Analyzing and Predicting Empathy in Neurotypical and Nonneurotypical Users with an Affective Avatar

Abstract

In recent times, diagnosing and treating different health issues have improved greatly with the help of technology, with an example being cognitive health issues. Despite this, there is still a difference between how the technology is working towards it and the actual potential that can be achieved. In this paper, we propose a mobile application with an affective avatar, encompassed in the area of serious games, which will obtain information related to the interactions performed by the users. There are a total of 50 users, of neurotypical and nonneurotypical backgrounds, with the latter being people with Down syndrome and intellectual disability. Based on collected data from the different users interacting with the avatar in a mobile device, we analyzed the results to obtain a ground truth about prototypic empathic interactions and feed those interactions to a learning algorithm to support the diagnosis process and therapy treatment of empathy and socialization issues.