AutonoMe

Analysis and recording of the emotional state of people with high levels of dependence during educator-user activities

People with high levels of dependency can not directly report their emotions. So far, we have to interpret certain signals subjectively, by supposing that they like a thing, activity, space or person.

Adding to the information we already have, the evaluation of emotions against certain activities, allows us to know if a highly dependent person is happy or if the enjoys a certain activity (participating in activities of psychopedagogical intervention within the field of educational research processes of a participative modality within an action-research process), raising the capacity of intervention og our professionals and providing a precious information to the families.

With this project, we incorporate a software and several wearables sensors, to analyze and register the emotional state of the users during the activities with the educator.

The main objective is to know the emotional state of people with high degrees of dependency in order to further personalize therapeutic interventions, more effectively and obtaining better psychosocial development.

The project is developed incorporating these sensors into the educational programs developed by the Ave Maria Foundation, which measure the evolution of the user’s cognitive state (memory, logic, visual-motor coordination, fine motor skills and others). Following all the necessary protocols, we will evaluate 60 people, and with the collaboration of IDIBELL we will clinically validate the goodness of the data obtained. In addition, this data obtained through an integrated software will allow to automatically adapt the activities that are carried out.

This project opens up a world of new possibilities of choice in favor of the user that allows us to offer personalized and specific content for better use.

Improved users’ cognition, better and more objective interventions by professionals, specialized care, more information for families, new quality measurement factors.