All-printed flexible multidirectional strain sensor with dual-mode response for human motion detection

Flexible multidirectional strain sensors that can distinguish different strain directions and magnitudes have attracted increasing attention. However, previous designs of multidirectional strain sensors usually use the same type of sensing signals, which makes it difficult to decouple the response signals and hinders the simple distinction of strain directions. Herein, we propose a dual-mode response printed flexible multidirectional strain sensor (DRPMS) that uses resistance and capacitance signals to represent strains in the two principal planar directions, eliminating the requirement of conventional signal decoupling. With the assistance of machine learning algorithms, it can accurately distinguish the directions of strain with an accuracy rate of 98.3%, and can detect different driving postures and wrist motions. The results demonstrate broad application potential in distracted driving behavior detection and human motion monitoring.