GPS-Based Prediction of Energy Expenditure for Slow and Fast Outdoor Walking

Abstract

GPS monitors may prove to be an invaluable tool for investigations for Free-Living Activities but first need to be assessed as valid research instruments. PURPOSE: The purpose of this study was to determine the accuracy of GPS monitors for estimating energy expenditure (EE) for slow and fast outdoor walking and to evaluate differences in the predictive ability of waist and wrist-worn GPS monitors. METHODS: Thirteen subjects (28.4 ± 2.8 yrs, 67.2 ± 12.2 kg, 171.7 ± 9.4 cm) volunteered to complete a 2.4 km course at self-selected slow and fast walking paces. The course started at 1500m and featured 60 m elevation gain and 60 m elevation loss. The course distance was measured using a calibrated measuring wheel. Heart rate was monitored to identify intensity for each pace, insure constant intensity at each pace, and verify a distinction between fast and slow paces for each subject. Each subject carried two WAAS-Enabled GPS monitors, one wrist-worn and one waist-worn, as well as a portable metabolic unit to measure EE (total mass = 2.35 kg). GPS accuracy was reported as 5 – 10m for all trials. Time for each trial was measured using a stopwatch. Equations were used to estimate the energy cost of walking from speed and grade (Minetti, 2002), as well as the energy cost of wind resistance (Pugh, 1970) to calculate the total EE (EEGPS) for walking. Metabolic data collected was converted from VO2 and VCO2 into Kcals using the equation by Weir (1949). Comparisons between EE and EEGPS were made using repeated measures ANOVA. RESULTS: Prior to data analysis, two outliers were removed due to exceedingly large values for EEGPS. EEGPS (130.4 ± 15.4 Kcals) and EE (107.4 ± 25.8 Kcals) were significantly different (p < 0.01) when both GPS monitors and speeds were considered. There was no significant difference between the two GPS monitors for predicting total EE (128.6 ± 24.3 and 132.3 ± 26.9 Kcals for wrist and waist-worn, respectively; p=0.20), EE during fast walking (124.7 ±22.1; p=0.11), or EE during slow walking (132.9 ± 26.7; p=0.41). Using only waist-worn GPS data, EEGPS (132.87 ± 26.7 Kcals) and EE (101.7 ±25.3 Kcals) were significantly different (p < 0.01) for slow walking, but not for fast walking (EEGPS = 124.7±22.1 Kcals, EE= 113.7±26.2 Kcals; p=0.09). CONCLUSIONS: The WAAS-enabled GPS monitors significantly over-predicted EE except when the analysis was limited to fast-paced walking. GPS monitor placement should not be a concern for future studies, as both the wrist and waist-worn GPS monitors provided similar estimates for EE across all conditions. Due to variance in the GPS signal, GPS monitors appear better suited to estimate EE for fast walking (or possibly running), rather than slow walking.