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. 2022 Mar 25;22(7):2536.
doi: 10.3390/s22072536.

A Non-Invasive Hydration Monitoring Technique Using Microwave Transmission and Data-Driven Approaches

Deepesh Agarwal  1 , Philip Randall  1 , Zachary White  2 , Bayleigh Bisnette  1 , Jenalee Dickson  1 , Cross Allen  1 , Faraz Chamani  1 , Punit Prakash  1 , Carl Ade  2 , Balasubramaniam Natarajan  1
Affiliations

A Non-Invasive Hydration Monitoring Technique Using Microwave Transmission and Data-Driven Approaches

Deepesh Agarwal et al. Sensors (Basel). .

Abstract

Dehydration in the human body arises due to inadequate replenishment of fluids. An appropriate level of hydration is essential for optimal functioning of the human body, and complications ranging from mild discomfort to, in severe cases, death, could result from a neglected imbalance in fluid levels. Regular and accurate monitoring of hydration status can provide meaningful information for people operating in stressful environmental conditions, such as athletes, military professionals and the elderly. In this study, we propose a non-invasive hydration monitoring technique employing non-ionizing electromagnetic power in the microwave band to estimate the changes in the water content of the whole body. Specifically, we investigate changes in the attenuation coefficient in the frequency range 2-3.5 GHz between a pair of planar antennas positioned across a participant's arm during various states of hydration. Twenty healthy young adults (10M, 10F) underwent controlled hypohydration and euhydration control bouts. The attenuation coefficient was compared among trials and used to predict changes in body mass. Volunteers lost 1.50±0.44% and 0.49±0.54% body mass during hypohydration and euhydration, respectively. The microwave transmission-based attenuation coefficient (2-3.5 GHz) was accurate in predicting changes in hydration status. The corresponding regression analysis demonstrates that building separate estimation models for dehydration and rehydration phases offer better predictive performance (88%) relative to a common model for both the phases (76%).

Keywords: hydration monitoring; hypohydration and euhydration; microwave transmission; non-invasive; regression analysis.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1
Setup for the gel studies: (a) five agar gels with varying water content, (b) close-up image of the antennas, (c) measurement of dielectric properties, and (d) capturing of electromagnetic measurements.
Figure 2
Figure 2
Plot of changes in dielectric properties of agar phantom gels with increasing water content.
Figure 3
Figure 3
Plot of changes in electromagnetic transmission coefficient (S21) measurements of agar phantom gels with increasing water content.
Figure 4
Figure 4
Timeline of events in each treatment condition. Fluid balance measurements (FBM): nude body weight, urine specific gravity, hematocrit and S21 measurement; * Period 3 FBM: urine specific gravity was not assessed. BL: baseline.
Figure 5
Figure 5
Experimental setup used to obtain S21 measurements from the participant.
Figure 6
Figure 6
Sample plot of S21 magnitudes for one participant during different instances.
Figure 7
Figure 7
Summary of variations in percentage changes in body weight over different time intervals for the participants.
Figure 8
Figure 8
Correlation plots for selected cases. Percentage changes in (a): body weight vs. mean of S21 magnitudes in frequency band 1 during the measurement time “After Period 3”; (b): body weight vs. mean of S21 magnitudes in frequency band 2 during the measurement time “After Rehydration”; (c): body weight vs. mean of S21 magnitudes in frequency band 3 during the measurement time “After Exercise”; (d): body weight vs. mean of S21 magnitudes in frequency band 4 during the measurement time “After Period 3”.
Figure 9
Figure 9
Sample plots of true response vs. predicted response and residuals for predictions with SVR for male participants in sex-specific Analysis—Case 2.
See this image and copyright information in PMC

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