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Abstract
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.
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Details
1 College of Electronic and Information Engineering, Tongji University, Shanghai 200092, China
2 Key Laboratory for Information Science of Electromagnetic Waves, School of Information Science and Technology, Fudan University, Shanghai 200433, China
3 College of Electronic and Information Engineering, Shanghai Institute of Intelligent Science and Technology, Tongji University, Shanghai 200092, China