Classic muscle biopsy work by Per Bergström and Bengt Hultman, Uppsala University, established how muscle glycogen falls with sustained exercise and forms the physiological baseline for understanding depletion. Modern wearables cannot directly measure muscle glycogen, so the best predictors are those that estimate the athlete’s instantaneous and cumulative metabolic demand. Heart rate, running power, and pace/grade are the primary wearable metrics that, when combined, most accurately indicate approaching glycogen depletion. Each metric has limitations that change with environment, individual physiology, and device algorithms.
Physiological basis and evidence
Intensity determines the fraction of energy supplied from carbohydrate versus fat. Louise Burke, Australian Catholic University, emphasizes that higher intensity raises carbohydrate reliance and shortens time to depletion. Heart rate is a long-used proxy for oxygen uptake and thus for metabolic intensity, but it lags changes and is influenced by temperature, hydration, and stress. Running power from dedicated sensors more closely tracks mechanical work and instantaneous metabolic load on varied terrain, so it often improves prediction when available. Pace combined with GPS-derived grade and body mass can estimate metabolic rate where power meters are absent. Continuous glucose monitors measure blood glucose, not muscle glycogen, and can remain normal even as glycogen stores fall, so they are insufficient alone to signal depletion.
Causes, consequences, and contextual nuance
Causes of early glycogen depletion include prolonged high intensity, inadequate pre-race carbohydrate loading, or low-carbohydrate training; environmental heat, altitude, and hilly terrain all increase carbohydrate oxidation. Consequences range from impaired running economy and abrupt pace decline ("bonking") to cognitive impairment and increased injury risk. Cultural and territorial factors matter: dietary habits and access to carbohydrate-rich race fueling differ by region, and heat common in tropical races raises heart rate and carbohydrate use compared with temperate marathons.
In practice, the most reliable approach uses a fusion of wearable signals: rising heart rate relative to pace, sustained high running power or high pace on climbs, accumulated time at high intensity, and subjective strain. Coaches and athletes should interpret wearable estimates alongside planned fueling strategies and validated sports-nutrition guidance rather than expecting a single device metric to declare glycogen status. Real-time prediction improves when devices are calibrated to the athlete and contextualized for environment and prior nutrition.