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Project Overview
MoodLens is a conceptual mobile application that enables users to record, reflect on, and visualize their emotional states over time privately and intuitively. The project emerged in response to growing concerns over the emotional vulnerability and pressure that often accompany mental health tracking tools embedded in social platforms.
Unlike many apps that prioritize community sharing or gamified feedback, MoodLens is designed as a quiet, personal space. Its goal is to help users recognize emotional patterns, understand their internal landscape, and cultivate a deeper sense of self-awareness, all without fear of exposure or judgment.
Problem Space
Mental health documentation is deeply personal. Through primary user research (interviews and surveys), I identified several recurring issues in the existing landscape of wellness and mental health apps:
Lack of privacy: Many users expressed discomfort with the expectation of sharing sensitive emotional data, even anonymously.
Performance pressure: Some platforms unintentionally promote "emotional perfection," causing users to hide or distort negative states.
Cognitive overload: Interfaces with excessive features or notifications often triggered stress rather than alleviating it.
These pain points highlighted the need for a tool that was non-social, calming, and visually intuitive, allowing users to engage with their emotions on their own terms.
Research & Design Process
User Research
Conducted surveys with 44 participants and 6 in-depth interviews to understand existing behaviors around mood tracking. Built personas reflecting emotional needs, daily routines, and mental health habits.
Journey Mapping
Created an end-to-end user journey to identify friction points, emotional triggers, and moments of reflection. This process helped clarify when and how users are most open to self-documentation.
Information Architecture
Developed a clean, minimal IA that foregrounds ease of access, daily input, and trend overview. Avoided any “achievement” or “ranking” systems to preserve psychological safety.
Prototyping
Created wireframes and interactive prototypes in Figma. Key flows included:
Mood logging (color-coded and keyword-supported)
Weekly and monthly visualizations
Reflection prompts and optional journaling
“Private mode” with no account creation
Usability Testing
Conducted two rounds of testing. Users appreciated the emotional neutrality of the interface and the clarity of data visualization. They reported feeling more in control of their self-understanding.
Design Highlights
Emotion-to-Color Mapping
Users could tag emotions using colors, drawing from both established psychology (Plutchik’s wheel of emotions) and subjective interpretation. This allowed both analytical and intuitive reflection.
Privacy-First Architecture
No login. No identity binding. All data stored locally or encrypted if cloud syncing was enabled. The app doesn’t ask “How are you?” but instead offers a quiet space to respond when you're ready.
Gentle Data Visualization
Instead of graphs that resemble performance charts, the app displays moods as flowing color gradients and overlapping shapes, enabling a more organic emotional narrative rather than linear progress.
Key Learnings
This project profoundly shaped my thinking around emotional UX design and the ethical responsibilities involved in designing for mental health. I realized:
Silence and slowness can be features, not flaws.
Emotional safety must be embedded in both visual and interaction design.
Design is not neutral, a small interaction (like a push notification) can influence a user’s sense of well-being.
Tools & Methods
Figma: Wireframing, Prototyping, UI Design
Google Forms / Sheets: Survey data collection
Affinity Mapping: Qualitative data synthesis
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