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

Siddharth Arora, Fahd Baig, Christine Lo, Thomas R. Barber, Michael A. Lawton, Andong Zhan, Michal Rolinski, Claudio Ruffmann, Johannes C. Klein, Jane Rumbold, Amandine Louvel, Zenobia Zaiwalla, Graham Lennox, Tim Quinnell, Gary Dennis, Richard Wade-Martins, Yoav Ben-Shlomo, Max A. Little, Michele T. Hu

Research output: Contribution to journalArticle

Abstract

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.

Original languageEnglish
Pages (from-to)e1528-e1538
JournalNeurology
Volume91
Issue number16
DOIs
Publication statusPublished - 16 Oct 2018

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REM Sleep Behavior Disorder
Behavior Control
Parkinson Disease
Tremor
Reaction Time
Smartphone
Parkinsonian Disorders
Gait
Fingers
Consensus
Sleep
Biomarkers
Sensitivity and Specificity

Bibliographical note

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).

Cite this

Arora, S., Baig, F., Lo, C., Barber, T. R., Lawton, M. A., Zhan, A., ... Hu, M. T. (2018). Smartphone motor testing to distinguish idiopathic REM sleep behavior disorder, controls, and PD. Neurology , 91(16), e1528-e1538. https://doi.org/10.1212/WNL.0000000000006366
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. ; Hu, Michele T. / Smartphone motor testing to distinguish idiopathic REM sleep behavior disorder, controls, and PD. In: Neurology . 2018 ; Vol. 91, No. 16. pp. e1528-e1538.
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Arora, S, Baig, F, Lo, C, Barber, TR, Lawton, MA, Zhan, A, Rolinski, M, Ruffmann, C, Klein, JC, Rumbold, J, Louvel, A, Zaiwalla, Z, Lennox, G, Quinnell, T, Dennis, G, Wade-Martins, R, Ben-Shlomo, Y, Little, MA & Hu, MT 2018, 'Smartphone motor testing to distinguish idiopathic REM sleep behavior disorder, controls, and PD', Neurology , vol. 91, no. 16, pp. e1528-e1538. https://doi.org/10.1212/WNL.0000000000006366

Smartphone motor testing to distinguish idiopathic REM sleep behavior disorder, controls, and PD. / 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.; Hu, Michele T.

In: Neurology , Vol. 91, No. 16, 16.10.2018, p. e1528-e1538.

Research output: Contribution to journalArticle

TY - JOUR

T1 - Smartphone motor testing to distinguish idiopathic REM sleep behavior disorder, controls, and PD

AU - Arora, Siddharth

AU - Baig, Fahd

AU - Lo, Christine

AU - Barber, Thomas R.

AU - Lawton, Michael A.

AU - Zhan, Andong

AU - Rolinski, Michal

AU - Ruffmann, Claudio

AU - Klein, Johannes C.

AU - Rumbold, Jane

AU - Louvel, Amandine

AU - Zaiwalla, Zenobia

AU - Lennox, Graham

AU - Quinnell, Tim

AU - Dennis, Gary

AU - Wade-Martins, Richard

AU - Ben-Shlomo, Yoav

AU - Little, Max A.

AU - Hu, Michele T.

N1 - 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).

PY - 2018/10/16

Y1 - 2018/10/16

N2 - 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.

AB - 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.

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