Beyond Sport
Metabolic fitness and metabolic strain from heart rate.
TrueZone's metabolic scale opens a direct window into metabolic fitness (MFI) and metabolic strain (RZI)—from ordinary wearable data. Strong correlations with glycemic control and insulin sensitivity. No blood test required.
The Opportunity
Metabolic fitness is invisible to current wearables.
Cardiorespiratory fitness (CRF) is the strongest predictor of all-cause mortality. Wearables already estimate VO₂max as a CRF proxy—and so does TrueZone. But VO₂max alone misses a critical dimension: metabolic flexibility.
How efficiently does the body switch between fat and carbohydrate as fuel? How much metabolic strain does daily life impose? These questions require a metabolic scale—not just a single fitness number. TrueZone provides that scale.
- VO₂max estimate (single number, wide error margin)
- Step counts and generic calorie estimates
- No metabolic flexibility or substrate insight
- No glycolytic power tracking
- MFI: metabolic fitness correlated with glycemic control
- RZI: resting metabolic strain, trackable passively
- Glycolytic power separation without blood testing
- VO₂max derived from the same model
MFI
Metabolic Fitness Index.
A single score (0–5) that combines metabolic thresholds, cardiovascular bounds, and body size into one trackable number. MFI correlates strongly with glycemic response markers (R² = 0.99), supporting its use as a wearable-native proxy for metabolic flexibility, glycemic control, and insulin sensitivity.
Threshold speed
Speed at the lactate threshold (V2), reflecting oxidative capacity. Higher threshold speed at the same cardiac cost indicates greater metabolic efficiency.
Cardiovascular bounds
Resting heart rate and HRmax define the cardiac range. A wider range relative to threshold placement indicates better cardiovascular reserve and autonomic function.
Allometric scaling
Body size adjustment using allometric BMI reduces bias across different body types, making MFI comparable across populations without penalising larger or smaller individuals.
Glycolytic Power
Separating aerobic and glycolytic flux—without blood.
TrueZone uniquely separates metabolic demand into aerobic and glycolytic components. At any given intensity, the model estimates how much work is fuelled by oxidative metabolism and how much by glycolysis—replacing direct blood lactate testing with a heart-rate-derived estimate.
This matters for health because glycolytic power and glycolytic heart rate are blunted in ageing, obesity, and diabetes. Tracking glycolytic capacity over time provides a window into metabolic decline that no other wearable metric offers.
In healthy individuals
Clear separation between aerobic and glycolytic zones. High glycolytic power available when needed. Heart rate rises steeply through the glycolytic domain during intense effort.
In metabolic decline
Glycolytic power is blunted. The glycolytic heart rate response is compressed. The body loses its ability to access high-intensity energy systems—a pattern seen in ageing, obesity, and insulin resistance.
Metabolic Zones
Where daily life sits on the metabolic scale.
Metabolic zones map the slow domain (rest to moderate intensity) into three personalised heart rate bands anchored to your individual thresholds. The Metabolic Gradient (0–3) and Resting Zone Index (RZI) provide a simple, individualised window into metabolic state at rest—where two people with the same resting heart rate may sit in entirely different metabolic zones.
Below P0. Deep basal metabolism, predominantly fat-dominant. A young, fit individual rests deep in Z0 with low RZI—indicating strong fat-oxidation reserve and autonomic efficiency.
P0 to P0.5. Mixed oxidative metabolism with rising glucose flux. As fitness declines or metabolic load increases, resting HR shifts upward into Z1—a higher RZI and increasing carbohydrate reliance at rest.
P0.5 to P1. Upper slow domain with fast-oxidative onset. When even easy walking places someone in Z2, it signals significant metabolic strain—common in deconditioning, obesity, and ageing.
Resting Zone Index (RZI): Where your resting heart rate falls on the Metabolic Gradient (0–3). Lower RZI indicates greater fat-dominant reserve and better metabolic fitness. Higher RZI suggests a shift toward carbohydrate reliance at rest. Because thresholds are personalised, RZI is individualised—not just a heart rate number.
CRF & Endurance
VO₂max and Endurance—two dimensions of fitness.
TrueZone derives VO₂max from submaximal data, just as other wearable platforms do. But it also extracts Endurance (E)—a parameter that captures aerobic efficiency and fat-oxidation capacity independently of absolute aerobic power.
VO₂max reflects total aerobic capacity and remains the primary CRF marker. Endurance (E) adds a complementary dimension: the proportion of that capacity covered by efficient, fat-dominant metabolism. In older adults, where maximum speed declines, E becomes increasingly important as an indicator of metabolic reserve. Those with higher E benefit from lower metabolic strain at rest.
Energy Expenditure
Endurance-aware calorie estimation.
Current wearable calorie estimates use generic HR–VO₂ regressions that treat every user the same. A high-endurance individual and a sedentary person at the same heart rate have very different metabolic costs—but generic models cannot distinguish them.
TrueZone incorporates the endurance parameter (E) into energy expenditure estimation, separating basal, activity, and feeding components. Validated against indirect calorimetry at 5.8% mean absolute error.
Energy Intake (Pilot)
Postprandial HR dynamics.
After eating, heart rate rises as the body directs blood flow to digestion—the thermic effect of food. TrueZone includes pilot-scale modelling of these postprandial heart rate responses to estimate energy intake from HR dynamics alone.
This is early-stage research, but the signal is detectable. Combined with energy expenditure, it opens the door to continuous, non-invasive energy balance estimation from a single wearable sensor.
Validation
Validated in two clinical studies.
The metabolic calculations have been validated in the METFIT PhD study at the University of Iceland and in the FITSILVER Eurostars project—a total of 70 participants across three scientific papers (submitted).
MFI vs glycemic response
MFI correlates strongly with glycemic response markers in controlled feeding studies, supporting its use as a wearable-native proxy for metabolic flexibility and insulin sensitivity.
Energy expenditure MAE
Mean absolute error against indirect calorimetry (metabolic cart) during rest, walking, running, and recovery. Validated in the FITSILVER Eurostars project with CSEM, Switzerland.
Energy intake MAE
Mean absolute error in pilot-scale energy intake estimation from postprandial heart rate dynamics, validated against controlled standardised meals.
Applications
Where metabolic health meets scale.
These capabilities are designed for platforms that serve populations—not just athletes. The same SDK, the same parameters, applied to health instead of performance.
Digital health platforms
Integrate metabolic fitness screening into consumer health apps. Replace step counts with physiologically grounded metrics like MFI and RZI.
Corporate wellness
Track workforce metabolic health at scale using existing wearable data. Identify metabolic risk trends before clinical symptoms appear.
Preventive medicine
Provide clinicians with continuous, non-invasive metabolic monitoring. MFI and RZI as trackable vital signs for metabolic risk.
Ageing research
Longitudinal tracking of metabolic flexibility decline and glycolytic blunting. Quantify the effect of interventions on metabolic trajectories over months and years.
Obesity and insulin resistance
Metabolic zones reveal substrate inflexibility. Track changes in fat oxidation capacity, glycolytic power, and metabolic state through lifestyle interventions.
Clinical trials
Continuous, objective metabolic endpoints from wearable data. Reduce reliance on periodic lab visits for metabolic assessment.
The same heart rate signal. A new layer of insight.
MFI, RZI, glycolytic power, metabolic zones, and energy balance—all derived from data your users already collect. No hardware changes. No blood tests.