Browsing by Author "Muhammed, Mustafa Hassaan"

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    Bio-medical Device for Blood Glucose Measurement using Non-invasive Technology
    (October university for modern sciences and arts, 2019) Muhammed, Mustafa Hassaan; Saad, Abdalla Radwan
    The quantity of individuals affected by diabetes is rapidly expanding around the world because of the expansion of middle age in the populace and lifestyle that doesn’t include any activity for the body. The quantity is possible to be exceeded in 2030 to 500 million cases, bringing out the most socio-health crises of the 3rd millennium. Monitoring blood glucose concentration levels daily is an advantageous thing to avoid a problem in health. The devices available in the market have many side effects as they use an invasive method in measuring glucose concentration level. Over the last few years, the level of blood glucose is self-monitored using a glucose meter that works with an invasive way. Invasive method of testing blood glucose concentration causes a risk of skin infection, physical and psychological pain due to pricking the finger at least three times. Currently, there are some devices that monitor glucose concentration levels continuously and they are called continuous glucose monitoring (CGM) devices. CGM devices working by placing a sensor on the body by a needle stick. Nowadays, there are a lot of researches about a new technology which will be used in measuring blood glucose concentration with a non-invasive way to dispose the side effects of the available devices in the market. The purpose of this project is to provide a non-invasive technique for measuring blood glucose concentration level to replace the available devices in the Egyptian market. A signal called “photoplethysmography (PPG)” is used in estimating blood glucose concentration level. PPG signal is obtained using near-infrared spectroscopy which contains near-Infrared (NIR) LED and Indium Galium Arsenide (InGaAs) photodiode of peak wavelength 1550nm. Regression analysis will be used to obtain a regression equation that is going to predict the glucose concentration level using a dataset that contains invasive blood glucose measurements and the corresponding analog voltage for a certain number of diabetic individuals.