Particle Filter based Diagnosis and Prognosis for Human Hydration States

A miniature microwave resonator to probe the dielectric properties in the dermis layer of the forearm skin was demonstrated in whole-body water consumption experiments to evaluate hydration processes. This work furthers its applications by using a particle filter-based estimation and prediction meth...

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Bibliographic Details
Published in:IEEE sensors letters 2023-09, Vol.7 (9), p.1-4
Main Authors: Niu, Guangxing, Sen, Bing, Zhang, Bin, Chiao, J.-C.
Format: Article
Language:English
Subjects:
Bayesian estimation
Catastrophic events
Diagnosis
Dielectric properties
Estimation
Human hydration
Hydration
Particle filtering
Particle filters
Predictive models
Prognosis
Prognostics and health management
Resonant frequency
Sensors
State estimation
Water consumption
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Summary:A miniature microwave resonator to probe the dielectric properties in the dermis layer of the forearm skin was demonstrated in whole-body water consumption experiments to evaluate hydration processes. This work furthers its applications by using a particle filter-based estimation and prediction method for human hydration states so the system can be used for continuous monitoring of the body. The hydration state is an important indicator of human health conditions. Accurate hydration estimation and prediction can help to reduce the risk of disease development and prevent catastrophic events. A Bayesian estimation method and a particle filtering-based human hydration state diagnosis and prognosis method were demonstrated and tested with experimental data from human subjects. Preliminary results showed that the proposed estimation approach has a satisfactory performance in accuracy between 82.1% and 93.8%. Our investigation found different models may be needed for different physiological conditions.
ISSN:2475-1472
2475-1472
DOI:10.1109/LSENS.2023.3306984