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Data sets of gait time series
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Data sets for the study of human locomotion with inertial measurements units

The data provided in this repository are described in the following article:

  • Charles Truong, Rémi Barrois-Müller, Thomas Moreau, Clément Provost, Aliénor Vienne-Jumeau, Albane Moreau, Pierre-Paul Vidal, Nicolas Vayatis, Stéphane Buffat, Alain Yelnik, Damien Ricard, and Laurent Oudre, A Data Set for the Study of Human Locomotion with Inertial Measurements Units, Image Processing On Line, 9 (2019), pp. 381–390.

Please cite this article whenever you want to make a reference to this data set.

A simple online exploration tool is available online. Data can be downloaded as a zipped archive (, ~200MB):

Once extracted, the data can be read using the following code snippets (in Python, R). Be sure to execute those lines while in the same directory as the extracted GaitData folder.


Signals are loaded into Pandas data frames. Please be sure to have it installed (pip install pandas).

from load_data import get_code_list, load_trial, load_metadata

# Load and manipulate all signals and metadata.
all_codes = get_code_list()
print("There are {} trials.".format(len(all_codes)))
for code in all_codes:
    signal = load_trial(code)  # pandas data frame
    metadata = load_metadata(code)  # dictionary
    # Do something.
    # ...


Be sure to set the working directory (with the function setwd) to wherever the data file has been unzipped. To read JSON files, the package jsonlite must be installed.

code_list <- fromJSON("code_list.json")

for(code in code_list){
    signal <- read.csv(paste(code, ".csv", sep=""))
    metadata <- fromJSON(paste(code, ".json", sep=""))
    # Do something.
    # ...
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