Robot-assisted therapy is regarded as an effective and reliable method for the de-livery of highly repetitive training that is needed to trigger neuroplasticity followinga stroke. However, the lack of fully adaptive assist-as-needed control of the roboticdevices and an inadequate immersive virtual environment that can promote activeparticipation during training are obstacles hindering the achievement of bettertraining results with fewer training sessions required. This study thus focuses onthese research gaps by combining these 2 key components into a rehabilitationsystem, with special attention on the rehabilitation of fine hand motion skills. Theeffectiveness of the proposed system is tested by conducting clinical trials on achronic stroke patient and verified through clinical evaluation methods by mea-suring the key kinematic features such as active range of motion (ROM), fingerstrength, and velocity. By comparing the pretraining and post-training results, thestudy demonstrates that the proposed method can further enhance the effective-ness of fine hand motion rehabilitation training by improving finger ROM, strength,and coordination.