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Dementia","award":["R01AG21051"],"award-info":[{"award-number":["R01AG21051"]}]},{"name":"Bluefield Project to Cure Frontotemporal Dementia","award":["CARDS-NIH"],"award-info":[{"award-number":["CARDS-NIH"]}]},{"name":"Bluefield Project to Cure Frontotemporal Dementia","award":["SG-20- 725707"],"award-info":[{"award-number":["SG-20- 725707"]}]},{"name":"Global Brain Health Institute","award":["IAPFI23-1-01"],"award-info":[{"award-number":["IAPFI23-1-01"]}]},{"name":"Global Brain Health Institute","award":["PI2023-58010"],"award-info":[{"award-number":["PI2023-58010"]}]},{"name":"Global Brain Health Institute","award":["R01AG075775"],"award-info":[{"award-number":["R01AG075775"]}]},{"name":"Global Brain Health Institute","award":["2P01AG019724"],"award-info":[{"award-number":["2P01AG019724"]}]},{"name":"Global Brain Health Institute","award":["1210176"],"award-info":[{"award-number":["1210176"]}]},{"name":"Global Brain Health Institute","award":["1210195"],"award-info":[{"award-number":["1210195"]}]},{"name":"Global Brain Health Institute","award":["032351G-DAS"],"award-info":[{"award-number":["032351G-DAS"]}]},{"name":"Global Brain Health Institute","award":["01-PICTE-2022-05-00103"],"award-info":[{"award-number":["01-PICTE-2022-05-00103"]}]},{"name":"Global Brain Health Institute","award":["EI-X-2023-1-176993"],"award-info":[{"award-number":["EI-X-2023-1-176993"]}]},{"name":"Global Brain Health Institute","award":["R01AG057234"],"award-info":[{"award-number":["R01AG057234"]}]},{"name":"Global Brain Health Institute","award":["R01AG075775"],"award-info":[{"award-number":["R01AG075775"]}]},{"name":"Global Brain Health Institute","award":["R01AG21051"],"award-info":[{"award-number":["R01AG21051"]}]},{"name":"Global Brain Health Institute","award":["CARDS-NIH"],"award-info":[{"award-number":["CARDS-NIH"]}]},{"name":"Global Brain Health Institute","award":["SG-20- 725707"],"award-info":[{"award-number":["SG-20- 725707"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Diagnostics"],"abstract":"<jats:p>Background: Parkinson\u2019s disease (PD) is the second most prevalent neurodegenerative disorder worldwide. People suffering from PD exhibit motor symptoms that affect the control of upper and lower limb movement. Among daily activities that depend on proper upper limb control is the handwriting process, which has been studied in state-of-the-art research, mainly considering non-semantic drawings like spirals, geometric figures, cursive lines, and others. Objectives: This paper analyzes the suitability of modeling the handwriting process of digits from 0 to 9 to automatically discriminate between PD patients and healthy control subjects. The main hypothesis is that modeling these numbers allows a more natural evaluation of upper limb control. Methods: Two approaches are considered: modeling of the images resulting from the strokes collected by the digital tablet and modeling of the time series yielded by the digital tablet while performing the strokes, i.e., time-dependent signals. The first approach is implemented by fine-tuning a CNN-based architecture, while the second approach is based on hand-crafted features measured upon the time series, namely pressure and kinematic measurements. Features extracted from time-dependent signals are represented following two strategies, one based on statistical functionals and the other one based on creating Gaussian Mixture Models (GMMs). Results: The experiments indicate that pressure-based features modeled with functionals are the ones that yield the highest accuracy, indicating that PD-related symptoms are better modeled with dynamic approaches than those based on images. Conclusions: The dynamic approach outperformed the image-based model, indicating that the writing process, modeled with signals collected over time, reveals motor symptoms more clearly than images resulting from handwriting. This finding is in line with previous results in the state-of-the-art research and constitutes a step forward to create more accurate and informative methods to detect and monitor PD symptoms.<\/jats:p>","DOI":"10.3390\/diagnostics15030381","type":"journal-article","created":{"date-parts":[[2025,2,6]],"date-time":"2025-02-06T06:30:29Z","timestamp":1738823429000},"page":"381","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Towards Parkinson\u2019s Disease Detection Through Analysis of Everyday Handwriting"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0003-3474-4166","authenticated-orcid":false,"given":"Jeferson David","family":"Gallo-Aristizabal","sequence":"first","affiliation":[{"name":"GITA Lab., Faculty of Engineering, University of Antioquia, Medell\u00edn 510010, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-3257-0134","authenticated-orcid":false,"given":"Daniel","family":"Escobar-Grisales","sequence":"additional","affiliation":[{"name":"GITA Lab., Faculty of Engineering, University of Antioquia, Medell\u00edn 510010, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-0174-1452","authenticated-orcid":false,"given":"Cristian David","family":"R\u00edos-Urrego","sequence":"additional","affiliation":[{"name":"GITA Lab., Faculty of Engineering, University of Antioquia, Medell\u00edn 510010, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-8794-6429","authenticated-orcid":false,"given":"Jes\u00fas Francisco","family":"Vargas-Bonilla","sequence":"additional","affiliation":[{"name":"GITA Lab., Faculty of Engineering, University of Antioquia, Medell\u00edn 510010, Colombia"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6936-0114","authenticated-orcid":false,"given":"Adolfo M.","family":"Garc\u00eda","sequence":"additional","affiliation":[{"name":"Cognitive Neuroscience Center, Universidad de San Andr\u00e9s, Buenos Aires B1644BID, Argentina"},{"name":"Global Brain Health Institute (GBHI), University of California San Francisco, San Francisco, CA 94143, USA"},{"name":"Trinity College Dublin, D02 R590 Dublin, Ireland"},{"name":"Departamento de Ling\u00fc\u00edstica y Literatura, Facultad de Humanidades, Universidad de Santiago de Chile, Santiago 9170020, Chile"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-8507-0782","authenticated-orcid":false,"given":"Juan Rafael","family":"Orozco-Arroyave","sequence":"additional","affiliation":[{"name":"GITA Lab., Faculty of Engineering, University of Antioquia, Medell\u00edn 510010, Colombia"},{"name":"LME Lab., University of Erlangen, 91054 Erlangen, Germany"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"1968","published-online":{"date-parts":[[2025,2,5]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"S2","DOI":"10.1212\/WNL.51.2_Suppl_2.S2","article-title":"Biochemical aspects of Parkinson\u2019s disease","volume":"51","author":"Hornykiewicz","year":"1998","journal-title":"Neurology"},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"79","DOI":"10.1016\/j.neuroimage.2018.11.021","article-title":"The role of dopamine in the brain-lessons learned from Parkinson\u2019s disease","volume":"190","author":"Meder","year":"2019","journal-title":"Neuroimage"},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"318","DOI":"10.1111\/jnc.13691","article-title":"The clinical symptoms of Parkinson\u2019s disease","volume":"139","author":"Sveinbjornsdottir","year":"2016","journal-title":"J. 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