AI-Powered Mood Detection App Using Facial Recognition
Scan your face, detect your mood, and receive personalized activities to boost your emotional well-being. Designed with empathy and guided by intelligent analysis.
Client
Mood App
Service Provided
App Design
Overview
A mobile app that scans the user’s face to detect mood, then offers guided activities such as breathing, meditation, and music therapy based on emotional state. Focused on designing an intuitive flow that supports users during vulnerable moments.
1
Challenges
⚠️ Users often don’t know what they’re feeling or how to describe it. The app simplifies this by visually breaking down their mood using facial scans.
⚠️ Existing apps overwhelm users with choices. This app personalizes suggestions based on both detected mood and its underlying cause.
⚠️ Users feel stuck during emotional lows. A minimal, calming UI paired with guided audio/video cues makes starting wellness activities effortless.
2
Goals:
✅ Create a UI that feels gentle and comforting—reducing anxiety through soft visuals, calm colors, and minimal interaction.
✅ Help users understand their mood without needing to type or talk—using facial analysis paired with visual mood breakdowns.
✅ Personalize every suggestion by first asking the emotional trigger (e.g., grief, financial stress) before offering solutions.
✅ Limit overwhelming choices by offering curated paths—just one decision per screen from detection to action.
3
Key Features
🔹 Visually shows percentages of various emotions. Easy to digest at a glance.
🔹 4 steps only: Detect → Reason → Category → Action.
🔹 Users pick what’s affecting them (e.g., relationship, grief) for tailored support.
🔹 Each activity has a visual timer, icons, and voice/video guidance.
4
Results & Impact (Hypothetical)
🚀 Improved user engagement due to personalized mood tracking.
🚀 High usability score in internal testing—reduced bounce rate during mood entry.
🚀 Test users reported feeling “less overwhelmed” due to the calming UI tone.
5
Prototype
6
