Intelligent Intensive Care Unit

Summary

Delirium, as a common complication of hospitalization, poses significant health problems in hospitalized patients. Though about a third of delirium cases can benefit from intervention, detecting and predicting delirium is still very limited in practice. A common characterization of delirium is change in activity level, causing patients to become hyperactive or hypoactive which is manifested in facial expressions and total body movements. This pilot study is designed to test the feasibility of a delirium detection system using movement data obtained from 3-axis wearable accelerometers and commercially available camera with facial recognition video system in conjunction with electronics medical record (EMR) data to analyze the relation of whole-body movement and facial expressions with delirium.

Conditions

• Delirium
• Confusion

Interventions

BEHAVIORAL

Confusion Assessment Method

Confusion Assessment Method (CAM) score

DEVICE

Accelerometer

3 accelerometers (placed on upper arm, wrist and ankle) and 1 placed on wall as ambient light sensor

DEVICE

Commercially available camera

As part of facial recognition video system

DEVICE

Internet Pod (iPod)

Monitors noise levels in the room

DIAGNOSTIC_TEST

Cortisol Swab

Cortisol level collected through self administered salivary swab

Sponsors & Collaborators

• U.S. National Science Foundation

  collaborator FED

• National Institute for Biomedical Imaging and Bioengineering (NIBIB)

  collaborator NIH

• National Institute of Neurological Disorders and Stroke (NINDS)

  collaborator NIH

• University of Florida

  lead OTHER

Principal Investigators

• Azra Bihorac, MD · University of Florida

Eligibility

Min Age

18 Years

Sex

ALL

Healthy Volunteers

Yes

Timeline & Regulatory

Start

2016-02-29

Primary Completion

2020-03-11

Completion

2028-05-30

Countries

• United States

Study Locations