International Conference on Smart Health

Smart Health pp 43-54

Network Analysis of Ecological Momentary Assessment Data for Monitoring and Understanding Eating Behavior

  • Gerasimos Spanakis
  • Gerhard Weiss
  • Bastiaan Boh
  • Anne Roefs
Conference paper

DOI: 10.1007/978-3-319-29175-8_5

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9545)
Cite this paper as:
Spanakis G., Weiss G., Boh B., Roefs A. (2016) Network Analysis of Ecological Momentary Assessment Data for Monitoring and Understanding Eating Behavior. In: Zheng X., Zeng D., Chen H., Leischow S. (eds) Smart Health. Lecture Notes in Computer Science, vol 9545. Springer, Cham

Abstract

Ecological Momentary Assessment (EMA) techniques have been blooming during the last years due to the emergence of smart devices (like PDAs and smartphones) that allow the collection of repeated assessments of several measures (predictors) that affect a target variable. Eating behavior studies can benefit from EMA techniques by analysing almost real-time information regarding food intake and the related conditions and circumstances. In this paper, an EMA method protocol to study eating behavior is presented along with the mobile application developed for this purpose. Mixed effects and vector autoregression are utilized for conducting a network analysis of the data collected and lead to inferring knowledge for the connectivity between different conditions and their effect on eating behavior.

Keywords

Ecological momentary assessment Mixed effects Vector autoregression Network analysis 

Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Gerasimos Spanakis
    • 1
  • Gerhard Weiss
    • 1
  • Bastiaan Boh
    • 2
  • Anne Roefs
    • 2
  1. 1.Department of Knowledge EngineeringMaastricht UniversityMaastrichtThe Netherlands
  2. 2.Faculty of Psychology and NeuroscienceMaastricht UniversityMaastrichtThe Netherlands

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