Strategies to Improve Activity Recognition Based on Skeletal Tracking: Applying Restrictions Regarding Body Parts and Similarity Boundaries.

This paper aims to improve activity recognition systems based on skeletal tracking through the study of two different strategies (and its combination): (a) specialized body parts analysis and (b) stricter restrictions for the most easily detectable activities. The study was performed using the , which is able to analyze activities using only a single key sample. This system allows to select, for each considered activity, which are its , which makes it possible to monitor the body of the user selecting only a subset of the same.

Correlation between videogame mechanics and executive functions through EEG analysis.

This paper addresses a different point of view of videogames, specifically serious games for health. This paper contributes to that area with a multidisciplinary perspective focus on neurosciences and computation. The experiment population has been pre-adolescents between the ages of 8 and 12 without any cognitive issues.

Assessing empathy and managing emotions through interactions with an affective avatar.

Assistive technologies can improve the quality of life of people diagnosed with different forms of social communication disorders. We report on the design and evaluation of an affective avatar aimed at engaging the user in a social interaction with the purpose of assisting in communication therapies. A human-avatar taxonomy is proposed to assist the design of affective avatars aimed at addressing social communication disorder.