Noncontact Human–Machine Interface Using Complementary Information Fusion Based on MEMS and Triboelectric Sensors

Abstract

Abstract Current noncontact human–machine interfaces (HMIs) either suffer from high power consumption, complex signal processing circuits, and algorithms, or cannot support multidimensional interaction. Here, a minimalist, low‐power, and multimodal noncontact interaction interface is realized by fusing the complementary information obtained from a microelectromechanical system (MEMS) humidity sensor and a triboelectric sensor. The humidity sensor composed of a two‐port aluminum nitride (AlN) bulk wave resonator operating in its length extensional mode and a layer of graphene oxide (GO) film with uniform and controllable thickness, possesses an ultra‐tiny form factor (200 × 400 µm2), high signal strength (Q = 1729.5), and low signal noise level (±0.31%RH), and is able to continuously and steadily interact with an approaching finger. Meanwhile, the facile triboelectric sensor made of two annular aluminum electrodes enables the interaction interface to rapidly recognize the multidirectional finger movements. By leveraging the resonant frequency changes of the humidity sensor and output voltage waveforms of the triboelectric sensor, the proposed interaction interface is successfully demonstrated as a game control interface to manipulate a car in virtual reality (VR) space and a password input interface to enter high‐security 3D passwords, indicating its great potential in diversified applications in the future Metaverse.

Keywords

• bulk wave resonators
• graphene oxide
• human–machine interface
• humidity sensors
• noncontact
• triboelectric sensors