HCMay 10, 2017

Visualization of Wearable Data and Biometrics for Analysis and Recommendations in Childhood Obesity

arXiv:1705.03691v18 citations
Originality Synthesis-oriented
AI Analysis

This work addresses childhood obesity for health researchers and practitioners, but it is incremental as it applies existing visualization methods to new data.

The paper tackled the problem of understanding childhood obesity by designing a dashboard for visualizing actigraphy and biometric data from a camp in Qatar, enabling quantitative discoveries to guide patient behavior and orient qualitative research.

Obesity is one of the major health risk factors be- hind the rise of non-communicable conditions. Understanding the factors influencing obesity is very complex since there are many variables that can affect the health behaviors leading to it. Nowadays, multiple data sources can be used to study health behaviors, such as wearable sensors for physical activity and sleep, social media, mobile and health data. In this paper we describe the design of a dashboard for the visualization of actigraphy and biometric data from a childhood obesity camp in Qatar. This dashboard allows quantitative discoveries that can be used to guide patient behavior and orient qualitative research.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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