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阿尔茨海默病认知评估早期诊断方法综述

A Survey of Alzheimer's Disease Early Diagnosis Methods for Cognitive Assessment.

作者信息

Fernández Montenegro Juan Manuel, Villarini Barbara, Angelopoulou Anastassia, Kapetanios Epaminondas, Garcia-Rodriguez Jose, Argyriou Vasileios

机构信息

Department of Networks and Digital Media, Kingston University, London KT1 2EE, UK.

Department of Computer Science, University of Westminster, London W1W 7BY, UK.

出版信息

Sensors (Basel). 2020 Dec 18;20(24):7292. doi: 10.3390/s20247292.

Abstract

Dementia is a syndrome that is characterised by the decline of different cognitive abilities. A high rate of deaths and high cost for detection, treatments, and patients care count amongst its consequences. Although there is no cure for dementia, a timely diagnosis helps in obtaining necessary support, appropriate medication, and maintenance, as far as possible, of engagement in intellectual, social, and physical activities. The early detection of Alzheimer Disease (AD) is considered to be of high importance for improving the quality of life of patients and their families. In particular, Virtual Reality (VR) is an expanding tool that can be used in order to assess cognitive abilities while navigating through a Virtual Environment (VE). The paper summarises common AD screening and diagnosis techniques focusing on the latest approaches that are based on Virtual Environments, behaviour analysis, and emotions recognition, aiming to provide more reliable and non-invasive diagnostics at home or in a clinical environment. Furthermore, different AD diagnosis evaluation methods and metrics are presented and discussed together with an overview of the different datasets.

摘要

痴呆症是一种以不同认知能力衰退为特征的综合征。其后果包括高死亡率以及检测、治疗和患者护理的高昂成本。尽管痴呆症无法治愈,但及时诊断有助于获得必要的支持、适当的药物治疗,并尽可能维持患者参与智力、社交和体育活动。阿尔茨海默病(AD)的早期检测对于改善患者及其家人的生活质量至关重要。特别是,虚拟现实(VR)是一种不断发展的工具,可用于在虚拟环境(VE)中导航时评估认知能力。本文总结了常见的AD筛查和诊断技术,重点关注基于虚拟环境、行为分析和情感识别的最新方法,旨在在家中或临床环境中提供更可靠且非侵入性的诊断。此外,还介绍并讨论了不同的AD诊断评估方法和指标,以及不同数据集的概述。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5e83/7766748/68f96056db20/sensors-20-07292-g001.jpg

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