Gait in Aging and Disease Database

@article{pollard_physionet_2026, title = {{PhysioNet} as a global platform for biomedical research}, volume = {1}, issn = {3005-0693}, url = {https://doi.org/10.1038/s44360-026-00096-z}, doi = {10.1038/s44360-026-00096-z}, abstract = {Twenty-five years after its first public repository was established, the PhysioNet resource for biomedical and clinical data has enabled tens of thousands of research papers. Further efforts are ongoing to advance secure data sharing, community engagement and scalable research infrastructure.}, number = {8}, journal = {Nature Health}, author = {Pollard, Tom and Moody, Benjamin E. and Lehman, Li-wei H. and Gow, Brian J. and Fernandes, Chrystinne and Xie, Chen and Johnson, Alistair and Mark, Roger G. and Heldt, Thomas}, month = aug, year = {2026}, pages = {792--795},}

Data Description

Walking stride interval time series included are from 15 subjects: 5 healthy young adults (23 - 29 years old), 5 healthy old adults (71 - 77 years old), and 5 older adults (60 - 77 years old) with Parkinson's disease. The file name indicates old (o), young (y) or Parkinson's disease (pd). For the old and young subjects, the age (in years) is also included in the filename.

Subjects walked continuously on level ground around an obstacle-free path. The stride interval was measured using ultra-thin, force sensitive resistors placed inside the shoe. The analog force signal was sampled at 300 Hz with a 12 bit A/D converter, using an ambulatory, ankle-worn microcomputer that also recorded the data. Subsequently, the time between foot-strikes was automatically computed. The method for determining the stride interval is a modification of a previously validated method that has been shown to agree with force-platform measures, a “gold” standard.

Data were collected from the healthy subjects as they walked in a roughly circular path for 15 minutes, and from the subjects with Parkinson’s disease as they walked for 6 minutes up and down a long hallway.

Files

You may download gait-data.tar (150K), a UNIX tar archive of this entire mini-collection, also available in gzip-compressed form as gait-data.tar.gz ( 47K). (WinZip users, please read this important note.) If you prefer, you may download individual text recordings.

For each subject, two columns of data are included. The first column is time (in seconds) and the second is the stride interval (variously known as stride time, gait cycle duration, and time between successive heel strikes of the same foot).

The same data are also available as standard PhysioBank-format annotation (.str) and header (.hea) files, for viewing or analysis using PhysioToolkit software from this site.

References

JM Hausdorff, PL Purdon, CK Peng, Z Ladin, JY Wei, AL Goldberger. Fractal dynamics of human gait: stability of long-range correlations in stride interval fluctuations. J Appl Physiol 80:1448-1457, 1996.

JM Hausdorff, SL Mitchell, R Firtion, CK. Peng, ME Cudkowicz, JY Wei and AL Goldberger. Altered fractal dynamics of gait: reduced stride interval correlations with aging and Huntington's disease. J Appl Physiol 82:262-269, 1997.

JM Hausdorff, ME Cudkowicz, R Firtion, JY Wei, AL Goldberger. Gait variability and basal ganglia disorders: stride-to-stride variations of gait cycle timing in Parkinson's and Huntington's disease. Mov Disord 13:428-437, 1998.

On the Reylab web site, a mini-tutorial, including an introduction to this database, is available. For further information, please contact JM Hausdorff.

Cited by

6 publications cite this project. The most recent are listed below.

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• PyBioS: A freeware computer software for analysis of cardiovascular signals
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• Unified Wavelet Transform Analysis Adapted to Different Biomedical Applications
  Girisha Garg, Vijander Singh. IGI Global eBooks, 2017.
• Unified Wavelet Transform Analysis Adapted to Different Biomedical Applications
  Girisha Garg, Vijander Singh. Advances in data mining and database management book series, 2016.
• Assessment of gait nonlinear dynamics by inhomogeneous point-process models
  Gaetano Valenza, Luca Citi, Riccardo Barbieri. Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 2014.

View all 6 publications

Citation data from OpenAlex. Papers that use the project without citing it may be missing.