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We have built the glucose meter from scratch by buying the individual parts (resisters, op amps, photodiode, photoemitter) and integrating them into the design that we chose to do. The necessary software has been developed in python programming, using the serial python libraries and C programming with Arduino software.

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From my 7th grade, I decided that I wanted to do something in the field of biology. So as a middle schooler,  I volunteer a lot of my time at medshare. Medshare is a non-profit organization in which they send medical instruments to developing countries with the help of major hospitals such as Kaiser Permanente. They send unused medical instruments to third world countries in Africa such as Nigeria to help them with acquiring basic medical supplies. One of the common technologies they ship is invasive glucose meter test strips. But I thought, wouldn’t it be a painful process to go through every day? Now some young children are diagnosed with diabetes as well, there had to be a more economical and comfortable/non-painful way to check glucose levels. The problem with normal noninvasive glucose meters is that they cost too much and lack the continuous monitoring capability as well. So I decided to build a low-cost, non-invasive glucose meter that would solve both problems.

At the conclusion of the project, We were successful in creating a glucose meter that has approx. +/- 20% error rate to measure glucose levels. The cost is extremely low compared with other glucometer so that it can be a beneficiary for the developing countries in Africa. If the proposed meter is marketed by any industry, millions of people in developing and underdeveloped countries can benefit.


MOD SARS-CoV-2 Telemedicine Diagnostic Solution

There are currently about 82.3 million COVID-19 cases worldwide with 24% of these cases being severe, and a 2% mortality rate. When diagnosed with COVID-19, people are required to stay in 14 days of self-isolation where they have no insight into their state-of-being. In these 14 days, if the condition become critical, people are immediately rushed to the ICU. 

To address this problem, I have developed a home-based telemedicine solution can enable patients to monitor their symptoms along with correlating them to provide meaningful clinical results for a better understanding of the impact of SARS-CoV-2 on overall patient health. My research entails the testing of this platform to see if it can yield results that can warn patients about their health condition by leveraging a product that deploys a contactless and easy-to-use telehealth solution.

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Device Components: The biomedical device integrates three biosensors on a single platform - MAX30102 pulse oximeter, MLX90640 thermal sensor, and MPXV7025 spirometer. All 3 biosensors are connected to the ESP32 microprocessor (or the “brain”). Microprocessor collects the data and processes it using a correlational algorithm to output results onto the LCD screen. All the necessary software has been developed in C programming with Arduino IDE.

Non-linear regression analysis has been utilised by the device to show predictive analytics of the trend of the readings increasing or decreasing depending on the model parameters chosen and variables being measured. 

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