A formative evaluation of human activity recognition technology for parent-child interactions

Studies in recognition of human activities have been developed in populations of all ages. It is possible to use various technologies to obtain data from environmental sensors or equipment, such as wheelchairs or wearable devices, for everyday and specialized use. With children, using augmented toys has become one of the preferred mechanisms to obtain information about the interaction between children and the toy. However, few efforts have been made to study mechanisms for receiving data from child and adult interactions. This work presents the design and evaluation of a computationally augmented glove and puzzle piece based on the specifications from the literature. After the evaluation, we proposed changes to the glove design to ensure the correct interaction data was obtained.