Intelligent Intensive Care Unit

Summary

Participation Requirements

Description

The aim of the study is to assess the potential of using motion and facial expression data to detect delirium in ICU patients by comparing motion and facial expression patterns in delirium and control groups. In this study, the investigators will use ActiGraph accelerometers to record each subject's...

The aim of the study is to assess the potential of using motion and facial expression data to detect delirium in ICU patients by comparing motion and facial expression patterns in delirium and control groups. In this study, the investigators will use ActiGraph accelerometers to record each subject's movement patterns. Also, a processed video using a commercially available camera interfaces with a specialized program to identify patient facial expressions and movement patterns. A total of 60 participants will be enrolled with delirium, and 30 patients without delirium will be used as control group. Motion profiles will be compared in the motorically defined subgroups (hyperactive, hypoactive, normal) based on accelerometer and facial recognition data. Then, differences in facial expression, number of changes in postures, and percentage of time spent moving will be compared between motorically defined subgroups and in delirium and control groups. EMR data will also be used to assess the feasibility of detecting delirium by including additional information on related risk factors.

Tracking Information