Smartwatch data could detect Parkinson's disease up to 7 years before symptoms show

Wearable devices could revolutionise diagnosis, researcher tells The National

Motion tracking data from smartphones could be crucial to the early detection of Parkinson's disease. Getty

Smartwatches could be play a key role in detecting Parkinson's disease up to seven years before the classic symptoms surface, new research suggests.

This early diagnosis could pave the way for preventive interventions before the disease inflicts extensive brain damage.

The study, published in Nature Medicine and led by scientists from the UK Dementia Research Institute and Neuroscience and Mental Health Innovation Institute at Cardiff University, evaluated motion-tracking data captured by smartwatches over seven days.

The researchers found that they could use artificial intelligence to accurately predict which of the wearers would later develop Parkinson's disease.

The study's leader, Dr Cynthia Sandor, told The National: “People affected by Parkinson's experience motor symptoms such as slow movement, rigidity, co-ordination difficulties, and tremors.

“Importantly, this disease can start years before individuals receive a clinical diagnosis, during which they may exhibit subtle motor or non-motor symptoms that often go unnoticed by the individuals themselves.”

Dr Sandor noted that around 30 per cent of the UK and US population uses smartwatches, which contain the motion sensors to collect data.

“The wristband activity tracker used in our study includes motion sensors commonly found in smartwatches. These sensors passively collect data on movement,” she explained.

The data from these devices is complex, and AI models help to recognise and select the most pertinent features that contribute to the predictive value of the model.

Smartphone motion sensors track subtle movement changes which, combined with AI, could help predict Parkinson's onset. Getty

The study highlighted certain distinct patterns related to movement acceleration and sleep quality that indicated an increased likelihood of Parkinson's disease.

According to Dr Sandor: “Individuals before a Parkinson's diagnosis exhibit indications of reduced sleep quality and duration. These individuals also experience slowness of movement during normal physical activity compared to individuals without a diagnosis.”

However, she stressed that wearable devices should not be mistaken for diagnostic tools, pointing out limitations such as variations in data accuracy, user compliance, complex data interpretation, the need for contextual information, limited generalizability, and ethical considerations.

This pioneering study offers a potential new screening tool for Parkinson's disease, enabling detection at a much earlier stage than current methods.

Dr Kathryn Peall, clinical senior lecturer in the Neuroscience and Mental Health Innovation Institute at Cardiff University, said: “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.”

The next phase of this research involves replicating these results in different cohorts. Dr Sandor expressed her excitement about continuing studies, primarily led by the Michael J. Fox Foundation, to further this research.