2023

Scientific Data

A dataset of asymptomatic human gait and movements obtained from markers, IMUs, insoles and force plates

Gautier Grouvel, Lena Carcreff, Florent Moissenet, Stéphane Armand

Kinesiology Laboratory, Geneva University Hospitals and University of Geneva, Geneva, Switzerland

Keywords

gait, motion caputre, imu, sensor insoles, squats

Abstract

Human motion capture and analysis could be made easier through the use of wearable devices such as inertial sensors and/or pressure insoles. However, many steps are still needed to reach the performance of optoelectronic systems to compute kinematic parameters. The proposed dataset has been established on 10 asymptomatic adults. Participants were asked to walk at different speeds on a 10-meters walkway in a laboratory and to perform different movements such as squats or knee flexion/extension tasks. Three-dimensional trajectories of 69 reflective markers placed according to a conventional full body markerset, acceleration and angular velocity signals of 8 inertial sensors, pressure signals of 2 insoles, 3D ground reaction forces and moments obtained from 3 force plates were simultaneously recorded. Eight calculated virtual markers related to joint centers were also added to the dataset. This dataset contains a total of 337 trials including static and dynamic tasks for each participant. Its purpose is to enable comparisons between various motion capture systems and stimulate the development of new methods for gait analysis.

Moticon's Summary

In this paper the authors aimed to establish a dataset for the evaluation of wearable motion capture systems. For this purpose, the authors carried out gait measurements using wearable IMUs, Moticon sensor insoles and force plates as well as marker-based motion capture on asymptomatic participants. With this work the authors introduced a dataset of over 300 trials which can be used for comparisons in the evaluation of motion capture systems for gait analysis.

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