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Technical Brief

A Force-Sensing Insole to Quantify Impact Loading to the Foot

[+] Author and Article Information
Ishan Acharya

Department of Mechanical Engineering, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4L7
acharyi@mcmaster.ca

John Van Tuyl

Department of Mechanical Engineering, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4L7
jtvantuyl@gmail.com

Julia de Lange

School of Biomedical Engineering, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4L7
delangej@mcmaster.ca

Cheryl Quenneville

Department of Mechanical Engineering, JHE 316, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada, L8S 4L7; School of Biomedical Engineering, McMaster University, 1280 Main Street West, Hamilton, Ontario, Canada L8S 4L7
quennev@mcmaster.ca

1Corresponding author.

ASME doi:10.1115/1.4041902 History: Received July 15, 2017; Revised October 15, 2018

Abstract

Lower leg injuries commonly occur in frontal automobile collisions, and are associated with high disability rates. Accurate methods to predict these injuries must be developed to facilitate the testing and improvement of vehicle safety systems. Anthropomorphic Test Devices (ATDs) are often used to assess injury risk by mimicking the behavior of the human body in a crash while recording data from sensors at discrete locations, which are then compared to established safety limits developed by cadaveric testing. Due to the difference in compliance of cadaveric and ATD legs, the force dissipating characteristics of footwear, and the lack of direct measurement of injury risk to the foot and ankle, a novel instrumented insole was developed that could be applied equally to all specimens both during injury limit generation and during safety evaluation tests. An array of piezoresistive sensors were calibrated over a range of speeds using a pneumatic impacting apparatus, and then applied to the insole of a boot. The boot was subsequently tested and compared to loads measured using ankle and toe load cells in an ATD, and found to have an average error of 10%. The sensors also provided useful information regarding the force distribution across the sole of the foot during an impact, which may be used to develop regional injury criteria. This work has furthered the understanding of lower leg injury prediction and developed a tool that may be useful in developing accurate injury criteria in the future for the foot and lower leg.

Copyright (c) 2018 by ASME
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