期刊
SENSORS
卷 20, 期 8, 页码 -出版社
MDPI
DOI: 10.3390/s20082218
关键词
cognitive frailty; motoric cognitive risk syndrome; wearable; cognitive impairment; telehealth; remote patient monitoring; digital health
资金
- National Institutes of Health/National Institute on Aging [1R42AG060853-01]
- National Institutes of Health/National Cancer Institute [1R21CA190933-01A1]
- Center for Innovations in Quality, Effectiveness and Safety at the Michael E. DeBakey Veterans Affairs Medical Center, Houston, TX [CIN 13-413]
- Big Data-Scientist Training Enhancement Program (BD-STEP) at the Department of Veterans Affairs
- National Cancer Institute
Physical frailty together with cognitive impairment (Cog), known as cognitive frailty, is emerging as a strong and independent predictor of cognitive decline over time. We examined whether remote physical activity (PA) monitoring could be used to identify those with cognitive frailty. A validated algorithm was used to quantify PA behaviors, PA patterns, and nocturnal sleep using accelerometer data collected by a chest-worn sensor for 48-h. Participants (N = 163, 75 +/- 10 years, 79% female) were classified into four groups based on presence or absence of physical frailty and Cog: PR-Cog-, PR+Cog-, PR-Cog+, and PR+Cog+. Presence of physical frailty (PR-) was defined as underperformance in any of the five frailty phenotype criteria based on Fried criteria. Presence of Cog (Cog-) was defined as a Mini-Mental State Examination (MMSE) score of less than 27. A decision tree classifier was used to identify the PR-Cog- individuals. In a univariate model, sleep (time-in-bed, total sleep time, percentage of sleeping on prone, supine, or sides), PA behavior (sedentary and light activities), and PA pattern (percentage of walk and step counts) were significant metrics for identifying PR-Cog- (p < 0.050). The decision tree classifier reached an area under the curve of 0.75 to identify PR-Cog-. Results support remote patient monitoring using wearables to determine cognitive frailty.
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