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Currently doctors rely on tools such as the Unified Parkinson’s Disease Rating Scale (MDS-UDPRS) and the Scale for the Assessment and Rating of Ataxia (SARA) to make diagnoses for movement disorders based on clinical observations of a patient’s motor movement. Observation-based assessments however are inherently subjective and can differ by person. Moreover, different movement disorders show overlapping symptoms, challenging neurologists to make a correct diagnosis based on eyesight alone. In this work, we create an intelligent interface to highlight movements and gestures that are indicative of a movement disorder to observing doctors. First, we analyzed the walking patterns of 43 participants with Parkinson’s Disease (PD), 60 participants with ataxia, and 52 participants with no movement disorder to find ten metrics that can be used to distinguish PD from ataxia. Next, we designed an interface that provides context to the gestures that are relevant to a movement disorder diagnosis. Finally, we surveyed two neurologists (one who specializes in PD and the other who specializes in ataxia) on how useful this interface is for making a diagnosis. Our results not only showcase additional metrics that can be used to evaluate movement disorders quantitatively but also outline steps to be taken when designing an interface for these kinds of diagnostic tasks.