Fundamental Intelligent Building Blocks of the Intensive Care Unit (ICU) of the Future: Intelligent ICU of the Future

The objective of this project is to create deep learning and machine learning models capable of recognizing patient visual cues, including facial expressions such as pain and functional activity. Many important details related to the visual assessment of patients, such as facial expressions like pain, head and extremity movements, posture, and mobility are captured sporadically by overburdened nurses or are not captured at all. Consequently, these important visual cues, although associated with critical indices, such as physical functioning, pain, and impending clinical deterioration, often cannot be incorporated into clinical status. The study team will develop a sensing system to recognize facial and body movements as patient visual cues. As part of a secondary evaluation method the study team will assess the models ability to detect delirium.

ICU Patients: Inclusion Criteria: * patient admitted to University of Florida (UF) Health Gainesville ICU Exclusion Criteria: * Anticipated ICU stay is less than one day * Patient is on any form of contact precaution or isolation * Patient is unable to wear a Shimmer3 unit ICU Patient Friends/Family: Inclusion Criteria: * Individual has their name designated on a patient's informed consent form giving them permission to view and modify facial and activity data collected about that patient Exclusion Criteria: * Age \< 18 * They are unable to answer short questions on a touch screen display * They are unable to wear a proximity sensor * They were not on the listed of designated individuals specified in their friend/family members informed consent form