MindCare: An Innovative Application for Depression Diagnosis and Treatment Support
Depression screening remains challenging due to reliance on subjective assessments and limited accessibility of mental health services. This paper presents MindCare, an integrated mobile platform combining standardized questionnaires, AI-powered therapeutic interactions, emotional journaling, and EEG-based neurophysiological assessment. The system implements a novel visual stimulation protocol using 60 emotionally evocative images from the Open Affective Standardized Image Set (OASIS) to elicit measurable neural responses. User evaluation with 7 participants demonstrated high satisfaction across all features. EEG analysis of 4 participants during emotional stimulation revealed strong correlations between frontal channel neural features and PHQ-9 depression scores. Machine learning classification achieved 97.9 % accuracy in distinguishing depression status using segment-based analysis of 240 stimulus-response pairs. The integration of objective neurophysiological markers with subjective assessment tools demonstrates significant potential for enhancing digital mental health screening capabilities.
