This paper proposes two robot-assisted exercise training methods for knee rehabilitation based on a practical EMG-driven model, aiming to beneficially exploit the patient's ability through neurorehabilitation process. The EMG-driven model is a simplified representation of the musculoskeletal system, with acceptable accuracies to predict the muscle forces and active torque of knee joint. Thus the patient's voluntary contribution can be introduced to the control loop through admittance controller. Preliminary experiments verify that the model prediction performance is able to reflect the subjects' motion intention in real-time and assist the subjects to perform exercise training with a lower limb rehabilitation robot. The information recorded during exercise training could be useful to understand the process of recovery and make quantitative evaluations to the patient's motor abilities.