Bioinspired triboelectric-driven multisensory framework with autonomous cross-modal adaptation

作者：Yao Xiong, Yang Liu, Jiahong Yang, Mingxia Chen, Zhong Lin Wang, Qijun Sun · 发表于：eScience · 年份：2025 · DOI：10.1016/j.esci.2025.100482 · 被引用次数：12 · 研究领域：Advanced Sensor and Energy Harvesting Materials、Conducting polymers and applications、Tactile and Sensory Interactions

The human multisensory neural network supports advanced cognitive functions through cross-modal integration, recognition, and imagination by synergistically processing visual, tactile, auditory, olfactory, and gustatory stimuli. This biological mechanism generates comprehensive environmental representations through dynamic sensory interactions rather than isolated processing. In this study, a bioinspired multisensory framework is developed, integrating triboelectric sensors with artificial vision, tactile receptors, auditory interfaces, and simulated olfactory/gustatory modules. The system employs a distributed multisensory framework for biomimetic hierarchical processing of multimodal data perception, storage, and fusion. Through cross-modal learning, the system establishes effective associations among different sensory inputs, achieving 97.12% accuracy in tactile-visual recognition and 94.62% accuracy in auditory-visual-olfactory-gustatory reconfiguration. Beyond empirical learning, the framework also demonstrates non-empirical human-like cognitive functions, such as association, inference, and creative pattern generation. The proposed multisensory cross-modal system establishes a versatile framework with significant technological advantages of energy-efficient cognition, adaptive processing, and cognitive scalability. The bioinspired cross-modal reconfiguration combining with triboelectric sensing provides technical innovation and methodological impact to establishing new ...