Assessment of physical activity of the human body considering the thermodynamic system. Issue 9 (3rd July 2016)

• Record Type: Journal Article
• Authors: Hochstein, Stefan; Rauschenberger, Philipp; Weigand, Bernhard; Siebert, Tobias; Schmitt, Syn; Schlicht, Wolfgang; Převorovská, Světlana; Maršík, František
• Is Part Of: Computer methods in biomechanics and biomedical engineering. Volume 19:Issue 9(2016)
• Page Start: 923
• Page End: 933
• Publication Date: 2016-07-03
• Subjects: Physical activity -- entropy -- activity assessment -- cardiovascular model; Biomechanics -- Data processing -- Periodicals; Biomedical engineering -- Periodicals; Biomechanics -- Periodicals; Biomedical Engineering -- methods -- Periodicals; Computing Methodologies -- Periodicals; 612.7
• DOI: Http://www.tandfonline.com/doi/10.1080/10255842.2015.1076804
• Languages: English
• ISSNs: 1025-5842

Abstract

Abstract : Correctly dosed physical activity is the basis of a vital and healthy life, but the measurement of physical activity is certainly rather empirical resulting in limited individual and custom activity recommendations. Certainly, very accurate three-dimensional models of the cardiovascular system exist, however, requiring the numeric solution of the Navier–Stokes equations of the flow in blood vessels. These models are suitable for the research of cardiac diseases, but computationally very expensive. Direct measurements are expensive and often not applicable outside laboratories. This paper offers a new approach to assess physical activity using thermodynamical systems and its leading quantity of entropy production which is a compromise between computation time and precise prediction of pressure, volume, and flow variables in blood vessels. Based on a simplified (one-dimensional) model of the cardiovascular system of the human body, we develop and evaluate a setup calculating entropy production of the heart to determine the intensity of human physical activity in a more precise way than previous parameters, e.g. frequently used energy considerations. The knowledge resulting from the precise real-time physical activity provides the basis for an intelligent human–technology interaction allowing to steadily adjust the degree of physical activity according to the actual individual performance level and thus to improve training and activity recommendations.