Application Of Artificial Intelligence for Optimizing Wellness Programs: Integrating Diet, Exercise Regimens, And the Formation of Healthy Habits
Keywords:
Adaptive planning, affective-cognitive regulation, biometric monitoring, diet, healthy habits, artificial intelligence, personalized wellness, predictive modeling,, exercise regimen, physical activity, digital technologiesAbstract
This article examines the specifics of using artificial intelligence tools to optimize wellness programs, focusing on the integration of diet, exercise regimens, and the formation of healthy habits. The digital transformation of this field faces a paradox of information overload coupled with a lack of personalized solutions. The fragmented nature of existing approaches, in which nutrition, physical activity, and psychological aspects of health are treated in isolation, reduces the effectiveness of wellness programs. This study aims to systematize modern concepts regarding the integration of AI for creating holistic, adaptive systems that support a healthy lifestyle. The article highlights contradictions between the growing interest in algorithmic solutions in the wellness sector and the insufficient development of the methodological foundations for their implementation, as well as between the technological capabilities of AI systems and the ethical constraints on their use. The analysis demonstrates the potential of AI to overcome the limitations of traditional programs through multifactor analysis of biometric data, predictive modeling of individual regimens, and affective-cognitive regulation. A system architecture is proposed that integrates physiological parameter monitoring, adaptive planning of diet and exercise regimens, and a module for psychological support. The materials presented in the article are of value to researchers in digital health, developers of wellness applications, and specialists in preventive medicine.
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Copyright (c) 2025 Oleksandr Khodorkovskyi
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