Abstract
Background: The analysis of handwriting movements to quantify motor and cognitive impairments in neurodegenerative diseases is increasingly attracting interest. Non-invasive and quick-to-administer tools using handwriting movement analysis can be used in early screening of Parkinson’s disease (PD) and maybe in the diagnosis of other neurodegenerative disease. Theaim of this work is to identify the distinctive signs characterizing handwriting in the early stage of PD, in order to provide a diagnostic tool for the early detection of the disease. Compared to previous studies, here, we analyzed handwriting movements of patients on which the disease affects the contralateral side with respect to the one used for writing. Methods: We collected and analyzed a set of handwriting samples by PD patients and healthy subjects. Participants were asked to follow a novel protocol, containing handwriting patterns of various levels of complexity, using both familiar and unfamiliar movements. Results: We found that the signs characterizing the early stage of PD differ from those appearing in later stages. Our work provides evidence that early detection of PD, even when the disease affects mainly the contralateral side with respect to the one used for writing, could be achieved by analyzing specific features measured during the execution of specific handwriting tasks. Eventually, we found that patients’ performance benefits from the execution of handwriting in specific conditions. Conclusions: The analysis provides the guidelines for the design of a diagnostic tool for the early detection of PD and some suggestions for reducing motor impairments in PD patients.
Funder
Italian Ministero dell’Istruzione, dell’Università e della Ricerca
Subject
Fluid Flow and Transfer Processes,Computer Science Applications,Process Chemistry and Technology,General Engineering,Instrumentation,General Materials Science
Cited by
1 articles.
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