CN109620217A - A kind of epilepsy sample brain power detection circuit - Google Patents
A kind of epilepsy sample brain power detection circuit Download PDFInfo
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- CN109620217A CN109620217A CN201910044973.8A CN201910044973A CN109620217A CN 109620217 A CN109620217 A CN 109620217A CN 201910044973 A CN201910044973 A CN 201910044973A CN 109620217 A CN109620217 A CN 109620217A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/369—Electroencephalography [EEG]
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- A61B5/7225—Details of analog processing, e.g. isolation amplifier, gain or sensitivity adjustment, filtering, baseline or drift compensation
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
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Abstract
The invention discloses a kind of epilepsy sample brain power detection circuits, including analog wavelet filter 1, analog wavelet filter 2, delay circuit 1, delay circuit 2, full-wave rectifier 1, full-wave rectifier 2, switching circuit 1, switching circuit 2, comparator 1, comparator 2 and subtracter.EEG signals obtain the wavelet coefficient of two scales by two analog wavelet filters；The difference of analog wavelet filter output signal absolute value is obtained using full-wave rectifier and subtracter, is finally compared with given threshold, to determine the time of epilepsy sample waveform appearance, realizes the automatic detection of epilepsy sample brain electricity.The present invention has many advantages, such as that detection accuracy is high, and can be realized by analog circuit devices at full hardware, is very suitable to low-voltage, the realization of low-power consumption large scale integrated circuit, can be applied to the processing of biomedical signals fields such as epilepsy sample brain electro-detection.
Description
Technical field
The present invention relates to epilepsy sample brain power detection circuits, belong to the EEG Processing technical field of epilepsy.
Background technique
Epilepsy is the second largest the nervous system disease in the world today, is short caused by the electric discharge of cerebral neuron paroxysmal abnormality
Temporary property cerebral disorder.EEG signals (EEG) are always the key tool of Diagnosis of Epilepsy for a long time.Studies have shown that epilepsy
The EEG of patient will appear the epilepsys sample waveform such as spike or the slow complex wave of spine-, therefore the epilepsy sample wave of EEG signals in epileptic attack interphase
Shape detects the main method for having become epilepsy clinical diagnosis.EEG signals belong to non-stationary signal, and have a large amount of back
Scape noise and interference, therefore traditional Fourier transformation is difficult to meet the application requirement of epilepsy sample brain electro-detection.Wavelet transformation overcomes
The deficiency of Fourier transformation and Short Time Fourier Transform, all has excellent localization analytical characteristics in time domain and frequency domain, non-
The often analysis and processing suitable for transient signals such as EEG, meets the needs of epilepsy sample brain electro-detection is to detection accuracy.Meanwhile small echo
The computation complexity of transformation is not high, and the basic circuits module such as filter can be used and carry out devices at full hardware realization, suitable for low-power consumption
Application demand.In consideration of it, wavelet transformation is widely used in the epilepsy sample brain electro-detection of wearable dynamic EEG system.Currently,
The hardware circuit implementation of wavelet transformation is broadly divided into numeric type and analogue type two major classes.Due to needing A/D conversion equipment, small echo becomes
The digital circuit changed has the shortcomings that power consumption is higher, it is difficult to meet wearable electronic equipment and the application of low-power consumption is wanted
It asks.In this context, the analog circuit implementation method of wavelet transformation gradually attracts attention.
Summary of the invention
In order to overcome the shortcomings of existing epilepsy sample brain electro-detection digital circuit, the present invention provides a kind of new based on simulation
The epilepsy sample brain power detection circuit of technology.The present invention has low computation complexity and can be fully hard under the premise of meeting detection accuracy
The characteristics of part is realized, can be measured in real time EEG under conditions of low-power consumption, and it is wearable, just to be suitable for miniaturization, low power consuming
Take the application demand of formula electronic product.
The technical solution adopted by the present invention to solve the technical problems is: filtering including analog wavelet filter 1, analog wavelet
Wave device 2, delay circuit 1, delay circuit 2, full-wave rectifier 1, full-wave rectifier 2, switching circuit 1, switching circuit 2, comparator
1, comparator 2 and subtracter.
In above-mentioned epilepsy sample brain power detection circuit, the detection process is as follows:
Step 1: EEG signals carry out scale a respectively1=0.015, a2=0.1 continuous wavelet transform, after taking absolute value
Obtain the wavelet coefficient absolute value of corresponding scale | W1| and | W2|。
Step 2: given threshold T1And T2, when meeting following two condition simultaneously, EEG signals detected
For epilepsy sample signal:
(1)a1Wavelet coefficient absolute value when=0.015 | W1| it is greater than predetermined threshold T1, it may be assumed that | W1|>T1。
(2)a1=0.015 and a2The difference of the wavelet coefficient absolute value of=0.1 two scale is greater than predetermined threshold T2, it may be assumed that | W1
|-|W2|>T2。
In above-mentioned epilepsy sample brain power detection circuit, the input terminal of the analog wavelet filter 1 and analog wavelet filter 2
It is connected with input EEG signals, the input terminal as epilepsy sample brain power detection circuit；
The input terminal of subtracter is accessed to after the concatenation of analog wavelet filter 1 full-wave rectifier 1 through switching circuit 1；
The input terminal of subtracter is accessed to after the concatenation full-wave rectifier 2 of analog wavelet filter 2 through delay circuit 1.Analog wavelet filtering
Device 1 realizes scale a1=0.015 wavelet transformation, analog wavelet filter 2 realize scale a2=0.1 wavelet transformation.
The comparator 1 is by the output of full-wave rectifier 1 and predetermined threshold T1It is compared, the output control of comparator 1
Switching circuit 1；Comparator 2 is by the output of subtracter and predetermined threshold T2It is compared, the output control switch circuit of comparator 2
2。
The output of full-wave rectifier 2 is postponed τ by the delay circuit 11The input terminal of subtracter is accessed afterwards, wherein τ1=
0.06s；Delay circuit 2 will input EEG signals and postpone τ2Switching circuit 2 is accessed afterwards, wherein τ2=0.4s.
The output end of the switching circuit 2 is the output end of epilepsy sample brain power detection circuit.
5, in above-mentioned epilepsy sample brain electric-examination method of determining and calculating, the biography of the analog wavelet filter 1 and analog wavelet filter 2
Delivery function H1(s) and H2(s) it is respectively:
Wherein, H1(s) realize EEG signals in scale a1=0.015 continuous wavelet transform, H2(s) EEG signals are realized
In scale a2=0.1 continuous wavelet transform, the type of wavelet transformation are the transformation of Mexico's hat wavelet.
The technical effects of the invention are that: the invention proposes a kind of epilepsy sample brain power detection circuits, compare existing brain electricity
Signal detecting method, the present invention reduce computation complexity while guaranteeing detection accuracy, and can be fully hard by analog circuit
Part realizes have many advantages, such as that EEG detection accuracy is high, design process is simple, be suitable for low-voltage, low-power consumption large-scale integrated, can answer
For processing of biomedical signals fields such as epilepsy sample brain electro-detections.
The present invention is further illustrated with reference to the accompanying drawings and examples.
Detailed description of the invention
In order to illustrate the technical solution of the embodiments of the present invention more clearly, required use in being described below to embodiment
Attached drawing be briefly described, it should be apparent that, drawings in the following description are only some embodiments of the invention, for this
For the those of ordinary skill of field, without any creative labor, it can also be obtained according to these attached drawings other
Attached drawing.
Fig. 1 is epilepsy sample brain power detection circuit；
Fig. 2 (a) is the circuit structure of analog wavelet filter；
Fig. 2 (b) is the circuit structure for realizing operation transconductance amplifier in Fig. 2 (a)；
Fig. 3 is the full-wave rectifier based on the connection of grid cross-coupling；
Fig. 4 (a) is switching capacity delay cell, and Fig. 4 (b) is clock waveform；
Fig. 5 is the circuit structure of subtracter；
Fig. 6 is the circuit structure of voltage comparator.
Specific embodiment
The present embodiment provides a kind of epilepsy sample brain power detection circuits as shown in Figure 1, including analog wavelet filter 1, simulation
Wavelet filter 2, delay circuit 1, delay circuit 2, full-wave rectifier 1, full-wave rectifier 2, switching circuit 1, switching circuit 2,
Comparator 1, comparator 2 and subtracter.
The impulse response of analog wavelet filter 1 is Mexico's hat wavelet function, and corresponding wavelet transform dimension is
a1=0.015.Wherein, the transmission function of analog filter 1 is obtained by approximate algorithm, design procedure are as follows:
1, the rational approximations fraction of the mother wavelet function of Mexico's hat wavelet is obtained by approximate algorithm；
2, it by removing method for normalizing, goes the wavelets approximation function that the first step obtains to be normalized to scale 0.015, be passed
Delivery function is
The impulse response of analog wavelet filter 2 is Mexico's hat wavelet function, and corresponding wavelet transform dimension is
a2=0.1.Wherein, the transmission function of analog filter 2 is obtained by approximate algorithm, design procedure are as follows:
1, the rational approximations fraction of the mother wavelet function of Mexico's hat wavelet is obtained by approximate algorithm；
2, it by removing method for normalizing, goes the wavelets approximation function that the first step obtains to be normalized to scale 0.1, be transmitted
Function is
Input EEG signals can respectively obtain scale a by above-mentioned two analog wavelet filter1=0.015 and scale a2
=0.1 wavelet coefficient, can circuit structure as shown in Figure 2 realize.
In the circuit structure of analog wavelet filter shown in Fig. 2 (a), g1~g6And C1~C6Realize point of transmission function
Mother, ga1~ga6Realize that the molecule of transmission function, output voltage pass through feedback network and g1~g6Inverting input terminal be connected.If small
The general type of wave filter transmission function are as follows:
The topological relation of (a) according to fig. 2 can obtain the relational expression of each circuit parameter in Fig. 2 (a):
τ1=B1,τ2=B2/B1,τ2=B3/B2,τ3=B3/B2,τ4=B4/B3,τ5=B5/B4,τ6=B6/B5,
τj=Cj/gj, j=1,2...6
It, can be by g in order to facilitate circuit design1~g6Mutual conductance be set as identical value, utilize each parameters relationship of above formula
Solve the other parameters in Fig. 2 (a).
Therefore, according to H1(s) and H2(s) coefficient of denominator and molecule in utilizes the relational expression of above-mentioned Fig. 2 (a) circuit parameter
Scale a can be solved respectively1=0.015 and a2=0.1 wavelet filter circuit parameter.
Operation transconductance amplifier g in Fig. 2 (a)1~g6、ga1~ga6It can be realized by Fig. 2 (b), wherein transistor M1And M2For
Input difference pair, breadth length ratio having the same are used to input voltage VIN1And VIN2It is converted into electric current；Transistor M3、M4And crystal
Pipe M5、M6Two current mirroring circuits are constituted, and breadth length ratio is identical two-by-two.It, can be real when all transistors all work in weak inversion regime
Existing transconductance value is gmOperation transconductance amplifier, and
Wherein n is subthreshold value slope factor, UTFor thermal voltage, and UT=kT/q.
To realize the operation to take absolute value to wavelet coefficient, using as shown in Figure 3 based on the complete of grid cross-coupling connection
Wave rectifier handles wavelet coefficient.The transistor of two Main Branches is all cross-coupling connection type in circuit.At half week
In phase, electric current flows through M2、M3, and in another half cycle, electric current flows through M1、M4, the combination of four metal-oxide-semiconductors make input all-wave it is whole
The voltage of stream device is exported with same direction, realizes the effect to take absolute value to signal.
Fig. 4 (a) is switching capacity delay cell, and Fig. 4 (b) is clock waveform.Transistor M1Connect input voltage, transistor
M4Connect output voltage, transistor M1And M4Breadth length ratio having the same；Transistor M2And M3Composition current mirroring circuit, and the two
Breadth length ratio is identical.Switch S1It is realized by single NMOS transistor, switch S2The transmission gate being made of NMOS and PMOS transistor is real
It is existing.In phaseSwitch S1Closure, input voltage are sampled；In phaseSwitch S2NMOS transistor conducting, PMOS is brilliant
The shutdown of body pipe.For a complete clock, delay time caused by delay cell shown in Fig. 4 is τ=2T (1-D)
Wherein D is duty ratio, and T is the clock cycle, and adjusting T can be changed delay time T.For example, setting duty ratio D is
50%, frequency f=50Hz, the delay time that can obtain delay cell is 20ms, when can be realized any by cascaded delay
Between delay.Two delay circuits of the present invention are delayed 0.06s and 0.4s respectively, can by 3 delay cells of cascade and
20 delay cells are cascaded to realize.
Fig. 5 is a subtracter, wherein M1~M3Realize bias current；M4And M5For input difference pair, it is used to that electricity will be inputted
Press VIN1And VIN2It is converted into electric current；M8And M9Current mirror is formed, difference current is converted into M10On Single-end output electric current；Difference
To M6And M7Realize output voltage, i.e.,
VOUT=VIN1-VIN1
Subtracter is by scale a1=0.015 wavelet coefficient absolute value | W1| with scale a2=0.1 wavelet coefficient absolute value
|W2| subtract each other, by with predetermined threshold T2Comparison complete epilepsy sample brain electricity detection.
Fig. 6 is voltage comparator, wherein transistor M1~M6Difference preamplifier is constituted, input voltage is amplified,
Improve the sensitivity of comparator, disconnecting switch noise simultaneously.Transistor M7~M11Latch cicuit is constituted, is the core of comparator,
The size of two input signals can be compared.Transistor M13~M20Output buffer is constituted, is mainly put including self biased differential
Big device and phase inverter.Voltage comparator 1 is by scale a1=0.015 wavelet coefficient absolute value | W1| with predetermined threshold T1Compared
Compared with, can primarily determine epilepsy sample waveform occur time；Voltage comparator 2 is by subtracter treated signal and predetermined threshold T2
Compare, realizes the interference in removal EEG signals, reduce the false detection rate of epilepsy sample brain power detection circuit, increase detection accuracy.
The above is only a preferred embodiment of the present invention, the specific embodiment is merely used to help understand the present invention
Core concept.It should be pointed out that for those skilled in the art, without departing from the principle of the present invention,
Can be with several improvements and modifications are made to the present invention, these improvement and modification also belong to the protection model of the claims in the present invention
It encloses.
Claims (4)
1. a kind of epilepsy sample brain power detection circuit, it is characterised in that: including analog wavelet filter 1, analog wavelet filter 2, prolong
Slow circuit 1, delay circuit 2, full-wave rectifier 1, full-wave rectifier 2, switching circuit 1, switching circuit 2, comparator 1, comparator 2
And subtracter.
2. epilepsy sample brain power detection circuit according to claim 1, it is characterised in that: the detection of epilepsy sample brain electricity can be achieved,
Detection process is as follows:
Step 1: EEG signals carry out scale a respectively1=0.015 and a2=0.1 continuous wavelet transform obtains after taking absolute value
The wavelet coefficient absolute value of corresponding scale | W1| and | W2|。
Step 2: given threshold T1And T2, when meeting following two condition simultaneously, EEG signals detected are epilepsy
Sample signal:
(1)a1Wavelet coefficient absolute value when=0.015 | W1| it is greater than predetermined threshold T1, it may be assumed that | W1|>T1。
(2)a1=0.015 and a2The difference of the wavelet coefficient absolute value of=0.1 two scale is greater than predetermined threshold T2, it may be assumed that | W1|-|W2
|>T2。
3. epilepsy sample brain power detection circuit according to claim 1, it is characterised in that:
The input terminal of the analog wavelet filter 1 and analog wavelet filter 2 is connected with input EEG signals, as epilepsy sample
The input terminal of brain power detection circuit；
The input terminal of subtracter is accessed to after the concatenation of analog wavelet filter 1 full-wave rectifier 1 through switching circuit 1；Simulation
The input terminal of subtracter is accessed to after the concatenation full-wave rectifier 2 of wavelet filter 2 through delay circuit 1.Analog wavelet filter 1 is real
Existing scale a1=0.015 wavelet transformation, analog wavelet filter 2 realize scale a2=0.1 wavelet transformation.
The comparator 1 is by the output of full-wave rectifier 1 and predetermined threshold T1It is compared, the output control switch electricity of comparator 1
Road 1；Comparator 2 is by the output of subtracter and predetermined threshold T2It is compared, the output control switch circuit 2 of comparator 2.
The output of full-wave rectifier 2 is postponed τ by the delay circuit 11The input terminal of subtracter is accessed afterwards, wherein τ1=0.06s；
Delay circuit 2 will input EEG signals and postpone τ2Switching circuit 2 is accessed afterwards, wherein τ2=0.4s.
The output end of the switching circuit 2 is the output end of epilepsy sample brain power detection circuit.
4. epilepsy sample brain power detection circuit according to claim 1, it is characterised in that: analog wavelet filter 1 and simulation are small
The transfer function H of wave filter 21(s) and H2(s) it is respectively:
Wherein, H1(s) realize EEG signals in scale a1=0.015 continuous wavelet transform, H2(s) realize EEG signals in ruler
Spend a2=0.1 continuous wavelet transform, the type of wavelet transformation are the transformation of Mexico's hat wavelet.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114376584A (en) * | 2020-10-06 | 2022-04-22 | 蔡鸿文 | Brain-computer interface device with multiple channels |
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| CN101243972A (en) * | 2008-03-10 | 2008-08-20 | 湖南大学 | Logarithm field simulation wavelet converting circuit for detecting electrocardiosignal QRS wave |
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| CN104887224A (en) * | 2015-05-29 | 2015-09-09 | 北京航空航天大学 | Epileptic feature extraction and automatic identification method based on electroencephalogram signal |
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| CN101243972A (en) * | 2008-03-10 | 2008-08-20 | 湖南大学 | Logarithm field simulation wavelet converting circuit for detecting electrocardiosignal QRS wave |
| US20140358025A1 (en) * | 2013-05-29 | 2014-12-04 | Keshab K. Parhi | System and apparatus for seizure detection from EEG signals |
| CN104887224A (en) * | 2015-05-29 | 2015-09-09 | 北京航空航天大学 | Epileptic feature extraction and automatic identification method based on electroencephalogram signal |
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| ALEXANDER J. CASSON ETC.: "An analogue bandpass filter realisation of the Continuous Wavelet Transform", 《2007 29TH ANNUAL INTERNATIONAL CONFERENCE OF THE IEEE ENGINEERING IN MEDICINE AND BIOLOGY SOCIETY》 * |
| WENSHAN ZHAO ETC.: "Realization of wavelet transform using switched-current filters", 《ANALOG INTEGRATED CIRCUITS AND SIGNAL PROCESSING》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN114376584A (en) * | 2020-10-06 | 2022-04-22 | 蔡鸿文 | Brain-computer interface device with multiple channels |
| US11755058B2 (en) | 2020-10-06 | 2023-09-12 | National Taiwan University Of Science And Technology | Brain-computer interface device with multiple channels |
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