The integration of flexible sensors is crucial for soft robots to perform specific tasks during complex deformations (such as bending, twisting, compression, stretching, etc.) and interactions with unstructured environments. However, due to the high flexibility, deformability, and multiple degrees of freedom of soft robots, building high-performance flexible sensors remains a major challenge. An effective method is to convert the continuous deformation of soft robots into discrete representations, which enables scientists to better understand the deformation process and clarify the impact of surfaces and interfaces on sensor performance. Therefore, intelligent algorithms can be used to further optimize the number and arrangement of sensors, thereby improving the efficiency and performance of the entire system. We focused on studying the influence of surface interface structure on the performance of flexible sensors. Firstly, based on the basic classification of flexible sensors, the author systematically analyzed the construction strategies for the surface and interface of flexible sensors, including surface structure optimization, microstructure array design, and void structure. Secondly, the author discussed in detail the preparation methods of different surfaces and interfaces. Then, the wide application of flexible sensors in multiple fields was discussed. Finally, the author summarizes and looks forward to the future development direction of flexible sensors.