We introduce a novel component for smart garments: smart interlining, and validate its technical feasibility through a series of experiments. Our work involved the implementation of a prototype that employs a textile vibration sensor based on Triboelectric Nanogenerators (TENGs), commonly used for activity detection. We explore several unique features of smart interlining, including how sensor signals and patterns are influenced by factors such as the size and shape of the interlining sensor, the location of the vibration source within the sensor area, and various propagation media, such as airborne and surface vibrations. We present our study results and discuss how these findings support the feasibility of smart interlining. Additionally, we demonstrate that smart interlinings on a shirt can detect a variety of user activities involving the hand, mouth, and upper body, achieving an accuracy rate of 93.9% in the tested activities.
https://dl.acm.org/doi/10.1145/3706598.3713167
The ACM CHI Conference on Human Factors in Computing Systems (https://chi2025.acm.org/)