As digital health technology becomes more pervasive, machine learning (ML) provides a
robust way to analyze and interpret the myriad of collected features. The purpose of this …

Consumer wearables and sensors are a rich source of data about patients' daily disease
and symptom burden, particularly in the case of movement disorders like Parkinson's …

Digital assessments of motor severity could improve the sensitivity of clinical trials and
personalise treatment in Parkinson's disease (PD) but have yet to be widely adopted. Their …

Digital health technologies enable remote and therefore frequent measurement of motor
signs, potentially providing reliable and valid estimates of motor sign severity and …

Background: Ubiquitous digital technologies such as smartphone sensors promise to
fundamentally change biomedical research and treatment monitoring in neurological …

Smartphones and wearables are widely recognised as the foundation for novel Digital
Health Technologies (DHTs) for the clinical assessment of Parkinson's disease. Yet, only …

Background Objective assessments of Parkinson's disease (PD) patients' motor state using
motion capture techniques are still rarely used in clinical practice, even though they may …

Parkinson's disease (PD) has become the second most common neurodegenerative
condition following Alzheimer's disease (AD), exhibiting high prevalence and incident rates …

Parkinson's disease (PD) is a common neurological disease in elderly people, and its
morbidity and mortality are increasing with the advent of global ageing. The traditional …

Objective: The aim of this study is to develop a smartphone-based high-frequency remote
monitoring platform, assess its feasibility for remote monitoring of symptoms in Parkinson's …