Terahertz (THz) waves exhibit distinctive properties, such as high transmittance, pronounced absorption, and minimal photon energy, enabling a wide range of applications in biomedical diagnosis, non-destructive testing, and quality/safety monitoring of food and agricultural products. Consequently, THz-based sensors have garnered increasing attention. However, the design of traditional coupling structures fails to effectively match the high-frequency oscillation of THz waves, resulting in low signal energy transmission efficiency and limiting the performance of THz sensors, while microstructure technology can offer a solution by achieving localized enhancement of the electromagnetic field energy through precise matching of sub-wavelength resonance units with the high-frequency oscillation of THz waves, which significantly improves the sensitivity of THz sensors. This review summarizes the basic principles and research status of various THz sensors based on different microstructures, such as split-ring resonators (SRRs), photonic crystals, waveguide resonators, and surface plasmon resonance. Notably, the rapid development of artificial intelligence, especially deep learning, is increasingly influencing THz sensing technologies with its strengths in signal processing, pattern recognition accuracy, and inverse design. Integrating deep learning with THz sensor design enhances feature extraction from complex signals, improves target identification, and enables intelligent optimization of microstructure parameters for high-performance sensor design and performance prediction. This interdisciplinary approach provides a new pathway to overcome traditional design limitations and advance THz sensor performance.

Wearable devices have great application potential in the next generation of smart portable electronics, especially in the fields of medical monitoring, soft robotics, artificial intelligence, and human-machine interfaces. Piezoelectric flexible strain sensors are key components of wearable devices. However, existing piezoelectric flexible strain sensors have certain limitations in weak signal monitoring due to their large modulus and low sensitivity. To solve this problem, the concept of Kirigami (paper-cutting) was introduced in this study to design the sensor structure. By comparing the Kirigami structures of different basic structures, the serpentine structure was determined as the basic configuration of the sensor. The serpentine structure not only provides excellent tensile properties, but also significantly improves the sensitivity of the sensor, which performs well in monitoring weak signals. On this basis, the adhesion properties of the flexible sensor were analyzed and tested, and the optimal ratio of the substrate was selected for preparation. In addition, a low-cost and rapid prototyping process for stretchable patches was established in this study. Using this technology, we prepared the sensor device and tested its performance. Finally, we successfully developed a flexible sensor with a sensitivity of 0.128 mV/µɛ and verified its feasibility for wrist joint motion monitoring applications. This result opens up new avenues for the recovery care of tenosynovitis patients after surgery.