ParkinsoNET: Estimation of UPDRS Score Using Hubness-Aware Feedforward Neural Networks

Parkinson’s disease is a worldwide frequent neurodegenerative disorder with increasing incidence. Speech disturbance appears during the progression of the disease. UPDRS is a gold standard tool for diagnostic and follow up of the disease. We aim at estimating the UPDRS score based on biomedical voice recordings. In this paper, we study the hubness phenomenon in context of the UPDRS score estimation and propose hubness-aware error correction for feed-forward neural networks in order to increase the accuracy of estimation. We perform experiments on publicly available datasets derived form real voice data and show that the proposed technique systematically increases the accuracy of various feed-forward neural networks.