Establishing cut-points for physical activity classification using triaxial accelerometer in middle-aged recreational marathoners

• Published in: PloS one Vol. 13; no. 8; p. e0202815
• Main Authors: Hernando, Carlos, Hernando, Carla, Collado, Eladio Joaquin, Panizo, Nayara, Martinez-Navarro, Ignacio, Hernando, Barbara
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 29.08.2018; Public Library of Science (PLoS)
• Subjects: Accelerometers; Accelerometry; Adult; Adults; Area Under Curve; Biology and Life Sciences; Classification; Correlation analysis; Data collection; Energy; Energy expenditure; Energy Metabolism; Engineering and Technology; Exercise; Exercise Test - methods; Female; Females; Health aspects; Health sciences; Heart rate; Humans; Male; Males; Marathons; Medicine and Health Sciences; Metabolism; Middle age; Middle Aged; Physical activity; Physical fitness; Recreation; ROC Curve; Running; Running - classification; Sex; Sex Factors; Statistical analysis; Statistical methods; Studies; Support Vector Machine; Wrist; Spain
• ISSN: 1932-6203; 1932-6203
• DOI: 10.1371/journal.pone.0202815

The purpose of this study was to establish GENEA (Gravity Estimator of Normal Everyday Activity) cut-points for discriminating between six relative-intensity activity levels in middle-aged recreational marathoners. Nighty-eight (83 males and 15 females) recreational marathoners, aged 30-45 years, completed a cardiopulmonary exercise test running on a treadmill while wearing a GENEA accelerometer on their non-dominant wrist. The breath-by-breath V̇O2 data was also collected for criterion measure of physical activity categories (sedentary, light, moderate, vigorous, very vigorous and extremely vigorous). GENEA cut-points for physical activity classification was performed via Receiver Operating Characteristic (ROC) analysis. Spearman's correlation test was applied to determine the relationship between estimated and measured intensity classifications. Statistical analysis were done for all individuals, and separating samples by sex. The GENEA cut-points established were able to distinguish between all six-relative intensity levels with an excellent classification accuracy (area under the ROC curve (AUC) values between 0.886 and 0.973) for all samples. When samples were separated by sex, AUC values were 0.881-0.973 and 0.924-0.968 for males and females, respectively. The total variance in energy expenditure explained by GENEA accelerometer data was 78.50% for all samples, 78.14% for males, and 83.17% for females. In conclusion, the wrist-worn GENEA accelerometer presents a high capacity of classifying the intensity of physical activity in middle-aged recreational marathoners when examining all samples together, as well as when sample set was separated by sex. This study suggests that the triaxial GENEA accelerometers (worn on the non-dominant wrist) can be used to predict energy expenditure for running activities.