TY - JOUR
T1 - Promoting Obesity Prevention and Healthy Habits in Childhood
T2 - The OCARIoT Experience
AU - Bastida, Leire
AU - Cea, Gloria
AU - Moya, Ana
AU - Gallego, Alba
AU - Gaeta, Eugenio
AU - Sillaurren, Sara
AU - Barbosa, Paulo
AU - Souto, Sabrina
AU - Rodrigues, Eujessika
AU - Torrego-Ellacuria, Macarena
AU - Triantafyllidis, Andreas
AU - Alexiadis, Anastasios
AU - Votis, Konstantinos
AU - Tzovaras, Dimitrios
AU - Rocha, Cleilton
AU - Alves, Lucas
AU - Malo, Pedro
AU - Mateus, Marcio
AU - Ferreira, Fernando
AU - Arredondo, Maria Teresa
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - Objective: Long term behavioural disturbances and interventions in healthy habits (mainly eating and physical activity) are the primary cause of childhood obesity. Current approaches for obesity prevention based on health information extraction lack the integration of multi-modal datasets and the provision of a dedicated Decision Support System (DSS) for health behaviour assessment and coaching of children. Methods: Continuous co-creation process has been applied in the frame of the Design Thinking Methodology, involving children, educators and healthcare professional in the whole process. Such considerations were used to derive the user needs and the technical requirements needed for the conception of the Internet of Things (IoT) platform based on microservices. Results: To promote the adoption of healthy habits and the prevention of the obesity onset for children (9-12 years old), the proposed solution empowers children -including families and educators- in taking control of their health by collecting and following-up real-time information about nutrition, physical activity data coming from IoT devices, and interconnecting healthcare professionals to provide a personalised coaching solution. The validation has two phases involving +400 children (control/intervention group), on four schools in three countries: Spain, Greece and Brazil. The prevalence of obesity decreased in 75.5% from baseline levels in the intervention group. The proposed solution created a positive impression and satisfaction from the technology acceptance perspective. Conclusions: Main findings confirm that this ecosystem can assess behaviours of children, motivating and guiding them towards achieving personal goals. Clinical and Translational Impact Statement - This study presents Early Research on the adoption of a smart childhood obesity caring solution adopting a multidisciplinary approach; it involves researchers from biomedical engineering, medicine, computer science, ethics and education. The solution has the potential to decrease the obesity rates in children aiming to impact to get a better global health.
AB - Objective: Long term behavioural disturbances and interventions in healthy habits (mainly eating and physical activity) are the primary cause of childhood obesity. Current approaches for obesity prevention based on health information extraction lack the integration of multi-modal datasets and the provision of a dedicated Decision Support System (DSS) for health behaviour assessment and coaching of children. Methods: Continuous co-creation process has been applied in the frame of the Design Thinking Methodology, involving children, educators and healthcare professional in the whole process. Such considerations were used to derive the user needs and the technical requirements needed for the conception of the Internet of Things (IoT) platform based on microservices. Results: To promote the adoption of healthy habits and the prevention of the obesity onset for children (9-12 years old), the proposed solution empowers children -including families and educators- in taking control of their health by collecting and following-up real-time information about nutrition, physical activity data coming from IoT devices, and interconnecting healthcare professionals to provide a personalised coaching solution. The validation has two phases involving +400 children (control/intervention group), on four schools in three countries: Spain, Greece and Brazil. The prevalence of obesity decreased in 75.5% from baseline levels in the intervention group. The proposed solution created a positive impression and satisfaction from the technology acceptance perspective. Conclusions: Main findings confirm that this ecosystem can assess behaviours of children, motivating and guiding them towards achieving personal goals. Clinical and Translational Impact Statement - This study presents Early Research on the adoption of a smart childhood obesity caring solution adopting a multidisciplinary approach; it involves researchers from biomedical engineering, medicine, computer science, ethics and education. The solution has the potential to decrease the obesity rates in children aiming to impact to get a better global health.
KW - Children
KW - Internet of Things (IoT)
KW - health
KW - healthy habits
KW - obesity prevention
UR - http://www.scopus.com/inward/record.url?scp=85151557100&partnerID=8YFLogxK
U2 - 10.1109/JTEHM.2023.3261899
DO - 10.1109/JTEHM.2023.3261899
M3 - Article
C2 - 37056793
AN - SCOPUS:85151557100
SN - 2168-2372
VL - 11
SP - 261
EP - 270
JO - IEEE Journal of Translational Engineering in Health and Medicine
JF - IEEE Journal of Translational Engineering in Health and Medicine
ER -
