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A non-invasive ultra-wide band based system using artificial intelligence to determine blood glucose level

Master of Science in Computer Engineering

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Bibliographic Details
Main Author: Md Shawkat, Ali
Other Authors: Sabira, Khatun, Prof. Dr.
Format: Thesis
Language:English
Published: Universiti Malaysia Perlis (UniMAP) 2017
Subjects:
Blood sugar
Diabetes
Blood glucose
Diabetic patient
Ultra-wideband devices
Online Access:http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77983
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spelling my.unimap-779832023-03-06T02:27:38Z A non-invasive ultra-wide band based system using artificial intelligence to determine blood glucose level Md Shawkat, Ali Sabira, Khatun, Prof. Dr. Blood sugar Diabetes Blood glucose Diabetic patient Ultra-wideband devices Master of Science in Computer Engineering Diabetes is a serious health concern and declared as global epidemic by WHO due to its rapidly increasing incidence. It is a major cause of mortality worldwide. For a diabetic patient maintenance of blood glucose level within the physiological range is essential to lead a healthy life. The frequent monitoring of blood glucose is an important part of diabetic management specially for type-1 diabetes. A laboratory test or self-test with a small device uses a blood sample collected from a body part with a needle. In extreme cases a diabetic patient needs to undergo this painful process several times a day. To reduce this suffering, a non-invasive (without any blood sample) and patient friendly way of measurement is crucial. Unique advantageous features of UWB technology has demonstrated the widely use of biomedical applications, specially for early breast cancer detection. In the field of exploring potential non-invasive solutions to diabetes detection one promising alternative can be UWB based system using artificial intelligence technique. This relies on variation of dielectric properties (permittivity and conductivity) of target tissues or cells in a given frequency. Initially the experimental setup was prepared with different types of homemade antennas to select the appropriate antenna type, perfect measurable body place, and to confirm the proof of concept. In integrated system a rectangular patch antenna was fixed with a transceiver to generate 4.3 GHz frequency and pass through the earlobe. Received discriminated scattered signal was processed and discrete values were reduced to use as input of artificial neural network (ANN). Number of experiment was conducted to construct an optimal ANN module where actual blood glucose was used as target. The final network output was used to obtain the blood glucose reading from a given scattered signal value. 2017 2023-03-06T02:25:42Z 2023-03-06T02:25:42Z Thesis http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77983 en Universiti Malaysia Perlis (UniMAP) Universiti Malaysia Perlis (UniMAP) School of Computer and Communication Engineering
institution Universiti Malaysia Perlis
building UniMAP Library
collection Institutional Repository
continent Asia
country Malaysia
content_provider Universiti Malaysia Perlis
content_source UniMAP Library Digital Repository
url_provider http://dspace.unimap.edu.my/
language English
topic Blood sugar
Diabetes
Blood glucose
Diabetic patient
Ultra-wideband devices
spellingShingle Blood sugar
Diabetes
Blood glucose
Diabetic patient
Ultra-wideband devices
Md Shawkat, Ali
A non-invasive ultra-wide band based system using artificial intelligence to determine blood glucose level
description Master of Science in Computer Engineering
author2 Sabira, Khatun, Prof. Dr.
author_facet Sabira, Khatun, Prof. Dr.
Md Shawkat, Ali
format Thesis
author Md Shawkat, Ali
author_sort Md Shawkat, Ali
title A non-invasive ultra-wide band based system using artificial intelligence to determine blood glucose level
title_short A non-invasive ultra-wide band based system using artificial intelligence to determine blood glucose level
title_full A non-invasive ultra-wide band based system using artificial intelligence to determine blood glucose level
title_fullStr A non-invasive ultra-wide band based system using artificial intelligence to determine blood glucose level
title_full_unstemmed A non-invasive ultra-wide band based system using artificial intelligence to determine blood glucose level
title_sort non-invasive ultra-wide band based system using artificial intelligence to determine blood glucose level
publisher Universiti Malaysia Perlis (UniMAP)
publishDate 2017
url http://dspace.unimap.edu.my:80/xmlui/handle/123456789/77983
_version_ 1772813067272323072
score 13.222552

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