MindfulMood

Project Overview

During my time at Apple, I collaborated with a team of psychologists and designers to create MindfulMood, an innovative mental health tracking app that uses machine learning to provide personalized mood insights and wellness recommendations.

The app was designed to help users track their daily mood patterns, sleep quality, and stress levels through an intuitive interface. I led the development of the core tracking functionality, implementing HealthKit integration for seamless data collection and Core ML for mood prediction algorithms. The app featured a beautiful, calming design with smooth animations and haptic feedback to create a therapeutic user experience.

One of the most challenging aspects was implementing real-time mood analysis using the device’s camera to detect facial expressions and correlate them with user-reported mood data. I worked extensively with Core ML and Vision frameworks to create accurate emotion detection while maintaining user privacy. The app also included guided meditation sessions and breathing exercises, all built with SwiftUI for a native iOS feel.

The project taught me the importance of accessibility in health apps, leading me to implement comprehensive VoiceOver support and high contrast modes. MindfulMood received recognition from Apple’s App Store editorial team and was featured in the Health & Fitness category.