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Development of Self-Calibrating Sensor Footwear and Relevance of In-Shoe Characterization on Accurate Plantar Pressure Distribution Measurements.

Authors :
Martinez-Barba, Daniel A.
Martinez-Manuel, Rodolfo
Daza-Benitez, Leonel
Vidal-Lesso, Agustin
Source :
IEEE Sensors Journal; 3/15/2021, Vol. 21 Issue 6, p8421-8431, 11p
Publication Year :
2021

Abstract

In this article we present a self-calibrating sensor-footwear for plantar pressure distribution measurements; the self-calibrating process is implemented to adapt the force measurement range (FMR) to the weight of the user; four FMRs were generated, 0 – 25 N, 0 – 50 N, 0 – 100 N and 0 – 200 N. This self-calibrating step improves the force resolution for each individual using the proposed system. We also demonstrate that, even when normally not considered in literature, the response of each sensor to the applied pressure is different along the footwear due to its natural difference between the sole sections, back, middle and front. Furthermore, the implemented sensors were characterized and a coefficient of variation (CV) of 2.62 % was obtained before installing the sensors in the sensor-footwear, and a CV of 16.61 % was generated when the sensors were installed in the sensor-footwear. In order to overcome these differences in response, we propose and demonstrate that in-shoe characterization of all sensors allows removing the inherent difference in sensor response; which also contribute to obtain absolute force values from all sensors. In addition, an algorithm to obtain the gait-area of interest from the acquired sensing signal is proposed. The presented sensor-footwear, used for Plantar Pressure Distribution (PPD) measurement, communicates through a wireless local area network allowing real time PPD visualization and recording intended for indoor testing. Design, construction, characterization and implementation of the proposed sensor-footwear are presented; demonstrating the importance of the in-shoe characterization for a sensor-footwear system. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
1530437X
Volume :
21
Issue :
6
Database :
Complementary Index
Journal :
IEEE Sensors Journal
Publication Type :
Academic Journal
Accession number :
148969789
Full Text :
https://doi.org/10.1109/JSEN.2020.3048611