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Intelligent Toilet System for Non-invasive Estimation of Blood-Sugar Level from Urine - 31/10/19

Doi : 10.1016/j.irbm.2019.10.005 
P. Ghosh a, , D. Bhattacharjee b , M. Nasipuri b
a Department of Computer Science and Engineering, RCC Institute of Information Technology, Kolkata 700015, India 
b Department of Computer Science and Engineering, Jadavpur University, Kolkata 700032, India 

Corresponding author.
Sous presse. Épreuves corrigées par l'auteur. Disponible en ligne depuis le Thursday 31 October 2019
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Graphical abstract

Le texte complet de cet article est disponible en PDF.

Highlights

A complete customized mechanical unit, which controls the chemical process of urine sugar estimation.
An automatic technique to build the fuzzy membership functions from training data set.
Estimate the urine sugar level from training data set.

Le texte complet de cet article est disponible en PDF.

Abstract

Background and Objectives

Type-2 diabetes is one of the chronic diseases. This disease can be controlled by adjusting the dose of medicine, which is calculated from regular monitoring of blood sugar level. Blood glucose estimation methods are grouped into two categories direct and indirect. The direct method (invasive in nature) provides more accurate results; but people are not interested to test their blood several times in the day; because blood sample collection process is painful. On the other hand, indirect estimation methods are popular due to its non-invasive nature. The most widely used non-invasive blood glucose estimation method is based on urine sugar level estimation. Urine sugar level estimation is a chemical process requiring manual involvement. Human nature is very different; they dislike the repetitive work of testing urine regularly, although the process is not at all cumbersome. It will be very helpful if a system exists, which monitors urine sugar level automatically from the toilet.

Methods

This work describes an automatic technique to estimate blood sugar level from urine. The contribution of this work is as follows:

A complete customized mechanical unit, which controls the chemical process of urine sugar estimation.
An automatic technique to build the fuzzy membership functions from training data set.
This system includes a chemical process control along with a fuzzy logic based color estimation technique, where fuzzy membership functions are derived from training data set. One salient feature of this fuzzy membership functions generator is that it is tuneable, that means it allows calibration after constructing membership functions. From application point of view, it is an intelligent toilet to keep track of blood sugar level from urine.

The system is divided into two sub sections named as a control section and a computation section. The control section includes the control of mechanical units and chemical process initiation. The activeness of chemical reagent changes over time, this system has the provision to handle such situation through volume adjustment chamber. The control section includes a lot of valve control, they are interdependent. Petri-net is used to synchronise them. Computation section is used for estimation of urine sugar level from the changed color of Benedict's Qualitative Solution.

Result

From operational point of view, this system is a combination of sequential and parallel sub processes. It can be divided into 9 sub processes. The time required to complete all 9 processes is 660.5 second. This time includes sample collection time, chemical reaction time, result calculation and system cleaning time. The average Sensitivity, Specificity and error rate of the system are as follows 88.0225%, 95.95% and 5.765%. PIPEv4.3.0 is used to analysis the Petri-net. As per the analysis report, the system is safe (reliable).

Discussion

This system is efficient to estimate blood sugar level from urine. This system senses the urine sugar level indirectly using the color sensor. The color sensor is not directly in touch with the chemical of the reaction chamber. The normal toilet cleaning (acidic) solution can be used to clean the chambers. So, maintenance process is quite easy. The proposed system can reduce the probability of glaucoma, kidney problem etc. by assisting doctors to control high blood sugar level through regular monitoring of urine sugar level.

Le texte complet de cet article est disponible en PDF.

Keywords : Fuzzy membership function, Reaction chamber, Process control, HSI color model, Image filtering, Petri-net, Urine sugar estimation


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