Design and Development of Multi-modal Intelligent Anesthesia Monitoring System

Not yet recruiting

• Conditions: Anesthesia
• Interventions: Diagnostic Test: Multi-modal Intelligent Anesthesia Monitoring System

• Registration Number: NCT06317025
• Lead Sponsor: Beijing Chao Yang Hospital

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.

Detailed Description

Not available

Study Timeline

• Study First Submitted: 2024-02-21
• Status Verified: 2024-03
• Study First Submitted QC: 2024-03-17
• Last Update Submitted: 2024-03-17
• Study First Posted: 2024-03-19
• Last Update Posted: 2024-03-19
• Study Start: 2024-05
• Primary Completion: 2025-12
• Study Completion: 2025-12

Recruitment & Eligibility

• Status: NOT_YET_RECRUITING
• Sex: All
• Target Recruitment: 330

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

Study & Design

• Study Type: OBSERVATIONAL
• Study Design: Not specified

Arm && Interventions

Group	Intervention	Description
General anaesthetic patient	Multi-modal Intelligent Anesthesia Monitoring System	Monitoring depth of anaesthesia using PRST （P：pressure， T：tear，R：rate， S：sweat）score developed by Evans and bispectral index

Primary Outcome Measures

Name	Time	Method
the depth of anesthesia (too deep or too shallow)	During general anesthesia	PRST score system, combined with BIS index for comprehensive judgment

Secondary Outcome Measures

Name	Time	Method
Characteristics of perioperative neurovascular coupling	Perioperative	EEG power and entropy indexes are extracted by moving window method as new time series, and a new time series consistent with NIRS is constructed. The entropy and power of different frequency bands after resampling were used as the indexes of neural activity, and ΔHbO and ΔHb were selected as the indexes of hemodynamic activity. The neurovascular coupling was evaluated by calculating the coherence of neural activity and hemodynamic activity.
EEG characteristics of loss of consciousness induced by different general anesthesia drugs	During general anesthesia	Spectral Analysis，Connectivity Analysis，Brain Networks Analysis