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Dissertation
On the Real-World Interactivity Potential of Minimalistic Knitted Sensors at the Intersection of Artificial Intelligence and User Experience
Doctor of Philosophy (Ph.D.), Drexel University
Dec 2021
DOI:
https://doi.org/10.17918/00000901
Abstract
Recent work has demonstrated the feasibility of producing knitted capacitive touch sensors through digital fabrication, which rely on a single conductive yarn and two external connections. This technique increases these sensors' robustness and usability, while shifting the complexity of enabling interactivity from the hardware to computational models. The application of algorithmic and artificial intelligence models to these novel pervasive technologies is key to unfolding their potential, particularly when real-world and user experience considerations are also included. To bring this technology closer to real-world use, this dissertation goes beyond previous work on coarse touch discrimination, to enable fine, accurate touch localization and complex gesture recognition on these low-profile knitted sensors. Deep learning and algorithmic models are presented to analyze noisy time-series signal data, which are able to capture the temporal behavior of the sensors and extract relevant local features. Furthermore, several user studies are conducted to train these models, demonstrate their generalizability with new users, and investigate their robustness when exposed to everyday use events. To start shaping the future of touch-sensitive fabric technology according to user expectations and everyday use scenarios, through a formative focus group study, users' views of these fabrics are also explored in different contexts. The contributions of this work set the foundations for creating pervasive interactive systems powered by artificial intelligence models that use minimalistically-designed knitted sensors as an input medium.
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Details
- Title
- On the Real-World Interactivity Potential of Minimalistic Knitted Sensors at the Intersection of Artificial Intelligence and User Experience
- Creators
- Denisa Qori McDonald
- Contributors
- Ali Shokoufandeh (Advisor)Genevieve Dion (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Philosophy (Ph.D.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- xviii, 165 pages
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- Computer Science (Computing) [Historical]; College of Computing and Informatics (2013-2026); Drexel University
- Other Identifier
- 991016456058504721