Towards Physiologically-Responsive Interactive Garments with Machine Learning Techniques
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Authors
Armstrong, Victoria
Date
Type
thesis
Language
eng
Keyword
human computer interaction , interactive garments , machine learning , artificial intelligence , wearables
Alternative Title
Abstract
Emotional experiences shape our lives every day. Negative emotions can impact not only our mood but also our biological signals, overall health, and wellness, especially if they are not addressed. Emotion-regulation and self-care techniques, such as meditation and exercise, can help to alleviate these emotions, but we have to remember to actively engage in them. Compression applied to the body, called Deep Pressure Stimulation, has also been shown to help suppress reactions from our nervous system under stress. In this work, we address the challenges of emotion regulation when experiencing negative emotions while doing desk work. To accomplish this, we custom-built two interactive jackets that have a removable, embedded microcontroller, sensors, and airbags. The airbags are used to apply compression to the sides when a user presses a button. 12 participants interacted with the jackets during a user study and were interviewed after. Data collected from 8 of these 12 participants during the user study was used to train 3 machine learning models: Logistic Regression, Support Vector Machine and XGBoost. Over 4 different testing conditions, XGBoost proved to be an efficient and effective predictor of when users choose to turn on the pump. Coupled with interview data from participants exploring desires for slow interfaces and automatic actuation, we have established a foundation for individualized interactive garment analytics using customized models for affect prediction.
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Queen's University's Thesis/Dissertation Non-Exclusive License for Deposit to QSpace and Library and Archives Canada
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Copying and Preserving Your Thesis
This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.
ProQuest PhD and Master's Theses International Dissemination Agreement
Intellectual Property Guidelines at Queen's University
Copying and Preserving Your Thesis
This publication is made available by the authority of the copyright owner solely for the purpose of private study and research and may not be copied or reproduced except as permitted by the copyright laws without written authority from the copyright owner.