Most reference ranges in medicine are population-derived. A measurement is flagged as abnormal when it falls outside a range constructed from a reference cohort. That approach works well for measurements with narrow population-level variation and clear biological thresholds. It works less well when inter-individual variation is large and intra-individual change is more informative than absolute position.
Many physiological signals fit this second description. Two people with the same absolute measurement may be at very different points relative to their own typical range. One person may be in a stable state; the other may have shifted substantially from their baseline. Without a personal reference, both look equivalent when compared to the population norm.
Building personal baselines into infrastructure
A personal baseline requires longitudinal data, collection under stable conditions, and a model that can distinguish true biological change from measurement noise, day-to-day variation, and seasonal or behavioral effects. That is a harder statistical problem than population comparison, and it requires more data per person. It also requires that people contribute measurements over time, which means the value of the system increases as longitudinal records accumulate.
For Cytognosis, personal baselines are a core design element rather than an optional feature. The health-state coordinate system is built around the idea that deviation from an individual's own history is as important as absolute position. That choice shapes how we design data collection, how we structure models, and how we communicate results.
Open notebook
The methods for establishing and updating personal baselines are still being developed and validated. This page is part of our open notebook and will be updated as the work progresses.