cbms_parkinsons.pdf (174.87 kB)
Supervised classification of bradykinesia for Parkinson’s disease diagnosis from smartphone videos
conference contribution
posted on 2019-05-14, 14:26 authored by David C. Wong, Samuel D. Relton, Hui FangHui Fang, Rami Qhawaji, Christopher D. Graham, Jane Alty, Stefan WilliamsSlowness 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 - 37Citation
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
IEEEVersion
- AM (Accepted Manuscript)
Rights holder
© IEEEPublisher 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
2019-03-28Publication date
2019-08-05Copyright date
2019ISBN
9781728122861eISSN
2372-9198Language
- en