Scaling behavior in measured keystroke time series from patients with Parkinson’s disease

Parkinson has remained as one of the most difficult diseases to diagnose, as there are no biomarkers to be measured, and this requires one patient to do neurological and physical examinations. As Parkinson is a progressive disease, accurate detection of its symptoms is a crucial factor for therapeut...

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Bibliographic Details
Published in:The European physical journal. B, Condensed matter physics Condensed matter physics, 2020-07, Vol.93 (7), Article 126
Main Authors: Madanchi, Ata, Taghavi-Shahri, Fatemeh, Taghavi-Shahri, Seyed Mahmood, Rahimi Tabar, Mohammed Reza
Format: Article
Language:English
Subjects:
Biomarkers
Complex Systems
Condensed Matter Physics
Distribution functions
Fluid- and Aerodynamics
Parkinson's disease
Physical examinations
Physics
Physics and Astronomy
Probability distribution functions
Regular Article
Signs and symptoms
Solid State Physics
Time measurement
Time series
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Summary:Parkinson has remained as one of the most difficult diseases to diagnose, as there are no biomarkers to be measured, and this requires one patient to do neurological and physical examinations. As Parkinson is a progressive disease, accurate detection of its symptoms is a crucial factor for therapeutic reasons. In this study, we perform Multifractal Detrended Fluctuation Analysis (MFDFA) on measured keystroke time series for three different categories of subjects: healthy, early-PD, and De-Novo patients. We have observed different scaling behavior in terms of multifractality of the measured time series, which can be used as a practical tool for diagnosis purposes. Additionally, the source of the multifractality has been studied which shows that in healthy and early-PD subjects, multifractality due to the long-range correlations is stronger than the influence of its probability distribution function (PDF) fatness, while in De-Novo patients, both shape of PDF and long-range correlations are contributing to observed multifractality. Graphical abstract
ISSN:1434-6028
1434-6036
DOI:10.1140/epjb/e2020-100561-4