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| + | # 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. |
| + | |
| + | 1. Core platform for real-time signals, features, and states. |
| + | 2. Construct axes as reusable dimensions. |
| + | 3. 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. |