Laser-Induced Graphene Strain Sensor for Conformable Lip-Reading Recognition and Human–Machine Interaction

Lip-reading recognition (LRR) has gained significant attention due to its potential applications in various scenarios, such as communication for the speech-impaired, conversations in noisy or dark environments, and human–machine interactions. However, existing LRR technologies based on computer vision suffer from drawbacks such as the high cost of electronic camera equipment and the negative impact of ambient lighting on recognition accuracy. Herein, a graphene-based flexible strain sensor is developed through a facile, high-efficiency, and low-cost laser-induced carbonization technique, which involves the ablation of polyimide (PI) films using ultraviolet lasers. The sensor’s patterned stripes and porous structure endow it with sensitivity to deformations caused by bending and pressing. The well-designed flexible strain sensor can tightly attach on facial skin and record high-quality strain signals of various lip muscle movements. When compared to a preconstructed lip-reading database using a fixed algorithm, the collected lip-reading signals exhibit a recognition rate exceeding 90%, enabling seamless human–machine interaction and precise control over manipulators. Consequently, the LRR approach based on the flexible strain sensor demonstrates immense potential as a promising platform for speech-impaired communication and human–machine interactions in variable environments.