Related Experiment Video
Updated: Dec 26, 2025
Home-Based Monitor for Gait and Activity Analysis
Published on: August 8, 2019
Role of Wearable Accelerometer Devices in Delirium Studies: A Systematic Review
Anis Davoudi1,2, Todd M Manini3, Azra Bihorac2,4
1Crayton Pruitt Family Department of Biomedical Engineering, University of Florida, Gainesville, FL.
Abstract:
We sought to determine the feasibility of using wearable accelerometer devices for determining delirium effects on patients' physical activity patterns and detecting delirium and delirium subtype.
Data Sources:
PubMed, Embase, and Web of Science.
Study Selection:
Screening was performed using predefined search terms to identify original research studies using accelerometer devices for studying physical activity in relation to delirium.
Data Extraction:
Key data were extracted from the selected articles.
Data Synthesis:
Among the 14 studies identified, there were a total of 315 patients who wore accelerometer devices to record movements related to delirium. Eight studies (57.1%) used accelerometer devices to compare the activity of delirious and nondelirious patients. Delirious patients had lower activity levels, lower restlessness index, higher number of daytime immobility minutes, lower mean activity levels during the day, and higher mean activity levels at night. Delirious patients also had lower actual sleep time, lower sleep efficiency, fewer nighttime minutes resting, fewer minutes resting over 24 hours, and smaller change in activity from day to night. Six studies (42.9%) evaluated the feasibility of using accelerometer devices for detection of delirium and its subtype. Variables including number of postural changes during daytime, frequency of ultrashort, short, and continuous movements were significantly different among the nondelirium and the three delirium subtypes.
Conclusions:
The results from the studies using accelerometer devices in studying delirium demonstrate that accelerometer devices can potentially detect the differences between delirious and nondelirious patients, detect delirium, and determine delirium subtype. We suggest the following directions as the next steps for future studies using accelerometer devices for predicting delirium: benchmark studies with longer data collection, larger and more diverse population size, incorporating related factors (e.g., medications), and evaluating delirium subtype and severity.
