A new smartphone app is enabling doctors to remotely monitor their patients’ progression of Parkinson’s.
Developed by University College London (UCL) and Birbeck, University of London, the app can provide clinicians with a more complete picture of a person’s condition than they can get from a typically brief medical check-up, according to findings published in npj Parkinson’s Disease.
cloudUPDRS was developed by a team of computer scientists and clinical researchers, working alongside people with Parkinson’s disease, who regularly provided feedback to ensure the app was user-friendly. The scientists employed machine learning to train the app.
Lead researcher Dr Ashwani Jha 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.”
Birkbeck professor George Roussos manufactured the app, which is certified as a medical device under UK regulations and includes both self-assessment questions and physical tests, enabled by the smartphone’s movement and touch sensors, to measure symptoms such as tremors and gait.
Roussos said: “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.”