Um framework conceitual para a seleção de sensores móveis para fenotipagem digital de estudantes com possível perfil depressivo

Abstract

This capstone project presents the development of a framework for selecting mobile sensors for the digital phenotyping of university students with possible depressive profiles. Inspired by a seminal study by Torous that analyzes digital phenotyping in varied contexts, this work performs a critical reinterpretation of this literature to adapt and apply concepts to the specific context of depression in academic settings. The proposed framework was developed based on a review of existing work that uses behavioral data captured by sensors on smartphones and other mobile devices, such as GPS and accelerometers, to identify patterns that may be related to depressive symptoms. The methodology involved collaborative discussions with experts in computing and health, seeking to align the technical capabilities of the sensors with the diagnostic and therapeutic needs of potentially depressed students. As a result, possible relationships are presented between the data collected by the sensors and symptoms of depression. This study aims to provide a basis for future practical implementations of computer systems mental health support, using accessible and non-intrusive technologies in educational contexts.