A junior in biomedical engineering, a graduate in biotechnology and a second-year biomedical sciences student are working on a project that would help people determine whether they are diabetic or not. Guarav Agrawal, Christlin Ponraj and Angelin Ponraj have created Integrated Latrine Technology for Early Diseases Detection according to the University of Alabama at Birmingham. And it has something to do with...toilets.
The idea is that the water in the toilet bowl will change colour to suggest to a person that there is a likelihood that they have diabetes.
The Centers for Disease Control and Prevention have said that 18.8 million Americans were "diagnosed with diabetes in 2010."
Agrawal said, "Southern states have the highest percentage of diagnosed cases, making them essential targets for preventive and early detection diabetic care."
Giving a tidbit of information as to what they are building, Angelin Ponraj, said: "We hope that this affordable, easy-to-use device will also allow us to advocate for the benefits of preventative medicine."
How the device would work is yet to be defined but the students have every intention of spreading the word that soon you will be able to detect diabetes early on so treatment can be started as soon as possible.
However, in Singapore, two students from Singapore Polytechnic's Centre for Biomedical and Life Sciences, with help from the Singapore Institute of Manufacturing Technology have designed a working prototype of a chip that would detect diseases such as Ebola, HIV and SARS, according to TodayOnline.
The biochip would perform the task the blood sample testing that big laboratories do. It is alleged that the chip is "pumped through a spiral in the chip" and then the cells are "separated by their sizes."
Perhaps the students over at UAB can learn a thing or two from the students in Singapore and vice versa. Nonetheless, disease detection is becoming easier and easier in the world of today. This means that people would get the treatment they need the minute they need it after detection.
