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

arXiv: https://arxiv.org/abs/2203.11269 · HTML: https://mlsanity.com/paper/2203.11269/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- Builds on 0 of its 28 references that are in the map.
- First posted on arXiv 18 Mar 2022.

## Built on by (most cited first, 1 of 1)

- [Exploration of Various Fractional Order Derivatives in Parkinson's Disease Dysgraphia Analysis](https://mlsanity.com/paper/2301.08529/) (2023)

## Abstract (arXiv)

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.