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Rehabilitation Dataset Directory: Dataset Profile
Dataset: Retraining Walking Over Ground in a Powered Exoskeleton After Spinal Cord Injury ()
Basic Information | |
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Dataset Full Name | Retraining Walking Over Ground in a Powered Exoskeleton After Spinal Cord Injury |
Dataset Acronym | |
Summary | The Retraining Walking Over Ground in a Powered Exoskeleton After Spinal Cord Injury is a mixed-methods study using both observation and interviews. It was designed to determine quantitative and qualitative outcomes in a cohort of individuals with chronic, spinal cord injury, who learned to use the ReWalk exoskeleton to walk. Researchers determined the training dosage required for walking proficiency, the sensory and motor changes in the nervous system with the training, and the perspectives of the participants with respect to both the training and the device. It was a prospective cohort study with measures taken before, during, immediately after training, and 2-3 months after training was completed. |
Key Terms | Spinal Cord Injury (SCI), Rehabilitation, Assistive devices |
Study Design | Longitudinal |
Data Type(s) |
Clinical Survey |
Sponsoring Agency/Entity | Craig H. Neilsen Foundation (SCIRTS-2015), Alberta Spinal Cord Injury Research Fund |
Health Conditions/Disability Measures |
Health Condition(s) | Spinal Cord Injury (SCI) |
Disability Measures | Ambulatory disability, Special equipment use/assistive technology Scales used: Physiological Cost Index; International Standards for Neurological Classification of Spinal Cord Injury; Spinal Cord Assessment Tool for Spasticity (SCATS); McGill Pain Questionnaire Rating Index |
Measures/Outcomes of Interest |
Topics | Wheelchair use, Walking speed (over 10 meters), Walking distance (6 min walking test), Manual muscle strength, Spasticity (Spinal Cord Assessment Tool for Spasticity- SCATS), Neuropathic pain |
Sample |
Sample Population | Individuals with severe spinal cord injury who resided, or maintained
temporary residence for the purpose of the study, in Edmonton, Alberta, Canada.
Further criteria required at least one year since qualifying injury; wheelchair
use as primary mode of locomotion; and sufficient arm strength to control
forearm crutches. |
Sample Size/Notes | 12 participants |
Unit of Observation | Individual/Patient |
Continent(s) | North America |
Countries | Canada |
Geographic Coverage | Edmonton, Alberta, Canada. |
Geographic Specificity | NA |
Data Collection |
Data Collection Mode | Observation and interviews |
Years Collected | 2014-18 |
Data Collection Frequency | Measures were taken at four points in time (relative to training):
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Strengths and Limitations |
Strengths |
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Limitations |
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Data Details |
Primary Website | |
Data Access | |
Data Access Requirements | Restricted use: Researchers must agree to the terms and conditions of a Restricted Data Use Agreement in accordance with existing ICPSR servicing policies. |
Summary Tables/Reports | NA |
Data Components | DS1: Training Measures and Outcomes Data: Comprised of 31 files including 14 spreadsheets containing participant metrics in relation to the study task. An additional 17 files providing explanatory documentation in support of the spreadsheets:
DS2: Participant Interview Data: 29 files, comprised of 28 interview transcripts and a file provides explanatory documentation in support of the interview transcripts:
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Selected Papers |
Other Papers | |
Technical | https://www.icpsr.umich.edu/web/ADDEP/studies/37983/datadocumentation |
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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).
Other CLDR supported resources and collaborative opportunities:
- Archive of Data on Disability to Enable Policy and research (ADDEP)
- Data Sharing & Archiving at CLDR
- Pilot Project Program
- Visiting Scholars Program
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.
For questions or comments please contact disabilitystatistics@cornell.edu