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Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson’s Disease
Parkinson’s disease (PD) and progressive supranuclear palsy (PSP) are neurodegenerative movement disorders associated with cognitive dysfunction. The Luria’s Alternating Series Test (LAST) is a clinical tool sensitive to both graphomotor problems and perseverative tendencies that may suggest the dys...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8880639/ https://www.ncbi.nlm.nih.gov/pubmed/35214587 http://dx.doi.org/10.3390/s22041688 |
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author | Stępień, Paula Kawa, Jacek Sitek, Emilia J. Wieczorek, Dariusz Sikorski, Rafał Dąbrowska, Magda Sławek, Jarosław Pietka, Ewa |
author_facet | Stępień, Paula Kawa, Jacek Sitek, Emilia J. Wieczorek, Dariusz Sikorski, Rafał Dąbrowska, Magda Sławek, Jarosław Pietka, Ewa |
author_sort | Stępień, Paula |
collection | PubMed |
description | Parkinson’s disease (PD) and progressive supranuclear palsy (PSP) are neurodegenerative movement disorders associated with cognitive dysfunction. The Luria’s Alternating Series Test (LAST) is a clinical tool sensitive to both graphomotor problems and perseverative tendencies that may suggest the dysfunction of prefrontal and/or frontostriatal areas and may be used in PD and PSP assessment. It requires the participant to draw a series of alternating triangles and rectangles. In the study, two clinical groups—51 patients with PD and 22 patients with PSP—were compared to 32 neurologically intact seniors. Participants underwent neuropsychological assessment. The LAST was administered in a paper and pencil version, then scanned and preprocessed. The series was automatically divided into characters, and the shapes were recognized as rectangles or triangles. In the feature extraction step, each rectangle and triangle was regarded both as an image and a two-dimensional signal, separately and as a part of the series. Standard and novel features were extracted and normalized using characters written by the examiner. Out of 71 proposed features, 51 differentiated the groups (p < 0.05). A classifier showed an accuracy of 70.5% for distinguishing three groups. |
format | Online Article Text |
id | pubmed-8880639 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-88806392022-02-26 Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson’s Disease Stępień, Paula Kawa, Jacek Sitek, Emilia J. Wieczorek, Dariusz Sikorski, Rafał Dąbrowska, Magda Sławek, Jarosław Pietka, Ewa Sensors (Basel) Article Parkinson’s disease (PD) and progressive supranuclear palsy (PSP) are neurodegenerative movement disorders associated with cognitive dysfunction. The Luria’s Alternating Series Test (LAST) is a clinical tool sensitive to both graphomotor problems and perseverative tendencies that may suggest the dysfunction of prefrontal and/or frontostriatal areas and may be used in PD and PSP assessment. It requires the participant to draw a series of alternating triangles and rectangles. In the study, two clinical groups—51 patients with PD and 22 patients with PSP—were compared to 32 neurologically intact seniors. Participants underwent neuropsychological assessment. The LAST was administered in a paper and pencil version, then scanned and preprocessed. The series was automatically divided into characters, and the shapes were recognized as rectangles or triangles. In the feature extraction step, each rectangle and triangle was regarded both as an image and a two-dimensional signal, separately and as a part of the series. Standard and novel features were extracted and normalized using characters written by the examiner. Out of 71 proposed features, 51 differentiated the groups (p < 0.05). A classifier showed an accuracy of 70.5% for distinguishing three groups. MDPI 2022-02-21 /pmc/articles/PMC8880639/ /pubmed/35214587 http://dx.doi.org/10.3390/s22041688 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Stępień, Paula Kawa, Jacek Sitek, Emilia J. Wieczorek, Dariusz Sikorski, Rafał Dąbrowska, Magda Sławek, Jarosław Pietka, Ewa Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson’s Disease |
title | Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson’s Disease |
title_full | Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson’s Disease |
title_fullStr | Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson’s Disease |
title_full_unstemmed | Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson’s Disease |
title_short | Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson’s Disease |
title_sort | computer aided written character feature extraction in progressive supranuclear palsy and parkinson’s disease |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8880639/ https://www.ncbi.nlm.nih.gov/pubmed/35214587 http://dx.doi.org/10.3390/s22041688 |
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