Information technology support for assessing psychophysiological characteristics of physical health

        The article examines scientific approaches to determining an integral physical health index and highlights its relevance for monitoring the human body's condition. Modern research indicates the need for comprehensive assessment methods that consider both traditional anthropometric parameters and advanced psychophysiological markers. The aim of this study is to develop a conceptual framework for an information technology platform that enables automated assessment of human physical health using modern analytical and monitoring techniques. Methods.        A bibliosemantic analysis was conducted to define the research problem and assess the degree of its development. The study involved an examination of monographs, dissertations, journal articles, conference proceedings, and online scientific resources. Keyword and citation analysis were conducted based on data from Web of Science Core Collection, Scopus, and PubMed. Results.           A review of scientific publications on psychophysiological markers of physical health and traditional assessment methods was performed. The advantages and limitations of these methods were identified, and modern composite health indices, such as A Body Shape Index (ABSI) and Body Roundness Index (BRI), were analyzed. The importance of continuous health monitoring was substantiated to enhance the effectiveness of health-improving technologies. A quantitative mathematical model for health assessment was developed, incorporating logical-mathematical approaches that integrate anthropometric, physiological, and adaptive indicators. The study explored the ICF Index (International Classification of Functioning, Disability, and Health) as a tool for evaluating students' health and creating a personalized health index. A comparison of traditional and modern health assessment methods was conducted, with an emphasis on their predictive accuracy across various domains, including medicine, sports, and rehabilitation. An integrated health index was proposed, encompassing key psychophysiological parameters (anthropometric, physiological, and adaptive). A mathematical model for dynamic health monitoring was developed, enabling its application in personalized medicine, disease prevention, sports science, fitness industries, and mobile health applications. Conclusions. The analysis of scientific approaches to physical health assessment confirmed its significance for psychophysiology, medicine, sports, and rehabilitation. The strengths and weaknesses of existing methods were identified, highlighting the need for a comprehensive health monitoring system that integrates functional, psychological, and physiological parameters. Despite the extensive development of health assessment methodologies, scientific support for this process remains an open challenge. The study proposes promising applications of an integrated health index.