online-offline Iraquian hand-drawing dataset for early Parkinson’s disease detection

Citation Author(s):
Mohammed F.
Allebawi
Technical Institute of Babylon, Al-Furat Al-Awsat Technical University (ATU), Iraq.
Thameur
Dhieb
REGIM-Lab.: REsearch Groups in Intelligent Machines, Enis, University of Sfax, Tunisia.
Islem
Jarraya
REGIM-Lab.: REsearch Groups in Intelligent Machines, Enis, University of Sfax, Tunisia.
Mohamed
Neji
REGIM-Lab.: REsearch Groups in Intelligent Machines, Enis, University of Sfax, Tunisia.
Nouha
Farhat
Laboratory of Neurogenetics, Parkinson’s Disease and Cerebrovascular Disease (LR-12-SP-19), University of Sfax, Tunisia.
Tarek M.
Hamdani
REGIM-Lab.: REsearch Groups in Intelligent Machines, Enis, University of Sfax, Tunisia.
Mariem
Damak
Laboratory of Neurogenetics, Parkinson’s Disease and Cerebrovascular Disease (LR-12-SP-19), University of Sfax, Tunisia.
Chokri
Mhiri
Laboratory of Neurogenetics, Parkinson’s Disease and Cerebrovascular Disease (LR-12-SP-19), University of Sfax, Tunisia.
Adel M.
Alimi
REGIM-Lab.: REsearch Groups in Intelligent Machines, Enis, University of Sfax, Tunisia.
Submitted by:
Thameur Dhieb
Last updated:
Sat, 08/03/2024 - 12:59
DOI:
10.21227/3z4w-gq35
Data Format:
*.avi; *.png; *.csv; *.zip
License:
Creative Commons Attribution
441 Views
Categories:
Artificial Intelligence
Signal Processing
Biomedical and Health Sciences
Health
Keywords:
Parkinson’s disease, online-offline hand-drawing, Iraquian, PD patients, healthy controls
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Abstract 

We introduce an online-offline Iraquian hand-drawing dataset for early Parkinson’s disease detection, exclusively collected using smartphones, thus eliminating the need for specialized equipment like digitizing tablets and pens. Our dataset comprises data from 30 healthy individuals (17 men, 13 women) with an average age of 56 years (SD = 6.12) and 30 PD patients (23 men, 7 women) with an average age of 60 years (SD = 4.91), gathered at Marjan Hospital in Hilla, Babil Governorate, Iraq. Participants undertook various hand-drawing tasks, including repetitive ellipses, spirals, digits, and Arabic word writing. We anticipate that our dataset will aid in early detection of Parkinson's disease and contribute to advancing understanding and treatment of the condition.

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Submitted by Pammi Siddhaarth on Sat, 07/27/2024 - 11:45

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