Automatic Analysis of Arabic Online Handwriting of Patients with Parkinson's Disease

Aouraghe, Ibtissame; Ammour, Alae; Khaissidi, Ghizlane; Mrabti, Mostafa; Aboulem, Ghita; Belahsen, M.F.

doi:10.1145/3314074.3314100

Cited by 4 publications

(1 citation statement)

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“…Handwriting (HW) is a complex activity requiring fine motor control, it is characterized by a major involvement of muscles and brain, and touches the deepest mechanisms of cognition and sensorimotor. The HW alteration is mostly due to neurodegenerative diseases such as Alzheimer [1][2][3], and Parkinson's Disease (PD) [4][5][6][7].…”

Section: Introductionmentioning

confidence: 99%

Unsupervised learning for characterization of Arabic online handwriting of Parkinson’s disease patients

et al. 2020

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In this paper, we propose to characterize the on-line handwriting for the early detection of Parkinson's disease. Thus, using kinematics, mechanical, and spatial features of handwriting, we are looking for the characterization of Parkinson's disease. This paper describes the phase of the data acquisition which is currently carried out with in the Neurological department of UHC Hassan II of Fez. Following this paper, we have proposed an approach based on unsupervised learning techniques for analyzing on-line handwriting of 34 Parkinson's disease patients and 34 Healthy Controls according to quantitative and qualitative features. Based on 230 computed features for each participant, our study has uncovered three different types of writers. The results show that the complications of fine motor abilities in Parkinson's disease patients is especially characterized by a significant degradation in handwriting kinematic features.

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