Design and Development of Multi-modal Intelligent Anesthesia Monitoring System

Capital Medical University

Status: Completed

Conditions: Anesthesia

Treatments: Diagnostic Test: Multi-modal Intelligent Anesthesia Monitoring System

Study type: Observational

Funder types: Other

Identifiers

NCT06317025

SHOUFA2022-2Z-2039

Details and patient eligibility

About

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.

Enrollment: 330 patients

Sex: All

Ages: Under 85 years old

Volunteers: No Healthy Volunteers

Inclusion criteria

1. Age: 0-65 years old
2. ASA: Level I-III
3. Patients undergoing non cardiac surgery under general anesthesia
4. Informed consent of the patient or legal representative

Exclusion criteria

1. Previous history of severe neurological disorders
2. History of mental illness and related medication use
3. Individuals who are unable to cooperate in completing cognitive function tests
4. Severe hearing or visual impairment
5. Preoperative delirium in patients
6. Individuals who have experienced severe adverse reactions such as cardiac arrest and cardiopulmonary resuscitation during surgery
7. Those who require neurosurgery, head and facial surgery
8. Individuals who are allergic to EEG and fNIRS electrodes

Trial design

330 participants in 1 patient group

General anaesthetic patient

Description:

Monitoring depth of anaesthesia using PRST （P：pressure， T：tear，R：rate， S：sweat）score developed by Evans and bispectral index

Treatment:

Diagnostic Test: Multi-modal Intelligent Anesthesia Monitoring System