Characterising Eye Movement Events with an Unsupervised Hidden Markov Model

Eye-tracking allows researchers to infer cognitive processes from eye movements that are classified into distinct events. Parsing the events is typically done by algorithms. Here we aim at developing an unsupervised, generative model that can be fitted to eye-movement data using maximum likelihood e...

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Detalles Bibliográficos
Autores principales: Lüken, Malte, Kucharský, Šimon, Visser, Ingmar
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Bern Open Publishing 2022
Materias:
Research Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076077/
https://www.ncbi.nlm.nih.gov/pubmed/37032712
http://dx.doi.org/10.16910/jemr.15.1.4

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10076077/
https://www.ncbi.nlm.nih.gov/pubmed/37032712
http://dx.doi.org/10.16910/jemr.15.1.4

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