James Parkinson first flagged a link between changes in breathing patterns and the debilitating disease that now bears his name. But since his work in the early 19th century, only minimal progress has been made in treating a condition that has become alarmingly prevalent.
The paper by researchers at the Massachusetts Institute of Technology and several other institutions describes an Artificial Intelligence tool that can analyze changes in nighttime breathing to detect and track the progression of disease, which causes tremors and other serious issues with movement.
The AI was able to accurately flag Parkinson’s using one night of breathing data collected from a belt worn around the abdomen or from a passive monitoring system that tracks breathing using a low-power radio signal. It was trained on breathing data collected during 12,000 nights of sleep from institutions around the country, and tested on outside data.
Results from 12 patients who didn’t have Parkinson’s during their initial sleep study, and later developed the disease, indicated that the AI may be able to catch Parkinson’s far earlier in the disease process than existing methods. The researchers are working on a new study to confirm that finding.
“That is really the golden question,” said Dina Katabi, a co-author of the study who directs MIT’s center for wireless networks and mobile computing. “All the indications so far are positive and we hope that we can start detecting Parkinson’s much earlier.”
The ability to do so points to the power of AI to extend the capabilities of human perception to find new signals of disease and shake up the science surrounding some of medicine’s hardest problems. Parkinson’s is especially difficult to treat because there is no objective way to measure the disease. Existing methods rely on a series of largely subjective assessments that must be conducted by highly-trained specialists. But the analysis of breathing patterns offers hope of an objective biomarker that could diagnose and monitor the condition in a person’s home, reducing reliance on visits with far-flung experts.
“Most people never make their way to Harvard,” said Ray Dorsey, a Parkinson’s expert at the University of Rochester who was also a co-author on the study. “It’s a figment of their imagination. That you can measure health outside the clinical setting is really, really powerful, and it opens the door to providing more care in the home.”
A significant portion of the data used in the study was collected via a wireless radio transmitter that could be placed in a subject’s bedroom. Rather than requiring the use of clunky belts and tubes, it measures the reflections off a person’s body, allowing the AI to analyze a surprisingly rich trove of data about human physiology.
Contained in the data is information about a person’s breathing, the pulsing of their blood, and the twitching of their muscles.
