The upper limb rehabilitation exoskeleton with cable-driven parallel structure has the advantages of light weight and large payload, etc. However, due to the non-rigid nature of the actuating cables and the different body shape of the wearer, the geometric parameters of the exoskeleton have a large error. The parameter identification of cable-driven exoskeleton is of great significance. An asynchronous self-identification method for the upper limb seven degree-of-freedom (DOF) cable-driven exoskeleton was proposed and used in a wearable multi-redundant exoskeleton. Asynchronous iteration eliminates the accumulation of joint errors. High identification reliability is achieved by selecting proper identification parameters and optimizing error model.With the method, the geometric parameters of the exoskeleton can be identified by using exoskeleton joint angle and cable length data. The experiment verifies that the success rate of parameter identification for different wearers is in line with expectations, and the control precision and stability of the prototype are greatly improved after parameter identification.