This article thoroughly describes a data set of 1020 multivariate gait signals collected with two inertial measurement units, from 230 subjects undergoing a fixed protocol: standing still, walking 10 m, turning around, walking back and stopping. In total, 8.5 h of gait time series are distributed. The measured population was composed of healthy subjects as well as patients with neurological or orthopedic disorders. An outstanding feature of this data set is the amount of signal metadata that are provided. In particular, the start and end time stamps of more than 40,000 footsteps are available, as well as a number of contextual information about each trial. This exact data set was used in [Oudre et al., Template-based step detection with inertial measurement units, Sensors 18, 2018] to design and evaluate a step detection procedure.
Source CodeThe source code contains the signals and metadata of the data set described in this article, and is available on this web page 1 . Usage instructions are included in the README.txt file of the archive. Additional functions to load and manipulate the data (in Python and R) are provided on a separate repository 2 .