Nonlinear speech analysis algorithms mapped to a standard metric achieve clinically useful quantification of average Parkinson's disease symptom severity


The standard reference clinical score quantifying average Parkinson's disease (PD) symptom severity is the Unified Parkinson's Disease Rating Scale (UPDRS). At present, UPDRS is determined by the subjective clinical evaluation of the patient's ability to adequately cope with a range of tasks. In this study, we extend recent findings that UPDRS can be objectively assessed to clinically useful accuracy using simple, self-administered speech tests, without requiring the patient's physical presence in the clinic. We apply a wide range of known speech signal processing algorithms to a large database (approx. 6000 recordings from 42 PD patients, recruited to a six-month, multi-centre trial) and propose a number of novel, nonlinear signal processing algorithms which reveal pathological characteristics in PD more accurately than existing approaches. Robust feature selection algorithms select the optimal subset of these algorithms, which is fed into non-parametric regression and classification algorithms, mapping the signal processing algorithm outputs to UPDRS. We demonstrate rapid, accurate replication of the UPDRS assessment with clinically useful accuracy (about 2 UPDRS points difference from the clinicians' estimates, p < 0.001). This study supports the viability of frequent, remote, cost-effective, objective, accurate UPDRS telemonitoring based on self-administered speech tests. This technology could facilitate large-scale clinical trials into novel PD treatments.

Publication DOI:
Additional Information: © 2010 The Royal Society
Uncontrolled Keywords: nonlinear speech signal processing,nonlinear regression and classification,Parkinson's disease,telemedicine,unified Parkinson's disease rating scale,Biophysics,Biotechnology,Bioengineering,Biomedical Engineering,Biomaterials,Biochemistry
Publication ISSN: 1742-5662
Last Modified: 14 Jun 2024 07:10
Date Deposited: 28 Jan 2013 15:51
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
PURE Output Type: Article
Published Date: 2011-06-06
Published Online Date: 2010-11-17
Authors: Tsanas, Athanasios
Little, Max A. (ORCID Profile 0000-0002-1507-3822)
McSharry, Patrick E.
Ramig, Lorraine O.



Version: Accepted Version

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