Using wearable technologies to understand social context
Aristotle University of Thessaloniki (AUTH)
Prof Athena Vakali
Wearable analytics, User engagement, Data analysis, Machine learning, IoT, Mental health
The gap between wearable devices in the research world and commercial technologies has been decreasing in the last few years. My research interests within the RAIS project lie in understanding how peoples’ emotions change, focusing on stress and the severity of depressive symptoms. My goal is to study the between- and within-person variability regarding emotions, stress, and mental outbreaks. I aim to connect my research to different disciplinary fields: data analysis, machine learning, and mental health studies. This approach aims to predict daily mood and the presence of depressive symptoms to detect risks and possibly help mitigate anxiety and depression.