A Temperature-Based Bioimpedance Correction for Water Loss Estimation During Sports

Ring M, Lohmüller C, Rauh M, Mester J, Eskofier B (2016)


Publication Language: English

Publication Type: Journal article

Publication year: 2016

Journal

Publisher: Institute of Electrical and Electronics Engineers (IEEE)

Book Volume: 20

Pages Range: 1477-1484

Journal Issue: 6

DOI: 10.1109/JBHI.2015.2466076

Abstract

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 sports because the increased body temperature corrupts bioimpedance measurements. Therefore, this paper proposes 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. In the future, the proposed method in combination with portable bioimpedance devices might facilitate the development of wearable devices for continuous and noninvasive TBW loss monitoring during sports.

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How to cite

APA:

Ring, M., Lohmüller, C., Rauh, M., Mester, J., & Eskofier, B. (2016). A Temperature-Based Bioimpedance Correction for Water Loss Estimation During Sports. IEEE Journal of Biomedical and Health Informatics, 20(6), 1477-1484. https://dx.doi.org/10.1109/JBHI.2015.2466076

MLA:

Ring, Matthias, et al. "A Temperature-Based Bioimpedance Correction for Water Loss Estimation During Sports." IEEE Journal of Biomedical and Health Informatics 20.6 (2016): 1477-1484.

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