1 research outputs found
Supervised classification of bradykinesia for Parkinson’s disease diagnosis from smartphone videos
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