Running posture is reflected in the stride frequency, gait, landing way. Wrong running posture can easily lead to lower limb injury. In this paper, we analyze the landing patterns of full-foot, heel and toe in running movement, and design and develop the hardware and software system of running monitoring system. Data acquisition, signal pre-processing, and Kalman posture angle solution are all done in the wearable device, and the processed data are sent to the running monitoring platform via WiFi wireless communication module. The running monitoring platform extracts the gait feature points from the uploaded data and uses two thin-film pressure sensors to verify whether the gait feature points are correctly marked. Finally, three running landing postures are identified using hierarchical classification-based and SVM-based running posture detection algorithms, and the classification results are above 90%, proving the method's effectiveness.