Monitoring Parkinson Disease from speech articulation kinematics

Monitoring Parkinson Disease from speech articulation kinematics

WoS Article

Parkinson Disease (PD) is a neuromotor illness affecting general movements of different muscles, those implied in speech production being among them. The relevance of speech in monitoring illness progression has been documented in these last two decades. Most of the studies have concentrated in dysarthria and dysphonia induced by the syndrome. The present work is devoted to explore how PD affects the dynamic behavior of the speech neuromotor biomechanics (neuromechanics) involved in deficient articulation (dysarthria), in contrast to classical measurements based on static features as extreme and central vowel triangle positions. A statistical distribution of the kinematic velocity of the lower jaw and tongue is introduced, which presents interesting properties regarding pattern recognition and classification. This function may be used to establish distances between different articulation profiles in terms of information theory. Results show that these distances are correlated with a set of tests currently used by neurologists in PD progress evaluation, and could be used in elaborating new speech testing protocols.

Parkinson Disease (PD) is a neuromotor illness affecting general movements of different muscles, those implied in speech production being among them. The relevance of speech in monitoring illness progression has been documented in these last two decades. Most of the studies have concentrated in dysarthria and dysphonia induced by the syndrome. The present work is devoted to explore how PD affects the dynamic behavior of the speech neuromotor biomechanics (neuromechanics) involved in deficient articulation (dysarthria), in contrast to classical measurements based on static features as extreme and central vowel triangle positions. A statistical distribution of the kinematic velocity of the lower jaw and tongue is introduced, which presents interesting properties regarding pattern recognition and classification. This function may be used to establish distances between different articulation profiles in terms of information theory. Results show that these distances are correlated with a set of tests currently used by neurologists in PD progress evaluation, and could be used in elaborating new speech testing protocols.

neuromotor deterioration; Parkinson Disease speech; hypokinetic dysarthria; speech articulation modeling; speech neuromechanics

neuromotor deterioration; Parkinson Disease speech; hypokinetic dysarthria; speech articulation modeling; speech neuromechanics

GOMEZ-VILDA, P.; MEKYSKA, J.; GÓMEZ-RODELLAR, A.; PALACIOS-ALONSO, D.; RODELLAR BIARGE, M.; ÁLVAREZ-MARQUINA, A.

2018

01.12.2017

2386-2637

Loquens

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Kingdom of Spain

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