Digital technologies for Parkinson’s disease

While healthcare for persons with Parkinson’s disease continues to move rapidly into a digital age, there remain important challenges. Emerging digital technologies offer significant potential in many areas of clinical care and research that include the delivery of telemedicine, assessments of symptoms and remote patient monitoring, and expanded understanding of population health; however, much of this potential has yet to be realized, and clinical uptake remains limited in many of these areas. It is clear that innovations in mobile applications, wearable devices, electronic health records, and artificial intelligence provide unprecedented volumes and types of data that could be used to improve the clinical care and scientific understanding of Parkinson’s disease. It is less clear how this expansion of data will be used to improve the lives of patients.

On this basis, the editors at npj Parkinson’s Disease and npj Digital Medicine invite submissions of primary research studies that leverage digital technologies for improving the abilities to treat, assess, and understand Parkinson’s disease. The goal of this collection is to move toward realization of this significant potential for digital technologies in the research and clinical care of Parkinson’s disease. 

We are particularly interested in manuscripts that address the following with relevance to Parkinson’s disease:

• Innovative digital approaches to the delivery of telemedicine
• Direct clinical applications of digital technologies and solutions for facilitating clinical uptake
• Use of wearable devices for monitoring of motor (e.g., physical activity) and non-motor (e.g., sleep) features
• Applications of artificial intelligence and machine learning in prediction of disease progression and subtyping
• Use of big data approaches to population health data, electronic health records, medical imaging, and other clinical data
• Novel techniques for measurement of symptoms
• Use of digital technologies to expand access of care or address social determinants of health
• Digitally-enabled insights into pathophysiology
• Data-driven personalization of care