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Pubmed for Handhelds

PUBMED FOR HANDHELDS

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  • Title: Walking Gait Step Length Asymmetry Induced by Handheld Device.
    Author: Abid M, Renaudin V, Aoustin Y, Le-Carpentier E, Robert T.
    Journal: IEEE Trans Neural Syst Rehabil Eng; 2017 Nov; 25(11):2075-2083. PubMed ID: 28541210.
    Abstract:
    The modeling and feature extraction of human gait motion are crucial in biomechanics studies, human localization, and robotics applications. Recent studies in pedestrian navigation aim at extracting gait features based on the data of low-cost sensors embedded in handheld devices, such as smartphones. The general assumption in pedestrian dead reckoning (PDR) strategy for navigation application is that the presence of a device in hand does not impact the gait symmetry and that all steps are identical. This hypothesis, which is used to estimate the traveled distance, is investigated in this paper with an experimental study. Ten healthy volunteers participated in motion lab tests with a 0.190 kg device in hand. Several walking trials with different device carrying modes and several gait speeds were performed. For a fixed walking speed, it is shown that the steps differ in their duration when holding a mass equivalent to a smartphone mass, which invalidates classical symmetry hypothesis in the PDR step length modeling. It is also shown that this hypothesis can lead to a 2.5% to 6.3% error on the PDR estimated traveled distance for the different walking trials.
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