Biosensing technology aids early diagnosis of disease

Share this on social media:

A low-cost imaging-based biosensing system has been developed to analyse blood and urine for the early diagnosis of illnesses such as diabetes and Alzheimer’s disease.

Developed by Professor Kazuaki Sawada and Dr Takigawa of Japan’s National Center for Geriatrics and Gerontology, and colleagues at Toyohashi University of Technology, the biosensing technology consists of a semiconductor image sensor (charge coupled device developed by Toyohashi University of Technology) that is sensitive to extremely small changes in electric potential, and microbeads on which antigen-antibody reactions take place.

Specific proteins in the blood and urine often give early indications of a disease. Unlike conventional protocols which employ fluorescent probes and cameras to monitor antibody-antigen reactions, the biosensing system uses a semiconductor image sensor consisting of 128 x 128 pixels to detect minute changes in the electric potential generated during an antigen-antibody reaction.

Diseases for which specific protein markers are known can be diagnosed and monitored using very small volumes of blood or urine - the technology has been used to detect amiloid beta-peptide, an agent responsible for Alzheimer’s disease, for instance.

Multiple diseases can also be simultaneously diagnosed by placing different antibodies on different sensing pixels out of a total of 16,384 pixels (128 x 128).

Implementation of the technology will be tested for the daily control of lifestyle diseases such as diabetes, with expansion for the early diagnosis of Alzheimer’s and Parkinson’ diseases expected in the future.

Related articles:

All in vein

Further information:

National Center for Geriatrics and Gerontology

Toyohashi University of Technology

Recent News

25 May 2021

The face recognition imager consumes 10,000 times less energy than a typical camera and processor. CEA-Leti is working with STMicroelectronics on the imager

06 May 2021

The GTOF0503 sensor features a 5µm three-tap iToF pixel, incorporating an array with a resolution of 640 x 480 pixels

30 April 2021

The algorithm can deduce the shape, size and layout of a room by measuring the time it takes for sound from speakers to return to the phone's microphone

20 April 2021

The Kria K26 SOM is built on top of the Zynq UltraScale+ MPSoC architecture. It has 4GB of DDR4 memory and 245 IOs for connecting sensors