Researchers at Google's ATAP division have detailed ZebraSense, a dual-sided touch sensor designed for smart clothing applications — enabling, they claim, an entirely new "capacitive sensing paradigm" compared to the existing "sensor sandwich" approach.
"ZebraSense is a novel dual-sided woven touch sensor that can recognize and differentiate interactions on the top and bottom surfaces of the sensor," the researchers explain. "ZebraSense is based on an industrial multi-layer textile weaving technique, yet it enables a novel capacitive sensing paradigm, where each sensing element contributes to touch detection on both surfaces of the sensor simultaneously.
"Unlike the common 'sensor sandwich' approach used in previous work, ZebraSense inherently minimizes the number of sensing elements, which drastically simplifies both sensor construction and its integration into soft goods, while preserving maximum sensor resolution. The experimental evaluation confirmed the validity of our approach and demonstrated that ZebraSense is a reliable, efficient, and accurate solution for detecting user gestures in various dual-sided interaction scenarios, allowing for new use cases in smart apparel, home decoration, toys, and other textile objects."
ZebraSense itself, named for the stripes of touch-sensitive elements which run its length, works by spacing the capacitive sensors apart then using readings from multiple sensors to triangulate the actual touch location. While the researchers claim it can be applied to sensors of any shape and style, the prototypical implementation concentrated on single-dimension sensing — "for," they explain, "the purpose of simplicity and clarity."
Constructed from ten conductive yarns integrated into two layers of denim, the sensor was connected to a microcontroller built around a Cypress CY8C4146 system-on-chip — chosen for its built-in support for capacitive sensing and a SparkFun Bluetooth Mate for data streaming to Processing. "Note that the basic heuristics used for ZebraSense," the researchers say, "are simple enough to run on any microcontroller in real time and it is trivial to create a full enclosed wearable system."
The prototype design was integrated into the cuff of a jacket across tight, relaxed, and loose fits, and proved capable of sensing touches and classifying multi-touch gestures. The researchers also proposed, but did not implement, additional use-cases including a flexible table game mat, an interactive pocket, movement-tracking yoga pants, and a smart COVID-19 face mask which discourages users from touching its external surface.
The team's work has been published as part of the proceedings of the ACM Symposium on User Interface Software and Technology Session: 8B: Sensing and Actuation on Textiles (UIST'20), and is available under open-access terms on the ACM Digital Library.