cbms_parkinsons.pdf (174.87 kB)
Supervised classification of bradykinesia for Parkinson’s disease diagnosis from smartphone videos
conference contributionposted 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 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.
- Computer Science
Published in2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)
Pages32 - 37
CitationWONG, 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.
- AM (Accepted Manuscript)
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