The Science

A number you can audit.

The Signal Score is deterministic fusion, not a black box. We use Kalman filtering and CUSUM to detect longitudinal decline early — and we tell you exactly which parts are computed, estimated, or merely narrated.

Deterministic fusion

Domain signals are normalized, weighted, and combined by a fixed formula. The same inputs always produce the same Signal Score — independently verifiable.

InputsNormalized signalsEach domain scaled to a common 0–1 range with device-level provenance retained.
Fusion weighted sumFixed, published weights map signals → Physical + Cognitive sub-scores.
Output0–100 + R/A/GA single composite and a traffic light from published thresholds.

Catching decline before it's obvious

A Kalman filter smooths noisy day-to-day signal into a stable state estimate. CUSUM accumulates small deviations and raises an early-decline alarm the moment the trend breaks — weeks before a person would self-report feeling off.

HRV-derived signal · 12-week window
Raw signalKalman estimateCUSUM alarm
CUSUM alarm · wk 10

At week 10, CUSUM crosses threshold — the estimated state has drifted enough to flag early decline. This is an estimate with a confidence band, not a diagnosis.

What's computed, estimated, or narrated

Every figure in the app carries its epistemic status. You always know how much to trust a number — and where the model's judgment begins and ends.

Deterministic

Deterministic

Computed by a fixed formula. Reproducible to the bit. No model judgment.

Signal Score · sub-scores · R/A/G threshold

Estimated

Estimated

Statistical inference with a stated confidence band. Updates as data arrives.

Kalman state estimate · CUSUM change-point · VO₂ est.

Narrated

Narrated

Plain-language explanation of the numbers above. The LLM describes, it never decides.

Monthly summary · trend narration

The LLM only narrates. It turns the deterministic and estimated numbers into plain language. It cannot change a score, move a traffic light, or raise an alarm — those are computed, not generated.

Methodology you can put in front of a clinician.