D 2017

Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation

MUCHA, J.; Z. GALAZ; J. MEKYSKA; T. KISKA; V. ZVONCAK et al.

Základní údaje

Originální název

Identification of Hypokinetic Dysarthria Using Acoustic Analysis of Poem Recitation

Autoři

MUCHA, J.; Z. GALAZ; J. MEKYSKA; T. KISKA; V. ZVONCAK; Z. SMEKAL; Ilona ELIÁŠOVÁ; Martina MRAČKOVÁ; Milena KOŠŤÁLOVÁ ORCID; Irena REKTOROVÁ; M. FAUNDEZ-ZANUY a JB. ALONSO-HERNANDEZ

Vydání

Barcelona, 40th International Conference on Telecommunications and Signal Processing, TSP 2017, od s. 739-742, 4 s. 2017

Nakladatel

Institute of Electrical and Electronics Engineers Inc.

Další údaje

Jazyk

angličtina

Typ výsledku

Stať ve sborníku

Obor

30103 Neurosciences

Stát vydavatele

Španělsko

Utajení

není předmětem státního či obchodního tajemství

Forma vydání

elektronická verze "online"

Označené pro přenos do RIV

Ano

Kód RIV

RIV/00216224:14740/17:00095717

Organizační jednotka

Středoevropský technologický institut

ISBN

978-1-5090-3982-1

EID Scopus

Klíčová slova anglicky

acoustic analysis; binary classification; hypokinetic dysarthria; Parkinson’s disease; poem recitation

Štítky

Změněno: 24. 4. 2020 12:34, Mgr. Pavla Foltynová, Ph.D.

Anotace

V originále

Up to 90% of patients with Parkinson’s disease (PD) suffer from hypokinetic dysarthria (HD). In this work, we analysed the power of conventional speech features quantifying imprecise articulation, dysprosody, speech dysfluency and speech quality deterioration extracted from a specialized poem recitation task to discriminate dysarthric and healthy speech. For this purpose, 152 speakers (53 healthy speakers, 99 PD patients) were examined. Only mildly strong correlation between speech features and clinical status of the speakers was observed. In case of univariate classification analysis, sensitivity of 62.63% (imprecise articulation), 61.62% (dysprosody), 71.72% (speech dysfluency) and 59.60% (speech quality deterioration) was achieved. Multivariate classification analysis improved the classification performance. Sensitivity of 83.42% using only two features describing imprecise articulation and speech quality deterioration in HD was achieved. We showed the promising potential of the selected speech features and especially the use of poem recitation task to quantify and identify HD in PD.

Návaznosti

NV16-30805A, projekt VaV
Název: Efekt neinvazivní stimulace mozku na hypokinetickou dysartrii, mikrografii a mozkovou plasticitu u pacientů s Parkinsonovou nemocí