Journal Article

Long-term unsupervised mobility assessment in movement disorders

Warmerdam, Elke, Espay, Alberto J, Maetzler, Walter, Lamoth, Claudine, Atrsaei, Arash, Zhou, Yuhan, Mirelman, Anat, Rochester, Lynn, Pilotto, Andrea, Schmidt, Gerhard, Bloem, Bastiaan R, Hansen, Clint, Evers, Luc J W, Keller, Andreas, Hausdorff, Jeffrey M, Aminian, Kamiar

2020

Overview

Mobile health technologies (wearable, portable, body-fixed sensors, or domestic-integrated devices) that quantify mobility in unsupervised, daily living environments are emerging as complementary clinical assessments. Data collected in these ecologically valid, patient-relevant settings can overcome limitations of conventional clinical assessments, as they capture fluctuating and rare events. These data could support clinical decision making and could also serve as outcomes in clinical trials. However, studies that directly compared assessments made in unsupervised and supervised (eg, in the laboratory or hospital) settings point to large disparities, even in the same parameters of mobility. These differences appear to be affected by psychological, physiological, cognitive, environmental, and technical factors, and by the types of mobilities and diagnoses assessed. To facilitate the successful adaptation of the unsupervised assessment of mobility into clinical practice and clinical trials, clinicians and researchers should consider these disparities and the multiple factors that contribute to them.

• Publisher: Elsevier Ltd,Elsevier Limited
• Subject: Algorithms / Clinical decision making / Clinical trials / Cognitive ability / Decision making / Gait / Measurement techniques / Mobility / Movement disorders / Neurology / Older people / Parkinson's disease / Posture / Quality of life