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Capafoldable: Self-Tracking Foldable Smart Textiles With Capacitive Sensing

Lala Shakti Swarup Ray; Daniel Geißler; Bo Zhou; Paul Lukowicz; Berit Greinke
In: Adjunct Proceedings of the 2023 ACM International Joint Conference on Pervasive and Ubiquitous Computing & the 2023 ACM International Symposium on Wearable Computing. International Joint Conference on Pervasive and Ubiquitous Computing (UbiComp-2023), Cancun, Mexico, UbiComp/ISWC '23 Adjunct, ISBN 9798400702006, Association for Computing Machinery, 2023.


Folding is a unique structural technique to equip planar materials with motion or 3D mechanical properties. Textile-based capacitive sensing has shown to be sensitive to the geometry deformation and relative motion of conductive textiles. In this work, we propose a novel self-tracking foldable smart textile by combining folded fabric structures and capacitive sensing to detect the structural motions using state-of-the-art sensing circuits and deep learning technologies. We created two folding patterns, Accordion and Chevron, each with two layouts of capacitive sensors in the form of thermobonded conductive textile patches. In an experiment of manually moving patches of the folding patterns, we developed deep neural network to learn and reconstruct the vision-tracked shape of the patches. Through our approach, the geometry primitives defining the patch shape can be reconstructed from the capacitive signals with R-squared value of up to 95% and tracking error of 1cm for 22.5cm long patches. With mechanical, electrical and sensing properties, Capafoldable could enable a new range of smart textile applications.


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