@文章{信息:doi/10.2196/43777，作者=“David, Michael C B和Kolanko, Magdalena和Del Giovane, Martina和Lai, Helen和True, Jessica和Beal, Emily和Li, Lucia M和Nilforooshan, Ramin和Barnaghi, Payam和Malhotra, Paresh A和Rostill, Helen和Wingfield, David和Wilson, Danielle和Daniels, Sarah和Sharp, David J和Scott, Gregory”，标题=“痴呆症患者的生理学远程监测:《一项观察性队列研究》，期刊=“JMIR衰老”，年=“2023”，月=“3”，日=“9”，卷=“6”，页=“e43777”，关键词=“痴呆;远程监控;生理学;物联网;警报;监控;技术;检测;血压; support; feasibility; system; quality of life", abstract="Background: Internet of Things (IoT) technology enables physiological measurements to be recorded at home from people living with dementia and monitored remotely. However, measurements from people with dementia in this context have not been previously studied. We report on the distribution of physiological measurements from 82 people with dementia over approximately 2 years. Objective: Our objective was to characterize the physiology of people with dementia when measured in the context of their own homes. We also wanted to explore the possible use of an alerts-based system for detecting health deterioration and discuss the potential applications and limitations of this kind of system. Methods: We performed a longitudinal community-based cohort study of people with dementia using ``Minder,'' our IoT remote monitoring platform. All people with dementia received a blood pressure machine for systolic and diastolic blood pressure, a pulse oximeter measuring oxygen saturation and heart rate, body weight scales, and a thermometer, and were asked to use each device once a day at any time. Timings, distributions, and abnormalities in measurements were examined, including the rate of significant abnormalities (``alerts'') defined by various standardized criteria. We used our own study criteria for alerts and compared them with the National Early Warning Score 2 criteria. Results: A total of 82 people with dementia, with a mean age of 80.4 (SD 7.8) years, recorded 147,203 measurements over 958,000 participant-hours. The median percentage of days when any participant took any measurements (ie, any device) was 56.2{\%} (IQR 33.2{\%}-83.7{\%}, range 2.3{\%}-100{\%}). Reassuringly, engagement of people with dementia with the system did not wane with time, reflected in there being no change in the weekly number of measurements with respect to time (1-sample t-test on slopes of linear fit, P=.45). A total of 45{\%} of people with dementia met criteria for hypertension. People with dementia with $\alpha$-synuclein--related dementia had lower systolic blood pressure; 30{\%} had clinically significant weight loss. Depending on the criteria used, 3.03{\%}-9.46{\%} of measurements generated alerts, at 0.066-0.233 per day per person with dementia. We also report 4 case studies, highlighting the potential benefits and challenges of remote physiological monitoring in people with dementia. These include case studies of people with dementia developing acute infections and one of a person with dementia developing symptomatic bradycardia while taking donepezil. Conclusions: We present findings from a study of the physiology of people with dementia recorded remotely on a large scale. People with dementia and their carers showed acceptable compliance throughout, supporting the feasibility of the system. Our findings inform the development of technologies, care pathways, and policies for IoT-based remote monitoring. We show how IoT-based monitoring could improve the management of acute and chronic comorbidities in this clinically vulnerable group. Future randomized trials are required to establish if a system like this has measurable long-term benefits on health and quality of life outcomes. ", issn="2561-7605", doi="10.2196/43777", url="https://aging.www.mybigtv.com/2023/1/e43777", url="https://doi.org/10.2196/43777", url="http://www.ncbi.nlm.nih.gov/pubmed/36892931" }