Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 1227-1244 |
| Number of pages | 18 |
| Journal | Diabetes, Metabolic Syndrome and Obesity |
| Volume | 15 |
| DOIs | |
| Publication status | Published - 2022 |
Bibliographical note
Publisher Copyright:© 2022 Alotaibi et al.
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This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
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