Development and Validation of Delirium Recognition Using Computer Vision in Neuro-critical Patients
Research on Delirium Recognition in Neurocritical Patients Based on Facial Expression Behavior Patterns
Beijing Tiantan Hospital
1,000 participants
Aug 30, 2025
OBSERVATIONAL
Conditions
Summary
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.
Eligibility
Inclusion Criteria3
- Neurocritical patients admitted to the ICU, including postoperative neurosurgical patients, stroke patients, and those receiving ICU care due to other neurological conditions.
- Age over 18 years.
- Signed informed consent.
Exclusion Criteria5
- Age under 18 years.
- Persistent coma (GCS ≤ 8) within 7 days pre- and post-surgery, making delirium assessment impossible.
- Did not survive more than 24 hours in the ICU.
- Patients with facial paralysis, post-traumatic facial disfigurement, or other conditions that could significantly affect facial recognition.
- Exclusion of patients with severe dementia, Parkinson's disease, depression, or other conditions that might impact facial emotional expressions.
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Locations(1)
View Full Details on ClinicalTrials.gov
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NCT07136207