CN103637798A - DOA (depth of anesthesia) monitoring device - Google Patents

Abstract

The invention discloses a DOA (depth of anesthesia) monitoring device which comprises an EEG (electroencephalogram) collecting electrode, a pre-arrangement module, a Fourier transform module, an Ac (activity of cortex) calculation module, an As (activity of subcortex) calculation module, a balanced DOA calculation module and a display module, wherein the pre-arrangement module comprises a pre-amplification module and an analog-digital conversion module which are connected sequentially; the Ac calculation module receives output data of the Fourier transform module and calculates subparameters of Ac; the As calculation module receives output data of the Fourier transform module and calculates subparameters of As; the balanced DOA calculation module receives subparameters output by the Ac calculation module and the As calculation module and obtains a balanced DOA with a weighted sum method; and the display module displays the balanced DOA. On the premise that the DOA monitoring accuracy in the state of pure inhalation or intravenous general anesthetics is reserved, the DOA monitoring device has the advantage that the DOA monitoring is more accurate in the state of opioid medicine composite inhalation or intravenous general anesthetics.

Description

A kind of anesthesia depth monitor

Technical field

The present invention relates to a kind of anesthesia depth monitor.

Background technology

Anesthesia depth monitoring is the important process content that guarantees anesthesia quality.It is the anesthesia composition of core that consciousness disappears, and due to the application of muscle relaxant, vigilance/calmness (Observer ' s Assessment of Alertness/Sedation Scale, OAA/S) so reliable clinical indices of marking cannot be implemented.The isolated arm technology (Isolated forearm technology, IFT) that temporary interruption limbs blood is transported to retain its instruction reaction is as the goldstandard of consciousness monitoring in art, and the restriction that is subject to again the limb ischemia time can not continue to monitor at whole anesthetic stage.

Use the state of consciousness in the general anesthesia of instrument Real-Time Monitoring to become the dream of anaesthetizing doctor.At present existing several anaesthesia deepness monitoring instruments based on brain electric (Electroencephalogram, EEG) of take that bispectral index (Bispectrum, BIS) be representative obtain clinical practice.BIS is at present in wide clinical application and there are many Research Literatures to deliver, along with going deep into of research, discovery is after single anesthesia with propofol or compound opioid drug, although clinical indices is if OAA/S or IFT evaluate patient are under equal depth of anesthesia, BIS monitor draws not identical monitor value.

As Lysakowski reports all fentanyl class medicines, all increase clinical hypnosis effect, but BIS does not reflect.After the auspicious sweet smell of Schmidt report application, BIS can not provide suitable anesthesia depth monitoring.In the research of Lequeux, the auspicious sweet smell of target control 8ng/ml and 1.3mg/ml propofol patient lose consciousness, but BIS=93 is at this moment obviously unreasonable.Although the research of Manyam thinks that remifentanil is added to meeting in Sevoflurane and deepens clinical calmness, BIS is insensitive to the variation of this clinical condition, therefore at heavy opium Sevoflurane, in auspicious fragrant anesthesia, BIS desired value is less than 60, AAI value and is less than 30 and can causes unnecessary dark anesthesia.

The widest three subparameter beta rates for BIS monitor, the speed of clinical practice is synchronous and break out and suppress to calculate single index BIS by weighted sum.Under the anesthesia of single suction or intravenous anesthetic, BIS monitor is reliable at present, but in clinical under the more common compound suction of opioid drug or intravenous anesthetic anesthesia, the monitoring accuracy of the depth of anesthesia of BIS monitor is unsatisfactory.

Inquire into the BIS monitor reason that Monitoring efficiency declines under combined anesthesia, must start with from its internal algorithm.BIS is calculated by subparameters such as beta rate (β ratio), speeds synchronous (SynchFastSlow, SFS).

The computational methods of β ratio are as follows:

$\mathrm{\βratio}=\log \frac{E_{(30~47)}}{E_{(11~20)}}$

In above formula, E _(30～47)the power sum within the scope of 30 to 47Hz, E _(11～20)it is the power sum within the scope of 11 to 20Hz.

The computational methods of SFS are as follows:

First calculate the bispectrum of two specific frequencies:

B（f1,f2）=E(f1)×E(f2)×E ^*(f1+f2)

Calculate again SFS:

$\mathrm{SFS}=\log \frac{B_{(0.5~47)}}{B_{(30~47)}}$

In above formula, B _(0.5～47)be within the scope of 0.5 to 47.0Hz all combination of frequency bispectrums and, B _(30～47)all combination of frequency bispectrum sums within the scope of 40 to 47Hz.Although SFS reflects the phase matched of different frequency composition to a certain extent, be also subject to the significant impact of each frequency content relative power.

Generally speaking, need at present the urgent technical problem solving of those skilled in the art to be: the accuracy that how to improve Depth of Anesthesia under combined anesthesia.

Summary of the invention

Object of the present invention is exactly, in order to address the above problem, to provide a kind of anesthesia depth monitor, and it has under combined anesthesia anesthesia depth monitoring advantage more accurately.

To achieve these goals, the present invention adopts following technical scheme:

An anesthesia depth monitor, comprising:

Eeg signal acquisition electrode;

Preposition module, comprises the pre-amplifying module and the analog-to-digital conversion module that connect successively; Described pre-amplifying module is used for receiving the simulation EEG signals that eeg signal acquisition electrode gathers, and this simulation EEG signals is amplified; Described analog-to-digital conversion module, for receiving the simulation EEG signals after pre-amplifying module amplifies, is converted to digital brain electrical signal by simulation EEG signals;

Fourier transformation module, carries out Fourier transformation for the digital brain electrical signal to after analog-to-digital conversion module conversion; Obtain the performance number of each frequency of EEG signals;

Cortical activity computing module, receives the output data of Fourier transformation module, and realizes the calculating of cortical activity temper parameter;

Activeness computing module under cortex, receives the output data of Fourier transformation module, and realizes the calculating of activeness subparameter under cortex;

Balanced anesthesia depth calculation module, receives the subparameter that under cortical activity computing module and cortex, activeness computing module is exported, by calculating balanced anesthesia depth B DA(Balanced Depth of Anesthesia);

Display module, shows the balanced anesthesia degree of depth.

Described balanced anesthesia depth calculation module, receives the subparameter that under cortical activity computing module and cortex, activeness computing module is exported, and by weighted sum method, calculates balanced anesthesia depth B DA.

The computational methods of described cortical activity temper parameter are as shown in following formula:

${\mathrm{<figure-callout\; id="1"\; label="Ac"\; filenames="HDA0000440009440000023.png"\; state="\{\{state\}\}">Ac</figure-callout>}}_1={\mathrm{\&Sigma;}}_{i=65}^m{E}_i/{\mathrm{\&Sigma;}}_{i=3}^7{E}_i;$

${\mathrm{<figure-callout\; id="2"\; label="Ac"\; filenames="HDA0000440009440000022.png"\; state="\{\{state\}\}">Ac</figure-callout>}}_2={\mathrm{\&Sigma;}}_{i=65}^m{E}_i/{\mathrm{\&Sigma;}}_{i=30}^{47}{E}_i;$

Wherein, Ac ₁and Ac ₂cortical activity temper parameter, E _ibe the electroencephalogram power of iHz frequency, m is the frequency of power spectrum, 65≤m≤95.

Under described cortex, the computational methods of activeness subparameter are as shown in following formula:

${\mathrm{As}}_1={\mathrm{\&Sigma;}}_{i=8}^n{E}_i/{\mathrm{\&Sigma;}}_{i=3}^7{E}_i$

${\mathrm{As}}_2={\mathrm{\&Sigma;}}_{i=8}^n{E}_i/{\mathrm{\&Sigma;}}_{i=30}^{47}{E}_i$

Wherein, As ₁and As ₂activeness subparameter under cortex, E _ibe the electroencephalogram power of iHz frequency, n is the frequency of power spectrum, 8≤n≤30.

Beneficial effect of the present invention:

1 it have in clinical practice anesthesia depth monitoring advantage more accurately under opiates and suction or intravenous anesthetics combined anesthesia the most widely.

2 it retained the accuracy of anesthesia depth monitoring under simple suction or intravenous anesthetics.

3 pre-amplifying modules and analog-to-digital conversion module are advanced near electrode for encephalograms, have shortened the length of analog signal cable, have reduced the interference of environmental electromagnetic wave to faint EEG signals.

Accompanying drawing explanation

Fig. 1 is apparatus structure schematic diagram of the present invention;

Fig. 2 (a) organizes the prenarcotic EEG signals schematic diagram of a routine typical patient for P;

Fig. 2 (b) realizes the EEG signals schematic diagram after disappearing for P organizes a routine typical patient;

Fig. 3 is EEG power spectrum before two groups of anesthesia;

Fig. 4 (a) is the EEG power spectrum after the anesthesia of P group is front and consciousness disappears;

Fig. 4 (b) is the EEG power spectrum after the anesthesia of RP group is front and consciousness disappears;

Fig. 5 is the EEG power spectrum after two groups of consciousness disappear.

The specific embodiment

Below in conjunction with accompanying drawing and embodiment, the invention will be further described.

The structure of embodiment

As shown in Figure 1, a kind of anesthesia depth monitor, comprising: eeg signal acquisition electrode; Preposition module, comprises the pre-amplifying module and the analog-to-digital conversion module that connect successively; Described pre-amplifying module is used for receiving the simulation EEG signals that eeg signal acquisition electrode gathers, and this simulation EEG signals is amplified; Described analog-to-digital conversion module, for receiving the simulation EEG signals after pre-amplifying module amplifies, is converted to digital brain electrical signal by simulation EEG signals; Fourier transformation module, carries out Fourier transformation for the digital brain electrical signal to after analog-to-digital conversion module conversion; Obtain the performance number of each frequency of EEG signals.Cortical activity computing module, receives the output data of Fourier transformation module, and realizes the calculating of cortical activity temper parameter; Activeness computing module under cortex, receives the output data of Fourier transformation module, and realizes the calculating of activeness subparameter under cortex; Balanced anesthesia depth calculation module, the subparameter that receives activeness computing module output under cortical activity computing module and cortex, is balanced depth of anesthesia BDA by weighted sum method, adaptive neural network-fuzzy inference system (ANFIS) or BP neural network algorithm; Display module, shows the balanced anesthesia degree of depth.

Described eeg signal acquisition electrode is connected with pre-amplifying module by the cable of 20 centimeter length; Described analog-to-digital conversion module is connected with Fourier transformation module by 2 meters of long digital signal cables.

Described acquisition electrode according to international 10-20 normal electrode system respectively at reference electrode Fpz, float electrode AT1, and left mastoid process position of sound production.

The gain of described pre-amplifying module is 10000 times, and this amplifier embedded 50Hz notch filter, has avoided the interference of 50Hz power frequency component to faint EEG signal in addition.

Described analog-to-digital conversion module is 16 analog-digital converters, and inversion frequency 1024 times/second is converted to digital brain electrical signal by the simulation EEG signals of pre-amplifying module output.

Described Fourier transformation module is carried out Fourier transformation by the digital brain electrical signal of analog-to-digital conversion module output, and conversion per second once.The original EEG of time-domain signal is converted to the power spectrum of frequency-region signal,

Described cortical activity computing module is according to the spectra calculation cortical activity temper parameter of Fourier transformation module output, calculating per second 1 time.Computational methods are as shown in following formula:

${\mathrm{<figure-callout\; id="1"\; label="Ac"\; filenames="HDA0000440009440000023.png"\; state="\{\{state\}\}">Ac</figure-callout>}}_1={\mathrm{\&Sigma;}}_{i=65}^m{E}_i/{\mathrm{\&Sigma;}}_{i=3}^7{E}_i;$

${\mathrm{<figure-callout\; id="2"\; label="Ac"\; filenames="HDA0000440009440000022.png"\; state="\{\{state\}\}">Ac</figure-callout>}}_2={\mathrm{\&Sigma;}}_{i=65}^m{E}_i/{\mathrm{\&Sigma;}}_{i=30}^{47}{E}_i;$

Wherein, Ac ₁and Ac ₂cortical activity temper parameter, E _ibe the electroencephalogram power of iHz frequency, m is the frequency of power spectrum.

Under described cortex, activeness computing module is according to activeness subparameter under the spectra calculation cortex of Fourier transformation module output, calculating per second 1 time.Computational methods are as shown in following formula:

${\mathrm{As}}_1={\mathrm{\&Sigma;}}_{i=8}^n{E}_i/{\mathrm{\&Sigma;}}_{i=3}^7{E}_i$

${\mathrm{As}}_2={\mathrm{\&Sigma;}}_{i=8}^n{E}_i/{\mathrm{\&Sigma;}}_{i=30}^{47}{E}_i$

Wherein, As ₁and As ₂activeness subparameter under cortex, E _ibe the electroencephalogram power of iHz frequency, n is the frequency of power spectrum.

Described balanced anesthesia depth calculation module is according to the output of activeness computing module under cortical activity computing module and cortex, by weighted sum method, adaptive neural network-fuzzy inference system (ANFIS) or BP neural network algorithm calculated equilibrium depth of anesthesia BDA, calculating per second 1 time.

Display module, shows the balanced anesthesia degree of depth.Renewal per second shows 1 time.

The clinical trial of embodiment

Above-described embodiment is applied to clinical, observes the anesthesia of simple Intravenous anesthetic propofol and the propofol compound remifentanil anesthesia time similarities and differences of EEG power spectrum and the similarities and differences of classical depth of anesthesia index BIS and depth of anesthesia index BDA of the present invention.

Select department of general surgery intend the descending U.S. anesthesia preoperative assessment classification I-II of the doctors'associations level of choosing date for operation of general anesthesia, age 18-65 year patient's 40 examples.Patient is assigned to propofol group (P group) and remifentanil combined propofol group (RP group) at random.Every group of each 20 examples.

Patient lays electrode for encephalograms sheet at left side of head or right side at random according to international 10-20 normal electrode system after entering operating room, riding position is Fpz(reference electrode), AT1 or AT2(float electrode), with left or right mastoid process (), at opposite side, lay to specifications the special-purpose electrode for encephalograms of BIS monitor, start the present embodiment and BIS monitor collection analysis EEG signals.P organizes not infusion opioid drug remifentanil, and RP is Base Primea syringe pump effective-site target controlled infusion remifentanil (people's good fortune Pharmaceutical, Yichang) for group, and target level is 4ng/ml.Then two groups of patients pass through Base Primea syringe pump effective-site target controlled infusion Intravenous anesthetic propofol, regulate propofol effective-site concentration to make patient reach just the disappear depth of anesthesia of (LOC) of consciousness.Record original electroencephalogram, EEG power spectrum, depth of anesthesia BIS and balance depth of anesthesia BDA now.

Clinical test results

After P organizes a routine typical patient anesthesia forebrain electrical schematic and sees Fig. 2 (a), LOC, Fig. 2 (b) is shown in by EEG signals schematic diagram.EEG oscillogram 2(b after anesthesia front Fig. 2 (a), LOC) there is significant change, but cannot directly to depth of anesthesia, make quantitative analysis according to EEG waveform.

Two groups of prenarcotic basic power spectrum are shown in Fig. 3, and P group represents with solid line, and RP group dots.Can find out, two groups of prenarcotic power spectrum are identical.

The variation of power spectrum, respectively as Fig. 4 (a) and Fig. 4 (b) as shown in, represents with solid line before anaesthetizing before the anesthesia of P group, RP group and after LOC, after LOC, dots.Can find out, the power spectrum after two groups of LOC is all different from before anesthesia.

Power spectrum after two groups of LOC is relatively shown in Fig. 5, and P group represents with solid line, and RP group dots.Can find out, although all enter the depth of anesthesia of LOC in just, the power spectrum after two groups of LOC is not overlapping.Two groups at 3 to 8Hz(θ ripples) with 30Hz to 50Hz(γ ripple) two groups of power spectrum are roughly similar, but under reflection cortex, the power spectrum of 8 to 30Hz frequency range P groups of activeness is greater than RP group.And the power spectrum of 65 to 95Hz frequency range RP groups of reflection cortical activity is greater than P group, although illustrate that two groups all enter the depth of anesthesia of LOC in just, cortex, infracortical active state is different.

Before two groups of anesthesia, after consciousness disappearance, BIS, BDA value all meet normal distribution, in Table 1.

BIS and BDA before table 1 liang group patient anesthesia, after consciousness disappearance

*: between group, relatively have utmost point significant difference (P<0.01).

From the data of table 1, can find out, after consciousness disappears, between group, BIS relatively has utmost point significant difference, illustrates that equal narcotism that BIS can not cause different anesthesia methods makes the assessment of par.BDA there was no significant difference relatively between group after consciousness disappears, illustrates that equal narcotism that BDA can cause different anesthesia methods makes the assessment of par.

The concept of EEG

EEG comes from brain, the electrical activity signal collecting from scalp.It is the good index of reflection brain function.Traditionally EEG is divided into different compositions according to frequency, 1-3.5Hz is called δ ripple, and 4-7Hz is called θ ripple, and 8-13Hz is called α ripple, and 13-30Hz is called β ripple, and 30Hz is called γ ripple above.It is generally acknowledged that low-frequency component is mainly derived from the cortex synchronization that thalamus or thalamus-cortex contact causes as α ripple, radio-frequency component is mainly derived from the spontaneous electric activity of cortex as γ ripple.Common sedative hypnotic and anesthesia all can cause the significant change of EEG, and sedative hypnotic can cause that the radio-frequency component γ ripple of EEG reduces, and low-frequency component α ripple increases, as Fig. 4 (a).This variation may be because sedative hypnotic obviously suppresses corticocerebral spontaneous high frequency waves, and the suppressed lighter or downtrod high frequency waves of thalamus have reduced the decomposition of low frequency wave is made to relative hyperfunction of low frequency wave.

The principle of EEG Depth of Anesthesia

Under narcotism, perusal EEG waveform will find that obvious variation has occurred for it, as shown in Fig. 2 (a) and Fig. 2 (b).But the evaluation depth of anesthesia that cannot quantize from original EEG, therefore anaesthesia deepness monitoring instrument is all that original EEG is converted into several sensitive indicators, be called subparameter, recycling certain weighting or differentiating algorithm is single dimensionless numerical value index by several subparameters unifications, realizes the quantitative evaluation to depth of anesthesia.Anaesthesia deepness monitoring instrument is as BIS, CSI, and Nacotrend etc. are based on this principle.In this principle, the selection of subparameter is the key point of decision systems performance.

BIS value under combined anesthesia and simple anesthesia with propofol is inconsistent

In current various EEG depth of anesthesia index, the clinical practice of BIS is the widest, and clinical research is also the most deep, and early stage research thinks that calmness that BIS and multiple anesthetics cause and behavioristics's measurement of light anaesthesia have dependency.And can when stablizing, anesthesia reflect propofol.General propofol will just can meet clinical needs with other drug Application of composite, has at present many pieces of documents to further investigate the Monitoring efficiency of BIS under combined anesthesia.Found that BIS can not be independent of combined anesthesia and accurate evaluation depth of anesthesia.Lysakowski reports that all fentanyl class medicines all increase clinical hypnosis effect, but BIS does not reflect.After Schmidt report application remifentanil, BIS can not provide suitable anesthesia depth monitoring.In the research of Lequeux, target control 8ng/ml remifentanil and 1.3mg/ml propofol patient lose consciousness, but BIS=93 is at this moment obviously unreasonable.Although the research of Manyam thinks that remifentanil is added to meeting in Sevoflurane and deepens clinical calmness, BIS is insensitive to the variation of this clinical condition, and therefore, in heavy opium anesthesia, BIS desired value is less than 60 can cause unnecessary dark anesthesia.The data of the clinical collection of the present invention also confirm, although compound and not two groups of compound remifentanil all depth of anesthesia is remained on to the level that just loses consciousness, BIS is more shallow by the depth of anesthesia assessment of compound remifentanil group obviously.

Depth of anesthesia is the concentrated expression of active degree under cortex and cortex

The present invention finds it is just to have occurred that consciousness disappears equally, and the EEG power spectrum that P, RP are two groups is different, as shown in Figure 5.It is higher that the EEG of P group (simple anesthesia with propofol) shows as 8 to 30Hz frequency band power, and 65 to 95Hz frequency band power are lower, and that the EEG of RP group (anesthesia of remifentanil combined propofol) shows as 8 to 30Hz frequency band power is low, and 65 to 95Hz frequency band power are higher, and at other frequency ranges (3-8Hz, 30-45Hz), the power spectrum of two groups is overlapping substantially.

the physiology of above-mentioned phenomenon is explained as follows: 8 to the 30Hz frequency ranges of EEG belong to α and β ripple, the cortex synchronization that " pace-making " effect by thalamus or thalamus-cortex contact of being commonly considered as causes causes, 65 to the 95Hz frequency ranges of EEG are commonly considered as that cortex spontaneous discharge forms.The propofol of median dose is stronger to the inhibitory action of cortex, and to thalamus inhibitory action a little less than, so P group shows as the relative hyperfunction of the obvious inhibition of 65 to 95Hz frequency ranges and 8 to 30Hz frequency ranges.And remifentanil is stronger to thalamus, thalamus cortex contact inhibitory action, to cortex inhibitory action a little less than, after remifentanil Application of composite, make in addition to reach the required propofol dosage of LOC less, so the inhibition that shows as 65 to 95Hz frequency ranges of RP group is compared with light and 8 to 30Hz frequency ranges suppress heavier.Generally speaking, postanesthetic consciousness is subject to the double influence of function under function of cortex and cortex, the depth of anesthesia that has just entered LOC state equally, different anesthesia hypodermal layers, infracortical active degree are not identical, and the being quick on the draw property that patient stimulates to external world should be the concentrated expression of active degree under cortex and cortex.

The subparameter of BIS is all to calculate from the frequency range below 47.5Hz, therefore with cortex under the good relationship of activeness, and it is poor with the dependency of cortical activity, the spectral range that BIS selects has just determined that it can not comprehensively react full brain comprehensive anesthesia state, so under different anesthesia methods, although patient may be in identical depth of anesthesia, BIS monitor value is not identical.

The new depth of anesthesia index that not affected by combined anesthesia

From above analysis, gain enlightenment, if the activeness of EEG under overall merit cortex and cortex in anesthesia depth monitoring is just expected to avoid the defect of BIS, improve monitoring adaptability, therefore, the present invention proposes the Ac of main reflection cortex state ₁, Ac ₂as with state under main reflection cortex ₁, As ₂four new subparameters, are then normalized to a single dimensionless numerical value BDA by the method for weighted sum or fuzzy neural network by these subparameters.The checking of being undertaken by clinical data shows, has just entered the moment of LOC patient, and the BDA of simple propofol group and compound remifentanil group does not have difference.

Main Conclusions of the present invention

The present invention has gathered under different anesthesia methods, the EEG of the identical anesthesia degree of depth has also carried out spectrum analysis to it, the similarities and differences of EEG EEG power spectrum under different anesthesia methods have been found out, and according to the physiological foundation of EEG, this similarities and differences are explained, proposed should carry out the assessment of balance to activeness under cortical activity and cortex in anesthesia depth monitoring, and finally set up new depth of anesthesia index BDA.Clinical trial of the present invention shows, BDA can be independent of the compound medication of remifentanil, assess accurately the degree of depth of anesthesia with propofol, discovery of the present invention has improved the accuracy of anesthesia depth monitoring under combined anesthesia, has improved the Clinical practicability of anesthesia depth monitoring.

Symbol description

The full name of initialism Full Name in English Chinese

EEG Electroencephalogram electroencephalogram

β ratio The Ratio of β beta rate

BIS Bispectrum bispectrum

SFS SynchFastSlow speed is synchronous

LOC Loss of Consciousness realizes disappearance

FFT Fast Fourier Transform fast Fourier transform

IFT Isolated Forearm Technology isolates arm technology

Observer’s?Assessment?of?Alertness/Sedation

OAA/S vigilance/calmness scoring

Scale

A _cactivity of Cortex cortical activity

A _sactiveness under Activity of Subcortex cortex

The BDA Balanced Depth of Anesthesia balanced anesthesia degree of depth

Although above-mentioned, by reference to the accompanying drawings the specific embodiment of the present invention is described; but be not limiting the scope of the invention; one of ordinary skill in the art should be understood that; on the basis of technical scheme of the present invention, those skilled in the art do not need to pay various modifications that creative work can make or distortion still in protection scope of the present invention.

Claims (5)

1. an anesthesia depth monitor, is characterized in that, comprising:

Eeg signal acquisition electrode;

Preposition module, comprises the pre-amplifying module and the analog-to-digital conversion module that connect successively; Described pre-amplifying module is used for receiving the simulation EEG signals that eeg signal acquisition electrode gathers, and this simulation EEG signals is amplified; Described analog-to-digital conversion module, for receiving the simulation EEG signals after pre-amplifying module amplifies, is converted to digital brain electrical signal by simulation EEG signals;

Fourier transformation module, carries out Fourier transformation for the digital brain electrical signal to after analog-to-digital conversion module conversion; Obtain the performance number of each frequency of EEG signals.

Cortical activity computing module, receives the output data of Fourier transformation module, and realizes the calculating of cortical activity temper parameter;

Activeness computing module under cortex, receives the output data of Fourier transformation module, and realizes the calculating of activeness subparameter under cortex;

Balanced anesthesia depth calculation module, receives the subparameter that under cortical activity computing module and cortex, activeness computing module is exported, by calculating balanced anesthesia depth B DA;

Display module, shows the balanced anesthesia degree of depth.

2. a kind of anesthesia depth monitor as claimed in claim 1, is characterized in that, the calculating of described balanced anesthesia depth calculation module realizes by weighted sum method, adaptive neural network-fuzzy inference system or BP neural network algorithm.

3. a kind of anesthesia depth monitor as claimed in claim 1, is characterized in that, the computational methods of described cortical activity temper parameter are as shown in following formula:

${\mathrm{Ac}}_1={\mathrm{\&Sigma;}}_{i=65}^m{E}_i/{\mathrm{\&Sigma;}}_{i=3}^7{E}_i;$

${\mathrm{Ac}}_2={\mathrm{\&Sigma;}}_{i=65}^m{E}_i/{\mathrm{\&Sigma;}}_{i=30}^{47}{E}_i;$

Wherein, Ac ₁and Ac ₂cortical activity temper parameter, E _ibe the electroencephalogram power of iHz frequency, m is the frequency of power spectrum.

4. a kind of anesthesia depth monitor as claimed in claim 1, is characterized in that, under described cortex, the computational methods of activeness subparameter are as shown in following formula:

${\mathrm{As}}_1={\mathrm{\&Sigma;}}_{i=8}^n{E}_i/{\mathrm{\&Sigma;}}_{i=3}^7{E}_i$

${\mathrm{As}}_2={\mathrm{\&Sigma;}}_{i=8}^n{E}_i/{\mathrm{\&Sigma;}}_{i=30}^{47}{E}_i$

Wherein, As ₁and As ₂activeness subparameter under cortex, E _ibe the electroencephalogram power of iHz frequency, n is the frequency of power spectrum.

5. a kind of anesthesia depth monitor as claimed in claim 1, it is characterized in that, described balanced anesthesia depth calculation module, receives the subparameter that under cortical activity computing module and cortex, activeness computing module is exported, and by weighted sum method, calculates balanced anesthesia depth B DA.

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