  This article presents a comprehensive analysis of the different tests
proposed in the recent ChildCI framework, proving its potential for generating
a better understanding of children's neuromotor and cognitive development along
time, as well as their possible application in other research areas such as
e-Health and e-Learning. In particular, we propose a set of over 100 global
features related to motor and cognitive aspects of the children interaction
with mobile devices, some of them collected and adapted from the literature.
  Furthermore, we analyse the robustness and discriminative power of the
proposed feature set including experimental results for the task of children
age group detection based on their motor and cognitive behaviours. Two
different scenarios are considered in this study: i) single-test scenario, and
ii) multiple-test scenario. Results over 93% accuracy are achieved using the
publicly available ChildCIdb_v1 database (over 400 children from 18 months to 8
years old), proving the high correlation of children's age with the way they
interact with mobile devices.
