We introduce a novel Italian language resource for the study of reading and comprehension in aging populations, combining behavioural and linguistic data from healthy controls (HC), individuals with subjective cognitive decline (SCI), participants with Mild Cognitive Impairment (MCI), and patients with mild dementia (CDR1). Reading performance was recorded through a finger-tracking based application during both silent and oral reading, enabling fine-grained temporal analyses at the text, token and character level. Comprehension was assessed via multiple question types (wh-, inferential, referential, and lexical). Descriptive and non-linear regression analyses informed a feature selection process, yielding temporal and comprehension-based measures that capture individual reading dynamics. These features were explored through unsupervised clustering and supervised classification to investigate their discriminative and predictive potential across cognitive profiles. The resource supports research on reading and cognitive decline, offers a reproducible protocol for large-scale data collection, and provides a foundation for developing early cognitive screening and monitoring tools for aging populations.

Reading Dynamics and Comprehension in Cognitive Aging: A Multimodal Language Resource

Claudia Marzi
Primo
;
Alice Todesco;Cristina Dolciotti;Marcello Ferro;Vito Pirrelli
2026

Abstract

We introduce a novel Italian language resource for the study of reading and comprehension in aging populations, combining behavioural and linguistic data from healthy controls (HC), individuals with subjective cognitive decline (SCI), participants with Mild Cognitive Impairment (MCI), and patients with mild dementia (CDR1). Reading performance was recorded through a finger-tracking based application during both silent and oral reading, enabling fine-grained temporal analyses at the text, token and character level. Comprehension was assessed via multiple question types (wh-, inferential, referential, and lexical). Descriptive and non-linear regression analyses informed a feature selection process, yielding temporal and comprehension-based measures that capture individual reading dynamics. These features were explored through unsupervised clustering and supervised classification to investigate their discriminative and predictive potential across cognitive profiles. The resource supports research on reading and cognitive decline, offers a reproducible protocol for large-scale data collection, and provides a foundation for developing early cognitive screening and monitoring tools for aging populations.
2026
Istituto di linguistica computazionale "Antonio Zampolli" - ILC
978-2-493814-49-4
reading behaviour, cognitive aging, finger-tracking, language resources for assistive technologies, cluster analysis, automatic classification
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/580325
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