Equity by construction
Intuitive Pathos builds physiological monitoring designed around each person’s own baseline rather than a population mean that was never built to include them. The aim is fairness built into the mathematics rather than promised in a policy, and it has to be measured group by group before anyone can claim it.
See it for yourself
A resting heart rate of 92 bpm sits comfortably inside the textbook adult range. For one of the two people below, it is the clearest warning of the day. Drag the reading, or jump to a scenario.
The problem
Nearly every physiological threshold in routine use is a population statistic: a range derived from some cohort of people, at some point in time, under some set of conditions. When the person in front of you resembles that cohort, the range works. When they do not, the range quietly stops being a measurement and starts being an assumption.
The failure is not that clinicians are careless. It is that the instrument itself encodes a comparison the clinician did not choose and often cannot see. A patient whose resting physiology sits at one end of a distribution can deteriorate substantially and still read “normal.” Another can be flagged, worked up, and labeled for being exactly who they have always been.
Both are errors of the same kind: a person compared against a distribution they were never part of.
This is not a hypothetical: reference-range and sensor bias are documented in the peer-reviewed literature; see the disparity case.
A number can be normal and still be wrong.
Normal for the population. Wrong for the person in front of you. Every reference range in routine use is capable of both at once.
The framework
These are not values we aspire to. They are constraints the system is constructed from, which is why we call it equity by construction.
01: the founding constraint
Statistical distance from a population mean is not, by itself, pathology. A body that runs differently from the average is reporting a fact about a distribution, not a defect in a person. Our within-subject methods are designed so that distance from the mean is never, on its own, grounds for an alert.
02: your reference range is you
Every subject accumulates a within-subject reference distribution: what their physiology does across time, rest, activity and recovery. Change is then measured against that, so the question the within-subject comparison asks is “what is different for you?” rather than “how unlike other people are you?”
03: equal and opposite
Departures above baseline (Yang) and departures below it () are treated as equal and opposite. Monitoring systems have a long habit of instrumenting one direction well and the other poorly: agitation over withdrawal, hyperactivity over shutdown, the loud failure over the quiet one. Symmetric treatment is designed to remove that asymmetry in the within-subject comparison, before it reaches a threshold or an alarm.
04: some harms should be unrepresentable
A protection enforced by policy can be waived, misconfigured or forgotten. A protection enforced by architecture cannot. Where a harm is serious enough, we design it to be something the system has no way to express, rather than something it is asked not to do. Examples include comparing a person to a demographic cohort, moving identifiable physiology off a device, and letting a non-clinical product emit a clinical conclusion.
Symmetry
Most monitoring is asymmetric by accident. The signals that get instrumented are the ones that are easy to see, easy to chart, and historically the ones that disrupted a ward. The person who becomes withdrawn, slowed, flat or unresponsive generates less noise, and so, in a system tuned by noise, less attention.
Symmetric fairness means the model does not have a preferred direction. A given magnitude of departure from a person’s own baseline carries the same weight whether it points up or down.
End to end
Continuous physiological signal from each subject, gathered over time in the setting the product is designed to serve.
Build a within-subject reference distribution over time. This is the comparison set. It belongs to one subject and is never swapped for a cohort average.
The Wu mathematics primitives, namely memory coefficient, critical slowing down, λ* criticality, and sliding-window regime detection, look for a system changing state.
The within-subject output is designed to be expressed as departure from the subject’s own baseline, with elevated and suppressed weighted equally and the direction preserved.
The federation contract is designed so that model improvement can be shared across deployments. What may cross the boundary and what may never cross it is expressed in the type system of the client rather than in a configuration setting.
Product family
The same primitives are designed to serve a critical-care unit, a veterinary clinic, a field team and a living room, because “compare this subject to themselves” is not a clinical idea. It is a measurement idea.
The regulated flagship: continuous level-of-consciousness and deterioration monitoring for acute and critical care. In FDA pre-submission preparation; not cleared or approved.
Your own physiology, on your own terms. A general-wellness application built on the per-subject baseline, with no clinical claim, by construction.
Pain and distress monitoring for animals, who cannot self-report and for whom the population-average problem is severe across breed, size and species.
Operator-state monitoring for high-consequence work, where the baseline that matters is the operator’s own and the quiet failure mode is the dangerous one.
Longitudinal wellbeing in the residential setting, oriented to gradual change against a personal baseline rather than to emergencies after the fact.
Occupational strain in industrial settings, and non-invasive stress monitoring for conservation and animal welfare research.
Where to go next
What a per-subject baseline changes at the bedside, what the regulatory posture is today, and what we will and will not claim.
Clinical overviewThe architecture of the moat, the product family, the layering strategy, and an honest statement of stage.
Platform thesisCapability statement, operator-state monitoring, data-sovereignty posture, and how to contract with us.
Capability statementThe idea in plain language: why being different from average is not the same as being unwell, and why that distinction is worth building.
The ideaWhy this exists
Every nurse has watched someone be told they were fine because their numbers matched a stranger’s. And watched someone else be treated as a problem for being exactly who they had always been.
Intuitive Pathos was founded by a registered nurse after about ten years at the bedside, not in a lab. The framework came out of the specific, repeated experience of watching measurement instruments answer the wrong question, and of noticing that the error was systematic, directional, and fixable in the mathematics rather than in the vigilance of tired people.
Talk to us
Clinical partnerships, veterinary and research deployments, government contracting, or investment: the conversation starts the same way.