Granular Motor State Monitoring of Free Living Parkinson's Disease Patients via Deep Learning

11/15/2019

∙

by   Kamer A. Yuksel, et al.

∙

Universität München

∙

0

∙

share

Parkinson's disease (PD) is the second most common neurodegenerative disease worldwide and affects around 1 industrial nations. More than 80 which could be well addressed if a personalized medication schedule and dosage could be administered to them. However, such personalized medication schedule requires a continuous, objective and precise measurement of motor symptoms experienced by the patients during their regular daily activities. In this work, we propose the use of a wrist-worn smart-watch, which is equipped with 3D motion sensors, for estimating the motor fluctuation severity of PD patients in a free-living environment. We introduce a novel network architecture, a post-training scheme and a custom loss function that accounts for label noise to improve the results of our previous work in this domain and to establish a novel benchmark for nine-level PD motor state estimation.