Mental health is often overlooked until it reaches a critical point. We wanted to create a solution that helps people become more aware of their emotional well-being in real time—before issues escalate. With increasing rates of anxiety, depression, and burnout, we were inspired to build something proactive, accessible, and tech-driven.
We developed a mobile/web application that uses real-time inputs—like facial expressions, text sentiment, and simple mood check-ins—to track emotional trends. Users can log how they feel, receive insights, and even share data (anonymously) with therapists or support systems. Features include:
Mood journaling and emoji-based mood logging Sentiment analysis using natural language processing (NLP) Data visualization of mood trends over time Optional alerts for mental health support when distress signals are detected
Working with real-time data streams (from user input and sensors) Implementing sentiment analysis with NLP libraries like spaCy and TextBlob Designing intuitive and non-intrusive UI for sensitive user experiences The importance of privacy and ethical data handling in mental health tools
Working with real-time data streams (from user input and sensors) Implementing sentiment analysis with NLP libraries like spaCy and TextBlob Designing intuitive and non-intrusive UI for sensitive user experiences The importance of privacy and ethical data handling in mental health tools
We plan to integrate passive monitoring (with user consent), gamify mood improvement habits, and partner with mental health professionals for enhanced guidance. Long term, we aim to make this a daily wellness companion that empowers users to understand and manage their mental well-being.
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