Online monitoring technology for deep phenotyping of cognitive impairment after stroke

Dragos-Cristian Gruia, Valentina Giunchiglia, Aoife Coghlan, Sophie Brook, Soma Banerjee, Jo Kwan, Peter J. Hellyer, Adam Hampshire, Fatemeh Geranmayeh
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Abstract

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.
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用于脑卒中后认知障碍深度表型的在线监测技术
背景 尽管脑卒中后致残性认知后遗症的发病率很高,但这些损伤往往诊断不足,也很少得到纵向监测。提供无监督远程在线认知技术将为这一问题提供可扩展的解决方案。然而,尽管最近取得了一些进展,但目前还缺乏这样的技术,现有的工具要么无法应对可扩展性的挑战,要么没有针对卒中后认知障碍的具体应用进行优化。为了弥补这一不足,我们设计并开发了一种综合性在线电池,该电池经过高度优化,可用于检测中风幸存者的认知障碍。
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