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

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 fr...

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Main Authors: Javad Razjouyan, Aanand D. Naik, Molly J. Horstman, Mark E. Kunik, Mona Amirmazaheri, He Zhou, Amir Sharafkhaneh, Bijan Najafi
Format: Article
Language:English
Published: MDPI AG 2018-04-01
Series:Sensors
Subjects:
Online Access:http://www.mdpi.com/1424-8220/18/5/1336
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spelling doaj-cfdd2389bdf9475695c13af4b74773312020-11-24T20:56:05ZengMDPI AGSensors1424-82202018-04-01185133610.3390/s18051336s18051336Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort StudyJavad Razjouyan0Aanand D. Naik1Molly J. Horstman2Mark E. Kunik3Mona Amirmazaheri4He Zhou5Amir Sharafkhaneh6Bijan Najafi7VA HSR&amp;D, Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX 77030, USAVA HSR&amp;D, Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX 77030, USAVA HSR&amp;D, Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX 77030, USAVA HSR&amp;D, Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX 77030, USAInterdisciplinary Consortium on Advanced Motion Performance (iCAMP), Division of Vascular Surgery and Endovascular Therapy, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, One Baylor Plaza, MS: BCM390, Houston, TX 77030, USA; Mona <email>Amirmazaheri@bcm.edu</email> (M.A.)Interdisciplinary Consortium on Advanced Motion Performance (iCAMP), Division of Vascular Surgery and Endovascular Therapy, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, One Baylor Plaza, MS: BCM390, Houston, TX 77030, USA; Mona <email>Amirmazaheri@bcm.edu</email> (M.A.)Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USAInterdisciplinary Consortium on Advanced Motion Performance (iCAMP), Division of Vascular Surgery and Endovascular Therapy, Michael E. DeBakey Department of Surgery, Baylor College of Medicine, One Baylor Plaza, MS: BCM390, Houston, TX 77030, USA; Mona <email>Amirmazaheri@bcm.edu</email> (M.A.)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.http://www.mdpi.com/1424-8220/18/5/1336frailtypre-frailwearable sensorphysical activitysedentary behaviormoderate-to-vigorous activitysteps
collection DOAJ
language English
format Article
sources DOAJ
author Javad Razjouyan
Aanand D. Naik
Molly J. Horstman
Mark E. Kunik
Mona Amirmazaheri
He Zhou
Amir Sharafkhaneh
Bijan Najafi
spellingShingle Javad Razjouyan
Aanand D. Naik
Molly J. Horstman
Mark E. Kunik
Mona Amirmazaheri
He Zhou
Amir Sharafkhaneh
Bijan Najafi
Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study
Sensors
frailty
pre-frail
wearable sensor
physical activity
sedentary behavior
moderate-to-vigorous activity
steps
author_facet Javad Razjouyan
Aanand D. Naik
Molly J. Horstman
Mark E. Kunik
Mona Amirmazaheri
He Zhou
Amir Sharafkhaneh
Bijan Najafi
author_sort Javad Razjouyan
title Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study
title_short Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study
title_full Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study
title_fullStr Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study
title_full_unstemmed Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study
title_sort wearable sensors and the assessment of frailty among vulnerable older adults: an observational cohort study
publisher MDPI AG
series Sensors
issn 1424-8220
publishDate 2018-04-01
description 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.
topic frailty
pre-frail
wearable sensor
physical activity
sedentary behavior
moderate-to-vigorous activity
steps
url http://www.mdpi.com/1424-8220/18/5/1336
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