Scientific Publications

2023

Ultra-Processed Food vs. Fruit and Vegetable Consumption before and during the COVID-19 Pandemic among Greek and Swedish Students. Dhammawati, F., Fagerberg, P., Diou, C., Mavrouli, I., Koukoula, E., Lekka, E., … & Ioakimidis, I. (2023).  Nutrients15(10), 2321.

2022

Towards systems models for obesity prevention: a big role for big data.  Tufford, A. R., Diou, C., Lucassen, D. A., Ioakimidis, I., O’Malley, G., Alagialoglou, L., … & Mars, M. (2022).Current Developments in Nutrition6(9), nzac123.

2021

Fast Eating is Associated with Increased BMI among High-School Students. Fagerberg, P., Charmandari, E., Diou, C., Heimeier, R., Karavidopoulou, Y., Kassari, P., Koukoula, E., Lekka, I., Maglaveras, N., Maramis, C., Pagkalos, I., Papapanagiotoum V., Riviou, K., Sarafis, I., Tragomalou, A., Ioakimidis, I. (2021).  Nutrients, 13(3), 880.  

Big Data Warehouse for Healthcare-Sensitive Data Applications. Shahid, A., Nguyen, T-A.N., Kechadi, M-T. (2021). Sensors, MDPI 21(7), 2353.

2020

Establishing consensus on key public health indicators for the monitoring and evaluating childhood obesity interventions: a Delphi panel study. O’Donnell, S., Doyle, G., O’Malley, G., Browne, S., O’Conner, J., Mars, M., Kechadi, T. (2020). BMC Public Health, 20(1): p. 1733.

Formative Evaluation of a Smartphone App for Monitoring Daily Meal Distribution and Food Selection in Adolescents: Acceptability and Usability Study. Langlet, B., Maramis, C., Diou, C., Maglaveras, N., Fagerberg, P., Heimeier, R., … & Ioakimidis, I. (2020).  JMIR mHealth and uHealth8(7), e14778.

A Data Driven End-to-end Approach for In-the-wild Monitoring of Eating Behavior Using Smartwatches. Kyritis K., Diou, C., Delopoulos, A. (2020).  IEEE Journal of Biomedical and Health Informatics.

Mobile Health Apps in Pediatric Obesity Treatment: Process Outcomes From a Feasibility Study of a Multicomponent Intervention. Browne, S., Kechadi, M. T., O’Donnell, S., Dow, M., Tully, L., Doyle, G., & O’Malley, G. (2020). JMIR mHealth and uHealth8(7), e16925.

Collecting big behavioral data for measuring behavior against obesity. Papapanagiotou, V., Sarafis, I., Diou, C., Ioakimidis, I., Charmandari, E., Delopoulos, A. (2020).  arXiv preprint arXiv:2005.04928.

Inferring the Spatial Distribution of Physical Activity in Children Population from Characteristics of the Environment. Sarafis, I., Diou, C., Papapanagiotou, V., Alagialoglou, L., Delopoulos, A. (2020).  arXiv preprint arXiv:2005.03957.

BigO: A public health decision support system for measuring obesogenic behaviors of children in relation to their local environment. Diou, C., Sarafis, I., Papapanagiotou, V., Alagialoglou, L., Lekka, I., Filos, D., Stefanoupoulos, L., Kilintzis, V., Maramis, C., Karavidopoulou, Y., Maglaveras, N., Ioakimidis, I., Charmandari, E., Kassari, P., Tragomalou, A., Mars, M., Ngoc Nguyen, T., Kechadi, T., O’Donnel, S., Doyle, G., Browne, S., O’Malley, G., Heimeier, R., Riviou, K., Koukoula, E., Filis, K., Hassapidou, M., Pagkalos, I., Ferri, D., Pérez, I., Delopoulos, A.  (2020).  arXiv preprint arXiv:2005.02928.

2019

Ultra-processed food advertisements dominate the food advertising landscape in two Stockholm areas with low vs high socioeconomic status. Is it time for regulatory action?  Fagerberg, P., Langlet, B., Oravsky, A., Sandborg, J., Löf, M., & Ioakimidis, I. (2019). BMC Public Health19(1), 1-10. 

Mobile health (mHealth) applications with children in treatment for obesity: A randomised feasibility study. Browne, S., O’Donell, S., Tully, L., Dow, M., O’Conner, J., Kechadi, T., Doyle, G., O’Malley, G. (2019, October) In FENS 13th European Nutrition Conference. 

Behaviour profiles for evidence-based policies against obesity. Sarafis, I., Diou, C., & Delopoulos, A. (2019, July).In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 3596-3599). IEEE.

Assessment of In-Meal Eating Behaviour using Fuzzy SVM. Sarafis, I., Diou, C., Ioakimidis, I., & Delopoulos, A. (2019, July).  In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 6939-6942). IEEE.

BigO: The use of New Technologies for the Management of Childhood Obesity–A Clinical Pilot Study. Tragomalou, A., Kassari, P., Ioakeimidis, I., Filis, K., Theodoropoulou, E., Lymperopoulos, G., … & Lekka, E. (2019, August).In 58th Annual ESPE (Vol. 92). European Society for Paediatric Endocrinology.

Detecting Meals In the Wild Using the Inertial Data of a Typical Smartwatch. Kyritsis, K., Diou, C., & Delopoulos, A. (2019, July). In 2019 41st Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 4229-4232). IEEE.

Developing a novel citizen-scientist smartphone app for collecting behavioral and affective data from children population.  Maramis, C., Ioakimidis, I., Kilintzis, V., Stefanopoulos, L., Lekka, I., Papapanagiotou, V., Diou, C., Delopoulos, A., Kassari, P., Charmandari, E., Maglaveras, N.

A methodology for obtaining objective measurements of population obesogenic behaviors in relation to the environment. Diou, C., Sarafis, I., Papapanagiotou, V., Ioakimidis, I., & Delopoulos, A. (2019). Statistical Journal of the IAOS, (Preprint), 1-14.

Span error bound for weighted SVM with applications in hyperparameter selection. Sarafis, I., Diou, C., & Delopoulos, A. (2018).  arXiv preprint arXiv:1809.06124.

Mobile health (mHealth) applications with children in treatment for obesity: A randomised feasibility study. Sarah Browne, Shane O’Donell, Louise Tully, Mckenzie Dow, James O’connor, Tahar Kechadi, Gerardine Doyle, Grace O’malley

2018

Automatic analysis of food intake and meal microstructure based on continuous weight measurements. Papapanagiotou, V., Diou, C., Ioakimidis, I., Södersten, P., & Delopoulos, A. (2018). IEEE journal of biomedical and health informatics23(2), 893-902.

Image-Based Surrogates of Socio-Economic Status in Urban Neighborhoods Using Deep Multiple Instance Learning. Diou, C., Lelekas, P., & Delopoulos, A. (2018).  Journal of Imaging4(11), 125.

End-to-end Learning for Measuring in-meal Eating Behavior from a Smartwatch. Kyritsis, K., Diou, C., & Delopoulos, A. (2018, July). In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 5511-5514). IEEE. Kyritsis, K., Diou, C., & Delopoulos, A.

Personalised meal eating behaviour analysis via semi-supervised learning. Papadopoulos, A., Kyritsis, K., Sarafis, I., & Delopoulos, A. (2018, July). In 2018 40th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC) (pp. 4768-4771). IEEE.Papadopoulos, A., Kyritsis, K., Sarafis, I., & Delopoulos, A.

Modeling Wrist Micromovements to Measure In-Meal Eating Behavior from Inertial Sensor Data. Kyritsis, K., Diou, C., & Delopoulos, A. (2019). IEEE journal of biomedical and health informatics23(6), 2325-2334. Konstantinos Kyritsis, Christos Diou, Anastasios Delopoulos.

Control of eating behavior using a novel feedback system. Esfandiari, M., Papapanagiotou, V., Diou, C., Zandian, M., Nolstam, J., Södersten, P., & Bergh, C. (2018).  JoVE (Journal of Visualized Experiments), (135), e57432.

BigO: big data against childhood obesity. e-Poster. The BigO consortium. 57th ESPE 2018.