Artificial Intelligence Meets Flexible Sensors: Emerging Smart Flexible Sensing Systems Driven by Machine Learning and Artificial Synapses

作者：Tianming Sun, Bin Feng, Jinpeng Huo, Yu Xiao, Wengan Wang, Wengan Wang, Jin Zhang Peng, Zehua Li, Chengjie Du, Wenxian Wang, Wenxian Wang, Guisheng Zou, Lei Liu · 发表于：Nano-Micro Letters · 年份：2023 · DOI：10.1007/s40820-023-01235-x · 被引用次数：370 · 研究领域：Advanced Memory and Neural Computing、Advanced Sensor and Energy Harvesting Materials、Ferroelectric and Negative Capacitance Devices

The recent wave of the artificial intelligence (AI) revolution has aroused unprecedented interest in the intelligentialize of human society. As an essential component that bridges the physical world and digital signals, flexible sensors are evolving from a single sensing element to a smarter system, which is capable of highly efficient acquisition, analysis, and even perception of vast, multifaceted data. While challenging from a manual perspective, the development of intelligent flexible sensing has been remarkably facilitated owing to the rapid advances of brain-inspired AI innovations from both the algorithm (machine learning) and the framework (artificial synapses) level. This review presents the recent progress of the emerging AI-driven, intelligent flexible sensing systems. The basic concept of machine learning and artificial synapses are introduced. The new enabling features induced by the fusion of AI and flexible sensing are comprehensively reviewed, which significantly advances the applications such as flexible sensory systems, soft/humanoid robotics, and human activity monitoring. As two of the most profound innovations in the twenty-first century, the deep incorporation of flexible sensing and AI technology holds tremendous potential for creating a smarter world for human beings.