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dc.contributor.author
Iaconis, Francisco Ramiro  
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Trujillo Jiménez, Magda Alexandra  
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Gasaneo, Gustavo  
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Rosso, O. A.  
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Delrieux, Claudio Augusto  
dc.date.available
2023-10-03T12:58:23Z  
dc.date.issued
2023-05  
dc.identifier.citation
Iaconis, Francisco Ramiro; Trujillo Jiménez, Magda Alexandra; Gasaneo, Gustavo; Rosso, O. A.; Delrieux, Claudio Augusto; Ordinal pattern transition networks in eye tracking reading signals; American Institute of Physics; Chaos; 33; 5; 5-2023; 1-7  
dc.identifier.issn
1054-1500  
dc.identifier.uri
http://hdl.handle.net/11336/213921  
dc.description.abstract
Eye tracking is an emerging technology with a wide spectrum of applications, including non-invasive neurocognitive diagnosis. An advantage of the use of eye trackers is in the improved assessment of indirect latent information about several aspects of the subjects' neurophysiology. The path to uncover and take advantage of the meaning and implications of this information, however, is still in its very early stages. In this work, we apply ordinal patterns transition networks as a means to identify subjects with dyslexia in simple text reading experiments. We registered the tracking signal of the eye movements of several subjects (either normal or with diagnosed dyslexia). The evolution of the left-to-right movement over time was analyzed using ordinal patterns, and the transitions between patterns were analyzed and characterized. The relative frequencies of these transitions were used as feature descriptors, with which a classifier was trained. The classifier is able to distinguish typically developed vs dyslexic subjects with almost 100% accuracy only analyzing the relative frequency of the eye movement transition from one particular permutation pattern (plain left to right) to four other patterns including itself. This characterization helps understand differences in the underlying cognitive behavior of these two groups of subjects and also paves the way to several other potentially fruitful analyses applied to other neurocognitive conditions and tests.  
dc.format
application/pdf  
dc.language.iso
eng  
dc.publisher
American Institute of Physics  
dc.rights
info:eu-repo/semantics/openAccess  
dc.rights.uri
https://creativecommons.org/licenses/by-nc-sa/2.5/ar/  
dc.subject
Machine Learning  
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Decision Theory  
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Eye tracking  
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Dyslexia  
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Otras Ciencias de la Computación e Información  
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Ciencias de la Computación e Información  
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CIENCIAS NATURALES Y EXACTAS  
dc.title
Ordinal pattern transition networks in eye tracking reading signals  
dc.type
info:eu-repo/semantics/article  
dc.type
info:ar-repo/semantics/artículo  
dc.type
info:eu-repo/semantics/publishedVersion  
dc.date.updated
2023-09-25T14:54:24Z  
dc.journal.volume
33  
dc.journal.number
5  
dc.journal.pagination
1-7  
dc.journal.pais
Estados Unidos  
dc.journal.ciudad
New York  
dc.description.fil
Fil: Iaconis, Francisco Ramiro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; Argentina  
dc.description.fil
Fil: Trujillo Jiménez, Magda Alexandra. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca; Argentina  
dc.description.fil
Fil: Gasaneo, Gustavo. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Física del Sur. Universidad Nacional del Sur. Departamento de Física. Instituto de Física del Sur; Argentina  
dc.description.fil
Fil: Rosso, O. A.. Universidade Federal de Alagoas; Brasil. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - La Plata. Instituto de Física La Plata. Universidad Nacional de La Plata. Facultad de Ciencias Exactas. Instituto de Física La Plata; Argentina  
dc.description.fil
Fil: Delrieux, Claudio Augusto. Universidad Nacional del Sur. Departamento de Ingeniería Eléctrica y de Computadoras; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Ciencias e Ingeniería de la Computación. Universidad Nacional del Sur. Departamento de Ciencias e Ingeniería de la Computación. Instituto de Ciencias e Ingeniería de la Computación; Argentina  
dc.journal.title
Chaos  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/url/https://pubs.aip.org/cha/article/33/5/053101/2887745/Ordinal-pattern-transition-networks-in-eye  
dc.relation.alternativeid
info:eu-repo/semantics/altIdentifier/doi/http://dx.doi.org/10.1063/5.0142230