Bungay, J, Emokpae, O, Relton, SD et al. (4 more authors) (2023) Contactless hand tremor amplitude measurement using smartphones: development and pilot evaluation. In: 2023 45th Annual International Conference of the IEEE Engineering in Medicine & Biology Society (EMBC). IEEE EMBC 2023, 24-27 Jul 2023, Sydney Australia. IEEE ISBN 979-8-3503-2448-8
Abstract
Background - Physiological tremor is defined as an involuntary and rhythmic shaking. Tremor of the hand is a key symptom of multiple neurological diseases, and its frequency and amplitude differs according to both disease type and disease progression. In routine clinical practice, tremor frequency and amplitude are assessed by expert rating using a 0 to 4 integer scale. Such ratings are subjective and have poor inter-rater reliability. There is thus a clinical need for a practical and accurate method for objectively assessing hand tremor.
Objective - to develop a proof-of-principle method to measure hand tremor amplitude from smartphone videos.
Methods - We created a computer vision pipeline that automatically extracts salient points on the hand and produces a 1-D time series of movement due to tremor, in pixels. Using the smartphones’ depth measurement, we convert this measure into real distance units. We assessed the accuracy of the method using 60 videos of simulated tremor of different amplitudes from two healthy adults. Videos were taken at distances of 50, 75 and 100 cm between hand and camera. The participants had skin tone II and VI on the Fitzpatrick scale. We compared our method to a gold-standard measurement from a slide rule. Bland-Altman methods agreement analysis indicated a bias of 0.04 cm and 95% limits of agreement from -1.27 to 1.20 cm. Furthermore, we qualitatively observed that the method was robust to limited occlusion.
Clinical relevance - We have demonstrated how tremor amplitude can be measured from smartphone videos. In conjunction with tremor frequency, this approach could be used to help diagnose and monitor neurological diseases.
Metadata
Item Type: | Proceedings Paper |
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Authors/Creators: |
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Copyright, Publisher and Additional Information: | © 2023 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. |
Dates: |
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Institution: | The University of Leeds |
Academic Units: | The University of Leeds > Faculty of Medicine and Health (Leeds) > School of Medicine (Leeds) > Leeds Institute of Health Sciences (Leeds) > Centre for Health Services Research (Leeds) |
Depositing User: | Symplectic Publications |
Date Deposited: | 25 Apr 2023 11:57 |
Last Modified: | 19 Jan 2024 14:52 |
Published Version: | https://ieeexplore.ieee.org/document/10340420 |
Status: | Published |
Publisher: | IEEE |
Identification Number: | 10.1109/EMBC40787.2023.10340420 |
Open Archives Initiative ID (OAI ID): | oai:eprints.whiterose.ac.uk:198358 |