Development and Validation of Delirium Recognition Using Computer Vision in Neuro-critical Patients

Sponsor
Beijing Tiantan Hospital
Study ID
NCT07136207
Status
Recruiting
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Conditions

  • Artificial Intelligence (AI)
  • Delirium

Eligibility Criteria

Sex
ALL
Age
18 Years - 80 Years
Healthy Volunteers
Not accepted

Study Details

This research project employs machine learning algorithms integrated with computer vision, image processing, and pattern recognition technologies to perform digital analysis of facial expression behaviors in neurocritical care patients with delirium. By constructing multidimensional high-level features of delirium, the investigators have established a classification model based on behavioral. The primary objective of this study is to address the critical challenge of achieving precise and efficient delirium diagnosis in neurologically critically ill patients through automated facial expression behavior recognition.

Key Dates

First listed
Aug 22, 2025
Start date
Aug 30, 2025
Status verified
Aug 2025
Primary completion
Dec 30, 2025
Completion
Jan 30, 2026

Study Design

Enrollment
1,000 participants (estimated)

Arms

  • Arm: Neurocritical non-delirium patients
    For neurocritical non-delirium patients, the investigators record facial expression videos, which are used during model development to compare with the facial expressions of delirium patients.
  • Arm: Neurocritical delirium patients
    The investigators record facial expression videos of neurocritical delirium patients and perform frame sampling on the videos to analyze and extract the facial expression features specific to delirium. Based on this analysis, the investigators develop a model for delirium recognition in neurocritical patients.

Primary Outcome Measure

Accuracy of the delirium prediction model [ Time Frame: Through study completion, an average of 1 year ]

Central Contacts

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