Using GPS, accelerometry and heart rate to predict outdoor graded walking energy expenditure

Abstract Objectives To determine the best method and combination of methods among global positioning system (GPS), accelerometry, and heart rate (HR) for estimating energy expenditure (EE) during level and graded outdoor walking. Design Thirty adults completed 6-min outdoor walks at speeds of 2.0, 3.5, and 5.0 km h −1 during three randomized outdoor walking sessions: one level walking session and two graded (uphill and downhill) walking sessions on a 3.4% and a 10.4% grade. EE was measured using a portable metabolic system (K4b 2 ). Participants wore a GlobalSat ® DG100 GPS receiver, an ActiGraph™ wGT3X+ accelerometer, and a Polar ® HR monitor. Linear mixed models (LMMs) were tested for EE predictions based on GPS speed and grade, accelerometer counts or HR-related parameters (alone and combined). Root-mean-square error (RMSE) was used to determine the accuracy of the models. Published speed/grade-, count-, and HR-based equations were also cross-validated. Results According to the LMMs, GPS was as accurate as accelerometry (RMSE = 0.89–0.90 kcal min −1 ) and more accurate than HR (RMSE = 1.20 kcal min −1 ) for estimating EE during level walking; GPS was the most accurate method for estimating EE during both level and uphill (RMSE = 1.34 kcal min −1 )/downhill (RMSE = 0.84 kcal min −1 ) walking; combining methods did not increase the accuracy reached using GPS (or accelerometry for level walking). The cross-validation results were in accordance with the LMMs, except for downhill walking. Conclusions Our study provides useful information regarding the best method(s) for estimating EE with appropriate equations during level and graded outdoor walking.