A Reference Data Set for the Study of Healthy Subject Gait with Inertial Measurements Units
Cyril Voisard, Nicolas de l’Escalopier, Albane Moreau, Alienor Vienne-Jumeau, Damien Ricard, Laurent Oudre
published
2023-12-08
reference
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

Communicated by Charles Truong and Miguel Colom
Demo edited by Miguel Colom and Cyril Voisard

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].

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