促进儿童肥胖预防和健康习惯:OCARIoT的经验

IF 3.7 3区 医学 Q2 ENGINEERING, BIOMEDICAL IEEE Journal of Translational Engineering in Health and Medicine-Jtehm Pub Date : 2023-03-27 DOI:10.1109/JTEHM.2023.3261899
Leire Bastida;Gloria Cea;Ana Moya;Alba Gallego;Eugenio Gaeta;Sara Sillaurren;Paulo Barbosa;Sabrina Souto;Eujessika Rodrigues;Macarena Torrego-Ellacuría;Andreas Triantafyllidis;Anastasios Alexiadis;Konstantinos Votis;Dimitrios Tzovaras;Cleilton Rocha;Lucas Alves;Pedro Maló;Márcio Mateus;Fernando Ferreira;María Teresa Arredondo
{"title":"促进儿童肥胖预防和健康习惯:OCARIoT的经验","authors":"Leire Bastida;Gloria Cea;Ana Moya;Alba Gallego;Eugenio Gaeta;Sara Sillaurren;Paulo Barbosa;Sabrina Souto;Eujessika Rodrigues;Macarena Torrego-Ellacuría;Andreas Triantafyllidis;Anastasios Alexiadis;Konstantinos Votis;Dimitrios Tzovaras;Cleilton Rocha;Lucas Alves;Pedro Maló;Márcio Mateus;Fernando Ferreira;María Teresa Arredondo","doi":"10.1109/JTEHM.2023.3261899","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":54255,"journal":{"name":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","volume":"11 ","pages":"261-270"},"PeriodicalIF":3.7000,"publicationDate":"2023-03-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10081348","citationCount":"3","resultStr":"{\"title\":\"Promoting Obesity Prevention and Healthy Habits in Childhood: The OCARIoT Experience\",\"authors\":\"Leire Bastida;Gloria Cea;Ana Moya;Alba Gallego;Eugenio Gaeta;Sara Sillaurren;Paulo Barbosa;Sabrina Souto;Eujessika Rodrigues;Macarena Torrego-Ellacuría;Andreas Triantafyllidis;Anastasios Alexiadis;Konstantinos Votis;Dimitrios Tzovaras;Cleilton Rocha;Lucas Alves;Pedro Maló;Márcio Mateus;Fernando Ferreira;María Teresa Arredondo\",\"doi\":\"10.1109/JTEHM.2023.3261899\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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.\",\"PeriodicalId\":54255,\"journal\":{\"name\":\"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm\",\"volume\":\"11 \",\"pages\":\"261-270\"},\"PeriodicalIF\":3.7000,\"publicationDate\":\"2023-03-27\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10081348\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/10081348/\",\"RegionNum\":3,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, BIOMEDICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Journal of Translational Engineering in Health and Medicine-Jtehm","FirstCategoryId":"5","ListUrlMain":"https://ieeexplore.ieee.org/document/10081348/","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, BIOMEDICAL","Score":null,"Total":0}
引用次数: 3

摘要

目的:长期行为障碍和对健康习惯(主要是饮食和体育活动)的干预是儿童肥胖的主要原因。目前基于健康信息提取的肥胖预防方法缺乏多模式数据集的集成,也缺乏为儿童的健康行为评估和指导提供专门的决策支持系统。方法:在设计思维方法论的框架下,采用持续的共创过程,让儿童、教育工作者和医疗保健专业人员参与到整个过程中。这些考虑因素用于推导基于微服务的物联网(IoT)平台概念所需的用户需求和技术要求。结果:为了促进儿童(9-12岁)养成健康习惯并预防肥胖,所提出的解决方案通过收集和跟踪来自物联网设备的营养、身体活动数据、,以及将医疗保健专业人员相互连接,以提供个性化的辅导解决方案。验证分为两个阶段,涉及西班牙、希腊和巴西三个国家的四所学校的400多名儿童(对照/干预组)。干预组的肥胖患病率比基线水平下降了75.5%。从技术接受的角度来看,所提出的解决方案给人留下了积极的印象和满足感。结论:主要研究结果证实,该生态系统可以评估儿童的行为,激励和引导他们实现个人目标。临床和转化影响声明——这项研究介绍了采用多学科方法的智能儿童肥胖护理解决方案的早期研究;它涉及生物医学工程、医学、计算机科学、伦理学和教育的研究人员。该解决方案有可能降低儿童的肥胖率,旨在改善全球健康。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

摘要图片

摘要图片

摘要图片

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
Promoting Obesity Prevention and Healthy Habits in Childhood: The OCARIoT Experience
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.
求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
7.40
自引率
2.90%
发文量
65
审稿时长
27 weeks
期刊介绍: The IEEE Journal of Translational Engineering in Health and Medicine is an open access product that bridges the engineering and clinical worlds, focusing on detailed descriptions of advanced technical solutions to a clinical need along with clinical results and healthcare relevance. The journal provides a platform for state-of-the-art technology directions in the interdisciplinary field of biomedical engineering, embracing engineering, life sciences and medicine. A unique aspect of the journal is its ability to foster a collaboration between physicians and engineers for presenting broad and compelling real world technological and engineering solutions that can be implemented in the interest of improving quality of patient care and treatment outcomes, thereby reducing costs and improving efficiency. The journal provides an active forum for clinical research and relevant state-of the-art technology for members of all the IEEE societies that have an interest in biomedical engineering as well as reaching out directly to physicians and the medical community through the American Medical Association (AMA) and other clinical societies. The scope of the journal includes, but is not limited, to topics on: Medical devices, healthcare delivery systems, global healthcare initiatives, and ICT based services; Technological relevance to healthcare cost reduction; Technology affecting healthcare management, decision-making, and policy; Advanced technical work that is applied to solving specific clinical needs.
期刊最新文献
A Multi-Task Based Deep Learning Framework With Landmark Detection for MRI Couinaud Segmentation Video-Based Respiratory Rate Estimation for Infants in the NICU A Novel Chest-Based PPG Measurement System Integrating Multimodal Neuroimaging and Genetics: A Structurally-Linked Sparse Canonical Correlation Analysis Approach A Pre-Voiding Alarm System Using Wearable Ultrasound and Machine Learning Algorithms for Children With Nocturnal Enuresis
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1