ABIPA: ARIMA-Based Integration of Accelerometer-Based Physical Activity for Adolescent Weight Status Prediction

Author:

Wang Yiyuan1ORCID,Wattelez Guillaume2ORCID,Frayon Stéphane2ORCID,Caillaud Corinne1ORCID,Galy Olivier2ORCID,Yacef Kalina1ORCID

Affiliation:

1. The University of Sydney, Sydney, NSW, Australia

2. Université de la Nouvelle-Calédonie, New Caledonia

Abstract

Obesity is a global health concern associated with various demographic and lifestyle factors including physical activity (PA). Research studies generally used self-reported PA data or, when accelerometer-based activity trackers were used, highly aggregated data (e.g., daily average). This suggests that the rich potential of detailed activity tracker data is largely under-exploited and that deeper analyses may help better understand such relationships. This is particularly true in children and adolescents who are distinct and engage more in bursts of PA. This article presents ABIPA, a machine learning-based methodology that integrates various aspects of accelerometer-based PA data into weight status prediction for adolescents. We propose a method to derive features regarding the structure of different PA time series using Auto-Regressive Integrated Moving Average (ARIMA). The ARIMA-based PA features are combined with other individual attributes to predict weight status and the importance of these features is further unveiled. We apply ABIPA to a dataset about young adolescents (N = 206) containing, for each participant, a 7-day continuous accelerometer dataset (60 Hz, GENEActiv tracker from ActivInsights) and a range of their socio-demographic, anthropometric, and lifestyle information. The results indicate that our method provides a practical approach for integrating accelerometer-based PA patterns into weight status prediction and paves the way for validating their importance in understanding obesity factors.

Publisher

Association for Computing Machinery (ACM)

Subject

Health Information Management,Health Informatics,Computer Science Applications,Biomedical Engineering,Information Systems,Medicine (miscellaneous),Software

Reference62 articles.

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