A new app is being developed by researchers at UCL and University of London, to be used to support doctors to remotely monitor their patients’ progression of Parkinson’s symptoms.
Following a clinical trial, the app has shown it can support clinicians by providing multiple symptom readings over time, rather than solely through scheduled check-ups.
The findings have been published in npj Parkinson’s Disease, where 60 participants in the study completed 990 tests for three separate clinical teams.
The app, cloudUPDRS, was developed by computer scientists and clinical researchers, to measure symptoms such as tremors and gait. It has a 79% accuracy of assessment, compared to the clinical teams assessment. The researchers noted that while the app’s performance does not quite match that of clinicians, one advantage is that the app may be more objective.
Lead researcher Dr Ashwani Jha (UCL Queen Square Institute of Neurology) said: “Parkinson’s disease is highly variable, as it can progress at very different rates in different people, who will not all experience the same symptoms. For that reason, people with the condition need regular check-ups, often about twice a year, so that doctors can monitor the progression of their symptoms and update their treatment plan.”
“One challenge of these regular check-ups is that symptoms can vary day-to-day, and even throughout the day, so getting a snapshot when a person visits the clinic will not always give the full picture of their condition.”
“Using an app to track symptoms from home, with multiple readings over a longer period of time, could more effectively capture fluctuations in symptoms.”
“Assessing physical symptoms has been particularly challenging during the COVID-19 pandemic; monitoring patients remotely could enable high-quality care while maintaining social distancing.”
Professor Roussos added: “Digital biomarkers developed using mobile and wearable technologies offer novel opportunities for disease management, especially in Parkinson’s, which sets distinctive challenges due to its complex presentation and high symptom variability. Nevertheless, before such technologies can be adopted widely, we must control for the additional sources of variability in measurement related to device and algorithm selection. In the study, we adopted an approach based on open sharing of software which we hope will foster wider sharing of practices and help establish digital endpoints for Parkinson’s as trusted clinical tools.”
The researchers are continuing to develop and refine the app and are planning a larger trial to help determine how the app could be integrated into clinical practice.
