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Intelligent Toilet System for Non-invasive Estimation of Blood-Sugar Level from Urine

机译:智能厕所系统,用于尿液中的血糖水平的非侵入性估算

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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. (C) 2019 AGBM. Published by Elsevier Masson SAS. All rights reserved.
机译:背景和目标:2型糖尿病是慢性疾病之一。这种疾病可以通过调节药物剂量来控制,这是根据血糖水平的定期监测计算的。血糖估计方法被分为两类直接和间接。直接方法(Innative In Nature)提供更准确的结果;但是在当天,人们对他们的血液几次没有兴趣;因为血液样本收集过程是痛苦的。另一方面,由于其非侵入性,间接估计方法很受欢迎。最广泛使用的无侵入性血糖估计方法是基于尿糖水平估计。尿糖水平估计是一种需要手动参与的化学过程。人性非常不同;他们不喜欢定期检测尿液的重复工作,尽管该过程并不繁琐。如果存在一个系统,这将是非常有帮助的,从而从厕所自动监测尿糖水平。方法:这项工作描述了一种自动技术来估算尿液中的血糖水平。这项工作的贡献如下:一个完整​​的定制机械单元,控制尿糖估计的化学过程。自动技术从训练数据集中构建模糊会员函数。本系统包括化学过程控制以及模糊的化学过程控制基于逻辑的颜色估计技术,其中模糊隶属函数从训练数据集导出。这种模糊隶属函数发生器的一个显着特征是它是可调调谐的,这意味着它允许校准构建隶属函数后。从应用角度来看,它是一种智能厕所,可以跟踪尿液中的血糖水平。该系统分为名为控制部分的两个子部分和计算部分。控制部分包括控制机械单元和化学过程启动。化学试剂的活度随着时间的推移而变化,该系统具有通过体积调节室处理这种情况的规定。控制部分包括大量阀门控制,它们是相互依存的。 Petri-net用于同步它们。计算部分用于估计来自本尼迪斯定性解决方案的改变颜色的尿糖水平。结果:从操作的角度来看,该系统是顺序和并行子进程的组合。它可以分为9个子进程。完成所有9个进程所需的时间为660.5秒。这次包括样本采集时间,化学反应时间,结果计算和系统清洁时间。系统的平均灵敏度,特异性和错误率均如下88.0225%,95.95%和5.765%。 PIPEV4.3.0用于分析Petri-Net。根据分析报告,系统是安全的(可靠)。探讨:该系统有效地估算尿液中的血糖水平。该系统间接地使用颜色传感器感测尿糖水平。颜色传感器与反应室的化学物质不直接接触。可以使用正常的马桶清洁(酸性)溶液清洁腔室。所以,维护过程很容易。通过辅助医生通过定期监测尿糖水平,通过协助医生控制高血糖水平来降低青光眼,肾问题等的可能性。 (c)2019年AGBM。由Elsevier Masson SA出版。版权所有。

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