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Supervised classification of bradykinesia for Parkinson’s disease diagnosis from smartphone videos

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conference contribution
posted on 14.05.2019, 14:26 by David C. Wong, Samuel D. Relton, Hui Fang, Rami Qhawaji, Christopher D. Graham, Jane Alty, Stefan Williams
Slowness of movement, known as bradykinesia, in an important early symptom of Parkinson’s disease. This symptom is currently assessed subjectively by clinical experts. However, expert assessment has been shown to be subject to inter-rater variability. We propose a low-cost, contactless system using smartphone videos to automatically determine the presence of bradykinesia. Using 70 videos recorded in a pilot study, we predict the presence of bradykinesia with an estimated test accuracy of 0.79 and the presence of Parkinson’s disease diagnosis with estimated test accuracy 0.63. Even on a small set of pilot data this accuracy is comparable to that recorded by blinded human experts.

History

School

  • Science

Department

  • Computer Science

Published in

2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)

Pages

32 - 37

Citation

WONG, D.C. ... et al, 2019. Supervised classification of bradykinesia for Parkinson’s disease diagnosis from smartphone videos. IN: 2019 32nd IEEE International Symposium on Computer-Based Medical Systems (CBMS), Cordoba, Spain, 5-7 June 2019, pp.32-37.

Publisher

IEEE

Version

AM (Accepted Manuscript)

Rights holder

© IEEE

Publisher statement

© 2019 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.

Acceptance date

28/03/2019

Publication date

2019-08-05

Copyright date

2019

ISBN

9781728122861

eISSN

2372-9198

Language

en

Location

Cordoba, Spain

Exports