Feature Selection as a Tool to Support the Diagnosis of Cognitive Impairments Through Handwriting Analysis

Abstract

Cognitive Impairments are cognitive deficits that are greater than expected for a person of a given age and level of education, but which do not significantly interfere with the daily life of the people affected. They range from mild to severe and are seen as a risk factor for Alzheimer's disease, currently the most common neurodegenerative brain disorder worldwide. In a previous study, we presented an experimental protocol comprising different handwriting tasks to be carried out by patients and a healthy control group: the aim was to investigate whether the analysis of the handwriting could be used as a tool to support the diagnosis of this kind of impairment. In the study presented here, we used a wellknown and widely-used feature selection approach to determine the most effective features for predicting the symptoms related to cognitive impairments via handwriting analysis. Our intention is to deepen the knowledge about the different cognitive functions affected by the onset of these diseases, as well as to improve the performance of the tools developed to support their diagnosis. The results showed that different sets of highly discriminant features, closely related to the cognitive skills impaired, were selected for the handwriting tasks making up the protocol, thus supporting our hypothesis that their use can be very helpful to support the diagnosis of cognitive impairment. INDEX TERMSMedical expert systems, Cognitive impairments, Feature selection.

Cognitive impairment assessment through handwriting (COGITAT) score: a novel tool that predicts cognitive state from handwriting for forensic and clinical applications

“…In recent years, there has been an increase in scientific interest in using handwriting in the diagnosis of Alzheimer’s Disease (AD), and researchers have investigated this issue even by using machine-based approaches. Among them, Cilia and coworkers found that physical parameters of the movement carried out in either handwriting or drawing may be useful in the early diagnosis of AD ( Cilia et al, 2019 , 2021a , b , 2022 ). Those results are of great interest and relevance, however we must not forget that AD is mainly defined by a failure in cognition, while motor, sensory, or coordination deficits are less prominent early in the disease ( McKhann et al, 1984 , 2011 ; Albert et al, 2011 ).…”

Managing the Intersection of Artificial Intelligence, Digital Typing, and Handwriting for Sustainable Quality Education Enhancement

“…The practice of handwriting in educational settings has been linked to improved learning outcomes and a deeper understanding of the subject matter. By preserving handwriting practices, we can ensure that future generations continue to reap these cognitive benefits (Cilia et al, 2021).…”

Interpol questioned documents review 2019–2022

“…In the study presented by Cilia et al, a feature selection approach was used to determine the most effective features for predicting the symptoms related to cognitive impairments via handwriting analysis. The intention was to deepen the knowledge about the different cognitive functions affected by the onset of these diseases, as well as to improve the performance of the tools developed to support their diagnosis [ 54 ].…”