Noninvasive Intelligent Brain-Metasurface System for Real-Time Electromagnetic Wave Manipulation

A noninvasive intelligent brain-computer interface (BCI) is integrated with a reconfigurable metasurface to establish a direct neural-to-electromagnetic transduction pathway for real-time, multimodal wave control. By combining convolutional-neural-network-based decoding of motor-imagery electroencephalography (EEG) signals with threshold-based recognition of electrooculography (EOG) commands, the proposed system converts neural and ocular activities into high-speed control commands, which are subsequently implemented through an FPGA-driven dual-polarized reconfigurable metasurface for real-time electromagnetic-wave manipulation. This architecture concurrently enables beam steering, polarization conversion, and radar cross-section (RCS) reduction within a unified platform. Three distinct operational modes are demonstrated: polarization-invariant beam deflection, joint steering and polarization conversion, and broadband RCS reduction via random phase coding. Experimental results reveal a peak gain of 18.54-19.29 dBi with a 3 dB beamwidth of 12°-15° at a +20° steering angle, and an RCS reduction exceeding 10 dB across 3.7-3.85 GHz. The proposed intelligent BCI-metasurface paradigm validates the feasibility of brain-controlled electromagnetic manipulation, opening new avenues for adaptive wireless communications, immersive virtual environments, and next-generation assistive technologies.