NCT05545397

Sedation Level on Machine Learning With Electroencephalogram in Painless Gastroenteroscopy Patients

Sedation Level Estimation Based on Machine Learning of Quantitative Occipital Electroencephalogram Features in Gastroenteroscopy Patients

• Status: Unknown
• Phase: —
• Study type: Observational
• Enrollment: 50 (estimated)
• Sponsor: General Hospital of Ningxia Medical University · Academic / Other
• Sex: All
• Age: 18 Years – 65 Years
• Healthy volunteers: Accepted

Summary

Painless endoscopy technology can make patients comfortable under anesthesia, but because of the painless inside.The diagnosis and treatment time of endoscopic examination is short, and the transport is fast. Anesthesia related wind such as deep breathing depression and hypoxemia will occurRisks.Eeg depth monitoring can assist anesthesiologists to evaluate the depth of anesthesia and reduce the risk. Artificial intelligence is adopted.There are few reports on the evaluation of anesthesia depth and drug dosage by electroencephalogram (EEG) monitoring in outpatient patients with painless gastroenteroscopy.

Detailed description

1.examination, and establish brainClassification model of electrogram and sedation depth;2. The EEG characteristics, basic information and propofol were administered to all patients.The dose model of propofol painless gastroenteroscopy was established by machine learning to guide anesthesia Drug use;3. Evaluate the time and space complexity of the model, build the model, and assist the anesthesiologist to individualize the patient Chemical, safe and comfortable management.

Conditions

• Gastritis

Interventions

Type	Name	Description
DRUG	Propofol	And pump propofol at a rate of 600ml/h. The degree of sedation was assessed by the MOAA/S scale until the depth sadation of the patient during the monitor of EEG
DEVICE	EEG montior	And pump propofol at a rate of 600ml/h. The degree of sedation was assessed by the MOAA/S scale until the depth sadation of the patient during the monitor of EEG

Timeline

• Start date: 2022-09-15
• Primary completion: 2022-11-30
• Completion: 2022-12-31
• First posted: 2022-09-19
• Last updated: 2022-09-21

Locations

1 site across 1 country: China

Regulatory

• FDA-regulated drug study
• FDA-regulated device study