This study presents a novel approach for touch sensing using semi-elastic textile surfaces that does not require the placement of additional sensors in the sensing area, instead relying on sensors located on the border of the textile. The proposed approach is demonstrated through experiments involving an elastic Jersey fabric and a variety of machine-learning models. The performance of one particular border-based sensor design is evaluated in depth. By using visual markers, the best-performing visual sensor arrangement predicts a single touch point with a mean squared error of 1.36 mm on an area of 125 by 125 mm. We built a textile-only prototype that is able to classify touch at three indent levels (0, 15, and 20 mm) with an accuracy of 82.85%. Our results suggest that this approach has potential applications in wearable technology and smart textiles, making it a promising avenue for further exploration in these fields.
OriginalspracheDeutsch (Österreich)
TitelHuman Systems Engineering and Design (IHSED 2023)
UntertitelFuture Trends and Applications. AHFE (2023) International Conference.
Redakteure/-innenWaldemar Karwowski, Tareq Ahram, Mario Milicevic, Darko Etinger , Krunoslav Zubrinic
Herausgeber (Verlag)AHFE Open Access, vol 112. AHFE International, USA
Seiten327 - 335
PublikationsstatusVeröffentlicht - Aug. 2023