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Real-life Measurement of Tri-axial Walking Ground Reaction Forces using Optimal Network of Wearable Inertial Measurement Units

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posted on 2018-05-10, 14:27 authored by E. Shahabpoor, A. Pavic, J. Brownjohn, S. Billings, L.-Z. Guo, Mateusz Bocian
Monitoring natural human gait in real-life environment is essential in many applications including quantification of disease progression, and monitoring the effects of treatment and alteration of performance biomarkers in professional sports. Nevertheless, reliable and practical techniques and technologies necessary for continuous real-life monitoring of gait is still not available. This paper explores in detail the correlations between the acceleration of different body segments and walking ground reaction forces GRF( t )in three dimensions and proposes three sensory systems, with one, two and three inertial measurement units (IMUs), to estimate GRF( t )in the vertical (V), medial-lateral (ML) and anterior-posterior (AP) directions. The NARMAX non-linear system identification method was utilized to identify the optimal location for IMUs on the body for each system. A simple linear model was then proposed to estimate GRF( t )based on the correlation of segmental accelerations with each other. It was found that, for the three-IMU system, the proposed model estimatedGRF( t )with average peak-to-peak normalized root mean square error (NRMSE) of 7%, 16% and 18% in V, AP and ML directions, respectively. With a simple subject-specific training at the beginning, these errors were reduced to 7%, 13% and 13% in V, AP and ML directions, respectively. These results were found favorably comparable with the results of the benchmark NARMAX model, with subject-specific training, with 0% (V), 4% (AP) and 1% (ML) NRMSE difference.

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Citation

IEEE Transactions on Neural Systems and Rehabilitation Engineering, 2018

Author affiliation

/Organisation/COLLEGE OF SCIENCE AND ENGINEERING/Department of Engineering

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  • VoR (Version of Record)

Published in

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Publisher

Institute of Electrical and Electronics Engineers

issn

1534-4320

eissn

1558-0210

Copyright date

2018

Available date

2018-05-10

Publisher version

https://ieeexplore.ieee.org/document/8353848/

Language

en

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