Rehabilitation Dataset Directory: Dataset Profile

The Stroke Initiative for Gait Data Evaluation (STRIDE) is an initiative based at the University of Southern California to create an inter-institutional, public database containing de-identified demographic and kinematic, kinetic, and spatiotemporal measures assessed via gait analysis in individuals post-stroke, to provide a larger and more heterogeneous research dataset than that typically amassed at a single institution. The purpose of the study was to understand how persons post-stroke generate symmetric steps and how the resulting gait pattern relates to the metabolic cost of transport. Data was collected at the following institutions: Johns Hopkins University, University of Southern California, University of Pittsburgh and Emory University.

55 persons post-stroke walked on an instrumented treadmill under two conditions: preferred walking and symmetric stepping (using visual feedback). Kinematic and kinetic data was collected during both conditions via three-dimensional motion capture, as well as metabolic data.

The data in STRIDE can be used to run pilot analyses and power calculations for research studies, design and validate statistical models to test associations between gait variables, provides data for simulation-based biomechanical studies in stroke, and provides data to assess the reproducibility of research findings.

Gait, Locomotion, Physical rehabilitation, Stroke, Treadmill, Walking, Gait, Motion capture

National Institutes of Health (NIH)

Stroke

Ambulatory disability

Berg balance score (BBS), Lower extremity Fugl-Meyer score (out of 34 possible points)

Walking stride, Gait, Treadmill, Motion capture, Kinematic (100 Hz) and kinetic (1000 Hz) data, three-dimensional motion capture, Visual3D, Metabolic cost of transport

Survivors of a first, unilateral stroke between 18 and 90 years of age across the United States who are able to walk on a treadmill for more than 2 minutes

55 persons 

Individual/Patient

North America

United States

• Johns Hopkins University, Baltimore MD
  
• University of Southern California
• University of Pittsburgh, PA
• Emory University, Atlanta, GA

Data files broken down by location (see above)

Clinical/experimental

2012-20

NA

Extensive motion capture time series data available for each subject's step. Consistent "Core" of data collected across all 4 sites.

Limited documentation. Variation in content by location - some include additional data files that others don't have. Single participant data are presented in individual folders. Each participant's data broken into separate limb measures - up to 15 datafiles per individual.

https://www.icpsr.umich.edu/web/ICPSR/studies/38002# 

https://www.icpsr.umich.edu/web/ICPSR/studies/38002# 

Data Use agreement, No cost

NA

Example file structure for Subject 1 (S1) from Johns Hopkins University (JHU), 2019.

Separate folder for each subject

• Subject demographics, scores etc.
  • JHU_2019_s1_Demo.csv
• Ground reaction forces (GRF) timeseries in Newtons, for paretic (P) or non-paretic (NP) extremity
• • JHU_2019_s1_vert_GRF_NP.csv         Vert (vertical direction) 
  • JHU_2019_s1_vert_GRF_P.csv
  • JHU_2019_s1_AP_GRF_NP.csv         Fore-aft direction
  • JHU_2019_s1_AP_GRF_P.csv
  • JHU_2019_s1_ML_GRF_NP.csv         ML (medio-lateral direction)
  • JHU_2019_s1_ML_GRF_P.csv
• Stance and swing times in seconds (each row is a different stride)
  • JHU_2019_s1_StanceTime_NP.csv Stance  times 
  • JHU_2019_s1_StanceTime_P.csv
  • JHU_2019_s1_SwingTime_NP.csv         Swing times
  • JHU_2019_s1_SwingTime_P.csv
• Step lengths in meters (each row is a different stride)
  • JHU_2019_s1_StepLength_NP.csv
  • JHU_2019_s1_StepLength_P.csv

• Stroke Recovery in Underserved Populations 2005-2006 (SRUP)
• Anatomical Tracings of Lesions after Stroke (ATLAS)
• Medical University of South Carolina Stroke Data (ARRA)
• Investigating the Neurobiologic Basis for Loss of Cortical Laterality in Chronic Stroke Patients, Charleston, South Carolina, 2014-2016

Johns Hopkins University data:

Persons post-stroke restore step length symmetry by walking asymmetrically

https://www.biorxiv.org/content/10.1101/799775 

University of Pittsburgh data:

Self-selected step length asymmetry is not explained by energy cost minimization in individuals with chronic stroke.

https://pubmed.ncbi.nlm.nih.gov/32847596/ 

Cerebral Contribution to the Execution, But Not Recalibration, of Motor Commands in a Novel Walking Environment

https://pubmed.ncbi.nlm.nih.gov/32001549/ 

Augmenting propulsion demands during split-belt walking increases locomotor adaptation of asymmetric step lengths

https://pubmed.ncbi.nlm.nih.gov/32493440/ 

University of Southern California data:

Using biofeedback to reduce spatiotemporal asymmetry impairs dynamic balance in people post-stroke

https://journals.sagepub.com/doi/abs/10.1177/15459683211019346 

Individual Differences in Locomotor Function Predict the Capacity to Reduce Asymmetry

https://journals.sagepub.com/doi/10.1177/1545968318787913 

See "ReadMe" metadata text file (contained within each participating site's downloadable ZIP data file.)

• AphasiaBank