Abstract: Knee osteoarthritis（KOA） is a chronic disease, and early diagnosis is particularly important. At present,common diagnostic methods include arthroscopy, X-ray and magnetic resonance imaging, but these diagnostic methods are all used to detect the knee joint when it is still. In this study, based on the acoustic emission（AE） detection system and the knee joint angle data acquisition system, a KOA dynamic detection platform is built to realize the dynamic detection of the knee joint. According to the change of instantaneous angular velocity during the movement, the single sitting-standing-sitting movement is divided into four stages. The number of AE events and the cumulative probability of AE amplitude in the four movement are studied, and a comparative analysis is made between the healthy group and the control group. The number of AE events in control group are significantly higher than that in healthy group. The overall level of AE amplitude in control group are higher than that in healthy group. Compared with other motion stages, the number and amplitude of AE signals in the deceleration descent stage are of more research significance. This verified the effectiveness of the acoustic emission system for the dynamic detection of knee osteoarthritis, which can provide some inspiration for the early diagnosis of osteoarthritis.