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In this paper, an exosuit with twisted string actuators (TSAs) is developed to provide high-strength and variable-stiffness actuation for hemiplegic patients. By formulating the analytic model of the TSA and decoding the human impedance characteristic, the human-exosuit coupled dynamic model is constructed. An adaptive impedance controller is designed to transfer the skills of the patient\u2019s healthy limb (HL) to the bilateral impaired limb (IL) with a mirror training strategy, including the movement trajectory and stiffness profiles. A reinforcement learning (RL) algorithm is proposed to optimize the robotic assistance by adapting the impedance model parameters to the subject\u2019s performance. 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