Title | ||
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Project Tasca: Enabling Touch and Contextual Interactions with a Pocket-based Textile Sensor |
Abstract | ||
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ABSTRACTWe present Project Tasca, a pocket-based textile sensor that detects user input and recognizes everyday objects that a user carries in the pockets of a pair of pants (e.g., keys, coins, electronic devices, or plastic items). By creating a new fabric-based sensor capable of detecting in-pocket touch and pressure, and recognizing metallic, non-metallic, and tagged objects inside the pocket, we enable a rich variety of subtle, eyes-free, and always-available input, as well as context-driven interactions in wearable scenarios. We developed our prototype by integrating four distinct types of sensing methods, namely: inductive sensing, capacitive sensing, resistive sensing, and NFC in a multi-layer fabric structure into the form factor of a jeans pocket. Through a ten-participant study, we evaluated the performance of our prototype across 11 common objects including hands, 8 force gestures, and 30 NFC tag placements. We yielded a 92.3% personal cross-validation accuracy for object recognition, 96.4% accuracy for gesture recognition, and a 100% accuracy for detecting NFC tags at close distance . We conclude by demonstrating the interactions enabled by our pocket-based sensor in several applications. |
Year | DOI | Venue |
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2021 | 10.1145/3411764.3445712 | Conference on Human Factors in Computing Systems |
DocType | Citations | PageRank |
Conference | 0 | 0.34 |
References | Authors | |
0 | 5 |
Name | Order | Citations | PageRank |
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Te-Yen Wu | 1 | 16 | 7.38 |
Zheer Xu | 2 | 10 | 2.11 |
Xing-Dong Yang | 3 | 353 | 25.39 |
Steve Hodges | 4 | 3658 | 252.46 |
Teddy Seyed | 5 | 139 | 15.10 |