| dc.description.abstract | From an early age, children begin developing critical motor control skills that will be used for the rest of their lives. While everyday activities like standing or walking require gross motor control, fine motor control over the hands is vital to healthy development. Fine motor skills contribute significantly to reading, writing, crafting, drawing, and more, all of which are important for communication and school readiness. Pediatricians can evaluate a child's gross and fine motor skills using questionnaires and activities. For example, there may be periods when a pediatrician meets with a child to see if their tracing abilities are getting better or worse through sketching questionnaires. Usually, these questionnaires ask the adults to draw with their child. However, it is particularly difficult to fully evaluate a child's drawings through a handful of sketches created in just these meetings. We propose to create a sketching system that will collect all drawing data from parents and children that can then automatically evaluate and differentiate a child's sketch from an adult's using only their strokes. We believe that each sketching stroke is unique and includes artifacts of the user's age. Working with sketches from children between 2-5 and adults over 18, we build different statistical features to determine age groups and train a system by analyzing different stroke patterns. A system capable of automatically categorizing users into age groups can enable new solutions for the assessment of fine motor skills as well as enable novel applications related to collaborative learning software and age-based authentication. | |
