Novel Technology-Based Exercise for Childhood Obesity Prevention

A special issue of Obesities (ISSN 2673-4168).

Deadline for manuscript submissions: 31 May 2026 | Viewed by 1996

Special Issue Editors


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Guest Editor
Department of Biomedical and Biotechnological Sciences, Section of Anatomy, Histology and Movement Science, School of Medicine, University of Catania, Via S. Sofia No 97, 95123 Catania, Italy
Interests: performance; training; sport; body composition; adapted physical activity
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Guest Editor
Dipartimento di Scienze e Tecnologie Biologiche Chimiche e Farmaceutiche, Università degli Studi di Palermo, 90133 Palermo, PA, Italy
Interests: human nutrition; micronutrients; biofortified food; physical activity; gut peptides; bone remodeling and metabolism; glucose homeostasis; lipid homeostasis; systemic homeostasis; human physiology
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

The pediatric obesity epidemic requires a paradigm shift from generic "move more" advice towards specific, targeted exercise protocols for fat loss and prevention. Integrating digital technology is crucial to make these protocols engaging, personalized, and scalable. This Special Issue focuses on the synergy between technological innovation and exercise science. We invite research contributions exploring specific exercise prescription, comparing the efficacy of protocols for reducing fat mass and improving metabolic health. Additionally, we aim to investigate technology as a motivator, evaluating its effectiveness in promoting adherence to structured programs. We also explore personalization and long-term adherence, investigating strategies to tailor interventions and maintain long-term motivation in young populations. This issue will bridge the gap between general physical activity guidelines and the application of "precision exercise medicine." It will provide researchers and clinicians with evidence on how to design effective, technology-enhanced, and targeted exercise interventions to combat pediatric obesity.

Dr. Alessandra Amato
Dr. Sara Baldassano
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 250 words) can be sent to the Editorial Office for assessment.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Obesities is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1200 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • childhood
  • obesity prevention
  • exercise prescription
  • health promotion
  • physical activity
  • weight management
  • exergaming
  • wearable technology
  • health outcome

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Published Papers (1 paper)

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Review

20 pages, 1343 KB  
Review
Applying AI Tools for Monitoring Nutrition and Physical Activity in Populations with Obesity: Are We Ready?
by Alessandra Amato, Sara Baldassano and Giuseppe Musumeci
Obesities 2026, 6(2), 19; https://doi.org/10.3390/obesities6020019 - 27 Mar 2026
Viewed by 1433
Abstract
This review examines the current state of development and application of artificial intelligence (AI) tools for monitoring nutrition and physical activity in individuals with obesity, with a focus on the physiological complexity of energy balance and the role of chrono-nutrition. Energy intake and [...] Read more.
This review examines the current state of development and application of artificial intelligence (AI) tools for monitoring nutrition and physical activity in individuals with obesity, with a focus on the physiological complexity of energy balance and the role of chrono-nutrition. Energy intake and expenditure are dynamically coupled and circadian-regulated: meal timing and movement patterns influence insulin sensitivity, thermogenesis, and Non-Exercise Activity Thermogenesis within the same day. Traditional monitoring methods suffer from recall bias and low granularity, while isolated sensors operate in data silos, limiting accuracy. Effective solutions require multimodal, continuous, and temporally aligned data streams. Current AI models exhibit critical limitations in obesity-specific contexts: inaccurate gait and energy expenditure estimates due to biomechanical differences, dietary models underestimating glycemic variability, poor performance on mixed dishes, sauces, and culturally diverse foods, and a lack of validation against gold standards such as doubly labelled water (DLW) and weighed food records. This review proposes a paradigm shift toward obesity-specific AI design, including enriched datasets and multimodal integration. Physical activity monitoring faces similar challenges: systematic measurement bias in wearables, sensor placement issues, and algorithms trained on normal-weight cohorts. In the GLP-1/GIP era, if transparency, ethical safeguards, and equitable access are ensured, AI will act as a catalyst for personalized care, remote monitoring, trial optimization, and next-generation drug discovery. In conclusion, the integration of AI with rigorous validation procedures and inclusive sampling strategies is essential to achieve reliable, fair, and clinically relevant monitoring approaches for obesity management. Full article
(This article belongs to the Special Issue Novel Technology-Based Exercise for Childhood Obesity Prevention)
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