The distribution of intervals between human actions such as email posts or keyboard strokes demonstrates distinct properties at short vs long time scales. For instance, at long time scales, which are presumably controlled by complex process such as planning and decision making, it has been shown that those inter-event intervals follow a scale-invariant (or power-law) distribution. In contrast, at shorter time-scales - which are governed by different process such as sensorimotor skill - they do not follow the same distribution and little do we know how they relate to the scale-invariant pattern. Here, we analyzed 9 millions intervals between smartphone screen touches of 84 individuals which span several orders of magnitudes (from milliseconds to hours). To capture these intervals, we extend a priority-based generative model to smartphone touching events. At short-time scale, the model is governed by refractory effects, while at longer time scales, the inter-touch intervals are governed by the priority difference between smartphone tasks and other tasks. The flexibility of the model allows to capture inter-individual variations at short and long time scales while its tractability enables efficient model fitting. According to our model, each individual has a specific power-low exponent which is tightly related to the effective refractory time constant suggesting that motor processes which influence the fast actions are related to the higher cognitive processes governing the longer inter-event intervals.