Destress2Impress

A mood-adaptive entertainment hub where biometrics unlock games, memes, music, and movies.

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🎮 Destress to Impress

Clear your mind. Perform your ultimate best. An EmotiBit + AI powered entertainment hub that adapts to your stress levels with games, memes, music, and movies.

🎯 Inspiration

For many under 30, stress is constant — whether it comes from classes, internships, or just navigating everyday life. While entertainment is everywhere — movies, memes, music, games — it’s rarely designed to connect back to how we actually feel in the moment. Most people don’t know how to use entertainment intentionally for mood regulation, even though they already turn to it as a coping mechanism.

That insight inspired us to build Destress to Impress 🎮: a playful platform that syncs biometric stress signals with interactive entertainment experiences, helping students turn stress into quick, fun resets. Instead of passive distraction, our project reimagines entertainment as an active tool for stress relief and self-regulation.

🚀 What it does

Using the EmotiBit sensor, we track physiological signals such as:

  • Heart Rate (HR)
  • Heart Rate Variability (HRV)
  • Electrodermal Activity (EDA / skin response)

We process these into a stress score (0–10) and map them to four entertainment modules:

🐦 Flappy Breath – A breathing game where the length and steadiness of your breath control how far the bird flies. Calmer, deeper breaths = higher scores.

👗 Fit Check – Dress and style your avatar in creative outfits, earning points for each unique look.

😂 MeMeMeMer – Fetches trending safe-for-work memes and challenges users with meme puzzles, blending humor with interactivity.

🎶🎬 MuMo – A mood-based music and movie recommender, powered by Cerebras AI + YouTube API, that curates playlists and clips matched to your detected mood.

A central Dashboard ties this together:

  • Displays biometric data in real time (or simulated demo data if EmotiBit is unavailable).

  • Recommends a module based on your current stress score.

  • Provides a clear “mood-to-entertainment” loop where stress becomes input and entertainment becomes output.

🛠️ How we built it

  • Hardware → Integrated the EmotiBit wearable to stream HR, HRV, and EDA. Since device compatibility was a major issue, we also built a simulated JSON data generator to guarantee demo stability.

  • Frontend → Designed in React + TailwindCSS + shadcn-ui, with pastel gradients and playful animations. We initially prototyped in Lovable, but pivoted mid-hackathon to Bolt when backend support became necessary.

Backend & APIs →

  • Cerebras LLM: Classifies text into moods (Happy, Sad, Stressed, Chill) for powering MuMo.

  • YouTube API: Provides curated playlists and clips for music + movie recommendations.

  • Reddit / Imgflip APIs: For memes, with fallback to static data when endpoints failed.

  • Fallback Services: Wherever APIs failed (Cerebras, Reddit), we built cached JSON backups to ensure our demo would always run.

Games → Written in JavaScript/TypeScript:

  • Flappy Breath used breathing logic.

  • FitCheck implemented avatar customization.

  • MeMeMeMer combined meme APIs + puzzle logic.

  • MuMo embedded YouTube playlists and clips alongside Cerebras-powered mood classification.

⚡ Challenges we ran into

🔌 Hardware Integration Connecting EmotiBit to a live web app was far more complex than expected. We spent nearly 10 hours debugging signal streams, eventually creating a reliable fallback simulation mode to guarantee a demo.

🔄 Platform Pivot Our original plan used Lovable for both frontend and backend. When we realized it couldn’t handle backend logic, we had to rebuild significant portions of the project in Bolt with only ~5 hours left. This was stressful but forced us to adapt quickly.

🌐 API Reliability Both Reddit and Cerebras APIs had intermittent failures. To avoid breaking the presentation, we designed fallback systems where cached or static data would appear if the API didn’t respond.

🎨 Design Consistency With four separate games, the risk was ending up with a fragmented product. We worked hard to keep a cohesive UI (pastel gradients, rounded cards, icons, and consistent typography) so it felt like one platform, not four disconnected hacks.

🏆 Accomplishments we’re proud of

🩺 Successfully connected biometric data from EmotiBit to interactive modules.

🎮 Built and deployed 4 distinct games under extreme time pressure.

🌐 Integrated multiple APIs (YouTube, Cerebras, Reddit/Imgflip) with graceful fallbacks for reliability.

💡 Adaptability: Pivoting platforms, overcoming device incompatibilities, and still delivering a working, cohesive product in <30 hours.

📚 What we learned

🛠️ How to debug hardware integration in web environments under time pressure.

🌐 How to design resilient systems with fallback data when APIs are unreliable.

🎭 That entertainment can be reframed from passive distraction into a form of active mood regulation.

🔮 What’s next

🎶 Smarter MuMo → Enhance recommendations with Spotify integration and more refined AI algorithms.

🎮 Interactive Games Expansion → Build additional modules directly responsive to biometric input.

📱 Mobile-first support → Optimize for mobile devices to reach broader audiences.

💡 Entertainment for Wellbeing → Advance this category as a new approach to digital mental wellness — not therapy, but playful stress relief.

👩‍💻 Team

  • Candy Xie
  • Lara De
  • Lakshitha V.
  • Emily New

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