Contribution of Different Handwriting Modalities to Differential Diagnosis of Parkinson's Disease

Document detail

ID

oai:arXiv.org:2203.11269

Topic

Electrical Engineering and Systems... Computer Science - Computer Vision...

Author

Drotár, Peter Mekyska, Jiří Smékal, Zdeněk Rektorová, Irena Masarová, Lucia Faundez-Zanuy, Marcos

Year

2022

listing date

4/1/2022

Keywords

disease parkinson in-air pd features diagnosis movement handwriting

Metrics

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.

;Comment: The work was published by IEEE

Drotár, Peter,Mekyska, Jiří,Smékal, Zdeněk,Rektorová, Irena,Masarová, Lucia,Faundez-Zanuy, Marcos, 2022, Contribution of Different Handwriting Modalities to Differential Diagnosis of Parkinson's Disease