The global population of individuals is expanding rapidly. By 2024, the obesity rate among adults in China is expected to surge to 16.4%, while globally, over 4 billion people are facing issues of overweight or obesity. Traditional exercise prescriptions suffer from the limitations of "generalized guidance" and "static prescriptions." Studies have shown that due to the neglect of individual metabolic differences, only 20% of individuals can maintain clinically significant weight loss for more than 12 months, and merely 10-25% patients can sustain a weight loss of ≥10% in the long term. The intelligent technology-driven exercise intervention system is reshaping the paradigm of obesity management. By integrating multi-source physiological data and machine learning models, it has overcome the limitations of traditional exercise prescriptions, achieving a leap from generalized guidance to personalized adaptation. This study employs literature review and logic analysis to explore the application of artificial intelligence (AI) technology in exercise prescriptions and its effects on health interventions for obese populations. The focus is on the application of AI in exercise prescription generation, integration of behavioral theories, dynamic prescription optimization, and lifestyle interventions. Existing research has been systematically reviewed to identify the advantages, limitations, and future directions of AI technology in obesity management. (1) Multi-dimensional biological modeling for prescription generation, integrating interdisciplinary methods, collects parameters such as body fat distribution, resting metabolic rate, and cardiopulmonary endurance to establish personalized exercise prescriptions. (2) Integration of behavioral theories: Obese populations commonly exhibit executive dysfunction. Virtual reality exposure therapy and simulated dietary temptation scenarios are used to train patients' control abilities. (3) Dynamic prescription optimization: AI, combined with cutting-edge technologies such as wearable biosensors and radar monitoring, tracks real-time data on lactate threshold, oxygen saturation, and abnormal heart rates in obese subjects, ensuring the safety and effectiveness of the prescriptions. AI technology in the application of exercise prescriptions needs to address challenges related to data security, algorithmic fairness, and ethical regulation. Interdisciplinary technological collaboration and innovation are essential to promote its standardized adoption in the field of obesity management.
Qiqi Huang (Thu,) studied this question.