Large-scale Clustering of People Diagnosed with Parkinson’s Disease using Acoustic Analysis of Sustained Vowels: Findings in the Parkinson’s Voice Initiative Study

Thanasis Tsanas, Siddharth Arora

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Progress in exploring speech and Parkinson’s Disease (PD) has been hindered due to the use of different protocols across research labs/countries, single-site studies with relatively small numbers, and no external validation. We had recently reported on the Parkinson’s Voice Initiative (PVI), a large study where we collected 19,000+ sustained vowel phonations (control and PD groups) across seven countries, under acoustically non-controlled conditions. In this study, we explored how well findings generalize in the three English-speaking PVI cohorts (data collected in Boston, Oxford, and Toronto). We acoustically characterized each sustained vowel /a/ phonation using 307 dysphonia measures which had previously been successfully employed in speech-PD applications. We used the previously identified feature subset from the Boston cohort and explored hierarchical clustering with Ward’s linkage combined with 2D-data projections using t-distributed stochastic neighbor embedding to facilitate visual exploration of PD subgroups. Furthermore, we computed feature weights using LOGO to assess feature selection consistency towards differentiating PD from controls. Overall, findings are very consistent across the three cohorts, strongly suggesting the presence of four main PD clusters, and consistent identification of key contributing features. Collectively, these findings support the generalization of sustained vowels and robustness of the presented methodology across the English-speaking PVI cohorts.
Original languageEnglish
Title of host publication14th International Joint Conference on Biomedical Systems and Technology (BIOSTEC)
EditorsHugo Gamboa
Pages124-131
ISBN (Electronic)978-989-758-490-9
Publication statusPublished - 13 Feb 2021

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