The number of paralytic sufferers is currently growing huge because of the high incidence and disability rate of stroke and spinal cord injury (SCI). Exercise rehabilitation becomes a primary therapy to the paralytic sufferers after instant treatment like surgery, an approach that helps patients return to normal life as much as possible by regaining locomotor function of affected limbs and relearning ADL. However, rehabilitation for patients with paralysis is usually a long-time process, which may continue throughout most of their entire lifetimes. Compared to traditional physiotherapy, rehabilitation with the assistance of robots can reduce the cost and time consumed, and less labor intensity is required. Moreover, training strategies are variously provided by robots, so that rehabilitation effect can be improved. This paper introduces a lower limb rehabilitation robot named iLeg which is developed at our laboratory. The main contributions of the dissertation are as follows： 1. The human-robot hybrid system is built with respect to patients and iLeg, and the dynamic equation is derived to model the hybrid system. In order to estimate the torque that is generated by lower limb muscles, particle swam optimization and least square method are used to identify the dynamic parameters, with strong constraints and high nonlinearity. 2. An interactive control is proposed and implemented during passive training with iLeg. Compared to existing methods, the proposed method achieves active compliant behavior using impedance control and motion planing, to protect the lower limb from secondary injury that may be caused by excessive contact force between mechanism and lower limb from abnormal muscle activities such as spasm and trembling. Hence, the safety is promised during the passive training. 3. An interactive control is proposed to implement the task-oriented active training with iLeg. Compared to existing methods, the proposed method adjusts motion impedance in real time directly based on the voluntary motion intention of patients, which establishes an adaptive haptic interface. Impedance increases when patients intend to resist the predefined motion task. Impedance decreases when the voluntary motion intention agrees with the motion task. Hence, the proposed method not only motivates patients' voluntary participation but also supervises patients to contributes to the training task. 4. sEMG-based single joint active training is proposed and implemented wit...
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