This caloric measurement device integrates biomechanical machine learning models for precise energy expenditure tracking. Preliminary results, visualized in the accompanying graph, demonstrate promising accuracy within 3 to 20%. As more data is collected and fed into the model, the device’s predictive accuracy is expected to improve significantly, enabling more reliable and robust real-world applications. Specifics of the model can not be provided currently due to the project being in the reviewing stages.