Gesture-controlled reconfigurable metasurface system based on surface electromyography for real-time electromagnetic wave manipulation - Chen Junzai; Li Weiran; Gong Kailuo; Lu Xiaojie; Tong Mei Song; Wang Xiaoyi; Yang Guo-Min (Nanophotonics)
Gesture recognition plays a significant role in human-machine interaction (HMI) system. This paper proposes a gesture-controlled reconfigurable metasurface system based on surface electromyography (sEMG) for real-time beam deflection and polarization conversion. By recognizing the sEMG signals of user gestures through a pre-trained convolutional neural network (CNN) model, the system dynamically modulates the metasurface, enabling precise control of the deflection direction and polarization state of electromagnetic waves. Experimental results demonstrate that the proposed system achieves high-precision electromagnetic wave manipulation, in response to different gestures. This system has significant potential applications in intelligent device control, virtual reality systems, and wireless communication technology, and is expected to contribute to the advancement and innovation of HMI technology by integration of more advanced metasurfaces and sEMG processing technologies.