Synergistic Decoupling of Distance and Velocity in a Triboelectric Touchless Sensor for Intelligent Identity Recognition

Touchless identity recognition is a crucial direction for future human-computer interaction, with broad application potential particularly in healthcare, remote security, and augmented reality. With advancements in contactless triboelectric nanogenerator (TENG) technology, employed as touch-free monitoring sensors, touchless interaction will pave the way for more natural and seamless user experiences. However, achieving more intelligent and complex touchless interactions using contactless sensors remains a grand challenge, primarily due to the difficulty in synergistically decoupling multidimensional signals such as interaction distance and velocity. Here, we present a contactless TENG based on a single-electrode mechanism that enables synergistic spatiotemporal decoding of object distance and velocity through the independent analysis of open-circuit voltage and short-circuit current signals. Benefiting from the synergy between interaction distance and velocity, the proposed system enhances identification security via spatiotemporal information encoding by mapping spatial and temporal parameters into dual-channel authentication inputs. The proposed design concept and guidelines would provide new insights into touchless sensor development, promising benefits for applications like artificial intelligence, network security, and access control for computers and networks.