG), Treadmill, Motion capture system

Study Design Cross-Sectional
Data Type(s) Administrative
Sponsoring Agency/Entity

Department of Health and Human Services (HHS),

National Institutes of Health (NIH), the Department of Veterans Affairs, and the National Science Foundation

Health Conditions/Disability Measures
Health Condition(s)


Disability Measures

Ambulatory disability

Measures/Outcomes of Interest

Stroke, Post-stroke mobility, Walking, Walking speed, Electromyography (EMG),  Video motion capture

Sample Population

Males and Females, healthy and 6+ months post stroke, ages 40-80, living in the Southeastern United States.

  • Post-stroke patients  
  • Healthy control subjects 
Sample Size/Notes

44 subjects total:

  • 27 post-stroke subjects (6+ months post-stroke)
  • 17 healthy control subjects
Unit of Observation



North America


United States

Geographic Coverage

Southeastern United States (South Carolina)

Geographic Specificity


Special Population(s)

Aging/Older people (ages 40-80)

Data Collection
Data Collection Mode

Multiple modes of data collection:

  • 12 camera (3D) motion capture system
  • Fully instrumented split belt treadmill measuring 3D ground reaction forces and moments.
  • Electromyography
Years Collected


Data Collection Frequency

Single time period data collection

Strengths and Limitations

Well documented and extensive data collection.

Data includes both post stroke patients and control individuals allowing for comparisons.

The number of subjects and data collected provides researchers interested in EMG analyses of hemiparetic walking with a test set for analyses.


From related paper (Routson 2014) :

"Due to our limited recording of EMG from eight muscles, we were only able to identify four modules during healthy control walking... our methods did not include an analysis to determine whether a particular subject's muscle strength was sufficient to perform the mobility capability tasks."

Data Details
Primary Website 

Data Access

Download Restricted Data Use Agreement here: 

Data Access Requirements

 Data Use agreement, No cost

(Restricted Data Use Agreement)

Summary Tables/Reports

See the following publication:

Routson, Rebecca L., Kautz, Steven A., Neptune, Richard R. (2014) Modular organization across changing task demands in healthy and poststroke gait. Physiological Reports. 2, (6), e12055. 

Data Components


Similar/Related Dataset(s)
Stroke focused studies:
Selected Papers
Other Papers

Routson, Rebecca L., Kautz, Steven A., Neptune, Richard R. (2014) Modular organization across changing task demands in healthy and poststroke gait. Physiological Reports. 2, (6), e12055. 


Main documentation page: 

Includes the following:

  • Codebook
  • User Guide
  • Questionnaire (including data collection forms)
  • Restricted Data Use Agreement
Related Repositories

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The Rehabilitation Research Cross-dataset Variable Catalog has been developed through the Center for Large Data Research & Data Sharing in Rehabilitation (CLDR). The Center for Large Data Research and Data Sharing in Rehabilitation involves a consortium of investigators from the University of Texas Medical Branch, Cornell University's Yang Tan Institute (YTI), and the University of Michigan. The CLDR is funded by NIH - National Institute of Child Health and Human Development, through the National Center for Medical Rehabilitation Research, the National Institute for Neurological Disorders and Stroke, and the National Institute of Biomedical Imaging and Bioengineering. (P2CHD065702).

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Acknowledgements: This tool was developed through the efforts of William Erickson and Arun Karpur, and web designers Jason Criss and Jeff Trondsen at Cornell University. Many thanks to graduate students Kyoung Jo Oh and Yeong Joon Yoon who developed much of the content used in this tool.

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