Long-term unsupervised mobility assessment in movement disorders,The Lancet Neurology

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Long-term unsupervised mobility assessment in movement disorders
The Lancet Neurology ( IF 46.5 ) Pub Date : 2020-05-01 , DOI: 10.1016/s1474-4422(19)30397-7
Elke Warmerdam ₁ , Jeffrey M Hausdorff ₂ , Arash Atrsaei ₃ , Yuhan Zhou ₄ , Anat Mirelman ₅ , Kamiar Aminian ₃ , Alberto J Espay ₆ , Clint Hansen ₇ , Luc J W Evers ₈ , Andreas Keller ₉ , Claudine Lamoth ₄ , Andrea Pilotto ₁₀ , Lynn Rochester ₁₁ , Gerhard Schmidt ₁₂ , Bastiaan R Bloem ₈ , Walter Maetzler ₇

Affiliation

Department of Neurology, Kiel University, Kiel, Germany; Faculty of Engineering, Kiel University, Kiel, Germany.
Center for the Study of Movement, Cognition, and Mobility, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Physical Therapy, Sackler Faculty of Medicine and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel; Rush Alzheimer's Disease Center and Department of Orthopaedic Surgery, Rush University Medical Center, Chicago, IL, USA.
Laboratory of Movement Analysis and Measurement, École Polytechnique Fédérale de Lausanne, Lausanne, Switzerland.
University of Groningen, University Medical Center Groningen, Center for Human Movement Sciences, Groningen, Netherlands.
Center for the Study of Movement, Cognition, and Mobility, Tel Aviv Sourasky Medical Center, Tel Aviv, Israel; Department of Physical Therapy, Sackler Faculty of Medicine and Sagol School of Neuroscience, Tel Aviv University, Tel Aviv, Israel.
Gardner Family Center for Parkinson's Disease and Movement Disorders, University of Cincinnati, Cincinnati, OH, USA.
Department of Neurology, Kiel University, Kiel, Germany.
Radboud University Medical Center, Donders Institute for Brain, Cognition, and Behaviour, Department of Neurology, Center of Expertise for Parkinson & Movement Disorders, Nijmegen, Netherlands.
Center for Bioinformatics, Saarland University, Saarbrücken, Germany; Department of Neurology and Neurological Sciences, School of Medicine, Stanford University, Stanford, CA, USA.
Department of Clinical and Experimental Sciences, University of Brescia, Brescia, Italy; Parkinson's Disease Rehabilitation Centre, Fondazione Europea Ricerca Biomedica, St Isidoro Hospital, Bergamo, Italy.
Institute of Neuroscience, Newcastle University, Newcastle upon Tyne, UK; Newcastle upon Tyne Hospitals, National Health Service Foundation Trust, Newcastle upon Tyne, UK.
Faculty of Engineering, Kiel University, Kiel, Germany.

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.

中文翻译：

运动障碍的长期无监督活动评估

在无人监督的日常生活环境中量化移动性的移动健康技术（可穿戴、便携式、身体固定传感器或家用集成设备）正在成为补充临床评估。在这些生态有效、与患者相关的环境中收集的数据可以克服传统临床评估的局限性，因为它们可以捕捉波动和罕见的事件。这些数据可以支持临床决策，也可以作为临床试验的结果。然而，直接比较在无监督和有监督（例如，在实验室或医院）环境中进行的评估的研究表明，即使在相同的流动性参数方面也存在巨大差异。这些差异似乎受到心理、生理、认知、环境和技术因素的影响，以及评估的流动性和诊断类型。为了促进无监督的流动性评估成功适应临床实践和临床试验，临床医生和研究人员应考虑这些差异以及导致这些差异的多种因素。

更新日期：2020-05-01

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