Advances in robotic technologies offer objective, highly reliable tools for assessment of brain function following stroke. KINARM is an exoskeleton device that uses a number of behavioral tasks to objectively quantify sensorimotor, proprioceptive and cognitive brain function. As more tasks are developed to more broadly assess different aspects of behavior using the robot, different strategies are required to reduce the overall assessment time. The present study investigates how non-linear hierarchical ordering theory can be applied to determine the ordering on a set of four tasks on the KINARM exoskeleton robot. Evaluation is based on task discretization, which determines whether an individual passes or fails a certain task on the robot. Results of the study suggest an ordering which determines the results of success or failure on a sensorimotor task for the unaffected arm of stroke survivors based on the assessment results of a ball drop object-hit task with 97% confidence. This can be used to reduce the assessment time by over eight minutes for a subgroup of stroke survivors compared to the current KINARM assessment protocol.