DataSpoon: Overcoming Design Challenges in Tangible and Embedded Assistive Technologies

Abstract

The design of tangible and embedded assistive technologies poses unique challenges. We describe the challenges we encountered during the design of "DataSpoon", explain how we overcame them, and suggest design guidelines. DataSpoon is an instrumented spoon that monitors movement kinematics during self-feeding. Children with motor disorders often encounter difficulty mastering self-feeding. In order to treat them effectively, professional caregivers need to assess their movement kinematics. Currently, assessment is performed through observations and questionnaires. DataSpoon adds sensor-based data to this process. A validation study showed that data obtained from DataSpoon and from a 6-camera 3D motion capture system were similar. Our experience yielded three design guidelines: needs of both caregivers and children should be considered; distractions to direct caregiver-child interaction should be minimized; familiar-looking devices may alleviate concerns associated with unfamiliar technology.