To build a valuable, long-term dataset without triggering FDA medical device regulation, your EEG headband must stick strictly to General Wellness metrics.

Under FDA guidelines, you can collect a massive amount of data and raw signals with user consent, provided the metrics are framed around optimizing, tracking, or maintaining daily fitness, sleep, and cognitive performance [fda.gov]. They must never mention diagnosing, predicting, or screening for clinical conditions [fda.gov].

Here is the maximum classification of metrics you can collect safely for your longitudinal dataset, categorized by how they should be named and presented to the user.

1. Raw Data & Signal Characteristics (The Goldmine)

You can collect and store almost any raw physiological signal. The FDA regulates claims, not raw numbers. As long as you do not label these numbers as a "dementia risk score" in your database or app, you can collect them:

• Raw EEG Microvolts (μ V): Continuous time-series brainwave data.
• Power Spectral Density (PSD): The distribution of signal power across frequencies.
• Individual Frequency Bands: Absolute and relative power of Delta (0.5–4Hz), Theta (4–8Hz), Alpha (8–12Hz), Beta (12–30Hz), and Gamma (30–100Hz).
• Sensorimotor Rhythm (SMR): Brain activity associated with physical calmness and mental alertness (12–15Hz).
• Brain Symmetry & Connectivity: Coherence metrics mapping how well different areas of the brain are communicating with each other. [1, 2, 3, 4, 5]

2. Cognitive Performance & Focus Metrics

You can track cognitive states, provided they are framed as tools for productivity, studying, or workplace performance:

• Focus / Attention Score: Real-time tracking of mental concentration during tasks.
• Mental Fatigue / Burnout Index: Measuring cognitive strain or tiredness over a workday.
• Flow State Tracking: Identifying periods of deep, effortless concentration.
• Cognitive Load: Measuring how hard the brain is working to process information.
• Distraction Alerts: Detecting when a user’s mind wanders from a task. [6]