Gait in Aging and Disease Database

This "mini-collection" of human gait data was constructed as a teaching resource for an intensive course ("The Modern Science of Human Aging", conducted at MIT in October, 1999 under the auspices of NECSI). As such, this specific collection is not intended for basic research or publications. It may be useful, however, in other classroom or tutorial settings, and for self-guided explorations into the world of biologic complexity.

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.

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 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:

Old Parkinson’s Young
o1_76_si.str pd1_si.str y1_23_si.str
o1_76_si.hea pd1_si.hea y1_23_si.hea
o2_74_si.str pd2_si.str y2_29_si.str
o2_74_si.hea pd2_si.hea y2_29_si.hea
o3_75_si.str pd3_si.str y3_23_si.str
o3_75_si.hea pd3_si.hea y3_23_si.hea
o4_77_si.str pd4_si.str y4_21_si.str
o4_77_si.hea pd4_si.hea y4_21_si.hea
o5_71_si.str pd5_si.str y5_26_si.str
o5_71_si.hea pd5_si.hea y5_26_si.hea

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.

The following references may be of interest:

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.

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Updated Tuesday, 18-Oct-2016 23:00:17 CEST

PhysioNet is supported by the National Institute of General Medical Sciences (NIGMS) and the National Institute of Biomedical Imaging and Bioengineering (NIBIB) under NIH grant number 2R01GM104987-09.