Alotaibi Mohammad, Alnajjar Fady, Cappuccio Massimiliano, Khalid Sumaya, Alhmiedat Tareq, Mubin Omar
Faculty of Computers and Information Technology, University of Tabuk, Tabuk, Saudi Arabia.
College of Information Technology, United Arab Emirates University, Abu Dhabi, United Arab Emirates.
Diabetes Metab Syndr Obes. 2022 Apr 21;15:1227-1244. doi: 10.2147/DMSO.S357176. eCollection 2022.
Childhood obesity is a widespread medical condition and presents a formidable challenge for public health. Long-term treatment strategies and early prevention strategies are required because obese children are more likely to carry this condition into adulthood, increasing their risk of developing other major health disorders. The present review analyses various technological interventions available for childhood obesity prevention and treatment. It also examines whether machine learning and technological interventions can play vital roles in its management. Twenty-six studies were shortlisted for the review using various technological strategies and analysed regarding their efficacy. While most of the selected studies showed positive outcomes, there was a lack of studies using robots and artificial intelligence to manage obesity in children. The use of machine learning was observed in various studies, and the integration of social robots and other efficacious strategies may be effective for treating childhood obesity in the future.
儿童肥胖是一种普遍存在的医学状况,对公共卫生构成了巨大挑战。由于肥胖儿童更有可能将这种状况延续至成年期,从而增加他们患其他重大健康疾病的风险,因此需要长期治疗策略和早期预防策略。本综述分析了可用于预防和治疗儿童肥胖的各种技术干预措施。它还研究了机器学习和技术干预措施是否能在其管理中发挥重要作用。使用各种技术策略筛选出26项研究进行综述,并分析其疗效。虽然大多数所选研究显示出积极结果,但缺乏使用机器人和人工智能来管理儿童肥胖的研究。在各种研究中都观察到了机器学习的应用,未来社交机器人与其他有效策略的结合可能对治疗儿童肥胖有效。