Camera-based objective measures of Parkinson's disease gait features.

Autor: van Kersbergen J; Eindhoven University of Technology, 5612 AJ, Eindhoven, The Netherlands., Otte K; Motognosis GmbH, Schönhauser Allee 177, 10119, Berlin, Germany.; NeuroCure Clinical Research Center, Charité - Universitätsmedizin Berlin, Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health, Berlin, Germany.; Experimental and Clinical Research Center, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health and Max Delbrück Center for Molecular Medicine, Berlin, Germany., de Vries NM; Department of Neurology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands., Bloem BR; Department of Neurology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands., Röhling HM; Motognosis GmbH, Schönhauser Allee 177, 10119, Berlin, Germany.; Experimental and Clinical Research Center, Charité - Universitätsmedizin Berlin Corporate Member of Freie Universität Berlin, Humboldt-Universität zu Berlin, and Berlin Institute of Health and Max Delbrück Center for Molecular Medicine, Berlin, Germany., Mansow-Model S; Motognosis GmbH, Schönhauser Allee 177, 10119, Berlin, Germany., van der Kolk NM; Department of Neurology, Radboud University Medical Center, Geert Grooteplein Zuid 10, 6525 GA, Nijmegen, The Netherlands., Overeem S; Eindhoven University of Technology, 5612 AJ, Eindhoven, The Netherlands.; Sleep Medicine Center Kempenhaeghe, Sterkselseweg 65, 5591 VE, Heeze, The Netherlands., Zinger S; Eindhoven University of Technology, 5612 AJ, Eindhoven, The Netherlands., van Gilst MM; Eindhoven University of Technology, 5612 AJ, Eindhoven, The Netherlands. M.M.v.Gilst@tue.nl.; Sleep Medicine Center Kempenhaeghe, Sterkselseweg 65, 5591 VE, Heeze, The Netherlands. M.M.v.Gilst@tue.nl.
Jazyk: angličtina
Zdroj: BMC research notes [BMC Res Notes] 2021 Aug 26; Vol. 14 (1), pp. 329. Date of Electronic Publication: 2021 Aug 26.
DOI: 10.1186/s13104-021-05744-z
Abstrakt: Objective: Parkinson's disease is a common, age-related, neurodegenerative disease, affecting gait and other motor functions. Technological developments in consumer imaging are starting to provide high-quality, affordable tools for home-based diagnosis and monitoring. This pilot study aims to investigate whether a consumer depth camera can capture changes in gait features of Parkinson's patients. The dataset consisted of 19 patients (tested in both a practically defined OFF phase and ON phase) and 8 controls, who performed the "Timed-Up-and-Go" test multiple times while being recorded with the Microsoft Kinect V2 sensor. Camera-derived features were step length, average walking speed and mediolateral sway. Motor signs were assessed clinically using the Movement Disorder Society Unified Parkinson's Disease Rating Scale.
Results: We found significant group differences between patients and controls for step length and average walking speed, showing the ability to detect Parkinson's features. However, there were no differences between the ON and OFF medication state, so further developments are needed to allow for detection of small intra-individual changes in symptom severity.
(© 2021. The Author(s).)
Databáze: MEDLINE
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