Smart algorithm for plantar pressure classification and redistribution in wearable device based on machine learning techniques

Ntella, Sofia LydiaPerriard, YvesCouyoupetrou, Julien2022-03-222022-03-222021-01-14https://infoscience.epfl.ch/handle/20.500.14299/186525This document presents the choice and the optimization of a supervised classification algorithm, applied on plantar pressure measurements. Its purpose is to classify, based on pressure data coming from a smart insole, whether the user has risks of foot ulceration or not. The end goal is to implement this algorithm in a smart insole developed at LAI. The insole is able to perform weight redistribution to correct the abnormal plantar pressures measured on diabetic patients using actuators based on magneto-rheological fluids. Different algorithms are trained, optimized and evaluated using a dataset containing plantar pressure measurements of healthy subjects and of diabetic patients considered as ulceration risky. Then, possible weight redistribution strategies are explored for each algorithm.Smart algorithm for plantar pressure classification and redistribution in wearable device based on machine learning techniquesstudent work::master thesis