CN102293639A - Pulse condition signal time domain feature extraction method - Google Patents
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- 238000000034 method Methods 0.000 claims description 44
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- 230000002123 temporal effect Effects 0.000 claims description 9
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- 238000005259 measurement Methods 0.000 abstract description 3
- 230000008030 elimination Effects 0.000 abstract 1
- 238000003379 elimination reaction Methods 0.000 abstract 1
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- 230000036581 peripheral resistance Effects 0.000 description 2
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- 241000755266 Kathetostoma giganteum Species 0.000 description 1
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Abstract
The invention relates to a pulse condition signal time domain feature extraction method, which belongs to the technical field of pulse condition measurement in the traditional Chinese medical science, and comprises the steps of: carrying out wavelet transformation on collected pulse condition signals, eliminating high-frequency noise, rebuilding signals, and obtaining the pulse condition signals subjected to the high-frequency noise elimination; extracting base lines, eliminating base line drift and realizing pulse condition signal preprocessing; calculating first-order derivative of the preprocessed pulse condition signals, finding the maximum value in each section of pulse condition signals and positioning the ascending branch of each estimated pulse condition period; determining the pulse condition period for each section of pulse condition signals; and finding dicrotic notches E and dicrotic waves F. The extraction method can improve the pulse condition signal time domain feature extraction efficiency and accuracy.
Description
Technical field
The invention belongs to the Chinese medicine pulse field of measuring technique, relate to a kind of pulse signal feature extracting method.
Background technology
At present, have in the method for mainly using aspect the temporal signatures extraction of pulse signal: threshold method and extreme point method, smothing filtering and wavelet transformation etc.
Threshold method is meant the span of determining the pulse condition characteristic point according to the maximum of pulse condition waveform and minima, determines the characteristic point of pulse condition waveform again in conjunction with paired extreme point.This threshold method is for having the scope that can not accurately determine characteristic point than the pulse condition of great fluctuation process, and when utilizing the method searching characteristic point of extreme point method simultaneously, operand is bigger, and pulse profile data is not suitable for adopting this kind method more for a long time.
When utilizing the Y-factor method Y of wavelet transformation and zero-crossing method to judge the characteristic point of pulse signal, selected wavelet function may not necessarily adapt to all pulse signals.The zero-crossing method of wavelet transformation can produce a plurality of characteristic points, is unfavorable for accurate identification, should seek to utilize the small echo denoising to reach feature extraction effect preferably.
Summary of the invention
The objective of the invention is to overcome the above-mentioned deficiency of prior art, provide a kind of method that is applicable to that the Chinese medicine pulse signal characteristic extracts, to reach better feature extraction effect.For this reason, the present invention adopts following technical scheme.
A kind of pulse signal temporal signatures extracting method comprises the following steps:
1) pulse signal that collects is carried out wavelet transformation, remove high-frequency noise, and reconstruction signal, obtained removing the pulse signal of high-frequency noise;
2) extract baseline, and remove baseline drift, realize the pretreatment of pulse signal;
3) to asking for first derivative through pretreated pulse signal and finding out maximum in every section pulse signal, locate the upstroke in the pulse condition cycle of each estimation;
4) for every section pulse signal, be starting point with pulse condition upstroke basic point, seek the minima in 1/10 count in the pulse condition cycle account for estimation forward, first minima that finds is pulse condition cycle starting point; Maximum in 1/10 of the pulse condition cycle count backward, first maximum that finds is pulse condition cycle master's crest.
5) determine the pulse condition cycle;
6) be basic point with every section pulse condition end cycle point, in back 2/3 scope in pulse condition cycle, seek dicrotic notch E and dicrotic wave F forward according to the paired extreme point of pulse condition in this scope;
As preferred implementation, in the step 1), the pulse signal that collects is carried out the db8 wavelet transformation, decomposing the number of plies is 14, removes high-frequency noise, and the high frequency coefficient after low frequency coefficient and the processing is rebuild; Step 2) in, according to the pulse condition cycle of estimating with the pulse signal segmentation, takes out horizontal stroke, the vertical coordinate of every section minimum point, the data of taking out are done the third degree curve match, the extraction baseline; In the step 3),, ask for first derivative maximum according to following method for every section pulse signal:
A. find out the maximum of first derivative, be Imax;
B. setting threshold coefficient, and, obtain threshold value Ith with Imax and threshold value multiplication;
C. ask for maximum point i according to following condition:
(1)i＞＝Ith；
(2) i is simultaneously respectively greater than two contiguous 2 contiguous points of point and right side of left side.
The pulse signal temporal signatures extracting method that the present invention proposes, combining segmentation goes baseline and small echo denoising that pulse signal is carried out pretreatment, improved threshold method, and according to each characteristic point at the particular location of pulse condition in the cycle, this characteristic point is sought in proposition in a certain section time range, improved feature extraction efficient and accuracy.
Description of drawings
Fig. 1 primary signal and denoised signal and the local comparison diagram that amplifies thereof (a) and (b) are respectively primary signal and local signal thereof, (c) and (d) are respectively denoised signal and local signal thereof.
The comparison diagram of baseline drift signal is removed in Fig. 2 denoised signal and denoising, and last figure is a denoised signal, and figure below is pretreated pulse signal.
The last figure of Fig. 3 is pretreated pulse signal, and figure below is the first derivative of pulse signal.
Fig. 4 labelling the pulse signal of starting point (*) and main crest (o).
Fig. 5. labelling the pulse signal of dicrotic notch ("+") and dicrotic wave (five-pointed star).
Fig. 6. the dicrotic pulse prewave of pulse signal (with square labelling).
The specific embodiment
Before the present invention will be described, at first introduce various pulse parameter physiology implications:
1. ascending branch: by the ascending curve of baseline, be the fast rapid fire blood period of ventricle in the pulse condition shape to main crest top.
2. descending branch: pushing up a decline curve to baseline by main crest in the pulse condition shape, is that the Ve later stage is to the beginning of cardiac cycle next time.
3. main ripple: the main body wave amplitude of arteries and veins figure, general summit is the summit of arteries and veins figure, reflection intra-arterial pressure and volumetrical maximum.
4. tidal wave: the prewave of fighting of weighing again, be positioned at decent, after the main ripple, generally be lower than main ripple and be higher than dicrotic wave, the reflection left ventricle
Stop to penetrate blood, arteriectasia blood pressure lowering, retrodirective reflection ripple.
5. dicrotic notch: or claim dicrotic wave, be the downward incisura trough that main ripple descending branch and dicrotic wave ascending branch constitute, represent aorta static pressure emptying time, be the separation of heart contraction and diastole.
6. dicrotic wave: being outstanding in a descending branch ascending wave, is aortic valve closing, aorta elasticity retraction ripple.
Introduce the parameters commonly used in the pulse condition measurement and the physiology implication and the measuring method thereof of index below:
(1) time index
1. t: the pulsation period, promptly arteries and veins figure starting point is to the duration of terminal point.The t value is corresponding to a cardiac cycle of left ventricle.
Measuring method: measure U-U ' some interlude.
2. t
1: the ascending branch time, promptly arteries and veins figure starting point is to the duration of main wave crest point.t
1Value is corresponding to the left ventricle phase of maximum ejection.
Assay method: main wave crest point is to vertical line and the intersection point of baseline and the duration between the U point of baseline.
3. t
4: the heart contracts the time, and promptly arteries and veins figure starting point is to the duration between the dicrotic notch.t
4Value is corresponding to the systole of left ventricle.
Measuring method: the dicrotic notch incisura point is to vertical line and the intersection point of baseline and the duration between the U point of baseline.
4. t
5: slow falling the time, promptly dicrotic notch is to the duration between the arteries and veins figure terminal point.t
5Value is corresponding to left ventricular diastolic.
Measuring method: the dicrotic notch incisura point is to vertical line and the intersection point of baseline and the duration between the U ' point of baseline.
5. W: the width at 1/3 place on the main ripple is equivalent to the time that the intra-arterial high pressure level is kept.
Measuring method: earlier push up to the baseline vertical line 1/3 and make a horizontal line (being parallel to baseline) with 2/3 point of interface down and measure the duration that crossing point-to-point transmission is propped up in this horizontal line and the both sides lifting of main ripple again by main crest.
(2) wave amplitude index
1. h
1: main wave height, promptly main crest pushes up the length of perpendicular of arteries and veins figure baseline.h
1Pressure and volume that on behalf of the moving tube wall of systolic period, value bear have reflected left ventricular ejection function and aortic compliance.
Measuring method: measure main crest and push up to the baseline vertical dimension.
2. h
3: the tidal wave height, promptly the tidal wave summit is to the amplitude of arteries and veins figure baseline.h
3Value main reflection arteries tension force and Peripheral resistance state.
Measuring method: tidal wave pushes up the vertical dimension to baseline.
3. h
4: the dicrotic notch height, promptly tremulous pulse Peripheral resistance size is reflected to the amplitude of arteries and veins figure baseline in the dicrotic notch the lowest point.
Measuring method: measure the dicrotic notch minimum point to the vertical dimension between baseline.
4. h
5: the dicrotic wave height, promptly aortic elasticity (compliance) situation is reflected to the amplitude of crossing dicrotic notch the lowest point horizontal base line in the dicrotic wave peak maximum.
Measuring method: measured the distance between two horizontal lines being done in dicrotic pulse crest top and mistake dicrotic notch the lowest point.
(3) angle index: measuring with protractor, is unit with " degree ".
1. α: the angle of climb, or claim the U angle, the angle of main ripple ascending branch and baseline reflects blood vessel elasticity and blood viscosity.
Measuring method: with the U point is angular vertex, measures the number of degrees of ascending branch The initial segment and baseline angle.
2. θ: main wave angle, or claim the P angle, and be the angle of main ripple ascending branch and descending branch, reflect blood vessel elasticity and blood flow state.
Measuring method: with upstroke and the decent prompt drop section extended line of respectively extending, the angles that two extended lines intersect are the θ angle.If the θ angle is flat item person, the numerical value that can not take measurement of an angle, and be " flat-head type angle " with the literal record.
(4) area index: arteries and veins area of pictural surface index has 5.
1. Aa: the systole area is the above area of the systole arteries and veins figure baseline (mm of unit
2).
2. Ab: the relaxing period area is the above area of the relaxing period arteries and veins figure baseline (mm of unit
2).
3. AT: the arteries and veins figure gross area is the above arteries and veins figure of the baseline gross area (mm of unit
2).
Above Aa, Ab and AT can try to achieve by integration, but in real work, also can try to achieve by planimeter or trapezoidal area summation.Wherein, AT, Ab are the basic parameters of being evaluated some index of cardiac function by arteries and veins figure.
4. As: the systole gross area is the systole gross area (mmHgs of unit) that surrounds between lumen of artery pressure and the venous lumen pressure.
5. Ad: the relaxing period gross area is the relaxing period gross area (mmHgs of unit) that surrounds between lumen of artery pressure and the venous lumen pressure.
The computational methods of As and Ad are respectively:
As＝0.04[1/h
1·Aa·(Ps-Pd)+Pd·t
4]
Ad＝0.04[1/h
1·Ab·(Ps-Pd)+Pd·t
5]
Ps, Pd represent left arm brachial artery systolic pressure value and diastolic blood pressure values respectively in the formula.
(5) ratio index: in order to reflect cardiovascular functional status and sphygmogram characteristic better, survey the absolute figure, often get the relative ratio of each parameter except that above, more accurate and sensitive on the physiology implication of reflection arteries and veins figure.
1. h
1/ t
1: the ascending branch slope; 2. h
3/ h
1: the coefficient of tension; 3. h
4/ h
1: resistance coefficient; 4. h
5/ h
1: coefficient of elasticity.
Introduce the preprocess method that the present invention adopts below:
Pulse signal is a kind of weak bioelectrical signals, easily introduces ambient interferences.When gathering, it is tight etc. former thereby cause baseline drift that pulse signal can be subjected to human body respiration, muscle, also can sneak into high-frequency noise simultaneously, therefore will handle baseline drift before pulse signal is carried out feature point extraction, filtering simultaneously or attenuating noise disturb.After pretreatment is finished to pulse signal, extract the pulse signal characteristic information.
Denoising
Adopt small echo to force denoising method, select the db8 small echo for use, decomposing the number of plies is 14, with decomposition obtain high frequency coefficient cD1---cD5 all puts 0, remove high-frequency noise.High frequency coefficient reconstruction with low frequency coefficient and after handling obtains the pulse signal of noise just.
By primary signal with force denoised signal figure and partial, detailed view as can be known, small echo forces denoising method can remove shake in the pulse signal, can not lose the pulse condition Global Information again simultaneously, makes pulse signal more level and smooth, helps the identification and the extraction of characteristic point.The result as shown in Figure 1.
Go baseline drift
Estimating the count m of pulse condition in each cycle earlier, is one section with the m point, for pulse profile data being divided into the N section, take out horizontal stroke, the vertical coordinate of every section minimum point, the data that extract are done the third degree curve match, obtain curvilinear equation f (x), the curve that match obtains is the baseline that extracts.Deduct f (x) with pulse profile data, promptly remove baseline drift, realize the pretreatment of pulse signal.Fig. 2 goes the result of baseline drift for denoising
The present invention extracts following pulse condition characteristic information:
Extract pulse condition cycle t (pulse condition starting point A, pulse condition master crest B)
Whether the periodicity extraction of pulse signal is that the cycle of plurality of continuous in the pulse signal is resolved into the one independently cycle, so that calculate the parameter in each cycle of pulse condition, and investigate with this and to exist pulse frequency uneven.The key of periodicity extraction is accurately to find the initial point position in each cycle.Consider that point in pulse condition slope maximum in the cycle (among Fig. 3 with " * " labelling) is in the pulse condition upstroke stage, so, will through above-mentioned pretreatment to pulse profile data ask first derivative and find out maximum in every segment data (among Fig. 3 with " o " labelling) with threshold method.The method can accurately be located the upstroke of each cycle pulse condition, as shown in Figure 3.
The concrete grammar of finding out the maximum in every segment data with threshold method is as follows:
For every section pulse signal, ask for first derivative maximum according to following method:
A. find out the maximum of first derivative, be Imax;
B. determine threshold value Ith:Ith=0.8*Imax;
C. ask for maximum point i according to following condition:
(1)i＞＝Ith；
(2) i is simultaneously respectively greater than two contiguous 2 contiguous points of point and right side of left side.
To the pulse condition feature point extraction time, calculate with complete pulse condition waveform.With the pulse condition upstroke is basic point, within the specific limits, maximum, minima about the search basic point, maximum is the main crest of pulse condition, minima is the starting point in pulse condition cycle.Pulse condition cycle normal reference value is 0.6-1.0s, and ascending branch time normal reference value is 0.07-0.11s, accounts for 1/10 of the whole pulse condition cycle.Sample frequency is 1562HZ, concludes according to experiment and sums up, and be starting point with pulse condition upstroke basic point, seek the minima in 200 forward, first minima that finds is pulse condition cycle starting point; Seek the maximum in 200 backward, first maximum that finds is pulse condition cycle master's crest, has determined the upstroke time t1 of pulse condition." * " represents pulse condition starting point A among Fig. 4, and " o " represents pulse condition master crest, obtains the difference between each pulse condition starting point, multiply by sample rate, promptly gets each pulse condition cycle, is averaged to get final product again.
Extract dicrotic notch E, dicrotic wave F
When extracting dicrotic notch and dicrotic wave information, be basic point, in back 2/3 scope in pulse condition cycle, seek E and F point forward with every section pulse condition end cycle point.The EF point be according to pulse condition in this scope paired extreme point judge.
F point (among Fig. 5 with the five-pointed star labelling) need satisfy following condition and be:
A) 2 on i point right side increases continuously, and 2 in left side reduces continuously
B) in this a certain scope in some left side, there is corresponding with it minimal point, i.e. the E point
E point (among Fig. 5 with "+" labelling) Rule of judgment is: 2 on i point right side increases continuously, and 2 in left side reduces the information extraction result as shown in Figure 5 continuously.
Extract dicrotic pulse prewave (flex point CD)
In the pulse condition waveform, the how not obvious main broadcaster even of dicrotic pulse prewave (among Fig. 6 with square labelling) is merged fully, therefore when extracting the dicrotic pulse prewave, it is defined as follows:
When a) the dicrotic pulse prewave had tangible waveform, the dicrotic wave height was defined as crest height
B) the dicrotic pulse prewave does not overlap fully with main ripple, but does not have obvious waveform yet, and when occurring with the flex point form, the dicrotic pulse prewave is defined as the flex point between the main ripple and dicrotic notch in the descending branch
When c) the dicrotic pulse prewave overlapped fully with pulse condition master ripple, the dicrotic pulse prewave was defined as the mid point of main ripple and dicrotic notch.
Claims (5)
1. a pulse signal temporal signatures extracting method comprises the following steps:
1) pulse signal that collects is carried out wavelet transformation, remove high-frequency noise, and reconstruction signal, obtained removing the pulse signal of high-frequency noise;
2) extract baseline, and remove baseline drift, realize the pretreatment of pulse signal;
3) to asking for first derivative through pretreated pulse signal and finding out maximum in every section pulse signal, locate the upstroke in the pulse condition cycle of each estimation;
4) for every section pulse signal, be starting point with pulse condition upstroke basic point, seek the minima in 1/10 count in the pulse condition cycle account for estimation forward, first minima that finds is pulse condition cycle starting point; Maximum in 1/10 of the pulse condition cycle count backward, first maximum that finds is pulse condition cycle master's crest.
5) determine the pulse condition cycle;
6) be basic point with every section pulse condition end cycle point, in back 2/3 scope in pulse condition cycle, seek dicrotic notch E and dicrotic wave F forward according to the paired extreme point of pulse condition in this scope.
2. pulse signal temporal signatures extracting method according to claim 1 is characterized in that, in the step 1), the pulse signal that collects is carried out the db8 wavelet transformation, decomposing the number of plies is 14, removes high-frequency noise, and the high frequency coefficient after low frequency coefficient and the processing is rebuild.
3. pulse signal temporal signatures extracting method according to claim 1 is characterized in that step 2) in, according to the pulse condition cycle of estimating with the pulse signal segmentation, take out horizontal stroke, the vertical coordinate of every section minimum point, the data of taking out are done the third degree curve match, extract baseline.
4. pulse signal temporal signatures extracting method according to claim 1 is characterized in that, in the step 3), for every section pulse signal, asks for first derivative maximum according to following method:
A. find out the maximum of first derivative, be Imax;
B. setting threshold coefficient, and, obtain threshold value Ith with Imax and threshold value multiplication;
C. ask for maximum point i according to following condition:
(1)i＞＝Ith；
(2) i is simultaneously respectively greater than two contiguous 2 contiguous points of point and right side of left side.
5. pulse signal temporal signatures extracting method according to claim 1 is characterized in that, also comprises: for every section pulse signal, extract the dicrotic pulse prewave.
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