Developers of a new AI device aim to recreate neural networks to detect Parkinson’s in patients.
The device brings together a series of connected algorithms which collectively mimic the way a human brain works. It can assess whether someone has Parkinson’s from their nocturnal breathing.
This neural network is also able to discern the severity of someone’s Parkinson’s disease and track the progression of the condition over time.
Dina Katabi, part of the team that developed the device, said: “A relationship between Parkinson’s and breathing was noted as early as 1817, in the work of Dr. James Parkinson’s. This motivated us to consider the potential of detecting the disease from one’s breathing without looking at movements.
“Some medical studies have shown that respiratory symptoms manifest years before motor symptoms, meaning that breathing attributes could be promising for risk assessment prior to Parkinson’s diagnosis.”
Researchers demonstrated that the AI assessment of Parkinson’s can be done every night at home while the person is asleep and without touching their body.
To do so, the device emits radio signals, analyses their reflections off the surrounding environment, and extracts the subject’s breathing patterns without any bodily contact.
The study may also have a positive impact for Parkinson’s drug development and clinical care.
“In terms of drug development, the results can enable clinical trials with a significantly shorter duration and fewer participants, ultimately accelerating the development of new therapies,” said Katabi.
“In terms of clinical care, the approach can help in the assessment of Parkinson’s patients in traditionally underserved communities, including those who live in rural areas and those with difficulty leaving home due to limited mobility or cognitive impairment.”
Dr. Ray Dorsey, a professor of neurology at the University of Rochester, said that the study is likely one of the largest sleep studies ever conducted on Parkinson’s disease.
“We have very limited information about manifestations of the disease in their natural environment and this device allows you to get objective, real-word assessments of how people are doing at home.”
