Integration of wearable sensors with metabolic chamber data assesses energy expenditure, suggesting the potential for broader applications.
Accurate assessment of energy expenditure is crucial for characterizing human metabolism and health. The gold standard method for measuring energy expenditure is indirect calorimetry in a metabolic chamber, which provides accurate estimates of metabolic rate under controlled conditions. However, the limited availability of metabolic chambers worldwide limits large-scale research and clinical applications. Wearable technologies offer a promising alternative, allowing continuous monitoring of key physiological parameters such as heart rate variability, electrodermal activity, and physical activity, all of which correlate with metabolic rate. This study integrates 24-hour metabolic chamber measurements and multimodal wearable sensor data to quantify day-night (diurnal-nocturnal) differences in energy expenditure and autonomic state. Physiological data were collected using two multimodal wearable devices: a textile-based smart t-shirt (Wearable Wellness System, Smartex) and a wrist-worn smartwatch (Embrace Plus, Empatica). In a preliminary sample of six healthy men, the median metabolic rate was 42% higher during the daytime compared to nighttime, mirroring a 3.1-fold increase in sympathetic electrodermal activity power during the day. During daytime, metabolic rate showed the strongest pooled Spearman correlations with heart rate variability features derived from the smart t-shirt: mean RR interval (average time between heartbeats; ρ=−0.37), low-frequency (ρ=−0.31), and high-frequency (ρ=−0.28) components. At night, tonic electrodermal activity (EDA) features from the smartwatch (Embrace Plus) were most informative, with the minimum (minTonic, lowest baseline skin conductance, ρ=0.36) and mean (meanTonic, average baseline skin conductance, ρ=0.34) values showing the highest associations. Synchronizing wearable-derived measures with continuous chamber calorimetry validates their ability to track diurnal metabolic dynamics and provides a foundati...
No takes yet. Share an insight, caveat, or question.
Pisaneschi et al. (2025) studied this question.
Synapse has enriched 5 closely related papers on similar clinical questions. Consider them for comparative context: