Computerised Analysis of hypomimia and hypokinetic dysarthria for improved diagnosis of Parkinson's disease

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26220%2F23%3APU149222" target="_blank" >RIV/00216305:26220/23:PU149222 - isvavai.cz</a>

Result on the web

<a href="https://www.sciencedirect.com/science/article/pii/S2405844023083834" target="_blank" >https://www.sciencedirect.com/science/article/pii/S2405844023083834</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1016/j.heliyon.2023.e21175" target="_blank" >10.1016/j.heliyon.2023.e21175</a>

Result language

angličtina

Original language name

Computerised Analysis of hypomimia and hypokinetic dysarthria for improved diagnosis of Parkinson's disease

Original language description

Background and Objective: An ageing society requires easy-to-use approaches for diagnosis and monitoring of neurodegenerative disorders, such as Parkinson’s disease (PD), so that clinicians can effectively adjust a treatment policy and improve patients’ quality of life. Current methods of PD diagnosis and monitoring usually require the patients to come to a hospital, where they undergo several neurological and neuropsychological examinations. These examinations are usually time-consuming, expensive, and performed just a few times per year. Hence, this study explores the possibility of fusing computerised analysis of hypomimia and hypokinetic dysarthria (two motor symptoms manifested in the majority of PD patients) with the goal of proposing a new methodology of PD diagnosis that could be easily integrated into mHealth systems. Methods: We enrolled 73 PD patients and 46 age- and gender-matched healthy controls, who performed several speech/voice tasks while recorded by a microphone and a camera. Acoustic signals were parametrised in the fields of phonation, articulation and prosody. Video recordings of a face were analysed in terms of facial landmarks movement. Both modalities were consequently modelled by the XGBoost algorithm. Results: The acoustic analysis enabled diagnosis of PD with 77 % balanced accuracy, while in the case of the facial analysis, we observed 81 % balanced accuracy. The fusion of both modalities increased the balanced accuracy to 83 % (88 % sensitivity and 78 % specificity). The most informative speech exercise in the multimodality system turned out to be a tongue twister. Additionally, we identified muscle movements that are characteristic of hypomimia. Conclusions: The introduced methodology, which is based on the myriad of speech exercises likewise audio and video modality, allows for the detection of PD with an accuracy of up to 83 %. The speech exercise - tongue twisters occurred to be the most valuable from the clinical point of view. Addi

Czech name

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Czech description

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Type

J_imp - Article in a specialist periodical, which is included in the Web of Science database

CEP classification

—

OECD FORD branch

20601 - Medical engineering

Project

—

Continuities

S - Specificky vyzkum na vysokych skolach

Publication year

2023

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Name of the periodical

Heliyon

ISSN

2405-8440

e-ISSN

—

Volume of the periodical

9

Issue of the periodical within the volume

11

Country of publishing house

US - UNITED STATES

Number of pages

26

Pages from-to

„“-„“

UT code for WoS article

001111636000001

EID of the result in the Scopus database

2-s2.0-85174607876