MindLoop: A Cross-Platform Neurofeedback App for ADHD, Stress, and Sleep Support

How MindLoop Uses Brain Microstates to Drive Change

Users begin each session by answering a short survey about their mental and emotional state. The app then connects via Bluetooth to a custom headset-like wearable, which plays therapeutic audio tones and records brain activity.

Unlike conventional neurofeedback tools, MindLoop targets microstates. These are fleeting patterns of brain activity that recur over time and are associated with specific mental health conditions. MindLoop reinforces asynchronous activity and helps the brain move away from rigid, repetitive states. This supports neuroplasticity and encourages the development of new, healthier neural pathways.

After each session, users complete the same survey again, while clinicians access anonymised brain data to monitor outcomes and adjust treatment as needed.

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How We Helped MindLoop Bring Their Vision to Life

Stabilising Data Flow Between Device and App

While the hardware was developed by another team, we took charge of debugging and stabilising the data flow between the wearable device and the mobile app.

Initially, the volume and frequency of raw brainwave data overloaded the app’s API servers, leading to instability. To address this, we implemented data streaming, which processes the information bit by bit instead of all at once. This slightly slows things down when there’s only a small amount of data, but overall, it makes the app much more stable and reliable.

Bridging Native Android Logic with Flutter

The original Bluetooth communication logic was built natively in Android. To integrate this into the cross-platform Flutter app, we used platform channels, which enable native code to communicate with Flutter without compromising performance or stability.

This allowed us to reuse existing native functionality without rewriting it from scratch, saving development time and preserving performance.

Embedding Secure Surveys into the App

We integrated Jotform to handle both onboarding and post-session surveys. To ensure every form submission was legitimate, we added a secure, user-specific signature to each request.

This method prevents forgery and guarantees that user identities remain protected.

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Designing a Privacy-Focused Data Architecture

Working with sensitive neurological and mental health data demands strict privacy. We built a custom data structure that securely links survey responses to neurofeedback session data, without exposing personal identifiers.

The result: a system that meets best privacy practices and provides clinicians with the insights they need to track therapy outcomes.

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Our work on MindLoop demonstrates how we enable apps to connect with external devices, handle real-time data, and maintain security. We also made the app work smoothly across platforms using Flutter and protected user privacy, which is especially important for health-related products.

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