Prodromal Diagnosis of Lewy Body Diseases Based on the
Assessment of Graphomotor and Handwriting Difficulties

D 2022

Prodromal Diagnosis of Lewy Body Diseases Based on the Assessment of Graphomotor and Handwriting Difficulties

GALAZ, Zoltan, Jiri MEKYSKA, Jan MUCHA, Vojtech ZVONCAK, Zdenek SMEKAL et. al.

Basic information

Original name

Prodromal Diagnosis of Lewy Body Diseases Based on the Assessment of Graphomotor and Handwriting Difficulties

Authors

GALAZ, Zoltan, Jiri MEKYSKA (203 Czech Republic), Jan MUCHA (203 Czech Republic), Vojtech ZVONCAK (203 Czech Republic), Zdenek SMEKAL (203 Czech Republic), Marcos FAUNDEZ-ZANUY, Luboš BRABENEC (203 Czech Republic, belonging to the institution), Ivona MORÁVKOVÁ (703 Slovakia, belonging to the institution) and Irena REKTOROVÁ (203 Czech Republic, belonging to the institution)

Edition

CHAM, Intertwining Graphonomics with Human Movements, p. 255-268, 14 pp. 2022

Publisher

SPRINGER INTERNATIONAL PUBLISHING AG

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

30210 Clinical neurology

Country of publisher

Switzerland

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

References:

Correction version Original version

Impact factor

Impact factor: 0.402 in 2005

RIV identification code

RIV/00216224:14110/22:00134722

Organization unit

Faculty of Medicine

ISBN

978-3-031-19744-4

ISSN

DOI

http://dx.doi.org/10.1007/978-3-031-19745-1_19

UT WoS

000913319000019

Keywords in English

Lewy body diseases; Online handwriting; Graphomotor difficulties; Handwriting difficulties; Machine learning; Prodromal diagnosis

Abstract

V originále

To this date, studies focusing on the prodromal diagnosis of Lewy body diseases (LBDs) based on quantitative analysis of graphomotor and handwriting difficulties are missing. In this work, we enrolled 18 subjects diagnosed with possible or probable mild cognitive impairment with Lewy bodies (MCI-LB), 7 subjects having more than 50% probability of developing Parkinson's disease (PD), 21 subjects with both possible/probable MCI-LB and probability of PD > 50%, and 37 age- and gender-matched healthy controls (HC). Each participant performed three tasks: Archimedean spiral drawing (to quantify graphomotor difficulties), sentence writing task (to quantify handwriting difficulties), and pentagon copying test (to quantify cognitive decline). Next, we parameterized the acquired data by various temporal, kinematic, dynamic, spatial, and task-specific features. And finally, we trained classification models for each task separately as well as a model for their combination to estimate the predictive power of the features for the identification of LBDs. Using this approach we were able to identify prodromal LBDs with 74% accuracy and showed the promising potential of computerized objective and non-invasive diagnosis of LBDs based on the assessment of graphomotor and handwriting difficulties.

Links

NU20-04-00294, research and development project

Name: Diagnostika onemocnění s Lewyho tělísky v prodromálním stadiu založená na analýze multimodálních dat

Investor: Ministry of Health of the CR, Diagnostics of Lewy body diseases in prodromal stage based on multimodal data analysis

Citovat

GALAZ, Zoltan, Jiri MEKYSKA, Jan MUCHA, Vojtech ZVONCAK, Zdenek SMEKAL, Marcos FAUNDEZ-ZANUY, Luboš BRABENEC, Ivona MORÁVKOVÁ and Irena REKTOROVÁ. Prodromal Diagnosis of Lewy Body Diseases Based on the Assessment of Graphomotor and Handwriting Difficulties. In Cristina Carmona-Duarte, Moises Diaz, Miguel A. Ferrer, Aythami Morales. Intertwining Graphonomics with Human Movements. CHAM: SPRINGER INTERNATIONAL PUBLISHING AG, 2022, p. 255-268. ISBN 978-3-031-19744-4. Available from: https://dx.doi.org/10.1007/978-3-031-19745-1_19.

@inproceedings{2386059,
   author = {Galaz, Zoltan and Mekyska, Jiri and Mucha, Jan and Zvoncak, Vojtech and Smekal, Zdenek and FaundezandZanuy, Marcos and Brabenec, Luboš and Morávková, Ivona and Rektorová, Irena},
   address = {CHAM},
   booktitle = {Intertwining Graphonomics with Human Movements},
   doi = {http://dx.doi.org/10.1007/978-3-031-19745-1_19},
   editor = {Cristina Carmona-Duarte, Moises Diaz, Miguel A. Ferrer, Aythami Morales},
   keywords = {Lewy body diseases; Online handwriting; Graphomotor difficulties; Handwriting difficulties; Machine learning; Prodromal diagnosis},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {CHAM},
   isbn = {978-3-031-19744-4},
   pages = {255-268},
   publisher = {SPRINGER INTERNATIONAL PUBLISHING AG},
   title = {Prodromal Diagnosis of Lewy Body Diseases Based on the Assessment of Graphomotor and Handwriting Difficulties},
   url = {https://link.springer.com/chapter/10.1007/978-3-031-19745-1_27},
   year = {2022}
}

TY  - JOUR
ID  - 2386059
AU  - Galaz, Zoltan - Mekyska, Jiri - Mucha, Jan - Zvoncak, Vojtech - Smekal, Zdenek - Faundez-Zanuy, Marcos - Brabenec, Luboš - Morávková, Ivona - Rektorová, Irena
PY  - 2022
TI  - Prodromal Diagnosis of Lewy Body Diseases Based on the Assessment of Graphomotor and Handwriting Difficulties
PB  - SPRINGER INTERNATIONAL PUBLISHING AG
CY  - CHAM
SN  - 9783031197444
KW  - Lewy body diseases
KW  - Online handwriting
KW  - Graphomotor difficulties
KW  - Handwriting difficulties
KW  - Machine learning
KW  - Prodromal diagnosis
UR  - https://link.springer.com/chapter/10.1007/978-3-031-19745-1_27
N2  - To this date, studies focusing on the prodromal diagnosis of Lewy body diseases (LBDs) based on quantitative analysis of graphomotor and handwriting difficulties are missing. In this work, we enrolled 18 subjects diagnosed with possible or probable mild cognitive impairment with Lewy bodies (MCI-LB), 7 subjects having more than 50% probability of developing Parkinson's disease (PD), 21 subjects with both possible/probable MCI-LB and probability of PD > 50%, and 37 age- and gender-matched healthy controls (HC). Each participant performed three tasks: Archimedean spiral drawing (to quantify graphomotor difficulties), sentence writing task (to quantify handwriting difficulties), and pentagon copying test (to quantify cognitive decline). Next, we parameterized the acquired data by various temporal, kinematic, dynamic, spatial, and task-specific features. And finally, we trained classification models for each task separately as well as a model for their combination to estimate the predictive power of the features for the identification of LBDs. Using this approach we were able to identify prodromal LBDs with 74% accuracy and showed the promising potential of computerized objective and non-invasive diagnosis of LBDs based on the assessment of graphomotor and handwriting difficulties.
ER  -

GALAZ, Zoltan, Jiri MEKYSKA, Jan MUCHA, Vojtech ZVONCAK, Zdenek SMEKAL, Marcos FAUNDEZ-ZANUY, Luboš BRABENEC, Ivona MORÁVKOVÁ and Irena REKTOROVÁ. Prodromal Diagnosis of Lewy Body Diseases Based on the Assessment of Graphomotor and Handwriting Difficulties. In Cristina Carmona-Duarte, Moises Diaz, Miguel A. Ferrer, Aythami Morales. \textit{Intertwining Graphonomics with Human Movements}. CHAM: SPRINGER INTERNATIONAL PUBLISHING AG, 2022, p.~255-268. ISBN~978-3-031-19744-4. Available from: https://dx.doi.org/10.1007/978-3-031-19745-1\_{}19.

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