Estimating Energy Expenditure with ActiGraph GT9X Inertial Measurement Unit

AbstractPURPOSEThe purpose of this study was to explore whether gyroscope and magnetometer data from the ActiGraph GT9X improved accelerometer-based predictions of energy expenditure (EE).METHODSThirty participants (mean±SD; age, 23.0±2.3 years; BMI, 25.2±3.9 kg/m2) volunteered to complete the study. Participants wore five GT9X monitors (right hip, both wrists, and both ankles) while performing ten activities ranging from rest to running. A Cosmed K4b2 was worn during the trial, as a criterion measure of EE (30-s averages) expressed in metabolic equivalents (METs). Triaxial accelerometer data (80 Hz) were converted to milli-G's using Euclidean norm minus one (ENMO; 1-s epochs). Gyroscope data (100 Hz) were expressed as a vector magnitude (GVM) in degrees per second (1-s epochs) and magnetometer data (100 Hz) were expressed as direction changes per five seconds. Minutes 4-6 of each activity were used for analysis. Three two-regression algorithms were developed for each wear location: 1) ENMO; 2) ENMO and GVM; and 3) ENMO, GVM, and direction changes. Leave-one-participant-out cross-validation was used to evaluate the root mean square error (RMSE) and mean absolute percent error (MAPE) of each algorithm.RESULTSAdding gyroscope to accelerometer-only algorithms resulted in RMSE reductions between 0.0 METs (right wrist) and 0.17 METs (right ankle), and MAPE reductions between 0.1% (right wrist) and 6.0% (hip). When direction changes were added, RMSE changed by ≤ 0.03 METs and MAPE by ≤ 0.21%.CONCLUSIONThe combined use of gyroscope and accelerometer at the hip and ankles improved individual-level prediction of EE, compared to accelerometer only. For the wrists, adding gyroscope produced negligible changes. The magnetometer did not meaningfully improve estimates for any algorithms. PURPOSE The purpose of this study was to explore whether gyroscope and magnetometer data from the ActiGraph GT9X improved accelerometer-based predictions of energy expenditure (EE). METHODS Thirty participants (mean±SD; age, 23.0±2.3 years; BMI, 25.2±3.9 kg/m2) volunteered to complete the study. Participants wore five GT9X monitors (right hip, both wrists, and both ankles) while performing ten activities ranging from rest to running. A Cosmed K4b2 was worn during the trial, as a criterion measure of EE (30-s averages) expressed in metabolic equivalents (METs). Triaxial accelerometer data (80 Hz) were converted to milli-G's using Euclidean norm minus one (ENMO; 1-s epochs). Gyroscope data (100 Hz) were expressed as a vector magnitude (GVM) in degrees per second (1-s epochs) and magnetometer data (100 Hz) were expressed as direction changes per five seconds. Minutes 4-6 of each activity were used for analysis. Three two-regression algorithms were developed for each wear location: 1) ENMO; 2) ENMO and GVM; and 3) ENMO, GVM, and direction changes. Leave-one-participant-out cross-validation was used to evaluate the root mean square error (RMSE) and mean absolute percent error (MAPE) of each algorithm. RESULTS Adding gyroscope to accelerometer-only algorithms resulted in RMSE reductions between 0.0 METs (right wrist) and 0.17 METs (right ankle), and MAPE reductions between 0.1% (right wrist) and 6.0% (hip). When direction changes were added, RMSE changed by ≤ 0.03 METs and MAPE by ≤ 0.21%. CONCLUSION The combined use of gyroscope and accelerometer at the hip and ankles improved individual-level prediction of EE, compared to accelerometer only. For the wrists, adding gyroscope produced negligible changes. The magnetometer did not meaningfully improve estimates for any algorithms. Corresponding Author: Name: Paul Hibbing, Mailing Address: Department of Kinesiology, Recreation, and Sport Studies, 1914 Andy Holt Ave, Knoxville, TN 37996, Email: phibbing@vols.utk.edu This study was not funded. The authors declare no conflicts of interest. The results of this study are presented clearly, honestly, and without fabrication, falsification, or inappropriate data manipulation. This study does not constitute endorsement by ACSM. Accepted for Publication: 17 December 2017 © 2017 American College of Sports Medicine

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