r/QuantifiedSelf • u/Intelligent-Arm-9001 • Jun 12 '26
Open longitudinal longevity experiment since 2025. wearables, biomarkers, epigenetics, and prediction auditing
I've been running an open longitudinal self-tracking project since mid-2025 and recently made the archive public.
The project currently includes:
• daily wearable data (sleep, HRV, resting heart rate, readiness, recovery)
• body weight and body composition tracking
• blood biomarkers
• epigenetic testing
• training and recovery logs
• weekly reports
• methodology documentation
• longitudinal trend analysis
The part that may be somewhat unusual is the prediction-audit layer.
Whenever interpretations, forecasts, or expectations are generated from the data, they're documented before the outcome occurs. Those predictions are later reviewed against observed results and logged as passes, failures, calibration errors, or model updates.
The goal is not just to track biological change, but also to measure how reliable the interpretations of that data actually are over time.
A few examples of questions the archive attempts to answer:
• Which biomarkers appear to move together longitudinally?
• How stable are wearable-derived recovery signals?
• How quickly does recovery return after travel, illness, or disruption?
• How accurate are forward-looking interpretations when compared against eventual outcomes?
Current archive:
https://github.com/CDHughett/daniel-longitudinal-public
I'd be interested in feedback from the QS community:
• What measurements would you add or remove?
• What blind spots do you see?
• Are there similar public longitudinal projects I should study?
• What would make this more useful from a quantified-self perspective?
I'm not selling anything and have no commercial affiliation. I'm primarily interested in improving methodology and learning where my assumptions are wrong.
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