Feet first: Developing instrumented insoles to prove association between weight bearing and foot pain

Author: 
Date created: 
2019-12-06
Identifier: 
etd20607
Keywords: 
Activity Classification
Machine Learning
Force Sensors
Plantar Fasciitis
Smart Insole
Workplace Injury
Abstract: 

It is commonly thought that more time spent weight bearing at work increases the risk of developing plantar fasciitis, a condition causing pain on the bottom of the foot. This link is not recognized by workers compensation boards because the methods used by researchers to determine workers activities lack sufficient objectivity. This work aimed to solve this problem by developing a prototype of a low-cost smart shoe insole capable of accurately recording workplace activities. This device was implemented in a variety of workplaces to collect information about 34 worker’s activities over the course of 3-5 days. An algorithm was developed to classify sitting, standing and walking with an accuracy of 99.3% and analysis showed the time spent standing throughout the workday was correlated with the presence of foot pain. This work lays the foundation for a large population study to provide the objective results needed to change workplace policies.

Document type: 
Thesis
Rights: 
This thesis may be printed or downloaded for non-commercial research and scholarly purposes. Copyright remains with the author.
File(s): 
Supervisor(s): 
Carolyn Sparrey
Department: 
Applied Sciences: School of Mechatronic Systems Engineering
Thesis type: 
(Thesis) M.A.Sc.
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