TY - JOUR
T1 - Long-term unsupervised mobility assessment in movement disorders
AU - Warmerdam, Elke
AU - Hausdorff, Jeffrey M.
AU - Atrsaei, Arash
AU - Zhou, Yuhan
AU - Mirelman, Anat
AU - Aminian, Kamiar
AU - Espay, Alberto J.
AU - Hansen, Clint
AU - Evers, Luc J.W.
AU - Keller, Andreas
AU - Lamoth, Claudine
AU - Pilotto, Andrea
AU - Rochester, Lynn
AU - Schmidt, Gerhard
AU - Bloem, Bastiaan R.
AU - Maetzler, Walter
N1 - Publisher Copyright:
© 2020 Elsevier Ltd
PY - 2020/5/1
Y1 - 2020/5/1
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85083460219&partnerID=8YFLogxK
U2 - 10.1016/S1474-4422(19)30397-7
DO - 10.1016/S1474-4422(19)30397-7
M3 - Review article
AN - SCOPUS:85083460219
SN - 1474-4422
VL - 19
SP - 462
EP - 470
JO - The Lancet Neurology
JF - The Lancet Neurology
IS - 5
ER -