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Article

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

1
VA HSR&D, Center for Innovations in Quality, Effectiveness and Safety, Michael E. DeBakey VA Medical Center, Houston, TX 77030, USA
2
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 protected] (M.A.)
3
Department of Medicine, Baylor College of Medicine, Houston, TX 77030, USA
4
South Central Mental Illness Research, Education and Clinical Center (MIRECC), Houston, TX 77030, USA
*
Author to whom correspondence should be addressed.
Sensors 2018, 18(5), 1336; https://doi.org/10.3390/s18051336
Received: 12 March 2018 / Revised: 18 April 2018 / Accepted: 24 April 2018 / Published: 26 April 2018
(This article belongs to the Special Issue Sensors for Gait, Posture, and Health Monitoring)
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. View Full-Text
Keywords: frailty; pre-frail; wearable sensor; physical activity; sedentary behavior; moderate-to-vigorous activity; steps frailty; pre-frail; wearable sensor; physical activity; sedentary behavior; moderate-to-vigorous activity; steps
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MDPI and ACS Style

Razjouyan, J.; Naik, A.D.; Horstman, M.J.; Kunik, M.E.; Amirmazaheri, M.; Zhou, H.; Sharafkhaneh, A.; Najafi, B. Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study. Sensors 2018, 18, 1336. https://doi.org/10.3390/s18051336

AMA Style

Razjouyan J, Naik AD, Horstman MJ, Kunik ME, Amirmazaheri M, Zhou H, Sharafkhaneh A, Najafi B. Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study. Sensors. 2018; 18(5):1336. https://doi.org/10.3390/s18051336

Chicago/Turabian Style

Razjouyan, Javad, Aanand D. Naik, Molly J. Horstman, Mark E. Kunik, Mona Amirmazaheri, He Zhou, Amir Sharafkhaneh, and Bijan Najafi. 2018. "Wearable Sensors and the Assessment of Frailty among Vulnerable Older Adults: An Observational Cohort Study" Sensors 18, no. 5: 1336. https://doi.org/10.3390/s18051336

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