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...
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| Format: | Article |
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MDPI AG
2022-02-01
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| Series: | Sensors |
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| Online Access: | https://www.mdpi.com/1424-8220/22/4/1688 |
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| author | Paula Stępień Jacek Kawa Emilia J. Sitek Dariusz Wieczorek Rafał Sikorski Magda Dąbrowska Jarosław Sławek Ewa Pietka |
| author_facet | Paula Stępień Jacek Kawa Emilia J. Sitek Dariusz Wieczorek Rafał Sikorski Magda Dąbrowska Jarosław Sławek Ewa Pietka |
| author_sort | Paula Stępień |
| collection | DOAJ |
| 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 (<i>p</i> < 0.05). A classifier showed an accuracy of 70.5% for distinguishing three groups. |
| first_indexed | 2024-03-09T21:05:40Z |
| format | Article |
| id | doaj.art-e98a657822a045659e3d62d642862a8d |
| institution | Directory Open Access Journal |
| issn | 1424-8220 |
| language | English |
| last_indexed | 2024-03-09T21:05:40Z |
| publishDate | 2022-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Sensors |
| spelling | doaj.art-e98a657822a045659e3d62d642862a8d2023-11-23T22:03:32ZengMDPI AGSensors1424-82202022-02-01224168810.3390/s22041688Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson’s DiseasePaula Stępień0Jacek Kawa1Emilia J. Sitek2Dariusz Wieczorek3Rafał Sikorski4Magda Dąbrowska5Jarosław Sławek6Ewa Pietka7Faculty of Biomedical Engineering, Silesian University of Technology, 41-800 Zabrze, PolandFaculty of Biomedical Engineering, Silesian University of Technology, 41-800 Zabrze, PolandDivision of Neurological and Psychiatric Nursing, Faculty of Health Sciences, Medical University of Gdansk, 80-211 Gdansk, PolandDepartment of Rehabilitation, Faculty of Health Sciences, Medical University of Gdansk, 80-219 Gdansk, PolandDepartment of Rehabilitation, Saint Vincent a Paulo Hospital, Pomeranian Hospitals Ltd., 81-519 Gdynia, PolandDepartment of Neurology, St. Adalbert Hospital, Copernicus PL Ltd., 80-462 Gdansk, PolandDivision of Neurological and Psychiatric Nursing, Faculty of Health Sciences, Medical University of Gdansk, 80-211 Gdansk, PolandFaculty of Biomedical Engineering, Silesian University of Technology, 41-800 Zabrze, PolandParkinson’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 (<i>p</i> < 0.05). A classifier showed an accuracy of 70.5% for distinguishing three groups.https://www.mdpi.com/1424-8220/22/4/1688baseline estimationcharacter recognitioncomputer aided diagnosisneurodegenerative diseasespattern analysiswriting analysis |
| spellingShingle | Paula Stępień Jacek Kawa Emilia J. Sitek Dariusz Wieczorek Rafał Sikorski Magda Dąbrowska Jarosław Sławek Ewa Pietka Computer Aided Written Character Feature Extraction in Progressive Supranuclear Palsy and Parkinson’s Disease Sensors baseline estimation character recognition computer aided diagnosis neurodegenerative diseases pattern analysis writing analysis |
| 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 | baseline estimation character recognition computer aided diagnosis neurodegenerative diseases pattern analysis writing analysis |
| url | https://www.mdpi.com/1424-8220/22/4/1688 |
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