Self‐Powered Non‐Contact Motion Vector Sensor for Multifunctional Human–Machine Interface

Sensors as the significant units of the Internet of Things play an important role in the field of information interaction. Non-contact sensors have the advantages of flexible manipulation and a longer lifespan but it is constrained in motion detection due to their relative single detection function. Herein, a self-powered non-contact motion vector sensor (NMVS) for the multifunctional human-machine interface is reported. Based on the electrostatic induction effect, the motion vector is measured according to the output electrical signals from the non-contact triboelectric nanogenerator (NC-TENG). By simulation analysis and experimental validation, the output characteristics of NC-TENG dependence on structural and motion parameters are investigated in detail. On this basis, the resolution of NMVS is improved and exhibits for non-contact micro-vibration monitoring, rehabilitation gait detection, contactless smart lock, and the non-contact limit alarm. This work not only proposes an ingenious strategy for non-contact motion vector detection but also demonstrates the promising prospects of a multifunctional human-machine interface in intelligent electronics, health rehabilitation, and industrial inspection.