Robot-assisted therapy is regarded as an effective and reliable method for the delivery of highly repetitive rehabilitation training in restoring motor skills after a stroke. This study focuses on the rehabilitation of fine hand motion skills due to their vital role in performing delicate activities of daily living (ADL) tasks. The proposed rehabilitation system combines an adaptive assist-as-needed (AAN) control algorithm and a Virtual Reality (VR) based rehabilitation gaming system (RGS). The developed system is described and its effectiveness is validated through clinical trials on a group of eight subacute stroke patients for a period of six weeks. The impact of the training is verified through standard clinical evaluation methods and measuring key kinematic parameters. A comparison of the pre- and post-training results indicates that the method proposed in this study can improve fine hand motion rehabilitation training effectiveness.