Design and Development of Multi-modal Intelligent Anesthesia Monitoring System
1 other identifier
observational
330
1 country
1
Brief Summary
This project integrates the characteristics of electroencephalo-graph(EEG), cerebral oxygen, blood pressure, heart rate, etc., based on nonlinear theory and neural oscillation, large sample data and machine learning theory, to develop a multi-modal monitoring system suitable for domestic patients, taking into account changes in sedation, analgesia, cerebral hemodynamics and other factors, regardless of patient age and type of general anesthesia drugs.
Trial Health
Trial Health Score
Automated assessment based on enrollment pace, timeline, and geographic reach
participants targeted
Target at P75+ for all trials
Started Apr 2024
1 active site
Health score is calculated from publicly available data and should be used for screening purposes only.
Trial Relationships
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Study Timeline
Key milestones and dates
First Submitted
Initial submission to the registry
February 21, 2024
CompletedFirst Posted
Study publicly available on registry
March 19, 2024
CompletedStudy Start
First participant enrolled
April 1, 2024
CompletedPrimary Completion
Last participant's last visit for primary outcome
May 1, 2025
CompletedStudy Completion
Last participant's last visit for all outcomes
May 1, 2025
CompletedSeptember 12, 2025
April 1, 2024
1.1 years
February 21, 2024
September 8, 2025
Conditions
Keywords
Outcome Measures
Primary Outcomes (1)
the depth of anesthesia (too deep or too shallow)
PRST score system, combined with BIS index for comprehensive judgment
During general anesthesia
Secondary Outcomes (2)
EEG characteristics of loss of consciousness induced by different general anesthesia drugs
During general anesthesia
Characteristics of perioperative neurovascular coupling
Perioperative
Study Arms (1)
General anaesthetic patient
Monitoring depth of anaesthesia using PRST (P:pressure, T:tear,R:rate, S:sweat)score developed by Evans and bispectral index
Interventions
To evaluate the sensitivity and specificity of self-developed anesthesia monitoring systems in diagnosing the depth of anesthesia (too deep or too shallow)
Eligibility Criteria
Patients undergoing non-cardiac surgery under general anesthesia in Beijing Chaoyang Hospital, Capital Medical University
You may qualify if:
- Age: 0-65 years old
- ASA: Level I-III
- Patients undergoing non cardiac surgery under general anesthesia
- Informed consent of the patient or legal representative
You may not qualify if:
- Previous history of severe neurological disorders
- History of mental illness and related medication use
- Individuals who are unable to cooperate in completing cognitive function tests
- Severe hearing or visual impairment
- Preoperative delirium in patients
- Individuals who have experienced severe adverse reactions such as cardiac arrest and cardiopulmonary resuscitation during surgery
- Those who require neurosurgery, head and facial surgery
- Individuals who are allergic to EEG and fNIRS electrodes
Contact the study team to confirm eligibility.
Sponsors & Collaborators
Study Sites (1)
Department of Anesthesiology, Beijing Chaoyang Hospital, Capital Medical University
Beijing, Beijing Municipality, 100020, China
Study Design
- Study Type
- observational
- Observational Model
- OTHER
- Time Perspective
- PROSPECTIVE
- Sponsor Type
- OTHER
- Responsible Party
- SPONSOR
Study Record Dates
First Submitted
February 21, 2024
First Posted
March 19, 2024
Study Start
April 1, 2024
Primary Completion
May 1, 2025
Study Completion
May 1, 2025
Last Updated
September 12, 2025
Record last verified: 2024-04
Data Sharing
- IPD Sharing
- Will not share