Regresar

Predicting task execution time on Natural User Interfaces based on touchless hand gestures

Abstract:

Model-based evaluation has been widely used in HCI. However, current predictive models are insufficient to evaluate Natural User Interfaces based on touchless hand gestures. The purpose of this paper is to present a model based on KLM to predict performance time for doing tasks using this interface type. The required model operators were defined considering the temporal structure of hand gestures (i.e. using gesture units) and performing a systematic bibliographic review. The times for these operators were estimated by a user study consisting of various parts. Finally, the model empirical evaluation gave acceptable results (root-mean-square error = 10%, R2 = 0.936) when compared to similar models developed for other interaction styles. Thus, the proposed model should be helpful to software designers to carry out usability assessments by predicting performance time without user participation.