Flow Estimation Algorithm from Simulated Urination by Image Processing

Abstract

Inpatients of circulatory system disease must manage their urine volume every day since they have low ability to control fluid balance inside their bodies. In most hospitals, measuring cups are used which lead to nosocomial infection. Our study propose a new method of urine volume estimation without using a cup. We propose multiple cylindrical model to estimate the amount of liquid volume from images taken by a monocular camera. This model is based on the idea of calculating the total volume of cylinder extracted from each image. First, images of liquid simulating male urination are binarized to derive features for the model. Each volume of cylinder is calculated by the initial velocity and diameter of liquid in each image. We conducted experiments to evaluate the model. As a result, we suggest that this model could be a new way of urine volume management for inpatients.