Assessing progress of Parkinson's disease using acoustic
analysis of phonation

D 2015

Assessing progress of Parkinson's disease using acoustic analysis of phonation

MEKYSKA, J., Z. GALAZ, Z. MZOUREK, Z. SMÉKAL, Irena REKTOROVÁ et. al.

Basic information

Original name

Assessing progress of Parkinson's disease using acoustic analysis of phonation

Authors

MEKYSKA, J. (203 Czech Republic), Z. GALAZ (203 Czech Republic), Z. MZOUREK (203 Czech Republic), Z. SMÉKAL (203 Czech Republic), Irena REKTOROVÁ (203 Czech Republic, guarantor, belonging to the institution), Ilona ELIÁŠOVÁ (203 Czech Republic, belonging to the institution), Milena KOŠŤÁLOVÁ (203 Czech Republic, belonging to the institution), Martina MRAČKOVÁ (203 Czech Republic, belonging to the institution), Dagmar BERÁNKOVÁ (203 Czech Republic, belonging to the institution), M. FAUNDEZ-ZANUY (724 Spain), K. LÓPEZ-DE- IPINA (724 Spain) and Jesus B. ALONSO-HERNANDEZ (724 Spain)

Edition

neuveden, 4th International Work Conference on Bio-Inspired Intelligence, IWOBI 2015, p. 111-118, 8 pp. 2015

Publisher

Institute of Electrical and Electronics Engineers Inc.

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

30000 3. Medical and Health Sciences

Country of publisher

Spain

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

URL

RIV identification code

RIV/00216224:14740/15:00085829

Organization unit

Central European Institute of Technology

ISBN

978-1-4799-6174-0

DOI

http://dx.doi.org/10.1109/IWOBI.2015.7160153

Keywords in English

Biodiversity; Conservation; Decision trees; Intelligent systems; Neurodegenerative diseases; Patient rehabilitation; Speech Acoustic analysis;

Abstract

V originále

This paper deals with a complex acoustic analysis of phonation in patients with Parkinson's disease (PD) with a special focus on estimation of disease progress that is described by 7 different clinical scales (e. g. Unified Parkinson's disease rating scale or Beck depression inventory). The analysis is based on parametrization of 5 Czech vowels pronounced by 84 PD patients. Using classification and regression trees we estimated all clinical scores with maximal error lower or equal to 13 %. Best estimation was observed in the case of Mini-mental state examination (MAE = 0.77, estimation error 5.50 %). Finally, we proposed a binary classification based on random forests that is able to identify Parkinson's disease with sensitivity SEN = 92.86% (SPE = 85.71 %). The parametrization process was based on extraction of 107 speech features quantifying different clinical signs of hypokinetic dysarthria present in PD

Links

ED1.1.00/02.0068, research and development project

Name: CEITEC - central european institute of technology

NT13499, research and development project

Name: Řeč, její poruchy a kognitivní funkce u Parkinsonovy nemoci

Citovat

MEKYSKA, J., Z. GALAZ, Z. MZOUREK, Z. SMÉKAL, Irena REKTOROVÁ, Ilona ELIÁŠOVÁ, Milena KOŠŤÁLOVÁ, Martina MRAČKOVÁ, Dagmar BERÁNKOVÁ, M. FAUNDEZ-ZANUY, K. LÓPEZ-DE- IPINA and Jesus B. ALONSO-HERNANDEZ. Assessing progress of Parkinson's disease using acoustic analysis of phonation. In Alonso-Hernandez J.B.; Travieso-Gonzalez C.M.; Lopez de Ipina K. 4th International Work Conference on Bio-Inspired Intelligence, IWOBI 2015. neuveden: Institute of Electrical and Electronics Engineers Inc., 2015, p. 111-118. ISBN 978-1-4799-6174-0. Available from: https://dx.doi.org/10.1109/IWOBI.2015.7160153.

@inproceedings{1323791,
   author = {Mekyska, J. and Galaz, Z. and Mzourek, Z. and Smékal, Z. and Rektorová, Irena and Eliášová, Ilona and Košťálová, Milena and Mračková, Martina and Beránková, Dagmar and FaundezandZanuy, M. and Lópezanddeand Ipina, K. and AlonsoandHernandez, Jesus B.},
   address = {neuveden},
   booktitle = {4th International Work Conference on Bio-Inspired Intelligence, IWOBI 2015},
   doi = {http://dx.doi.org/10.1109/IWOBI.2015.7160153},
   editor = {Alonso-Hernandez J.B.; Travieso-Gonzalez C.M.; Lopez de Ipina K.},
   keywords = {Biodiversity; Conservation; Decision trees; Intelligent systems; Neurodegenerative diseases; Patient rehabilitation; Speech Acoustic analysis;},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {neuveden},
   isbn = {978-1-4799-6174-0},
   pages = {111-118},
   publisher = {Institute of Electrical and Electronics Engineers Inc.},
   title = {Assessing progress of Parkinson's disease using acoustic analysis of phonation},
   url = {http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=7160153},
   year = {2015}
}

TY  - JOUR
ID  - 1323791
AU  - Mekyska, J. - Galaz, Z. - Mzourek, Z. - Smékal, Z. - Rektorová, Irena - Eliášová, Ilona - Košťálová, Milena - Mračková, Martina - Beránková, Dagmar - Faundez-Zanuy, M. - López-de- Ipina, K. - Alonso-Hernandez, Jesus B.
PY  - 2015
TI  - Assessing progress of Parkinson's disease using acoustic analysis of phonation
PB  - Institute of Electrical and Electronics Engineers Inc.
CY  - neuveden
SN  - 9781479961740
KW  - Biodiversity
KW  - Conservation
KW  - Decision trees
KW  - Intelligent systems
KW  - Neurodegenerative diseases
KW  - Patient rehabilitation
KW  - Speech Acoustic analysis;
UR  - http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=7160153
L2  - http://ieeexplore.ieee.org/xpl/articleDetails.jsp?reload=true&arnumber=7160153
N2  - This paper deals with a complex acoustic analysis of phonation in patients with Parkinson's disease (PD) with a special focus on estimation of disease progress that is described by 7 different clinical scales (e. g. Unified Parkinson's disease rating scale or Beck depression inventory). The analysis is based on parametrization of 5 Czech vowels pronounced by 84 PD patients. Using classification and regression trees we estimated all clinical scores with maximal error lower or equal to 13 %. Best estimation was observed in the case of Mini-mental state examination (MAE = 0.77, estimation error 5.50 %). Finally, we proposed a binary classification based on random forests that is able to identify Parkinson's disease with sensitivity SEN = 92.86% (SPE = 85.71 %). The parametrization process was based on extraction of 107 speech features quantifying different clinical signs of hypokinetic dysarthria present in PD
ER  -

MEKYSKA, J., Z. GALAZ, Z. MZOUREK, Z. SMÉKAL, Irena REKTOROVÁ, Ilona ELIÁŠOVÁ, Milena KOŠŤÁLOVÁ, Martina MRAČKOVÁ, Dagmar BERÁNKOVÁ, M. FAUNDEZ-ZANUY, K. LÓPEZ-DE- IPINA and Jesus B. ALONSO-HERNANDEZ. Assessing progress of Parkinson's disease using acoustic analysis of phonation. In Alonso-Hernandez J.B.; Travieso-Gonzalez C.M.; Lopez de Ipina K. \textit{4th International Work Conference on Bio-Inspired Intelligence, IWOBI 2015}. neuveden: Institute of Electrical and Electronics Engineers Inc., 2015, p.~111-118. ISBN~978-1-4799-6174-0. Available from: https://dx.doi.org/10.1109/IWOBI.2015.7160153.

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