Characterization of Parkinson's disease dysarthria in terms of speech articulation kinematics. (July 2019)

• Record Type: Journal Article
• Authors: Gómez, P.; Mekyska, J.; Gómez, A.; Palacios, D.; Rodellar, V.; Álvarez, A.
• Is Part Of: Biomedical signal processing and control. Volume 52(2019)
• Page Start: 312
• Page End: 320
• Publication Date: 2019-07
• Subjects: Neuromotor disease -- Speech processing -- Articulation biomechanics -- Jensen-Shannon Divergence -- Speech kinematics; Signal processing -- Periodicals; Biomedical engineering -- Periodicals; Signal Processing, Computer-Assisted -- Periodicals; Image Processing, Computer-Assisted -- Periodicals; Biomedical Engineering -- Periodicals; 610.28
• DOI: 10.1016/j.bspc.2019.04.029
• Languages: English
• ISSNs: 1746-8094

Abstract

Highlights: The relationship between formant oscillations and jaw-tongue reference position has been stated by a biomechanical model. A method to estimate the parameters involved in this model has been proposed by kinematics derived from accelerometry. An absolute kinematic correlate to jaw-tongue reference position has been defined (AKV). Two Information Theory-based divergence measurements on the probability density of the AKV have been proposed (KLD and JSD) and their performance has been assessed. The performance of AKV pdfs in differentiating articulation kinematics between PD patients and normative subjects has been tested. Abstract: Speech is a vehicular tool to detect neurological degeneration using certain accepted biomarkers derived from sustained vowels, diadochokinetic exercises or running speech. Classically the Vowel Space Area (VSA) and the Formant Centralization Ratio (FCR) have been proposed to describe dysarthria in Parkinson's Disease (PD). These features are based in global estimations of the positions of the first two formants in the representation of a vowel triangle. The aim of the paper is to give a description of speech articulation dynamics as a probability density function of the kinematic features derived from the evolution of formants in the time domain. The statistical distribution of the dynamic behavior of articulation features can be used to estimate differences between speech features from subjects with Parkinson's dysarthria relative to normative subjects. Utterances of vowels [a:, i:, u:] from a subset of 16 subjects with PD (8 males and 8 females), confronted to a subset of 16 normative subjects (8 males and 8 females) have shown that the statistical distributions of dynamic articulation features can be differentiated using information theory based estimations such as Kullback-Leibler and Jensen-Shannon Divergence (JSD). These estimations allow establishing relevant statistical differences between PD and normative subjects both for males and females, improving the differentiation capability of VSA and FCR.