A Multicolor Artificial Sensing System with Optical Feedback for Real-Time Motion Recognition

Artificial sensing systems have broad application potential in areas such as health monitoring, human-computer interaction, and rehabilitation medicine. However, most existing systems are limited to one-way acquisition and transmission of electrical signals and lack intuitive, real-time feedback for interactive use. This unidirectional operation limits the availability of direct, human-interpretable output cues, thereby restricting their effectiveness in scenarios that require real-time guidance and dynamic interaction, such as rehabilitation training and interactive learning. Introducing a feedback mechanism can effectively overcome this limitation by providing intuitive visual output and enabling a more interactive "perception-feedback-adjustment" pathway, which may improve both the efficiency and precision of human-machine interaction. To address this challenge, we developed a novel artificial sensing system that integrates highly sensitive motion detection with real-time multicolor optical feedback. The stretchable triboelectric nanogenerator (TENG) used as a self-powered motion sensor exhibited sensitivities of 0.145 kPa^-1 in the low-pressure region (<8 kPa) and 0.019 kPa^-1 in the high-pressure region (8-30 kPa). The proposed artificial sensing system, integrating the TENG with a quantum dot light-emitting diode (QLED)-based synaptic device, achieved an overall motion-state recognition accuracy of 98.12%. Compared with conventional electrical feedback, optical feedback in the form of directly observable visual output provides intuitive visualization, strong resistance to electromagnetic interference, and the ability to support multichannel parallel information transmission, making it particularly suitable for delivering clear and unambiguous status indications in complex environments. The synergistic integration of TENG-based mechanical perception and QLED-based optoelectronic feedback demonstrated in this work offers a promising design paradigm for constructing simple, efficient, and intuitive artificial sensory systems.