The rapid development of wearable smart devices has contributed to the enormous demands for smart flexible strain sensors. However, to date, the poor stretchability and sensitivity of conventional metals or inorganic semiconductor-based strain sensors have restricted their application in this field to some extent, and hence many efforts have been devoted to find suitable candidates to overcome these limitations. Recently, novel resistive-type electrically conductive polymer composites (ECPCs)-based strain sensors have attracted attention based on their merits of light weight, flexibility, stretchability, and easy processing, thus showing great potential applications in the fields of human movement detection, artificial muscles, human–machine interfaces, soft robotic skin, etc. For ECPCs-based strain sensors, the conductive filler type and the phase morphology design have important influences on the sensing property. Meanwhile, to achieve a successful application toward wearable devices, several imperative features, including a self-healing capability, superhydrophobicity, and good light transmission, need to be considered. The aim of the present review is to critically review the progress of ECPCs-based strain sensors and to foresee their future development.

Lightweight conductive porous graphene/thermoplastic polyurethane (TPU) foams with ultrahigh compressibility were successfully fabricated by using the thermal induced phase separation (TISP) technique. The density and porosity of the foams were calculated to be about 0.11 g cm⁻³ and 90% owing to the porous structure. Compared with pure TPU foams, the addition of graphene could effectively increase the thickness of the cell wall and hinder the formation of small holes, leading to a robust porous structure with excellent compression property. Meanwhile, the cell walls with small holes and a dendritic structure were observed due to the flexibility of graphene, endowing the foam with special positive piezoresistive behaviors and peculiar response patterns with a deflection point during the cyclic compression. This could effectively enhance the identifiability of external compression strain when used as piezoresistive sensors. In addition, larger compression sensitivity was achieved at a higher compression rate. Due to high porosity and good elasticity of TPU, the conductive foams demonstrated good compressibility and stable piezoresistive sensing signals at a strain of up to 90%. During the cyclic piezoresistive sensing test under different compression strains, the conductive foam exhibited good recoverability and reproducibility after the stabilization of cyclic loading. All these suggest that the fabricated conductive foam possesses great potential to be used as lightweight, flexible, highly sensitive, and stable piezoresistive sensors.

An electrically conductive ultralow percolation threshold of 0.1 wt% graphene was observed in the thermoplastic polyurethane (TPU) nanocomposites. The homogeneously dispersed graphene effectively enhanced the mechanical properties of TPU significantly at a low graphene loading of 0.2 wt%. These nanocomposites were subjected to cyclic loading to investigate the influences of graphene loading, strain amplitude and strain rate on the strain sensing performances. The two dimensional graphene and the flexible TPU matrix were found to endow these nanocomposites with a wide range of strain sensitivity (gauge factor ranging from 0.78 for TPU with 0.6 wt% graphene at the strain rate of 0.1 min⁻¹ to 17.7 for TPU with 0.2 wt% graphene at the strain rate of 0.3 min⁻¹) and good sensing stability for different strain patterns. In addition, these nanocomposites demonstrated good recoverability and reproducibility after stabilization by cyclic loading. An analytical model based on tunneling theory was used to simulate the resistance response to strain under different strain rates. The change in the number of conductive pathways and tunneling distance under strain was responsible for the observed resistance-strain behaviors. This study provides guidelines for the fabrication of graphene based polymer strain sensors.