Using pen input features as indices of cognitive load

Abstract

Multimodal interfaces are known to be useful in map-based applications, and in complex, time-pressure based tasks. Cognitive load variations in such tasks have been found to impact multimodal behaviour. For example, users become more multimodal and tend towards semantic complementarity as cognitive load increases. The richness of multimodal data means that systems could monitor particular input features to detect experienced load variations. In this paper, we present our attempt to induce controlled levels of load and solicit natural speech and pen-gesture inputs. In particular, we analyse for these features in the pen gesture modality. Our experimental design relies on a map-based Wizard of Oz, using a tablet PC. This paper details analysis of pen-gesture interaction across subjects, and presents suggestive trends of increases in the degree of degeneration of pen-gestures in some subjects, and possible trends in gesture kinematics, when cognitive load increases.