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Recently, flexible sensors endowed with high sensitivity, low detection limit, broad working pressure range and fast response have aroused widespread concern owing to their vital role in the development of wearable artificial devices, human-machine interaction and healthcare systems. Herein, flexible and highly sensitive capacitive pressure sensors were fabricated based on flexible electrodes with convex microarrays and ultrathin dielectric layer. The proposed sensor is constructed by sandwiching a top micro-arrayed electrode, a middle ultrathin dielectric layer and a bottom micro-arrayed electrode, and it demonstrates an ultra-high sensitivity of 30.2 kPa−1 (0–130 Pa), fast response time of 25 ms, low detection limit of 0.7 Pa and extreme stability of 100 000 cycles without fatigue. The finite-element analysis indicates that the changes of contact area and distance between two electrodes under external stimulus are critical to achieve superior properties of the sensor. Benefitting from the outstanding comprehensive performance, the enormous potential ability of the capacitive sensor in monitoring physiological signals and robot hand grabbing motions have been successfully demonstrated, which indicates promising applications in wearable intelligent electronic devices. Ultra-high sensitivity capacitive sensors are fabricated by a simple, low-cost method and the application of flexible sensors in monitoring human biological signals and robot hand's motion are demonstrating successfully. Also, the results of the finite element analysis reveal the relationship between sensitivity and structural design of the capacitive sensor from the mechanical mechanism. Image 1 • Flexible capacitive pressure sensors with ultrahigh sensitivity of 30.2 kPa-1 were successfully fabricated • FEA analysis reveals the relationship between contact area, dielectric layer thickness and external pressure. • Ultrahigh stability up to 100,000 cycles for the flexible capacitive pressure sensors. • Flexible capacitive pressure sensors enable real-time human physiological signals and robotic hand movements monitoring. [ABSTRACT FROM AUTHOR]