Recognizing the Stages of Depression and Optimizing through Guided Imagery

Difficult to diagnose in a timely fashion, but early detection, prevention, and intervention are critical public health interventions in the emerging epidemic of depression. To overcome these challenges, we develop EmoCare, a novel system based on guidance imagery interventions, to first detect depression stages and accordingly offer personal assistance in this study. This project is based on the awareness of the high prevalence of mental health issues and the demand for effective and accessible interventions. We explore the use of computer vision techniques in emotion detection, machine learning algorithms in depression measurement, and guided imagery techniques in the delivery of the intervention. This is an extensive system in terms of methodologies: we used facial expressions, structured questionnaires, and data analytics. With the potential to provide personalized interventions, EmoCare may lead the way for new approaches to addressing emotional health in a timely manner, thereby opening up avenues of emotional support to millions of people to get ahead of depression.