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智能家居技术:一种用于测量老年人日常生活活动表现及预测轻度认知障碍的新方法。

Smart Home Technology: A New Approach for Performance Measurements of Activities of Daily Living and Prediction of Mild Cognitive Impairment in Older Adults.

作者信息

Lussier Maxime, Adam Stéphane, Chikhaoui Belkacem, Consel Charles, Gagnon Mathieu, Gilbert Brigitte, Giroux Sylvain, Guay Manon, Hudon Carol, Imbeault Hélène, Langlois Francis, Macoir Joel, Pigot Hélène, Talbot Lise, Bier Nathalie

机构信息

Research Center of Institut universitaire de gériatrie de Montréal, Montreal, Canada.

Faculty of Medicine, Université de Montréal, Montreal, Canada.

出版信息

J Alzheimers Dis. 2019;68(1):85-96. doi: 10.3233/JAD-180652.

Abstract

BACKGROUND

Functional assessment is of paramount importance when mild cognitive impairment is suspected, but common assessment tools such as questionnaires lack sensitivity. An alternative and innovative approach consists in using sensor technology in smart apartments during scenario-based assessments of instrumental activities of daily living (IADL). However, studies that investigate this approach are scarce and the technology used is not always transposable in healthcare settings.

OBJECTIVE

To explore whether simple and wireless technology used in two different smart environments could add value to performance and rater-based measures of IADL when it comes to predicting mild cognitive impairment (MCI) in older adults.

METHODS

Twenty-six (26) cognitively healthy older adults (CH) and 22 older adults with MCI were recruited. Functional performance in a set of five scripted tasks was evaluated with sensor-based observations (motion, contact, and electric sensors) and performance-based measures (rated with videotapes). The five tasks could be performed in any order and were detailed on an instruction sheet given to participants.

RESULTS

Sensor-based observations showed that participants with MCI spent more time in the kitchen and looking into the fridge and kitchen cabinets than CH participants. Moreover, these measures were negatively associated with memory and executive performances of participants and significantly contributed to the prediction of MCI.

CONCLUSION

Simple, wireless, and sensor-based technology holds potential for the detection of MCI in older adults as they perform daily tasks. However, some limits are discussed and we offer recommendations to improve the usefulness of this innovative approach.

摘要

背景

当怀疑存在轻度认知障碍时,功能评估至关重要,但诸如问卷调查等常用评估工具缺乏敏感性。一种替代且创新的方法是在基于场景的日常生活工具性活动(IADL)评估期间,在智能公寓中使用传感器技术。然而,研究这种方法的研究很少,并且所使用的技术在医疗环境中并不总是可转换的。

目的

探讨在两种不同的智能环境中使用的简单无线技术,在预测老年人轻度认知障碍(MCI)时,是否能为IADL的表现和基于评分者的测量增加价值。

方法

招募了26名认知健康的老年人(CH)和22名患有MCI的老年人。通过基于传感器的观察(运动、接触和电传感器)和基于表现的测量(根据录像带评分),对一组五个脚本任务中的功能表现进行评估。这五个任务可以按任何顺序执行,并在提供给参与者的指导手册中有详细说明。

结果

基于传感器的观察表明,与CH参与者相比,患有MCI的参与者在厨房以及查看冰箱和厨房橱柜中花费的时间更多。此外,这些测量与参与者的记忆和执行表现呈负相关,并对MCI的预测有显著贡献。

结论

简单、无线且基于传感器的技术在老年人执行日常任务时,具有检测MCI的潜力。然而,讨论了一些局限性,并提出了改进这种创新方法实用性的建议。

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