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Accuracy of smartphone video for contactless measurement of hand tremor frequency

Citation

Williams, S and Fang, H and Relton, SD and Wong, DC and Alam, T and Alty, JE, Accuracy of smartphone video for contactless measurement of hand tremor frequency, Movement Disorders Clinical Practice, 8, (1) pp. 69-75. ISSN 2330-1619 (2021) [Refereed Article]

Copyright Statement

© 2020 International Parkinson and Movement Disorder Society

DOI: doi:10.1002/mdc3.13119

Abstract

Background:

Computer vision can measure movement from video without the time and access limitations of hospital accelerometry/electromyography or the requirement to hold or strap a smartphone accelerometer.

Objective:

To compare computer vision measurement of hand tremor frequency from smartphone video with a gold standard measure accelerometer.

Methods:

A total of 37 smartphone videos of hands, at rest and in posture, were recorded from 15 participants with tremor diagnoses (9 Parkinsonís disease, 5 essential tremor, 1 functional tremor). Video pixel movement was measured using the computing technique of optical flow, with contemporaneous accelerometer recording. Fast Fourier transform and Bland-Altman analysis were applied. Tremor amplitude was scored by 2 clinicians.

Results:

Bland-Altman analysis of dominant tremor frequency from smartphone video compared with accelerometer showed excellent agreement: 95% limits of agreement −0.38 Hz to +0.35 Hz. In 36 of 37 videos (97%), there was <0.5 Hz difference between computer vision and accelerometer measurement. There was no significant correlation between the level of agreement and tremor amplitude.

Conclusion:

The study suggests a potential new, contactless point-and-press measure of tremor frequency within standard clinical settings, research studies, or telemedicine.

Item Details

Item Type:Refereed Article
Keywords:parkinson's, computer visions, smartphone, tremor, dystonia, essential tremor, functional tremor
Research Division:Information and Computing Sciences
Research Group:Computer vision and multimedia computation
Research Field:Computer vision
Objective Division:Health
Objective Group:Provision of health and support services
Objective Field:Outpatient care
UTAS Author:Alty, JE (Associate Professor Jane Alty)
ID Code:144165
Year Published:2021
Web of Science® Times Cited:2
Deposited By:Wicking Dementia Research and Education Centre
Deposited On:2021-04-27
Last Modified:2021-09-22
Downloads:0

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