Ai Anesthesia Depth

In clinical studies of EEG signaling, profound changes in EEG signals from waking to general anesthesia were accompanied by brain spontaneous electrical activity. The investigator propose to evaluate the depth of anesthesia with the EEG signal. The important feature is the gradual deepening of anesthesia EEG signal as follows: 1. Disorganized high-frequency signal activity occurs; 2. The frequency and amplitude of EEG signals become more regular, especially in the δ -wave frequency band; 3. The frequency mixing of low frequency band and high frequency band occurs, and δ -wave activity occurs under deep anesthesia; 4. The anesthesia deepens, and the burst suppression signal appears. The deeper the anesthesia, the longer the suppression period will be; 5. Equipotential activity will occur at the end.

Therefore, the researchers analyzed various processing methods of EEG signals, and according to the characteristics of EEG signals in the process of anesthesia, finally obtained the quantitative index of evaluating the depth of anesthesia, so as to quantitatively evaluate the depth of anesthesia.

Basic principle of Ai anesthesia depth index: Ai anesthesia awareness index is based on multiple indicators such as frequency, double frequency, time domain and complexity.Multivariate statistical methods were used to quantify the brain waves from the awake to the deepest anesthetic state.

Ai Anesthesia Depth一Advantage

High-performance EEG signal extraction

EEG signal acquisition requires the characteristics of a high co-mode inhibition ratio, high input impedance, and low noise.The design of EEG acquisition system mainly includes sensor electrode, front protection and defibrillation circuit, forward following circuit, EEG EMG filter circuit, baseline fast recovery circuit.

EEG post amplifier circuit, power supply, electrode impedance detection, high precision AD data acquisition, to ensure EEG signal extraction, system noise less than 5 uV, co-mode suppression ratio greater than 120dB.

Algorithm engine

Ai measurement technology has a special positive parameter calculation function. Through the time domain calculation and spectrum analysis of EEG signal, the signal quality index, EMG power and outbreak suppression ratio are calculated through the judgment of signal quality.

Big data models such as each band spectrum parameters and outbreak inhibition ratio are used to obtain Ai anesthesia depth index.

Integrated sensor design

Adopt disposable sensor design, using flexible PCB cable and electrode to adopt integrated design, add special intelligent certification technology, ensure that the EEG sensor matches the machine use, limit the use time to ensure the signal quality in the use process.And using the independently developed conductivity electrode.

with high performance conductive effect and very small contact impedance, to ensure the quality of the signal acquisition.

Powerful clinical validation database

In the process of establishing the clinical database, through a large number of clinical trials compared with international manufacturers BIS, Narcotrend and other manufacturers during the operation, the Ai algorithm has good characteristics, strong pertinence, good consistency and reliability in the anesthesia process, which is a reliable guarantee for the evaluation of the anesthesia depth index in clinic.

The following are a large number of statistical indicators of AI and BIS obtained under clinical verification, and the results show that the Ai index and the BIS index have significant consistency.