Activity monitoring and heart rate variability as indicators of fall risk: Proof-of-concept for application of wearable sensors in the acute care setting

Javad Razjouyan, Gurtej Singh Grewal, Cindy Rishel, Sairam Parthasarathy, Jane Mohler, Bijan Najafi

Research output: Research - peer-reviewArticle

Abstract

Growing concern for falls in acute care settings could be addressed with objective evaluation of fall risk. The current proof-of-concept study evaluated the feasibility of using a chest-worn sensor during hospitalization to determine fall risk. Physical activity and heart rate variability (HRV) of 31 volunteers admitted to a 29-bed adult inpatient unit were recorded using a single chest-worn sensor. Sensor data during the first 24-hour recording were analyzed. Participants were stratified using the Hendrich II fall risk assessment into high and low fall risk groups. Univariate analysis revealed age, daytime activity, nighttime side lying posture, and HRV were significantly different between groups. Results suggest feasibility of wearable technology to consciously monitor physical activity, sleep postures, and HRV as potential markers of fall risk in the acute care setting. Further study is warranted to confirm the results and examine the efficacy of the proposed wearable technology to manage falls in hospitals.

LanguageEnglish (US)
Pages53-62
Number of pages10
JournalJournal of Gerontological Nursing
Volume43
Issue number7
DOIs
StatePublished - Jul 1 2017

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Heart Rate
Posture
Thorax
Exercise
Technology
Feasibility Studies
Inpatients
Volunteers
Sleep
Hospitalization

ASJC Scopus subject areas

  • Gerontology

Cite this

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abstract = "Growing concern for falls in acute care settings could be addressed with objective evaluation of fall risk. The current proof-of-concept study evaluated the feasibility of using a chest-worn sensor during hospitalization to determine fall risk. Physical activity and heart rate variability (HRV) of 31 volunteers admitted to a 29-bed adult inpatient unit were recorded using a single chest-worn sensor. Sensor data during the first 24-hour recording were analyzed. Participants were stratified using the Hendrich II fall risk assessment into high and low fall risk groups. Univariate analysis revealed age, daytime activity, nighttime side lying posture, and HRV were significantly different between groups. Results suggest feasibility of wearable technology to consciously monitor physical activity, sleep postures, and HRV as potential markers of fall risk in the acute care setting. Further study is warranted to confirm the results and examine the efficacy of the proposed wearable technology to manage falls in hospitals.",
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