Quantitative assessment of motor abilities in stroke survivors undergoing rehabilitation can be a valuable feedback to guide the rehabilitation process. The Functional Ability Scale (FAS) part of Wolf Motor Function Test (WMFT) is used to evaluate movement quality during performance of a set of functional motor tasks. In this paper, we show that information collected using body worn sensors such as accelerometers during performance of functional motor tasks by stroke survivors can be used to build accurate classifiers of FAS scores for individual tasks. We perform feature selection to improve classification accuracy and show that it is possible to estimate the total FAS score from a subset of functional motor tasks taken from the WMFT.