Gas Sensing Technologies and Algorithms for Measurement of Energy Expenditure in Humans: A Review

The quantitative assessment of human energy expenditure is of critical importance to clinical diagnostics, nutritional management, and sports science. As the gold standard methodology, indirect calorimetry determines energy expenditure through the measurement of oxygen consumption and carbon dioxide production. However, translating these principles into robust monitoring systems involves complex engineering hurdles. This review organizes the technical discussion around three interrelated challenges inherent to indirect calorimetry systems: (1) intrinsic hardware limitations in gas sensors, (2) complexities in data processing, and (3) discrepancies between laboratory and field environments. The discussion begins with the fundamental principles of energy expenditure calculation, followed by an in-depth analysis of key sensor technologies (e.g., turbine and differential pressure flowmeters; electrochemical and paramagnetic oxygen sensors; non-dispersive infrared carbon dioxide sensors). Subsequently, particular attention is given to algorithmic solutions for mitigating hardware deficiencies—such as noise, latency, and drift—as well as multi-sensor fusion and calibration techniques. Crucially, this review addresses the practical obstacles hindering the transition to real-world applications, encompassing economic viability, regulatory compliance, user usability, and long-term maintenance. The review concludes that while hardware limitations persist, the synergistic application of sophisticated algorithms and the resolution of practical implementation hurdles are indispensable for advancing measurement accuracy and facilitating the transition of metabolic monitoring from controlled laboratory settings to real-world applications in personalized health and performance tracking.