A smartwatch can measure changes in involuntary arm tremors in people with early-stage Parkinson’s disease more accurately than an annual hospital check-up. This is shown by research conducted in the Radboudumc. As a result, it becomes easier and faster to determine whether new Parkinson’s treatments are effective.
More than 63,000 people in the Netherlands are living with Parkinson’s disease. The condition causes symptoms such as tremors, slowed movement, and muscle stiffness. While treatments can help reduce these symptoms, there is currently no cure. Researchers are therefore searching for new therapies that can slow disease progression in its early stages. To establish whether such treatments are effective, changes in symptoms must be measured reliably; something that has proven challenging in practice.
Parkinson’s symptoms are typically assessed during hospital visits, using questionnaires and physical examinations. Although these assessments provide valuable information, they also have important limitations. They capture only a snapshot in time, while symptoms can fluctuate substantially from day to day and even from hour to hour. In addition, stress during a hospital visit can temporarily worsen symptoms.
Measuring at home
Researchers of the Radboudumc therefore explored an alternative approach. People with early-stage Parkinson’s disease were asked to wear a smartwatch continuously in their daily lives. The watch constantly records arm movements. A smart computational method, specifically developed by the research team, analyses these data and identifies patterns associated with Parkinson’s symptoms. ‘For example, we can determine how often and how intensely someone experiences tremors’, explains PhD candidate Nienke Timmermans. ‘And instead of measuring this once a year, we can monitor it continuously.’
In total, 620 people participated in the study, wearing a smartwatch for two years. ‘This makes the Personalized Parkinson Project unique’, says researcher Luc Evers. ‘Never before have Parkinson’s symptoms been monitored for such a long period in such a large group, in a real-world home setting.’
Faster insight into what works
The results show that the smartwatch detects changes in Parkinson-related tremor more accurately than annual hospital assessments. This allows disease progression to be mapped reliably at an early stage. ‘That is extremely valuable’, says Evers. ‘We can determine much sooner whether a new disease-modifying therapy is promising or not. This doesn’t mean there will be a cure tomorrow, but it does mean we can identify effective treatments earlier.’
The method is freely available, allowing other researchers in the Netherlands and abroad to use it immediately. No specialized devices are required: many existing research smartwatches equipped with motion sensors are suitable.
In the future, this approach could also improve care for individual patients. For example, by monitoring whether medication is effective or by more accurately measuring the effects of deep brain stimulation. ‘Further research is still needed’, Timmermans emphasizes. ‘But these results show that we can now monitor Parkinson’s disease much more effectively; simply from home, using a watch.’
About the publication
This research was published in Annals of Neurology: Daily-life, sensor-derived tremor measures are sensitive to progression in early Parkinson's disease. Nienke Timmermans, Ioan Gabriel Bucur, Diogo Soriano, […], Bas Bloem, Rick Helmich, Luc Evers. DOI: 10.1002/ana.78236.
An earlier publication on the computational method for analyzing Parkinson’s symptoms appeared in The Journal of Open Source Software: ParaDigMa: a Python toolbox for extracting Parkinson’s disease digital biomarkers from daily life wrist sensor data. Erik Post, Kars Veldkamp, Nienke Timmermans, […], Yordan Raykov, Twan van Laarhoven, Luc Evers. DOI: 10.21105/joss.09502.
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