Machine learning and nanotechnology came together to create an implant that can regulate blood pressure in people with spinal cord injuries, according to a Physics World Weekly podcast. Medical researcher Jordan Squair, based in Switzerland, discussed with Physics World’s Tami Freeman how the device was created and successfully tested on a human subject. Amanda Barnard, editor-in-chief of Nano Futures and computational science lead at the Australian National University in Canberra, also discussed her career applying computational science across various fields, including medicine. She touched on her interest in machine learning, the challenges of university administration and her role leading a multidisciplinary research group.
The medical implant created by Squair is groundbreaking, with the ability to regulate blood pressure in people with spinal cord injuries who have orthostatic hypotension. This is where a person’s blood pressure drops when they move from lying or seated to standing up. The implant features electrodes that sit within the blood vessels near the spinal cord, alongside machine learning to accurately predict when blood pressure may drop, and sends signals accordingly.
As well as her work as editor-in-chief of Nano Futures, Barnard leads a multidisciplinary research group that works across various fields, including nanotechnology, materials science, chemistry and medicine. She explained in the podcast how she is interested in applying machine learning to several problems in these fields. Despite the challenges of university administration, Barnard enjoys the role, saying it helps to build a strong foundation for students.
Overall, the podcast highlights the potential benefits achieved when machine learning, nanotechnology and medicine come together to resolve medical problems.
