Publication detail

Contribution of different handwriting modalities to differential diagnosis of Parkinson's Disease

DROTÁR, P. MEKYSKA, J. SMÉKAL, Z. REKTOROVÁ, I. MASAROVÁ, L. FAÚNDEZ ZANUY, M.

Original Title

Contribution of different handwriting modalities to differential diagnosis of Parkinson's Disease

English Title

Contribution of different handwriting modalities to differential diagnosis of Parkinson's Disease

Type

conference paper

Language

en

Original Abstract

In this paper, we evaluate the contribution of different handwriting modalities to the diagnosis of Parkinson's disease. We analyse on-surface movement, in-air movement and pressure exerted on the tablet surface. Especially in-air movement and pressure-based features have been rarely taken into account in previous studies. We show that pressure and in-air movement also possess information that is relevant for the diagnosis of Parkinson's Disease (PD) from handwriting. In addition to the conventional kinematic and spatio-temporal features, we present a group of the novel features based on entropy and empirical mode decomposition of the handwriting signal. The presented results indicate that handwriting can be used as biomarker for PD providing classification performance around 89% area under the ROC curve (AUC) for PD classification.

English abstract

In this paper, we evaluate the contribution of different handwriting modalities to the diagnosis of Parkinson's disease. We analyse on-surface movement, in-air movement and pressure exerted on the tablet surface. Especially in-air movement and pressure-based features have been rarely taken into account in previous studies. We show that pressure and in-air movement also possess information that is relevant for the diagnosis of Parkinson's Disease (PD) from handwriting. In addition to the conventional kinematic and spatio-temporal features, we present a group of the novel features based on entropy and empirical mode decomposition of the handwriting signal. The presented results indicate that handwriting can be used as biomarker for PD providing classification performance around 89% area under the ROC curve (AUC) for PD classification.

Keywords

Acceleration, entropy, feature extraction, kinematics, Parkinson's disease, writing

RIV year

2015

Released

07.05.2015

ISBN

978-1-4799-6476-5

Book

Medical Measurements and Applications (MeMeA), 2015 IEEE International Symposium on

Pages from

344

Pages to

348

Pages count

5

BibTex


@inproceedings{BUT115289,
  author="Peter {Drotár} and Jiří {Mekyska} and Zdeněk {Smékal} and Irena {Rektorová} and Lucia {Masarová} and Marcos {Faúndez Zanuy}",
  title="Contribution of different handwriting modalities to differential diagnosis of Parkinson's Disease",
  annote="In this paper, we evaluate the contribution of different handwriting modalities to the diagnosis of Parkinson's disease. We analyse on-surface movement, in-air movement and pressure exerted on the tablet surface. Especially in-air movement and pressure-based features have been rarely taken into account in previous studies. We show that pressure and in-air movement also possess information that is relevant for the diagnosis of Parkinson's Disease (PD) from handwriting. In addition to the conventional kinematic and spatio-temporal features, we present a group of the novel features based on entropy and empirical mode decomposition of the handwriting signal. The presented results indicate that handwriting can be used as biomarker for PD providing classification performance around 89% area under the ROC curve (AUC) for PD classification.",
  booktitle="Medical Measurements and Applications (MeMeA), 2015 IEEE International Symposium on",
  chapter="115289",
  doi="10.1109/MeMeA.2015.7145225",
  howpublished="print",
  year="2015",
  month="may",
  pages="344--348",
  type="conference paper"
}