Abstract
Alzheimer’s Disease (AD) is a neurodegenerative disease which causes a continuous cognitive decline. This decline has a strong impact on daily life of the people affected and on that of their relatives. Unfortunately, to date there is no cure for this disease. However, its early diagnosis helps to better manage the course of the disease with the treatments currently available. In recent years, AI researchers have become increasingly interested in developing tools for early diagnosis of AD based on handwriting analysis. In most cases, they use a feature engineering approach: domain knowledge by clinicians is used to define the set of features to extract from the raw data. In this paper, we present a novel approach based on vectorial genetic programming (VE_GP) to recognize the handwriting of AD patients. VE_GP is a recently defined method that enhances Genetic Programming (GP) and is able to directly manage time series in such a way to automatically extract informative features, without any need of human intervention. We applied VE_GP to handwriting data in the form of time series consisting of spatial coordinates and pressure. These time series represent pen movements collected from people while performing handwriting tasks. The presented experimental results indicate that the proposed approach is effective for this type of application. Furthermore, VE_GP is also able to generate rather small and simple models, that can be read and possibly interpreted. These models are reported and discussed in the Last part of the paper.
Original language | English |
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Title of host publication | Applications of Evolutionary Computation |
Subtitle of host publication | 25th European Conference, EvoApplications 2022, Held as Part of EvoStar 2022, Madrid, Spain, April 20–22, 2022, Proceedings |
Editors | Juan Luis Jiménez LaredoJ, J. Ignacio Hidalgo, Kehinde Oluwatoyin Babaagba |
Publisher | Springer |
Chapter | 33 |
Pages | 517-530 |
Number of pages | 14 |
ISBN (Electronic) | 978-3-031-02462-7 |
ISBN (Print) | 978-3-031-02461-0 |
DOIs | |
Publication status | Published - 15 Apr 2022 |
Event | 25th International Conference on Applications of Evolutionary Computation - Virtual Duration: 20 Apr 2022 → 22 Apr 2022 Conference number: 25 http://www.evostar.org/2022/evoapps/ |
Publication series
Name | Lecture Notes in Computer Science |
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Volume | 13224 |
ISSN (Print) | 0302-9743 |
ISSN (Electronic) | 1611-3349 |
Conference
Conference | 25th International Conference on Applications of Evolutionary Computation |
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Abbreviated title | EvoApplications 2022 |
Period | 20/04/22 → 22/04/22 |
Internet address |
Keywords
- Alzheimer’s disease
- Artificial intelligence
- Handwriting analysis
- Vectorial genetic programming