Analysis of Hydration Level Estimation Strategies using Deep Learning

Abstract

Water is the vital component in a human body. Healthy body should be hydrated enough for the proper functioning of various organs. Water has major roles in the physical functioning of a human. Water plays a major role in the metabolic activities in the body. The various nutrients formed in the human body are transferred to different organs through water. Intake of water and water discharge should be controlled to maintain the water balance. Requirements of water in the human body may not meet through the food items or beverages and also not possible to get from metabolic activities. Sometimes the present dehydration level may be life threatening. There should be a proper mechanism to calculate the severity level of dehydration. If the severity of dehydration could be calculated, it is possible to take proper remedies. Dehydration may lead to different chronic diseases like kidney failure, coma, heart related illness, electrolyte abnormalities etc. The intake of plain water is required to maintain the water balance in the human body for better health. It is inevitable to meet the daily water requirements as the deficiency of water in human being may lead to various chronic diseases. Deep learning methods can be used to develop a predictive model for the early diagnosis of chronic diseases with a proper dataset which indudes not only the test results but also the hydration level in human body.