New app could lead to improved treatment for people with Parkinson’s Disease
Technology uses a smartphone app and online Big Data analytics to assess symptoms in real-time
A new app, developed by researchers from Birkbeck’s Department of Computer Science and Information Systems, UCL, Benchmark Performance Ltd (a specialist SME in Big Data Systems) and Retechnica Ltd (an AI and machine learning startup), could help track the development of Parkinson’s Disease symptoms and lead to improved and more personalised treatments for the 120,000 people in the UK who have the condition.
People with Parkinson’s Disease see a specialist nurse or doctor only once or twice a year, allowing only brief and intermittent assessment of the wide range of motor and non-motor symptoms. The difficulties of assessment are compounded later in the course of the disease when symptoms vary considerably from day-to-day and hour-to-hour while the clinician can only examine a single snapshot captured during the patient’s appointment. Yet, the ability to carry out detailed, reliable, consistent and objective assessments is critical for the development of effective treatment strategies.
The new app, called the cloudUPDRS system, combines a smartphone app and an online Big Data analytics service that is capable of making objective and reliable assessments of motor performance. The app sits on the patient’s smartphone at home recording the details of the movement of the patient while she performs a series of simple actions with each limb, such as tapping the screen to assess bradykinesia (slowness of movement) and holding the phone on their knee to assess tremor. The app securely uploads these measurements to the cloudUPDRS analytics server, which uses state-of-the-art cloud-based Big Data technology and analytics such as microservices and deep learning, to calculate a score in the format of the clinical Universal Parkinson’s Disease Rating Scale (UPDRS). Additional longitudinal analytics performed on tests collected frequently over a period of time enable trend analysis and patient stratification that can provide detailed information on disease progression and inform treatment strategies. Unusually for an app, cloudUPDRS has been certified as a medical device. Most apps are considered lifestyle applications.
Professor George Roussos, who is the research lead in computing technology for the app development, said: “The cloudUPDRS system can provide a range of benefits to both patients and clinicians. More regular assessments of disease progression mean that patients receive more consistent and reliable care, and detailed and automated patient analytics permit the early identification of problems such as medication side-effects. By collecting and analysing data ahead of appointments, clinicians and patients can focus clinic time on treatment strategies, rather than clinical assessment. Finally, by monitoring symptoms in real time, patients can be directly involved in efforts to improve the management of their own care and can receive tailored advice on managing their symptoms through measures such as improved nutrition and physical therapy.”
cloudUPDRS has been in development since 2012 and a clinical trial to measure how it compares to traditional methods of Parkinson’s Disease symptom tracking is currently underway.
Further information:
- Professor George Roussos
- Department of Computer Science and Information Systems
- School of Business, Economics and Informatics
- Courses in computer science
- Courses in data technology