Blood tests are vital for diagnosis and monitoring a number of diseases. In many rural areas, people have to travel a significant distance to reach the nearest health care facility to get their blood samples tested. Sometimes, this results in a delay in detecting serious diseases. But if two Indian researchers have their way, this roadblock in improving the health index of rural India would soon be a thing of the past. They have designed a simple and affordable device that can be transported to remote areas for blood analysis.
The device uses a Raspberry Pi computer and all it needs is a source of electricity. It has been designed by Sangeeta Palekar, a researcher at Shri Ramdeobaba College of Engineering and Management in Nagpur, and her colleague Jayu Kalambe.
Currently, most existing laboratory devices use light to test blood samples. When light passes through a blood sample, its intensity changes depending on the concentration of that sample. This helps analyse the number of red blood cells or glucose levels present in the blood.
The new analyser by Palekar and her colleague takes a similar approach. Their device has an automated fluid dispenser that adds a controlled amount of reagent into the blood sample and light is then passed through it. A tiny Raspberry Pi computer then analyses the data. The researchers say their device can be modified to test any biochemical substances in the blood. Their research has been published in the Institute of Electrical and Electronics Engineers (IEEE) Sensors Journal.
Talking to the IEEE Spectrum magazine, Palekar said she understands how important a blood test can be in detecting diseases. “Routine blood tests can help track and eliminate the threat of many potential diseases,” she said.
Palekar also said that there are several benefits of their design — automation, low cost, portability, and an easy interface.
Overall, she adds, their design “is an attractive solution” for low resource areas.
The two researchers are now focussed on expanding the types of blood tests that can be done, for example, proteins, cholesterol, triglyceride, and albumin levels.
