This paper describes the design and testing of a robotic device for finger therapy after stroke: FINGER (Finger Individuating Grasp Exercise Robot). FINGER makes use of stacked single degree-of-freedom mechanisms to assist subjects in moving individual fingers in a naturalistic grasping pattern through much of their full range of motion. The device has a high bandwidth of control (-3dB at approximately 8 Hz) and is backdriveable. These characteristics make it capable of assisting in grasping tasks that require precise timing. We therefore used FINGER to assist individuals with a stroke (n= 8) and without impairment (n= 4) in playing a game similar to Guitar Hero©. The subjects attempted to move their fingers to target positions at times specified by notes that were graphically streamed to popular music. We show here that by automatically adjusting the robot gains, it is possible to use FINGER to modulate the subject's success rate at the game, across a range of impairment levels. Modulating success rates did not alter the stroke subject's effort, although the unimpaired subjects exerted more force when they were made less successful. We also present a novel measure of finger individuation that can be assessed as individuals play Guitar Hero with FINGER. The results demonstrate the ability of FINGER to provide controlled levels of assistance during an engaging computer game, and to quantify finger individuation after stroke.