[IPOL announce] new article: A Reference Data Set for the Study of Healthy Subject Gait with Inertial Measurements Units

[announcements about the IPOL journal]

A new article is available in IPOL: https://www.ipol.im/pub/art/2023/497/

Cyril Voisard, Nicolas de l’Escalopier, Albane Moreau, Alienor 
Vienne-Jumeau, Damien Ricard, and Laurent Oudre,
A Reference Data Set for the Study of Healthy Subject Gait with Inertial 
Measurements Units,
Image Processing On Line, 13 (2023), pp. 314–320.
https://doi.org/10.5201/ipol.2023.497

Abstract
This article provides a comprehensive description of a dataset 
consisting of 110 multivariate gait signals collected using three 
inertial measurement units. The data was obtained from a sample of 19 
healthy subjects who followed a predefined protocol: standing still, 
walking 10 meters, turning around, walking back, and stopping. One 
notable aspect of this dataset is the inclusion of extensive signal 
metadata, including the start and end timestamps of each footstep, along 
with contextual information for each trial. Part of this dataset was 
previously used to develop and assess a gait event detection algorithm 
[Voisard et al., Automatic Gait Events Detection with Inertial 
Measurement Units: Healthy Subjects and Moderate to Severe Impaired 
Patients], and as a reference for a multidimensional tool in gait 
quantification [Voisard et al., Innovative Multidimensional Gait 
Evaluation using IMU in Multiple Sclerosis: introducing the Semiogram].