Evaluation of Fractional Calculus and Delta Parameters in Prodromal Diagnosis of Dementia with Lewy Bodies utilizing Online Handwriting
| Authors | |
|---|---|
| Year of publication | 2024 |
| Type | Article in Proceedings |
| Conference | 2nd European Signal Processing Conference (EUSIPCO 2024) proceedings : 26-30 August 2024, Lyon, France |
| MU Faculty or unit | |
| Citation | MUCHA, Jan, Michal GAVENCIAK, Jiri MEKYSKA, Marcos FAUNDEZ-ZANUY, Luboš BRABENEC and Irena REKTOROVÁ. Evaluation of Fractional Calculus and Delta Parameters in Prodromal Diagnosis of Dementia with Lewy Bodies utilizing Online Handwriting. In IEEE. 2nd European Signal Processing Conference (EUSIPCO 2024) proceedings : 26-30 August 2024, Lyon, France. NEW YORK: IEEE, 2024, p. 1731-1735. ISBN 978-94-645936-1-7. Available from: https://dx.doi.org/10.23919/EUSIPCO63174.2024.10715381. |
| web | https://ieeexplore.ieee.org/document/10715381 |
| Doi | http://dx.doi.org/10.23919/EUSIPCO63174.2024.10715381 |
| Keywords | biomedical signal processing; feature extraction; fractional calculus; delta parameters; dementia with Lewy bodies; online handwriting; prodromal diagnosis |
| Description | This study evaluates the effect of fractional order derivatives (FD) and delta parameters in the prodromal diagnosis of dementia with Lewy bodies (DLB) utilizing online handwriting analysis. With DLB being the second most prevalent neurodegenerative dementia, early detection is critical for timely intervention. Leveraging advanced mathematical models, we explored the potential of FD-based and delta-based kinematic handwriting features compared to baseline. The analysis included 45 participants at high risk of developing DLB and 29 healthy controls who performed the Archimedean spiral task. Our findings reveal that FD-based kinematic features, mainly derived from the horizontal velocity at low alpha levels, are significantly discriminative. Moreover, the binary classification model trained with FD-based features achieved a balanced accuracy BACC=0.75. The study emphasizes the relevance of advanced kinematic parametrization in neurodegenerative disease diagnostics, presenting novel features as promising tools for DLB screening. |
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