LONDON - Smart watches could help to identify Parkinson’s disease up to seven years before key symptoms appear and a clinical diagnosis can be made, a study has found.

Researchers analysed data collected by the devices over a seven-day period, measuring how fast people moved.

They found they could use artificial intelligence (AI) to accurately predict who would go on to later develop Parkinson’s disease.

According to the experts, this could be used as a new screening tool for Parkinson’s, enabling the disorder to be detected at a much earlier stage than current methods allow.

With these results we could develop a valuable screening tool to aid in the early detection of Parkinson’s

Dr Cynthia Sandor, Cardiff University

Study leader Dr Cynthia Sandor, emerging leader at the UK Dementia Research Institute at Cardiff University, said: “With these results we could develop a valuable screening tool to aid in the early detection of Parkinson’s.

“This has implications both for research, in improving recruitment into clinical trials; and in clinical practice, in allowing patients to access treatments at an earlier stage, in future when such treatments become available.”

Dr Kathryn Peall, clinical senior lecturer in the NMHII (Neuroscience and Mental Health Innovation Institute) at Cardiff University, said: “For most people with Parkinson’s disease, by the time they start to experience symptoms, many of the affected brain cells have already been lost.

“This means that diagnosing the condition early is challenging.

“Though our findings here are not intended to replace existing methods of diagnosis, smart watch data could provide a useful screening tool to aid in the early detection of the disease.

“This means that as new treatments hopefully begin to emerge, people will be able to access them before the disease causes extensive damage to the brain.”

Parkinson’s affects cells in the brain called dopaminergic neurons, located in an area of the brain known as the substantia nigra.

It causes motor symptoms such as tremor, rigidity (stiffness), and slowness of movement.

By the time these hallmark symptoms of the condition begin to show, and a clinical diagnosis can be made, more than half of the cells in the substantia nigra will already have died, the researchers say.

A cheap, reliable and easily accessible way to detect early changes could allow interventions to be made before the disease causes extensive damage to the brain.

In the new study, researchers analysed data collected from 103,712 people in the UK Biobank study who wore a medical-grade smart watch for seven days in 2013-2016.

The devices measured average acceleration – meaning speed of movement – continuously over the week-long period.

The scientists compared data from a group of people who had already been diagnosed with Parkinson’s disease, to another group who received a diagnosis up to seven years after the smart watch data was collected.

Not only could people who went on to develop Parkinson’s be distinguished from healthy people in the study, but the researchers then extended this to show that the AI could be used to identify individuals who would later develop Parkinson’s in the general population.

This was more accurate than any other risk factor or other recognised early sign of the disease in predicting whether someone would develop Parkinson’s disease.

The model was also able to predict time to diagnosis.

The study was led by scientists at the UK Dementia Research Institute and Neuroscience and Mental Health Innovation Institute at Cardiff University.

It was published on Monday in the journal Nature Medicine, and funded by the UK Dementia Research Institute, the Welsh Government and Cardiff University.