Most stroke patients with hand dysfunction have normal function of one side of the body and their intact musculoskeletal systems are intact. Their hand function can be recovered through rehabilitation training. In this paper, a 3D-printed pneumatic-driven soft robotic glove is designed for hand rehabilitation training controlled by the movements of the healthy hand. Data glove is used to collect the motion data of the healthy hand that is then used to control the robotic glove. Characterization tests of the glove were carried out to prove the feasibility of the soft robotic glove. The experimental results show that the robotic glove can assist users to complete the rehabilitation training task.