Indirect Calorimeter Market Size

Global Indirect Calorimeter Market size was valued at USD 58.6 billion in 2023 and is poised to grow from USD 62.64 billion in 2024 to USD 106.83 billion by 2032, growing at a CAGR of 6.9% during the forecast period (2025-2032). 

The indirect calorimeter market is witnessing consistent growth due to the increasing focus on metabolic health, nutritional assessment, and critical care monitoring. Indirect calorimeters are used to measure a patient’s energy expenditure by analyzing oxygen consumption and carbon dioxide production, making them essential tools in hospitals, sports science, and clinical nutrition. With rising prevalence of lifestyle-related conditions such as obesity, diabetes, and cardiovascular diseases, the demand for accurate metabolic assessment tools has significantly expanded.

Healthcare providers are increasingly integrating indirect calorimetry into patient management protocols to personalize nutrition plans and improve recovery outcomes, especially in intensive care units (ICUs) and post-operative care. In sports and fitness applications, these devices help optimize training and dietary programs by precisely assessing energy requirements. Furthermore, technological advancements such as portable calorimeters, wireless data transmission, and improved sensor accuracy are fueling adoption across both clinical and non-clinical environments.

The market is also benefiting from supportive regulatory environments and rising healthcare investments across both developed and emerging economies. As awareness about metabolic health grows, the indirect calorimeter market is expected to expand further, driven by innovations, broader clinical applications, and increased penetration in sports, wellness, and home care settings.

How Is AI Transforming the Indirect Calorimeter Market?

Artificial Intelligence (AI) is significantly reshaping the indirect calorimeter market by enhancing the accuracy, efficiency, and personalization of metabolic health assessments. AI-driven algorithms can process large volumes of patient data in real time, enabling automated analysis of respiratory exchange rates and improving diagnostic precision. This integration not only reduces manual errors but also aids clinicians in making faster, more informed decisions especially in critical care and nutritional therapy settings.

One notable recent development occurred in March 2024, when COSMED, a leading player in the metabolic equipment space, announced the integration of AI-based analytics in its Quark RMR system. The upgrade uses machine learning to predict patient metabolic trends, helping clinicians tailor nutrition plans more effectively, particularly in intensive care and sports medicine.