Neurofeedback Platform: Engineering Stack & SDK

High-Level Stack Overview

This platform is the backbone for building personalized neurofeedback applications. We separate core engineering from student-facing creativity. The result is a modular system: engineers build robust core libraries, while PhD/Masters students (or other developers) innovate apps on top.

Core platform for real-time signals, features, and states.
Construct axes as reusable dimensions.
SDK for student-led app development—defining new states, feedback, and interaction designs.

Core Platform Engineering Stack

Signal Acquisition & Processing

Integrate EEG (MVP) first, with future support for fNIRS.
Handle device streams, timestamps, channel metadata, and signal quality (impedance, artifacts).
Preprocessing includes: filtering, rereferencing, artifact detection, and signal reliability scoring.

Marker/Feature Extraction

Core library of evidence-backed markers (e.g. SMR, individualized alpha, theta/beta ratio, SCPs).
Expandable registry of features (e.g. band power, coherence).
Each marker is well-defined: modality, channels, latency, and evidence level.

Construct Axes Calculation

Axes are high-level dimensions derived from markers (e.g. Calm Focus, Task Engagement, Cognitive Control).
Each axis fuses multiple markers.
Axes are reusable across apps, acting as stable “control knobs.”

Task-Specific States

Pre-defined states are combinations of axes (e.g. calm-focused, distracted, over-aroused).
States are what apps respond to.

SDK for Student-Led Development

Defining New States

Students combine existing axes to create new states relevant to their domain.
Example: Define a “flow state” as a combination of high Task Engagement and Calm Focus.

Feedback Policy & Interactive Design

SDK exposes state listeners. Students define how feedback adapts when states change.
Students can build interactive experiences—games, tasks, or interfaces that shift based on user brain state.
Feedback can be visual, auditory, or task difficulty changes.

Vibecoding in the SDK

Students create new neurofeedback apps by:
- Subscribing to states or axes.
- Designing novel feedback rules (e.g. when calm, show visual expansion).
- Creating interactive games or tasks that adapt to brain state shifts.