Tap model that considers key arrangement to improve input accuracy of touch panels

The use of mobile devices that utilize touch panels as interfaces, such as smartphones and tablet PCs, has spread in recent years, and these have many advantages. For example, panels can be operated more intuitively than those with conventional physical buttons, and the devices are much more flexible than those that use traditional fixed UIs. However, mistakes frequently occur when inputting with a touch panel because the buttons have no physical boundaries and users cannot get tactile feedback from their fingers. Thus, the input accuracy of touch-panel devices is lower than that of devices with physical buttons. There have been studies on improving input accuracy. Most of them have used language models for typing natural language or probabilistic models to describe the errors made when users tap panels with their fingers. However, these models are not practical because they deal with kinematic errors, not cognitive errors. Thus, we propose a more practical model for improving input accuracy in this paper, in which the tap model includes cognitive errors to avoid tapping neighboring objects to a target object. We consider that our model can describe important properties for designing various UIs depending on practical applications. We also conducted experiments to build our model in a calibrated way and discussed our evaluation of the model and revision of the model.