An international study has found that wearable technology could help detect Parkinson’s disease up to nine years before clinical diagnosis simply by monitoring how people turn when they walk.

The collaborative research, involving five institutions, including the University Hospital of Kiel and Murdoch University, tracked 1,051 participants over the age of 50 for ten years.

Participants wore a single sensor on their lower back which measured their turning movements, including turning angle, duration, and speed, while walking down a 20 metre hallway.

The ongoing study, being conducted at the University Hospital Tübingen in Germany, with data collected over a decade, found slower peak angular velocity, how quickly someone turns at their fastest point, was linked to a higher risk of developing PD.

According to the results, estimated turning speeds started to decline around 8.8 years before a clinical diagnosis of PD, making it one of the earliest detectable motor signs of PD.

To validate the findings, researchers used a machine learning model that considered age, sex, and peak angular velocity to predict which participants would develop PD. The model identified Parkinson’s cases with an area under the curve (AUC) of 80.5%, indicating strong predictive accuracy.

“This research opens a vital window for early intervention,” said Associate Professor Brook Galna from Murdoch University’s School of Allied Health.

“By detecting changes in turning speed through wearable sensors, in combination with other early signs of Parkinson’s, we can identify individuals at risk long before symptoms become clinically apparent,” he said.

“Earlier detection of people at risk of developing Parkinson’s will speed the discovery and testing of neuroprotective treatments designed to slow disease progression and keep people living independently for longer.”

The full study, Turning Slowly Predicts Future Diagnosis of Parkinson’s Disease: A Decade-Long Longitudinal Analysis, is freely available in Annals of Neurology.