Wearable strain sensors have been attracting increased interest in human motion detection. To meet the demands of complex realistic situations, directed elaborate nanostructure design is indispensable. However, the lack of an efficient numerical calculation method for the prediction and analysis of resistance-strain response behavior greatly restricts sensors’ applications. In this work, a numerical calculation method based on Breadth-First Searching of nanostructured Conductive Network Paths (BFS-CNP) is demonstrated to precisely analyze the relationship between nanostructure and strain sensitivity. The multilayer-segregated structure was applied to illustrate how the numerical system works in the analysis of structure design and prediction of sensing performance. Strain sensors with different strain-sensing performances are developed under the guidance of the numerical calculation method for different applications, such as grasping and pronunciations. This work gives valuable guidance for the numerical analysis of nanostructures and provides critical insight into the nanostructure design for flexible strain sensors.
