Pervasive Sensing and Artificial Intelligence in Intelligent ICU Subtitles: -Intelligent Intensive Care Unit (I2CU): Pervasive Sensing and Artificial Intelligence for Augmented Clinical Decision-making -ADAPT: Autonomous Delirium Monitoring and Adaptive Prevention

Summary

Important information related to the visual assessment of patients, such as facial expressions, 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, delirious state, and impending clinical deterioration, often cannot be incorporated into clinical status. The overall objectives of this project are to sense, quantify, and communicate patients' clinical conditions in an autonomous and precise manner, and develop a pervasive intelligent sensing system that combines deep learning algorithms with continuous data from inertial, color, and depth image sensors for autonomous visual assessment of critically ill patients. The central hypothesis is that deep learning models will be superior to existing acuity clinical scores by predicting acuity in a dynamic, precise, and interpretable manner, using autonomous assessment of pain, emotional distress, and physical function, together with clinical and physiologic data.

Description

Eligibility

Age range

18+ years

Sex

All

Healthy volunteers

No

Interventions

• Other
  Video Monitoring

  continuous video monitoring

• Other
  Accelerometer Monitoring

  continuous accelerometer monitoring of patient movements

• Other
  Noise Level Monitoring

  continuous environmental noise monitoring

• Other
  Light Level Monitoring

  continuous environmental light monitoring

• Other
  Air Quality Monitoring

  continuous environmental air quality monitoring

• Other
  EKG Monitoring

  continuous EKG monitoring

• Other
  Vitals Monitoring

Location