A system for objectively measuring behavior and the environment to support large-scale studies on childhood obesity

TL;DR

This paper introduces an integrated IoT-based system that passively collects and analyzes behavioral and environmental data to support large-scale childhood obesity studies, offering detailed insights and evaluation results.

Contribution

The paper presents a novel, unified system combining multiple technologies and algorithms for large-scale, fine-grained behavior and environment monitoring related to childhood obesity.

Findings

Step counting error of 8-9 steps

F1-score of 0.86 for location detection

Less than 12 minutes error in sleep time estimation

Abstract

Advances in IoT technologies combined with new algorithms have enabled the collection and processing of high-rate multi-source data streams that quantify human behavior in a fine-grained level and can lead to deeper insights on individual behaviors as well as on the interplay between behaviors and the environment. In this paper, we present an integrated system that collects and extracts multiple behavioral and environmental indicators, aiming at improving public health policies for tackling obesity. Data collection takes place using passive methods based on smartphone and smartwatch applications that require minimal interaction with the user. Our goal is to present a detailed account of the design principles, the implementation processes, and the evaluation of integrated algorithms, especially given the challenges we faced, in particular (a) integrating multiple technologies, algorithms, and components under a single, unified system, and (b) large scale (big data) requirements. We also present evaluation results of the algorithms on datasets (public for most cases) such as an absolute error of 8-9 steps when counting steps, 0.86 F1-score for detecting visited locations, and an error of less than 12 mins for gross sleep time. Finally, we also briefly present studies that have been materialized using our system, thus demonstrating its potential value to public authorities and individual researchers.