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    A low-cost wireless system of inertial sensors to postural analysis during human movement


    Santos, Talysson M.O. and Barroso, Márcio F.S. and Ricco, Rodrigo A. and Nepomuceno, Erivelton and Alvarenga, Érika L.F.C. and Penoni, Álvaro C.O. and Santos, Ana F. (2019) A low-cost wireless system of inertial sensors to postural analysis during human movement. Measurement, 148 (106933). pp. 1-10. ISSN 0263-2241

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    Abstract

    The dynamics of the human body has generated considerable recent research interest among scientist devoted to reducing the number of injuries and for performance improvement. In these studies, the investigation is usually addressed by means of commercial devices based on video recordings. However, these systems based on video recordings are usually expensive and require suitable laboratories for their use, which makes it unfeasible to collect data for activities outside controlled environments. In this work, we have shown that it is possible to present similar results with a much lower sampling rate, focusing on the evaluation of minimum and maximum values of the gait. As a result, it has been possible to develop a wearable, compact, portable, low-cost, wireless and embedded system to simultaneously analyze the three-dimensional angular position in eight points. This technology can be used in many sorts of environments. It is also possible to access information in real time with reliable and accurate measurements by means of simple modelling for the use of fusion techniques implemented in the microcontroller. Tests were conducted to evaluate the metrological characteristics of the system using the Complementary Filter (CF) and the Kalman Filter (KF). An algorithm of evolutionary strategies tuned both filters, providing errors of less than 5% for static situations in the measurement of the angular position over the entire system utilization range. Our results have been compared with the commercial system Qualisys Motion-Capture. The statistical method elaborated by Bland and Altman has been used. We have found our method yields a motion analyses in good agreement with results using post-processed video.

    Item Type: Article
    Keywords: Bio-mechanics; Human movements; Kinematics; Gait analysis; Inertial sensors; Complementary filter; Kalman filter; Wireless sensor network;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 16741
    Identification Number: https://doi.org/10.1016/j.measurement.2019.106933
    Depositing User: Erivelton Nepomuceno
    Date Deposited: 22 Nov 2022 15:02
    Journal or Publication Title: Measurement
    Publisher: Elsevier
    Refereed: Yes
    URI:

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