EEG Stimulation

Inspiration ✨🧠

Finals week hit me hard — not just the stress of exams, but watching friends’ moods spiral down silently. I wondered: What if we could catch mood crashes early, before they take over? Commercial EEG devices cost over $10,000, locking advanced mental health tech behind a paywall. I wanted to break that barrier and create something anyone can use anytime, anywhere.

What it does 🚀💡

NeuroSync EEG Stimulation simulates real EEG brainwaves and decodes mood using machine learning — all offline. It lets users choose brain stimulation types to enhance focus, memory, or relaxation and delivers instant mood summaries through a sleek, easy-to-use app. Think of it as your personal brain coach in your pocket.

How we built it 🔧🛠️

We used open EEG datasets (Physionet) to simulate live brain data, applied signal processing to extract frequency bands, and trained hybrid ML models (SVM + Random Forest) for mood classification. The offline-first web app features brainwave visualization and stimulation timers with animated feedback.

Challenges ⚡🧩

No EEG hardware access, noisy brain data filtering, steep learning curve in signal processing and ML, and crafting a fully offline, polished user experience were key hurdles.

Accomplishments 🏆🔥

Built a fully offline EEG mood tracker and stim simulator, combined real-time ML with brainwave data, open-sourced the project for global access, and designed a smooth app UI that works anywhere.

What we learned 📚💡

EEG signal processing is tough but insightful, hybrid ML models boost prediction, offline-first apps empower users with privacy, and open datasets enable medical-tech innovation without expensive gear.

What’s next 🌟🚀

Integrate with low-cost EEG devices (like OpenBCI), add live brain training feedback, pursue medical validation, and develop AI-personalized stim protocols.