Doctors might soon diagnose multiple sclerosis by analyzing how patients speak. Canary Speech, an AI company that studies vocal biomarkers, has teamed up with Intermountain Health to test whether voice patterns can detect MS earlier than current methods.
The study marks the first time researchers have received approval to investigate MS detection through voice analysis. More than 2.9 million people worldwide have MS, and early detection can make a huge difference in treatment outcomes.
How does it work?
Canary Speech’s AI listens to voice samples and analyzes subtle speech patterns that humans can’t easily detect. The technology examines how people pronounce words, pause between phrases, and control their vocal muscles.
Dr. Timothy West, a neurologist at Intermountain Health’s Salt Lake Clinic, will lead the study by collecting voice samples from patients in the area. The AI will then analyze these recordings to see if it can accurately identify which patients have MS based solely on their speech.
The same technology has already shown promise in detecting other brain conditions like Huntington’s disease, Alzheimer’s, and Parkinson’s disease. Now researchers want to see if MS leaves similar vocal fingerprints.
Why does it matter?
Current MS diagnosis takes too long and involves uncomfortable procedures. Patients typically need detailed medical histories, MRI scans, and sometimes lumbar punctures where doctors insert needles into the spine to collect fluid.
This complex process often delays treatment while patients get passed between primary care doctors, general neurologists, and specialists. Early treatment is crucial because it can stop damage to the central nervous system and improve long-term quality of life.
A voice-based screening tool could change everything. Patients could potentially get screened during a regular phone call or doctor visit. “The ability to use voice to identify MS would offer a quick, non-invasive screening tool, enabling us to deliver faster care to patients,” Dr. West said.
The context
Voice analysis for medical diagnosis isn’t entirely new, but applying it to MS detection represents a significant step forward. Canary Speech has already launched Canary Ambient, an API that analyzes patient conversations in real-time to detect signs of anxiety, depression, and cognitive decline.
Intermountain Health operates 34 hospitals and 400 clinics across six states, giving the study access to a large patient population. The health system has built a reputation for adopting new technologies that improve patient care.
“We chose to work with Intermountain Health because they are leading the way in adopting innovative technologies to serve their patients better,” said Henry O’Connell, Canary Speech’s CEO. “Partnering on this critical study will hopefully allow us to screen for MS earlier and improve the quality of care for millions of patients.”
If successful, this voice-based approach could become a standard screening tool in doctors’ offices worldwide, making MS detection faster, cheaper, and more accessible to patients everywhere.