Ming Mei, Yin Xiaohong, Luo Yinchen, Zhang Bin, Xue Qian
School of Mechanical Engineering, Zhejiang University, Hangzhou 310058, China.
College of Electrical Engineering, Zhejiang University, Hangzhou 310058, China.
Sensors (Basel). 2025 Sep 16;25(18):5777. doi: 10.3390/s25185777.
Three-dimensional printing technology is fundamentally reshaping the design and fabrication of health monitoring sensors. While it holds great promise for achieving miniaturization, multi-material integration, and personalized customization, the lack of a clear selection framework hinders the optimal matching of printing technologies to specific sensor requirements. This review presents a classification framework based on existing standards and specifically designed to address sensor-related requirements, categorizing 3D printing technologies into point-based, line-based, and area-based modalities according to their fundamental fabrication unit. This framework directly bridges the capabilities of each modality, such as nanoscale resolution, multi-material versatility, and high-throughput production, with the critical demands of modern health monitoring sensors. We systematically demonstrate how this approach guides technology selection: Point-based methods (e.g., stereolithography, inkjet) enable micron-scale features for ultra-sensitive detection; line-based techniques (e.g., Direct Ink Writing, Fused Filament Fabrication) excel in multi-material integration for creating complex functional devices such as sweat-sensing patches; and area-based approaches (e.g., Digital Light Processing) facilitate rapid production of sensor arrays and intricate structures for applications like continuous glucose monitoring. The point-line-area paradigm offers a powerful heuristic for designing and manufacturing next-generation health monitoring sensors. We also discuss strategies to overcome existing challenges, including material biocompatibility and cross-scale manufacturing, through the integration of AI-driven design and stimuli-responsive materials. This framework not only clarifies the current research landscape but also accelerates the development of intelligent, personalized, and sustainable health monitoring systems.
三维打印技术正在从根本上重塑健康监测传感器的设计与制造。尽管它在实现小型化、多材料集成和个性化定制方面具有巨大潜力，但缺乏明确的选择框架阻碍了打印技术与特定传感器要求的最佳匹配。本综述提出了一个基于现有标准且专门针对传感器相关要求设计的分类框架，根据其基本制造单元将3D打印技术分为基于点、基于线和基于面的方式。该框架直接将每种方式的能力，如纳米级分辨率、多材料通用性和高通量生产，与现代健康监测传感器的关键需求联系起来。我们系统地展示了这种方法如何指导技术选择：基于点的方法（如立体光刻、喷墨）能够实现微米级特征以进行超灵敏检测；基于线的技术（如直接墨水书写、熔丝制造）在多材料集成方面表现出色，可用于制造复杂的功能设备，如汗液传感贴片；基于面的方法（如数字光处理）有助于快速生产传感器阵列和复杂结构，用于连续血糖监测等应用。点-线-面范式为设计和制造下一代健康监测传感器提供了强大的启发式方法。我们还讨论了通过整合人工智能驱动的设计和刺激响应材料来克服现有挑战的策略，包括材料生物相容性和跨尺度制造。这个框架不仅阐明了当前的研究状况，还加速了智能、个性化和可持续健康监测系统的发展。
