J 2014

Analysis of in-air movement in handwriting: A novel marker for Parkinson's disease

DROTÁR, Peter, Jiří MEKYSKA, Irena REKTOROVÁ, Lucia MASÁROVÁ, Zdeněk SMÉKAL et. al.

Základní údaje

Originální název

Analysis of in-air movement in handwriting: A novel marker for Parkinson's disease

Autoři

DROTÁR, Peter (703 Slovensko), Jiří MEKYSKA (203 Česká republika), Irena REKTOROVÁ (203 Česká republika, garant, domácí), Lucia MASÁROVÁ (703 Slovensko, domácí), Zdeněk SMÉKAL (203 Česká republika) a Marcos FAUNDEZ-ZANUY (724 Španělsko)

Vydání

Computer Methods and Programs in Biomedicine, Clare, Elsevier, 2014, 0169-2607

Další údaje

Jazyk

angličtina

Typ výsledku

Článek v odborném periodiku

Obor

30000 3. Medical and Health Sciences

Stát vydavatele

Irsko

Utajení

není předmětem státního či obchodního tajemství

Odkazy

Impakt faktor

Impact factor: 1.897

Kód RIV

RIV/00216224:14110/14:00078537

Organizační jednotka

Lékařská fakulta

UT WoS

000344937800001

Klíčová slova anglicky

Handwriting; Disease classification; Parkinson's disease; Micrographia; In-air movement; Decision support systems

Štítky

Příznaky

Mezinárodní význam, Recenzováno
Změněno: 26. 1. 2015 17:58, Soňa Böhmová

Anotace

V originále

Background and objective: Parkinson's disease (PD) is the second most common neurodegenerative disease affecting significant portion of elderly population. One of the most frequent hallmarks and usually also the first manifestation of PD is deterioration of handwriting characterized by micrographia and changes in kinematics of handwriting. There is no objective quantitative method of clinical diagnosis of PD. It is thought that PD can only be definitively diagnosed at postmortem, which further highlights the complexities of diagnosis. Methods: We exploit the fact that movement during handwriting of a text consists not only from the on-surface movements of the hand, but also from the in-air trajectories performed when the hand moves in the air from one stroke to the next. We used a digitizing tablet to assess both in-air and on-surface kinematic variables during handwriting of a sentence in 37 PD patients on medication and 38 age- and gender-matched healthy controls. Results: By applying feature selection algorithms and support vector machine learning methods to separate PD patients from healthy controls, we demonstrated that assessing the in-air/on-surface hand movements led to accurate classifications in 84% and 78% of subjects, respectively. Combining both modalities improved the accuracy by another 1% over the evaluation of in-air features alone and provided medically relevant diagnosis with 85.61% prediction accuracy. Conclusions: Assessment of in-air movements during handwriting has a major impact on disease classification accuracy. This study confirms that handwriting can be used as a marker for PD and can be with advance used in decision support systems for differential diagnosis of PD.

Návaznosti

ED1.1.00/02.0068, projekt VaV
Název: CEITEC - central european institute of technology
NT13499, projekt VaV
Název: Řeč, její poruchy a kognitivní funkce u Parkinsonovy nemoci