Dragos-Cristian Gruia, Valentina Giunchiglia, Aoife Coghlan, Sophie Brook, Soma Banerjee, Jo Kwan, Peter J. Hellyer, Adam Hampshire, Fatemeh Geranmayeh
{"title":"用于脑卒中后认知障碍深度表型的在线监测技术","authors":"Dragos-Cristian Gruia, Valentina Giunchiglia, Aoife Coghlan, Sophie Brook, Soma Banerjee, Jo Kwan, Peter J. Hellyer, Adam Hampshire, Fatemeh Geranmayeh","doi":"10.1101/2024.09.06.24313173","DOIUrl":null,"url":null,"abstract":"<strong>Background</strong> Despite the high prevalence of disabling post-stroke cognitive sequalae, these impairments are often underdiagnosed and rarely monitored longitudinally. Provision of unsupervised remote online cognitive technology would provide a scalable solution to this problem. However, despite recent advances, such technology is currently lacking, with existing tools either not meeting the scalability challenge or not optimised for specific applications in post-stroke cognitive impairment. To address this gap, we designed and developed a comprehensive online battery highly optimised for detecting cognitive impairments in stroke survivors.","PeriodicalId":501367,"journal":{"name":"medRxiv - Neurology","volume":"1 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2024-09-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Online monitoring technology for deep phenotyping of cognitive impairment after stroke\",\"authors\":\"Dragos-Cristian Gruia, Valentina Giunchiglia, Aoife Coghlan, Sophie Brook, Soma Banerjee, Jo Kwan, Peter J. Hellyer, Adam Hampshire, Fatemeh Geranmayeh\",\"doi\":\"10.1101/2024.09.06.24313173\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<strong>Background</strong> Despite the high prevalence of disabling post-stroke cognitive sequalae, these impairments are often underdiagnosed and rarely monitored longitudinally. Provision of unsupervised remote online cognitive technology would provide a scalable solution to this problem. However, despite recent advances, such technology is currently lacking, with existing tools either not meeting the scalability challenge or not optimised for specific applications in post-stroke cognitive impairment. To address this gap, we designed and developed a comprehensive online battery highly optimised for detecting cognitive impairments in stroke survivors.\",\"PeriodicalId\":501367,\"journal\":{\"name\":\"medRxiv - Neurology\",\"volume\":\"1 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2024-09-06\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"medRxiv - Neurology\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1101/2024.09.06.24313173\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"medRxiv - Neurology","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1101/2024.09.06.24313173","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Online monitoring technology for deep phenotyping of cognitive impairment after stroke
Background Despite the high prevalence of disabling post-stroke cognitive sequalae, these impairments are often underdiagnosed and rarely monitored longitudinally. Provision of unsupervised remote online cognitive technology would provide a scalable solution to this problem. However, despite recent advances, such technology is currently lacking, with existing tools either not meeting the scalability challenge or not optimised for specific applications in post-stroke cognitive impairment. To address this gap, we designed and developed a comprehensive online battery highly optimised for detecting cognitive impairments in stroke survivors.