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Digit Biomark. 2020 Nov 26;4(Suppl 1):100-118. doi: 10.1159/000512208. eCollection 2020 Winter.
3
Eating Behavior in Aging and Dementia: The Need for a Comprehensive Assessment.衰老与痴呆中的饮食行为:全面评估的必要性。
Front Nutr. 2020 Dec 16;7:604488. doi: 10.3389/fnut.2020.604488. eCollection 2020.
4
Relationship between Lower Urinary Tract Dysfunction and Dementia.下尿路功能障碍与痴呆症之间的关系。
Dement Neurocogn Disord. 2020 Sep;19(3):77-85. doi: 10.12779/dnd.2020.19.3.77.
5
Prediction of Mild Cognitive Impairment Using Movement Complexity.基于运动复杂性预测轻度认知障碍
IEEE J Biomed Health Inform. 2021 Jan;25(1):227-236. doi: 10.1109/JBHI.2020.2985907. Epub 2021 Jan 5.
6
Meal Timing, Aging, and Metabolic Health.饮食时间、衰老与代谢健康。
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7
Association between circadian rhythms and neurodegenerative diseases.昼夜节律与神经退行性疾病的关系。
Lancet Neurol. 2019 Mar;18(3):307-318. doi: 10.1016/S1474-4422(18)30461-7. Epub 2019 Feb 12.
8
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J Vis Exp. 2018 Jul 27(137):56942. doi: 10.3791/56942.
9
Circadian Rest-Activity Pattern Changes in Aging and Preclinical Alzheimer Disease.昼夜节律-活动模式在衰老和临床前阿尔茨海默病中的变化。
JAMA Neurol. 2018 May 1;75(5):582-590. doi: 10.1001/jamaneurol.2017.4719.
10
Weekly observations of online survey metadata obtained through home computer use allow for detection of changes in everyday cognition before transition to mild cognitive impairment.通过家用电脑使用获得的在线调查元数据的每周观察,可在向轻度认知障碍转变之前检测到日常认知的变化。
Alzheimers Dement. 2018 Feb;14(2):187-194. doi: 10.1016/j.jalz.2017.07.756. Epub 2017 Oct 26.

非侵入式感应技术可检测出轻度认知障碍患者日常生活中具有生态效度的时空模式。

Unobtrusive Sensing Technology Detects Ecologically Valid Spatiotemporal Patterns of Daily Routines Distinctive to Persons With Mild Cognitive Impairment.

机构信息

Department of Neurology, Oregon Health & Science University (OHSU), School of Medicine, Portland, Oregon, USA.

Oregon Center for Aging & Technology (ORCATECH), OHSU, Portland, Oregon, USA.

出版信息

J Gerontol A Biol Sci Med Sci. 2022 Oct 6;77(10):2077-2084. doi: 10.1093/gerona/glab293.

DOI:10.1093/gerona/glab293
PMID:34608939
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC9536445/
Abstract

BACKGROUND

The ability to capture people's movement throughout their home is a powerful approach to inform spatiotemporal patterns of routines associated with cognitive impairment. The study estimated indoor room activities over 24 hours and investigated relationships between diurnal activity patterns and mild cognitive impairment (MCI).

METHODS

One hundred and sixty-one older adults (26 with MCI) living alone (age = 78.9 ± 9.2) were included from 2 study cohorts-the Oregon Center for Aging & Technology and the Minority Aging Research Study. Indoor room activities were measured by the number of trips made to rooms (bathroom, bedroom, kitchen, living room). Trips made to rooms (transitions) were detected using passive infrared motion sensors fixed on the walls for a month. Latent trajectory models were used to identify distinct diurnal patterns of room activities and characteristics associated with each trajectory.

RESULTS

Latent trajectory models identified 2 diurnal patterns of bathroom usage (high and low usage). Participants with MCI were more likely to be in the high bathroom usage group that exhibited more trips to the bathroom than the low-usage group (odds ratio [OR] = 4.1, 95% CI [1.3-13.5], p = .02). For kitchen activity, 2 diurnal patterns were identified (high and low activity). Participants with MCI were more likely to be in the high kitchen activity group that exhibited more transitions to the kitchen throughout the day and night than the low kitchen activity group (OR = 3.2, 95% CI [1.1-9.1], p = .03).

CONCLUSIONS

The linkage between bathroom and kitchen activities with MCI may be the result of biological, health, and environmental factors in play. In-home, real-time unobtrusive-sensing offers a novel way of delineating cognitive health with chronologically-ordered movement across indoor locations.

摘要

背景

能够捕捉人们在家中的活动情况,是一种了解与认知障碍相关的日常活动时空模式的有力方法。本研究估计了 24 小时内的室内房间活动,并调查了日间活动模式与轻度认知障碍(MCI)之间的关系。

方法

本研究纳入了来自两个研究队列(俄勒冈老龄化技术中心和少数族裔老龄化研究)的 161 名独居老年人(26 名患有 MCI,年龄=78.9±9.2 岁)。通过进出房间的次数(浴室、卧室、厨房、客厅)来测量室内房间活动。使用固定在墙上的被动红外运动传感器检测一个月内进出房间(过渡)的次数。使用潜在轨迹模型来识别不同的日间房间活动模式和与每个轨迹相关的特征。

结果

潜在轨迹模型确定了两种浴室使用的日间模式(高使用和低使用)。患有 MCI 的参与者更有可能处于高浴室使用组,与低使用组相比,他们去浴室的次数更多(优势比[OR] = 4.1,95%置信区间[CI] [1.3-13.5],p =.02)。对于厨房活动,确定了两种日间模式(高活动和低活动)。患有 MCI 的参与者更有可能处于高厨房活动组,与低厨房活动组相比,他们在白天和晚上去厨房的次数更多(OR = 3.2,95% CI [1.1-9.1],p =.03)。

结论

浴室和厨房活动与 MCI 之间的联系可能是生物、健康和环境因素共同作用的结果。家庭内实时、非侵入性的感应提供了一种新颖的方法,可以通过按时间顺序排列的室内位置的运动来描绘认知健康状况。