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Instrumental assessment of stepping in place captures clinically relevant motor symptoms of Parkinson's disease

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Item Type:Article
Title:Instrumental assessment of stepping in place captures clinically relevant motor symptoms of Parkinson's disease
Creators Name:Otte, K. and Ellermeyer, T. and Vater, T.S. and Voigt, M. and Kroneberg, D. and Rasche, L. and Krüger, T. and Röhling, H.M. and Kayser, B. and Mansow-Model, S. and Klostermann, F. and Brandt, A.U. and Paul, F. and Lipp, A. and Schmitz-Hübsch, T.
Abstract:Fluctuations of motor symptoms make clinical assessment in Parkinson’s disease a complex task. New technologies aim to quantify motor symptoms, and their remote application holds potential for a closer monitoring of treatment effects. The focus of this study was to explore the potential of a stepping in place task using RGB-Depth (RGBD) camera technology to assess motor symptoms of people with Parkinson’s disease. In total, 25 persons performed a 40 s stepping in place task in front of a single RGBD camera (Kinect for Xbox One) in up to two different therapeutic states. Eight kinematic parameters were derived from knee movements to describe features of hypokinesia, asymmetry, and arrhythmicity of stepping. To explore their potential clinical utility, these parameters were analyzed for their Spearman’s Rho rank correlation to clinical ratings, and for intraindividual changes between treatment conditions using standard response mean and paired t-test. Test performance not only differed between ON and OFF treatment conditions, but showed moderate correlations to clinical ratings, specifically ratings of postural instability (pull test). Furthermore, the test elicited freezing in some subjects. Results suggest that this single standardized motor task is a promising candidate to assess an array of relevant motor symptoms of Parkinson’s disease. The simple technical test setup would allow future use by patients themselves.
Keywords:RGBD Camera, Movement Analysis, Parkinson’s Disease, Postural Instability
Source:Sensors
ISSN:1424-8220
Publisher:MDPI
Volume:20
Number:19
Page Range:5465
Date:1 October 2020
Official Publication:https://doi.org/10.3390/s20195465
PubMed:View item in PubMed

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