Static-electricity-induced luminescence trajectory tracking: A paradigm for noncontact human-machine interaction in dark environments.

Multiscenario adaptability is a core target of emerging human-machine interaction (HMI) technologies, but conventional visual HMI relies on ambient light illumination, failing to adapt to low-/no-light scenarios. Here, we propose a static-electricity-induced luminescence (SEL) trajectory tracking model, and develop a portable SEL platform integrated with SrAl2O4:Eu2+/polydimethylsiloxane film, featuring 5 to 50 kV operating voltage, 13 mm noncontact distance, ≥150-day stability, 400 K thermal tolerance, and <1 nA body current for high biosafety. Comprehensive mechanism investigations offer a deep and scientific mechanistic understanding of SEL, focusing on the interactions between air ionization, electron bombardment, and trap-state dynamics. Integration with a centroid displacement tracking algorithm and convolutional neural network, it achieves high-accuracy digit recognition and complex robot arm interactive motions, with 2.4× shorter training time and two orders of magnitude faster recognition speed (6.6 ms versus 730 ms in 192.5 lux) than mainstream gesture recognition. This work not only breaks illumination constraints for adaptive HMI but also provides a promising SEL-based HMI paradigm.