4.6 Article

Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study

期刊

SENSORS
卷 18, 期 5, 页码 -

出版社

MDPI
DOI: 10.3390/s18051336

关键词

frailty; pre-frail; wearable sensor; physical activity; sedentary behavior; moderate-to-vigorous activity; steps

资金

  1. National Institute of Health/National Institute of Aging [2R42AG032748-04]
  2. U.S. Department of Veterans Affairs, Veterans Health Administration, Health Services Research and Development Service
  3. Big Data-Scientist Training Enhancement Program (BD-STEP)

向作者/读者索取更多资源

Background: The geriatric syndrome of frailty is one of the greatest challenges facing the U.S. aging population. Frailty in older adults is associated with higher adverse outcomes, such as mortality and hospitalization. Identifying precise early indicators of pre-frailty and measures of specific frailty components are of key importance to enable targeted interventions and remediation. We hypothesize that sensor-derived parameters, measured by a pendant accelerometer device in the home setting, are sensitive to identifying pre-frailty. Methods: Using the Fried frailty phenotype criteria, 153 community-dwelling, ambulatory older adults were classified as pre-frail (51%), frail (22%), or non-frail (27%). A pendant sensor was used to monitor the at home physical activity, using a chest acceleration over 48 h. An algorithm was developed to quantify physical activity pattern (PAP), physical activity behavior (PAB), and sleep quality parameters. Statistically significant parameters were selected to discriminate the pre-frail from frail and non-frail adults. Results: The stepping parameters, walking parameters, PAB parameters (sedentary and moderate-to-vigorous activity), and the combined parameters reached and area under the curve of 0.87, 0.85, 0.85, and 0.88, respectively, for identifying pre-frail adults. No sleep parameters discriminated the pre-frail from the rest of the adults. Conclusions: This study demonstrates that a pendant sensor can identify pre-frailty via daily home monitoring. These findings may open new opportunities in order to remotely measure and track frailty via telehealth technologies.

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