The Best Choice of Oxygen Cost Prediction Equation for Computing Post-Stroke Walking Energy Expenditure Using an Accelerometer

Abstract

Background The integration of oxygen cost into the accelerometer’s algorithms improves accuracy of total energy expenditure (TEE) values as post-stroke individuals walk. Recent work has shown that oxygen cost can be estimated from specific prediction equations for stroke patients. Objective The objective is to the validity of the different oxygen cost estimation equations available in the literature for calculating TEE using ActigraphGT3x as individuals with stroke sequelae walk. Method Individuals with stroke sequelae who were able to walk without human assistance were included. The TEE was calculated by multiplying the walking distance provided by an ActigraphGT3x worn on the healthy ankle and the patient’s oxygen cost estimated from the selected prediction equations. The TEE values from each equation were compared to the TEE values measured by indirect calorimetry. The validity of the prediction methods was evaluated by Bland–Altman analysis (mean bias (MB) and limits of agreement (LoA) values). Results We included 26 stroke patients (63.5 years). Among the selected equations, those of Compagnat and Polese obtained the best validity parameters for the ActigraphGT3x: MBCompagnat = 1.2 kcal, 95% LoACompagnat = [−12.0; 14.3] kcal and MBPolese = 3.5 kcal, 95% LoAPolese = [−9.2; 16.1] kcal. For comparison, the estimated TEE value according to the manufacturer’s algorithm reported MBManufacturer = −15 kcal, 95% LoAManufacturer = [−52.9; 22.8] kcal. Conclusion The Polese and Compagnat equations offer the best validity parameters in comparison with the criterion method. Using oxygen cost prediction equations is a promising approach to improving assessment of TEE by accelerometers in post-stroke individuals.