Pervasive Sensing and AI in Intelligent ICU

Part of paid clinical trials in Gainesville, Florida.

Sponsor
University of Florida
Study ID
NCT05127265
Status
Recruiting
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Conditions

  • Confusion
  • Critical Illness
  • Delirium
  • Pain

Eligibility Criteria

Sex
ALL
Age
18 Years - N/A
Healthy Volunteers
Not accepted

Interventions

  • Video Monitoring — OTHER
    continuous video monitoring
  • Accelerometer Monitoring — OTHER
    continuous accelerometer monitoring of patient movements
  • Noise Level Monitoring — OTHER
    continuous environmental noise monitoring
  • Light Level Monitoring — OTHER
    continuous environmental light monitoring
  • Air Quality Monitoring — OTHER
    continuous environmental air quality monitoring
  • EKG Monitoring — OTHER
    continuous EKG monitoring
  • Vitals Monitoring — OTHER
    continuous vitals monitoring (heart rate, oxygen saturation)
  • Biosample Collection — OTHER
    blood and urine samples collected once on Day 1 and once on Day 2
  • Delirium Motor Subtyping Scale 4 (DMSS-4) — OTHER
    done daily on delirious patients to subtype delirium

Study Details

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.

Key Dates

Start date
May 24, 2021
Status verified
Jun 2025
Primary completion
Dec 31, 2026
Completion
Dec 31, 2026

Study Design

Enrollment
400 participants (estimated)

Arms

  • Arm: adult ICU patients
    adult patients aged 18 or older admitted to University of Florida Health Shands Gainesville ICU wards

Primary Outcome Measure

Algorithmic Activity Labeling [ Time Frame: Image frames collected continuously for up to 7 days maximum. ]

Central Contacts

Locations (1)

FacilityCityStateZIPSite coordinators
University of Florida Health Shands HospitalGainesvilleFlorida32610
Andrea Davidson, BS
[email protected]
352-294-8723
Azra Bihorac, MD, MS (PRINCIPAL_INVESTIGATOR)

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