FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4288443336> ?p ?o ?g. }

• W4288443336 abstract "Abstract Measuring cognitive function is essential for characterizing brain health and tracking cognitive decline in Alzheimer’s Disease and other neurodegenerative conditions. Current tools to accurately evaluate cognitive impairment typically rely on a battery of questionnaires administered during clinical visits which is essential for the acquisition of repeated measurements in longitudinal studies. Previous studies have shown that the remote data collection of passively monitored daily interaction with personal digital devices can measure motor signs in the early stages of synucleinopathies, as well as facilitate longitudinal patient assessment in the real-world scenario with high patient compliance. This was achieved by the automatic discovery of patterns in the time series of keystroke dynamics, i.e. the time required to press and release keys, by machine learning algorithms. In this work, our hypothesis is that the typing patterns generated from user-device interaction may reflect relevant features of the effects of cognitive impairment caused by neurodegeneration. We use machine learning algorithms to estimate cognitive performance through the analysis of keystroke dynamic patterns that were extracted from mechanical and touchscreen keyboard use in a dataset of cognitively normal (n = 39, 51% male) and cognitively impaired subjects (n = 38, 60% male). These algorithms are trained and evaluated using a novel framework that integrates items from multiple neuropsychological and clinical scales into cognitive subdomains to generate a more holistic representation of multifaceted clinical signs. In our results, we see that these models based on typing input achieve moderate correlations with verbal memory, non-verbal memory and executive function subdomains [Spearman’s ρ between 0.54 (P &lt; 0.001) and 0.42 (P &lt; 0.001)] and a weak correlation with language/verbal skills [Spearman’s ρ 0.30 (P &lt; 0.05)]. In addition, we observe a moderate correlation between our typing-based approach and the Total Montreal Cognitive Assessment score [Spearman’s ρ 0.48 (P &lt; 0.001)]. Finally, we show that these machine learning models can perform better by using our subdomain framework that integrates the information from multiple neuropsychological scales as opposed to using the individual items that make up these scales. Our results support our hypothesis that typing patterns are able to reflect the effects of neurodegeneration in mild cognitive impairment and Alzheimer’s disease and that this new subdomain framework both helps the development of machine learning models and improves their interpretability." @default.
• W4288443336 created "2022-07-29" @default.
• W4288443336 creator A5018577105 @default.
• W4288443336 creator A5026804774 @default.
• W4288443336 creator A5027450676 @default.
• W4288443336 creator A5061950375 @default.
• W4288443336 creator A5065582442 @default.
• W4288443336 creator A5076239413 @default.
• W4288443336 creator A5078537481 @default.
• W4288443336 creator A5089464393 @default.
• W4288443336 date "2022-07-04" @default.
• W4288443336 modified "2023-10-06" @default.
• W4288443336 title "A novel framework to estimate cognitive impairment via finger interaction with digital devices" @default.
• W4288443336 cites W1534350900 @default.
• W4288443336 cites W1966739319 @default.
• W4288443336 cites W1980827933 @default.
• W4288443336 cites W1986479636 @default.
• W4288443336 cites W2014876801 @default.
• W4288443336 cites W2033345578 @default.
• W4288443336 cites W2056132907 @default.
• W4288443336 cites W2061966808 @default.
• W4288443336 cites W2064610785 @default.
• W4288443336 cites W2143997631 @default.
• W4288443336 cites W2149659204 @default.
• W4288443336 cites W2151717432 @default.
• W4288443336 cites W2164305812 @default.
• W4288443336 cites W2165758561 @default.
• W4288443336 cites W2169322502 @default.
• W4288443336 cites W2460853517 @default.
• W4288443336 cites W2554158390 @default.
• W4288443336 cites W2555002837 @default.
• W4288443336 cites W2559699229 @default.
• W4288443336 cites W2589994265 @default.
• W4288443336 cites W2602555460 @default.
• W4288443336 cites W2732150368 @default.
• W4288443336 cites W2767465985 @default.
• W4288443336 cites W2789914560 @default.
• W4288443336 cites W2807561669 @default.
• W4288443336 cites W2834574677 @default.
• W4288443336 cites W2899752978 @default.
• W4288443336 cites W2907749054 @default.
• W4288443336 cites W3020417681 @default.
• W4288443336 cites W3087324787 @default.
• W4288443336 cites W3092041776 @default.
• W4288443336 cites W3092410709 @default.
• W4288443336 cites W3103552852 @default.
• W4288443336 doi "https://doi.org/10.1093/braincomms/fcac194" @default.
• W4288443336 hasPubMedId "https://pubmed.ncbi.nlm.nih.gov/35950091" @default.
• W4288443336 hasPublicationYear "2022" @default.
• W4288443336 type Work @default.
• W4288443336 citedByCount "0" @default.
• W4288443336 crossrefType "journal-article" @default.
• W4288443336 hasAuthorship W4288443336A5018577105 @default.
• W4288443336 hasAuthorship W4288443336A5026804774 @default.
• W4288443336 hasAuthorship W4288443336A5027450676 @default.
• W4288443336 hasAuthorship W4288443336A5061950375 @default.
• W4288443336 hasAuthorship W4288443336A5065582442 @default.
• W4288443336 hasAuthorship W4288443336A5076239413 @default.
• W4288443336 hasAuthorship W4288443336A5078537481 @default.
• W4288443336 hasAuthorship W4288443336A5089464393 @default.
• W4288443336 hasBestOaLocation W42884433361 @default.
• W4288443336 hasConcept C119857082 @default.
• W4288443336 hasConcept C14216870 @default.
• W4288443336 hasConcept C154945302 @default.
• W4288443336 hasConcept C15744967 @default.
• W4288443336 hasConcept C169760540 @default.
• W4288443336 hasConcept C169900460 @default.
• W4288443336 hasConcept C41008148 @default.
• W4288443336 hasConcept C71924100 @default.
• W4288443336 hasConcept C99508421 @default.
• W4288443336 hasConceptScore W4288443336C119857082 @default.
• W4288443336 hasConceptScore W4288443336C14216870 @default.
• W4288443336 hasConceptScore W4288443336C154945302 @default.
• W4288443336 hasConceptScore W4288443336C15744967 @default.
• W4288443336 hasConceptScore W4288443336C169760540 @default.
• W4288443336 hasConceptScore W4288443336C169900460 @default.
• W4288443336 hasConceptScore W4288443336C41008148 @default.
• W4288443336 hasConceptScore W4288443336C71924100 @default.
• W4288443336 hasConceptScore W4288443336C99508421 @default.
• W4288443336 hasIssue "4" @default.
• W4288443336 hasLocation W42884433361 @default.
• W4288443336 hasLocation W42884433362 @default.
• W4288443336 hasLocation W42884433363 @default.
• W4288443336 hasOpenAccess W4288443336 @default.
• W4288443336 hasPrimaryLocation W42884433361 @default.
• W4288443336 hasRelatedWork W2318244633 @default.
• W4288443336 hasRelatedWork W2748952813 @default.
• W4288443336 hasRelatedWork W2899084033 @default.
• W4288443336 hasRelatedWork W2961085424 @default.
• W4288443336 hasRelatedWork W3046775127 @default.
• W4288443336 hasRelatedWork W4285260836 @default.
• W4288443336 hasRelatedWork W4286629047 @default.
• W4288443336 hasRelatedWork W4306321456 @default.
• W4288443336 hasRelatedWork W4306674287 @default.
• W4288443336 hasRelatedWork W4224009465 @default.
• W4288443336 hasVolume "4" @default.
• W4288443336 isParatext "false" @default.
• W4288443336 isRetracted "false" @default.
• W4288443336 workType "article" @default.