Smartphone motor testing to distinguish idiopathic REM sleep behavior disorder, controls, and PD


OBJECTIVE: We sought to identify motor features that would allow the delineation of individuals with sleep study-confirmed idiopathic REM sleep behavior disorder (iRBD) from controls and Parkinson disease (PD) using a customized smartphone application. METHODS: A total of 334 PD, 104 iRBD, and 84 control participants performed 7 tasks to evaluate voice, balance, gait, finger tapping, reaction time, rest tremor, and postural tremor. Smartphone recordings were collected both in clinic and at home under noncontrolled conditions over several days. All participants underwent detailed parallel in-clinic assessments. Using only the smartphone sensor recordings, we sought to (1) discriminate whether the participant had iRBD or PD and (2) identify which of the above 7 motor tasks were most salient in distinguishing groups. RESULTS: Statistically significant differences based on these 7 tasks were observed between the 3 groups. For the 3 pairwise discriminatory comparisons, (1) controls vs iRBD, (2) controls vs PD, and (3) iRBD vs PD, the mean sensitivity and specificity values ranged from 84.6% to 91.9%. Postural tremor, rest tremor, and voice were the most discriminatory tasks overall, whereas the reaction time was least discriminatory. CONCLUSIONS: Prodromal forms of PD include the sleep disorder iRBD, where subtle motor impairment can be detected using clinician-based rating scales (e.g., Unified Parkinson's Disease Rating Scale), which may lack the sensitivity to detect and track granular change. Consumer grade smartphones can be used to accurately separate not only iRBD from controls but also iRBD from PD participants, providing a growing consensus for the utility of digital biomarkers in early and prodromal PD.

Publication DOI:
Divisions: College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
Additional Information: This is an open access article distributed under the terms of the Creative Commons Attribution License 4.0 (CC BY), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Funding: This study was funded by the Monument Trust Discovery Award from Parkinson’s UK and supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Centre based at Oxford University Hospitals NHS Trust and University of Oxford, and the Dementias and Neurodegenerative Diseases Research Network (DeNDRoN). This work was supported by Parkinson’s UK [grant number J-1403]. This study was funded by the Monument Trust Discovery Award from Parkinson’s UK and supported by the National Institute for Health Research (NIHR) Oxford Biomedical Research Center (BRC).
Uncontrolled Keywords: Clinical Neurology
Publication ISSN: 1526-632X
Last Modified: 29 Apr 2024 07:27
Date Deposited: 05 Nov 2018 09:36
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
http://n.neurol ... 1/16/e1528.long (Publisher URL)
PURE Output Type: Article
Published Date: 2018-10-16
Accepted Date: 2018-07-12
Authors: Arora, Siddharth
Baig, Fahd
Lo, Christine
Barber, Thomas R.
Lawton, Michael A.
Zhan, Andong
Rolinski, Michal
Ruffmann, Claudio
Klein, Johannes C.
Rumbold, Jane
Louvel, Amandine
Zaiwalla, Zenobia
Lennox, Graham
Quinnell, Tim
Dennis, Gary
Wade-Martins, Richard
Ben-Shlomo, Yoav
Little, Max A. (ORCID Profile 0000-0002-1507-3822)
Hu, Michele T.



Version: Published Version

License: Creative Commons Attribution

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