TY - GEN
T1 - BigO
T2 - 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society, EMBC 2020
AU - DIou, Christos
AU - Sarafis, Ioannis
AU - Papapanagiotou, Vasileios
AU - Alagialoglou, Leonidas
AU - Lekka, Irini
AU - Filos, Dimitrios
AU - Stefanopoulos, Leandros
AU - Kilintzis, Vasileios
AU - Maramis, Christos
AU - Karavidopoulou, Youla
AU - Maglaveras, Nikos
AU - Ioakimidis, Ioannis
AU - Charmandari, Evangelia
AU - Kassari, Penio
AU - Tragomalou, Athanasia
AU - Mars, Monica
AU - Ngoc Nguyen, Thien An
AU - Kechadi, Tahar
AU - O'Donnell, Shane
AU - Doyle, Gerardine
AU - Browne, Sarah
AU - O'Malley, Grace
AU - Heimeier, Rachel
AU - Riviou, Katerina
AU - Koukoula, Evangelia
AU - Filis, Konstantinos
AU - Hassapidou, Maria
AU - Pagkalos, Ioannis
AU - Ferri, Daniel
AU - Perez, Isabel
AU - Delopoulos, Anastasios
PY - 2020/7
Y1 - 2020/7
N2 - Obesity is a complex disease and its prevalence depends on multiple factors related to the local socioeconomic, cultural and urban context of individuals. Many obesity prevention strategies and policies, however, are horizontal measures that do not depend on context-specific evidence. In this paper we present an overview of BigO (http://bigoprogram.eu), a system designed to collect objective behavioral data from children and adolescent populations as well as their environment in order to support public health authorities in formulating effective, context-specific policies and interventions addressing childhood obesity. We present an overview of the data acquisition, indicator extraction, data exploration and analysis components of the BigO system, as well as an account of its preliminary pilot application in 33 schools and 2 clinics in four European countries, involving over 4,200 participants.
AB - Obesity is a complex disease and its prevalence depends on multiple factors related to the local socioeconomic, cultural and urban context of individuals. Many obesity prevention strategies and policies, however, are horizontal measures that do not depend on context-specific evidence. In this paper we present an overview of BigO (http://bigoprogram.eu), a system designed to collect objective behavioral data from children and adolescent populations as well as their environment in order to support public health authorities in formulating effective, context-specific policies and interventions addressing childhood obesity. We present an overview of the data acquisition, indicator extraction, data exploration and analysis components of the BigO system, as well as an account of its preliminary pilot application in 33 schools and 2 clinics in four European countries, involving over 4,200 participants.
U2 - 10.1109/EMBC44109.2020.9175361
DO - 10.1109/EMBC44109.2020.9175361
M3 - Conference paper
AN - SCOPUS:85091005901
T3 - Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
SP - 5864
EP - 5867
BT - 42nd Annual International Conferences of the IEEE Engineering in Medicine and Biology Society
PB - Institute of Electrical and Electronics Engineers Inc.
Y2 - 20 July 2020 through 24 July 2020
ER -
