The world could one day have ultrasound technology that is so sensitive where it can listen to the sound of living bacteria and cells, thanks to a team of researchers at the University of Queensland (UQ) who have developed a silicon chip containing ultra-precise ultrasound sensors that they said can measure miniscule random forces from surrounding air molecules.
"What [UQ's] developed is a high frequency sensor that takes us up to 1 megahertz (mHz), and with sensitivity that is about a factor of a hundred better than anything achieved before which allows you to push very, very high resolution imaging applications forward," Professor Warwick Bowen of UQ's Precision Sensing Initiative and the Australian Centre for Engineered Quantum Systems told ZDNet.
The silicon chip uses a type of biomedical ultrasound called photoacoustic ultrasound, where a laser or another technique generates an acoustic pulse in the body, and then uses ultrasound sensors to detect the resulting acoustic wave that propagates throughout the body.
Read also: Small, flexible plaster uses ultrasound waves to monitor blood pressure inside your body
Bowen said that a potential use case for the sensor is that its precise ultrasound measurements will be able to view the vibrations of thousands of cells and characterise, without contaminating them, whether they are healthy or cancerous cells.
He explained that current technologies characterising cells can only view a limited amount of them at a time, and have limited use cycles due to being contaminated from making contact with cells rather than watching the cell's acoustic waves.
Another example of the sensor's practical applications, according to Bowen, is that it can also track cells as they move around the body which will provide scientists with a better understanding of biology.
"For high resolution photoacoustic imaging, you use these types of sensors to track red blood cells as they move around; you can't go deep into the body but you can go 5mm deep and track blood cells as they go through veins and learn about how blood flows in your brain for example," he said.
Research leader Dr Sahar Basiri-Esfahani, now at Swansea University, said the accuracy of the technology will change how scientists understand biology.
"A deeper understanding of these biological systems may lead to new treatments, so we're looking forward to seeing what future applications emerge," Basiri-Esfahani said.
Read also: Sensors under the skin monitor your alcohol intake
UQ, in collaboration with the University of New South Wales, also announced in December that it has developed artificial intelligence that maps out the global foreshore to quantify how much of the world's crucial coastal environments have been lost.
The mapping process required nearly one million hours of computation and the use of 22,000 machines via the Google Earth Engine, and was conducted alongside Google and the Australian Institute of Marine Science.
Small, flexible plaster uses ultrasound waves to monitor blood pressure inside your body
The readings might be more accurate, too, considering how our blood pressure tends to rise in the doctor's office.
UNSW, UQ behind Printed Energy's AU$12m project to advance screen-printed batteries
Screen-printed batteries for cheap portable devices and intermittent renewable energy are closer to reality with UNSW and UQ backing the project to further develop the technology.
University of Queensland to use vibrations instead of electricity in chips for space
The vibration-powered chips will enable the creation of nanotechnologies that can be used in areas such as sensing, health, and communications, according to the University of Queensland.
UQ buys supercomputer for computational research
The University of Queensland's Australian Institute for Bioengineering and Nanotechnology will have a supercomputer by the end of November that will support research in computational modelling of physical, pharmaceutical, and biological systems.
AI that improves healthcare efficiency also threatens profits (TechRepublic)
Some medical technologies that use artificial intelligence might benefit patients but result in a drop in health system revenues. This could make widespread adoption of AI in medicine a tough sell.