@ARTICLE{10.21494/ISTE.OP.2017.0153, 

TITLE={Automatic analysis of on‐line handwriting for the early detection of neurodegenerative pathologies}, 
  
AUTHOR={Aouraghe Ibtissame, Ammour Alae, Aboulem Ghita, Khaissidi Ghizlane, Mrabti Mostafa, Belahsen Faouzi, Mounim A. El-Yacoubi, Sonia Garcia-Salicetti, }, 
	
JOURNAL={Internet of Things}, 
	
VOLUME={1}, 

NUMBER={Issue 2}, 
	
YEAR={2017}, 

URL={https://openscience.fr/Automatic-analysis-of-on-line-handwriting-for-the-early-detection-of}, 
	
DOI={10.21494/ISTE.OP.2017.0153}, 
	
ISSN={2514-8273}, 
	
ABSTRACT={We propose in this article to analyse on-line handwriting acquired on a digital graphic tablet for the early detection of neurological pathologies. Our main goal is the characterization of neurodegenerative diseases, such as Parkinson, Alzheimer, Mild Cognitive Impairment and neuropsychiatric diseases such as schizophrenia, through the use of spatiotemporal parameters of handwriting. This paper mainly describes the phase of handwriting and hand-drawn data acquisition currently underway at the Neurological Service at CHU Hassan II de Fez hospital, and gives a preliminary analysis of the spatiotemporal parameters extracted from the handwriting.}}