Heart rate-based metabolic rate estimation for military-relevant exercises

Area of Science:

• Exercise Physiology
• Biomedical Engineering
• Military Science

Background:

• Accurate metabolic rate (Ṁ) assessment is crucial for military personnel performance and safety.
• Traditional indirect calorimetry methods are impractical for field use.
• A novel heart rate (HR)-based algorithm was developed to estimate Ṁ during military-relevant activities.

Purpose of the Study:

• To construct and validate an algorithm for estimating metabolic rate (Ṁ) using only heart rate (HR).
• To create an adaptable framework for integrating cardiometabolic fitness parameters to enhance estimation precision.
• To enable accurate Ṁ assessment during standing, walking, and running.

Main Methods:

• A dataset of cardiometabolic data was compiled from healthy adults performing steady-state activities (standing, walking, running).
• External validation was conducted using data from a separate cohort across thirteen studies.
• The Heart Rate-based Metabolic Estimation Tool (HR-MET) was developed, estimating Ṁ based on HR and optional cardiometabolic fitness parameters (HRmax, HRrest, Ṁmax, Ṁrest).

Main Results:

• The HR-MET demonstrated high accuracy with a concordance correlation coefficient (CCC) of 0.953 and root-mean-square deviation (RMSD) of 0.89 W kg⁻¹ on the development dataset.
• External validation showed strong performance with an RMSD of 1.18 W kg⁻¹ and CCC of 0.961.
• Statistical equivalence between estimated and measured Ṁ was confirmed when utilizing all available cardiometabolic fitness parameters.

Conclusions:

• The HR-MET offers a valid and accurate method for estimating metabolic rate (Ṁ) during military activities using heart rate (HR).
• Inclusion of cardiometabolic fitness parameters further optimizes HR-MET accuracy.
• The HR-MET combines laboratory-level accuracy with field applicability, enhancing readiness, safety, and performance across various domains.