In conventional imitation control, optical tracking devices have been widely adopted to capture human motion and control robots in a laboratory environment. Wearable sensors are attracting extensive interest in the development of a lower-cost human-robot control system without constraints from stationary motion analysis devices. We propose an ambulatory human motion analysis system based on small inertial sensors to measure body segment orientations in real time. A new imitation control method was developed and applied to a biped robot using data of human joint angles obtained from a wearable sensor system. An experimental study was carried out to verify the method of synchronous imitation control for a biped robot. By comparing the results obtained from direct imitation control with an improved method based on a training algorithm, which includes a personal motion pattern, we found that the accuracy of imitation control was markedly improved and the tri-axial average errors of - and -moving displacements related to leg length were 12%, 8% and 4%, respectively. Experimental results support the feasibility of the proposed control method.