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A Simulation-based Approach to Generate Walking Gait Accelerations for Pedestrian Navigation Solutions

Abstract : In indoor environments, pedestrian dead reckoning (PDR) is the most used strategy for pedestrian position estimation from inertial data collected with handheld devices. PDR process recursively estimates positions using step length estimation based on parametric models that take into consideration some physiological parameters, displacement features and acceleration statistical properties. The coefficients of these models need frequent adjustment to limit cumulative errors induced by alteration of gait pattern. A large experimental database providing information about human locomotion variability is required for this calibration. However, the development of such database is costly in terms of time and effort. To make the collected data as reliable as possible, several gait-affecting factors should be considered, which highly increases the number of measurement trials. In this paper, we propose an alternative way of generating locomotion data that consists in simulating human walking gait motion under different conditions. We propose a multibody system simulator taking into account possible step-level asymmetry induced by handling a device in hand, as well as the correlation between arms and legs motions during gait. Our simulation approach was evaluated with data from overground walking experiments on one test subject. Preliminary results show some similarities between acceleration profiles related to different body parts, and the same variation trends of selected acceleration items in function of carrying mode and gait velocity.
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Submitted on : Thursday, February 14, 2019 - 9:14:38 AM
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Mahdi Abid, Valérie Renaudin, Thomas Robert, Yannick Aoustin, Eric Le Carpentier. A Simulation-based Approach to Generate Walking Gait Accelerations for Pedestrian Navigation Solutions. 9th International Conference on Indoor Positioning and Indoor Navigation (IPIN 2018), Sep 2018, Nantes, France. pp.24-27, ⟨10.1109/IPIN.2018.8533858⟩. ⟨hal-01997361⟩



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