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Title Study of 3D printed piezoresistive sensors for smart insole applications
Author Μαρή, Βερενίκη
Thesis advisor Ηλιόπουλος, Ελευθέριος
Πανταζής, Αλέξανδρος
Abstract Gait analysis, or the study of human and animal locomotion has been the object of various studies for hundreds of years. Since the first proposal for a scientific description of gait analysis by Galileo in 1680, gait analysis has been used in medicine to study not only the physics of the human body movement but to also pinpoint potential pathological reasons altering the gait and stance. Advancements in technology including wearable sensors and podographs offer a detailed and precise analysis of each subphase of the gait cycle and thus provide diagnosticians with more precise and accurate results faster Additive manufacturing is the process of creating a three-dimensional structure by adding layers of material instead of subtracting. 3D printing, aided by specialized software, allows the user to create intricate and precise designs at a low cost and fast rate, in a controlled environment. Additive manufacturing, with recent advances in technology that made the creation of flexible, conductive and even biocompatible filaments possible has become a valuable tool in a variety of fields, from engineering to medicine. In this study, the goal is to develop a set of 3D printed piezoresistive sensors for further applications in entirely 3d printed smart insoles. The study itself, consists of not only designing, but also testing the piezoresistive properties and the sensitivity to environmental changes of three flexible conductive filaments. In the first part of the thesis, a brief history of gait analysis and additive manufacturing is presented, along with their importance in developing wearable sensors and specifically smart insoles for diagnostic applications. The printers and filaments utilized in this experiment, along with the geometric characteristics of the sensors, are described in Section 2: Materials and Methods. Furthermore, a detailed description of the gait simulator set-up and the process of calibrating the set up and preparing the samples for testing is described in detail. In the last part of the section, the data collection process along with explanatory figures is presented. The Data collection section, contains the collective tables containing data for both the original and the measurements related to testing the aging of the samples The 4th part of this study is dedicated to data analysis. First, the formulas used to transform the weight applied and the resistance value units to pressure and Ohm respectively are presented. The data analysis process is described, along with the resulting figures which illustrate the results for how the resistance of each sample changes with different amounts of pressure applied. In order to conclude which sample has the highest sensitivity the graphs were fitted using tools provided by Origin. The process of reaching a conclusion concerning the optimal sensor is described in detail and accompanied by the formulas utilized. Lastly, figures showcasing how the resistance of each sample changes when exposed to different humidity percentages and temperatures as time passes accompanied by the conclusion that derives from figure comparison is presented. In the two final sections, the collective results indicating both the sensitivity of the sensors to pressure changes and environmental factors are compared and discussed in order to reach a conclusion as to which filament and sensor design is optimal and could potentially be utilized in smart insole applications. Furthermore, a review of the whole experimentation and analysis process, including difficulties and figures showcasing errors presented in the duration of the experiment is given along with the results of real time experimentation with the sensors placed inside a 3D printed insole. Eventually, the conclusion that derives from this study is that 3D printed piezoresistive sensors seem to be unsuitable for smart insole applications due to both their sensitivity to changes in humidity and temperature but also due to the instability in the resistance of each sample even in a relaxed state since the differentiation of which resistance changes occur due to an alteration in the wearer’s gait cycle and which are a result of sensor sensitivity compromission is almost impossible. Finally, a list of references is included while in the appendix section the collective tables for the resistance values obtained during the data collection process for each sensor are presented.
Language English
Issue date 2022-11-25
Collection   School/Department--School of Sciences and Engineering--Department of Physics--Graduate theses
  Type of Work--Graduate theses
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