EA CoBTeK, Université de Nice Sophia-Antipolis, Sophia-Antipolis, France.
Clin Interv Aging. 2012;7:539-49. doi: 10.2147/CIA.S36297. Epub 2012 Dec 4.
BACKGROUND: One of the key clinical features of Alzheimer's disease (AD) is impairment in daily functioning. Patients with mild cognitive impairment (MCI) also commonly have mild problems performing complex tasks. Information and communication technology (ICT), particularly techniques involving imaging and video processing, is of interest in order to improve assessment. The overall aim of this study is to demonstrate that it is possible using a video monitoring system to obtain a quantifiable assessment of instrumental activities of daily living (IADLs) in AD and in MCI. METHODS: The aim of the study is to propose a daily activity scenario (DAS) score that detects functional impairment using ICTs in AD and MCI compared with normal control group (NC). Sixty-four participants over 65 years old were included: 16 AD matched with 10 NC for protocol 1 (P1) and 19 MCI matched with 19 NC for protocol 2 (P2). Each participant was asked to undertake a set of daily tasks in the setting of a "smart home" equipped with two video cameras and everyday objects for use in activities of daily living (8 IADLs for P1 and 11 for P2, plus 4 temporal execution constraints). The DAS score was then computed from quantitative and qualitative parameters collected from video recordings. RESULTS: In P1, the DAS score differentiated AD (DAS(AD,P1) = 0.47, 95% confidence interval [CI] 0.38-0.56) from NC (DAS(NC,P1) = 0.71, 95% CI 0.68-0.74). In P2, the DAS score differentiated MCI (DAS(MCI,P2) = 0.11, 95% CI 0.05-0.16) and NC (DAS(NC,P2) = 0.36, 95% CI 0.26-0.45). CONCLUSION: In conclusion, this study outlines the interest of a novel tool coming from the ICT world for the assessment of functional impairment in AD and MCI. The derived DAS scores provide a pragmatic, ecological, objective measurement which may improve the prediction of future dementia, be used as an outcome measurement in clinical trials and lead to earlier therapeutic intervention.
背景:阿尔茨海默病(AD)的一个关键临床特征是日常功能受损。轻度认知障碍(MCI)患者也经常在执行复杂任务时出现轻度问题。信息和通信技术(ICT),特别是涉及成像和视频处理的技术,在改善评估方面很有意义。本研究的总体目标是证明使用视频监控系统可以对 AD 和 MCI 患者的工具性日常生活活动(IADLs)进行量化评估。
方法:该研究旨在提出一种日常活动场景(DAS)评分,该评分使用 ICT 在 AD 和 MCI 中检测与正常对照组(NC)相比的功能障碍。共有 64 名 65 岁以上的参与者入组:16 名 AD 患者与 10 名 NC 患者匹配用于方案 1(P1),19 名 MCI 患者与 19 名 NC 患者匹配用于方案 2(P2)。每个参与者都被要求在配备两个摄像头和日常生活用品的“智能家居”环境中完成一组日常任务(P1 为 8 项 IADLs,P2 为 11 项,外加 4 项时间执行限制)。然后,从视频记录中收集的定量和定性参数计算 DAS 评分。
结果:在 P1 中,DAS 评分区分了 AD(DAS(AD,P1)=0.47,95%置信区间[CI]0.38-0.56)和 NC(DAS(NC,P1)=0.71,95%CI0.68-0.74)。在 P2 中,DAS 评分区分了 MCI(DAS(MCI,P2)=0.11,95%CI0.05-0.16)和 NC(DAS(NC,P2)=0.36,95%CI0.26-0.45)。
结论:总之,本研究概述了来自 ICT 领域的新工具在评估 AD 和 MCI 患者功能障碍方面的意义。得出的 DAS 评分提供了一种实用、生态、客观的测量方法,可能会提高对未来痴呆的预测能力,用作临床试验的结果测量指标,并导致更早的治疗干预。
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