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Body Water and Dehydration

Temperature-Based Bioimpedance Correction for Water Loss Estimation during Physical Exercise
  • The amount of total body water (TBW) can be estimated based on bioimpedance measurements of the human body. In sports, TBW estimations are of importance because mild water losses can impair muscular strength and aerobic endurance. Severe water losses can even be life threatening. TBW estimations based on bioimpedance, however, fail during physical exercise because the increased body temperature corrupts bioimpedance measurements.

    Therefore, we propose a machine learning method that eliminates the effects of increased temperature on bioimpedance and, consequently, reveals the changes in bioimpedance that are due to TBW loss. This is facilitated by utilizing changes in skin and core temperature. The method was evaluated in a study in which bioimpedance, temperature, and TBW loss were recorded every 15 minutes during a two-hour running workout. The evaluation demonstrated that the proposed method is able to reduce the error of TBW loss estimation by up to 71%, compared to the state of art.

    This approach - in combination with portable bioimpedance devices - could facilitate the development of wearable devices for continuous and noninvasive TBW loss monitoring in the future.

    Journal Articles
    Ring, Matthias; Lohmueller, Clemens; Rauh, Manfred; Mester, Joachim; Eskofier, Björn
    A Temperature-Based Bioimpedance Correction for Water Loss Estimation During Sports
    IEEE Journal of Biomedical and Health Informatics, vol. 20, no. 6, pp. 1477-1484, 2016 (BiBTeX, Who cited this?)
    Articles in Conference Proceedings
    Ring, Matthias; Lohmüller, Clemens; Rauh, Manfred; Eskofier, Björn
    A Two-Stage Regression Using Bioimpedance and Temperature for Hydration Assessment During Sports
    Proceedings of the 2014 22nd International Conference on Pattern Recognition (2014 22nd International Conference on Pattern Recognition), Stockholm, Sweden, August 24-28, 2014, pp. 4519-4524, 2014 (BiBTeX, Who cited this?)
Sweat Analysis for Water Loss Estimation during Physical Exercise
  • Quantitative estimation of water loss during physical exercise is important because dehydrations can impair both muscular strength and aerobic endurance. A physiological indicator for total body water (TBW) loss could be the concentration of electrolytes in sweat. It has been shown that electrolyte concentrations differ after physical exercise, depending on whether water loss was replaced by fluid intake or not. However, this observation has not been explored for its potential to estimate TBW loss quantitatively.

    Therefore, we collected sweat samples during two hours of physical exercise without fluid intake. A statistical analysis of the analyzed measurements showed significant correlations between chloride concentration in sweat and TBW loss (r = 0.41, p < 0.01), and between sweat osmolality and TBW loss (r = 0.43, p < 0.01). The estimation of TBW loss using a Gaussian Process regression resulted in a mean absolute error of 0.49 liter. Although this precision has to be improved for usage in the field, the results suggest that TBW loss estimations could be realized based on sweat analysis.

    Articles in Conference Proceedings
    Ring, Matthias; Lohmüller, Clemens; Rauh, Manfred; Eskofier, Björn
    On Sweat Analysis for Quantitative Estimation of Dehydration during Physical Exercise
    Proceedings of the 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society), Milan, Italy, August, 25-29, pp. 7011-7014, 2015 (BiBTeX, Who cited this?)
Salivary Markers for Water Loss Estimation during Physical Exercise
  • Salivary markers have been proposed as noninvasive and easy-to-collect indicators of dehydrations during physical exercise. It has been demonstrated that threshold-based classifications can distinguish dehydrated from euhydrated subjects. However, considerable challenges were reported simultaneously, for example, high inter-subject variabilities in these markers.

    Therefore, we propose a machine learning approach to handle the inter-subject variabilities and to advance from binary classifications to quantitative estimations of total body water (TBW) loss. For this purpose, salivary samples and reference values of TBW loss were collected from ten subjects during a 2-h running workout without fluid intake. The salivary samples were analyzed for previously investigated markers (osmolality, proteins) as well as additional unexplored markers (amylase, chloride, cortisol, cortisone, potassium). Processing all these markers with a Gaussian process approach showed that quantitative TBW loss estimations are possible within an error of 0.34 l, roughly speaking, a glass of water.

    Furthermore, a data analysis illustrated that the salivary markers grow nonlinearly during progressive dehydration, which is in contrast to previously reported, linear observations. This insight could help to develop more accurate physiological models for salivary markers and TBW loss. Such models, in turn, could facilitate even more precise TBW loss estimations in the future.


    Ring, Matthias; Lohmueller, Clemens; Rauh, Manfred; Mester, Joachim; Eskofier, Bjoern M.
    Salivary Markers for Quantitative Dehydration Estimation during Physical Exercise.
    IEEE Journal of Biomedical and Health Informatics, forthcoming, DOI: 10.1109/JBHI.2016.2598854.