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Data from smartwatches can detect early brain changes linked to Parkinson’s disease with greater sensitivity than established clinical risk scores.

The , led by at the UK Dementia Research Institute at Imperial, shows that wearable technology can identify early signs of dopamine dysfunction and misfolded α-synuclein – key biological hallmarks of Parkinson’s – with higher sensitivity than established clinical scoring systems.

The findings, , highlight the potential of digital health tools for earlier, more accessible, and cost-effective detection of Parkinson’s risk. 

Comparing digital and clinical measures 

Previous research from the demonstrated that wearable devices could predict Parkinson’s years before diagnosis based on movement data. However, this is the first time smartwatch-derived data has been directly compared to gold-standard biological markers – including specialist scans known as dopamine transporter imaging (DaTscan) and cerebrospinal fluid spinal fluid tests for misfolded α-synuclein – as well as to established clinical risk scores. 

Using data from the Parkinson’s Progression Markers Initiative (PPMI), a major international research project led by the Michael J. Fox Foundation, the researchers analysed information from participants who wore Verily smartwatches for an average of 16 months. These devices continuously and passively recorded sleep patterns, heart rate, and physical activity.

Developing a digital risk score

Using this data, the team developed a digital risk score and assessed its ability to distinguish individuals with Parkinson’s from healthy controls. They compared this score to the Movement Disorder Society (MDS) research criteria, a commonly used clinical risk score, and then applied it to a separate group of at-risk individuals due to genetic variants or early symptoms. The team compared the digital score’s performance against DaTscan and spinal fluid results.

The digital risk score correlated with both clinical and biological markers and showed higher sensitivity than the MDS criteria for detecting early Parkinson’s-related changes. When combined with smell testing (hyposmia, a common early symptom of Parkinson’s), the smartwatch-derived score identified over 80% of individuals with abnormal brain scans or spinal fluid markers.

Towards earlier, easier diagnosis

The researchers say that the digital score could provide a simple, non-invasive screening method to help identify those most likely to benefit from more detailed clinical testing. This could make early diagnosis of Parkinson’s more accessible and affordable.

"This kind of digital monitoring could be a game-changer – offering a simple, non-invasive way to screen those most at risk." Dr Cynthia Sandor

Dr Cynthia Sandor, Edmond & Lily Safra Assistant Professor in Parkinson's Disease at Imperial’s Department of Brain Sciences, said: "Our findings suggest that everyday smartwatch data could help flag early signs of Parkinson’s long before a clinical diagnosis is made. The accuracy of this data is on par with current standard tests, which can be expensive and invasive. This kind of digital monitoring could be a game-changer – offering a simple, non-invasive way to screen those most at risk and helping to guide who should receive more definitive testing."

Publication
Schalkamp AK, Peall KJ, Harrison NA, Escott-Price V, Barnaghi P, Sandor C. Wearables-derived risk score for unintrusive detection of α-synuclein aggregation or dopaminergic deficit. eBioMedicine. 2025 Jun 5;117:105782. doi: 10.1016/j.ebiom.2025.105782

This article is adapted from a , Senior Communications and Media Officer at UK Dementia Research Institute.