Abstract
Low physical activity (PA), and often concomitant overweight in the developmental age are well documented risk factors for cardiovascular diseases (CVD) and many other chronic civilization diseases. Regular monitoring of health related physical fitness (H-RF) is an important part of early prevention and school health education. An assessment of components of H-RF is complex and controversial. In the assessment of H-RF components, systems of fuzzy inference based on simple linguistic variables can be used. The paper presents a system intended to support the evaluation of the H-RF components based on the EUROFIT battery tests and the anthropometric measurements. A basis of the system is the EUROFIT calculator which converts absolute results of individual trials to standarized values and the fuzzy inference system for four H-RF components (Morphological, Cardiorespiratory, Musculoskeletal and Motor Fitness). The system is implemented in MS Visual Studio in C# and has a friendly graphical interface for archiving test results. An application of fuzzy inference elements in the evaluation of the H-RF components is a new approach that can be used in monitoring and rational planning of PA dosing in prophylaxis and therapy.
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Nawarycz, T., Pytel, K., Ostrowska-Nawarycz, L. (2012). Evaluation of Health-Related Fitness Using Fuzzy Inference Elements. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29347-4_35
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DOI: https://doi.org/10.1007/978-3-642-29347-4_35
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