CN101897578B - Method for segmenting arterial pressure signal by beats - Google Patents

Method for segmenting arterial pressure signal by beats Download PDF

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CN101897578B
CN101897578B CN2010102146086A CN201010214608A CN101897578B CN 101897578 B CN101897578 B CN 101897578B CN 2010102146086 A CN2010102146086 A CN 2010102146086A CN 201010214608 A CN201010214608 A CN 201010214608A CN 101897578 B CN101897578 B CN 101897578B
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point
beat
arterial pressure
local minimum
signal
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CN101897578A (en
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赵明玺
杨力
彭承琳
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Chongqing University
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Abstract

The invention provides a method for segmenting an arterial pressure signal by beats. The method takes vector differences among points as a base feature. The base feature has translational and rotational invariance and can overcome the influence of baseline drift of the arterial pressure signal; logarithmic polar coordinate conversion is performed on the vector differences to measure the similarity of waveforms; and the measurement is sensitive to morphological characteristics of the adjacent waveforms, can capture global contour information of the waveforms at the same time and has robustness on waveform swinging; meanwhile, different weightings are given to waveform characteristics before and after points to be measured respectively so as to weaken the influence of beat tail interference points of the arterial pressure signal on beat initial point identification and further improve the rate of the beat initial point identification; and the method further eliminates the interference points in the arterial pressure signal and avoids segmentation chaos by beats by setting appropriate thresholds. The method can precisely segment the arterial pressure signal by beats and contributes to improving capacities of detecting and analyzing arterial pressure analytical equipment.

Description

A kind of method for dividing arterial pressure signal beat by beat
Technical field
The present invention relates to arterial pressure and detect automatically and analysis technical field, particularly a kind of method for dividing arterial pressure signal beat by beat based on wave character extraction and template matching.
Background technology
Arterial pressure signal is carrying important physiological and pathological information, for example incident of blood flow and reflection, the heart information such as blood function, the elasticity of ductus arteriosus wall and stiffness index of fighting.Arterial pressure signal fluctuates along with heartthrob, it is a kind of paracycle of propagating of signal by shooting in the mode of continuous fluctuation, continuously by shooting in the starting point of each beat representing the arrival of a pulse wave, between two continuous beat starting points is the arterial pressure signal of a complete beat, it is providing important blood pressure information and heartbeat information, and blood pressure that the patient is current and cardiac parameters can be calculated by the arterial signal of a beat.At present, the arterial pressure analytical equipment of Shi Yonging by the arterial pressure signal of the different beats of analysis-by-synthesis, is obtained current blood pressure of patient and cardiac parameters just clinically, thereby detects patient's heart rate, systolic pressure and diastolic pressure.Therefore, for the arterial pressure analytical equipment, the cutting techniques by shooting of arterial pressure signal is very crucial, cut apart by shooting accurately whether, will directly have influence on the quality of arterial pressure analytical equipment to the accuracy of detection of heart rate, systolic pressure and diastolic pressure.
In the cutting techniques by shooting of arterial pressure signal, it is very important and basic that the beat starting point detects, usually the method realization of the cutting apart all by shooting and adopt of arterial pressure signal " detection beat starting point → be that cut-point by shooting cut apart with the beat starting point ".In the prior art, the main beat that adopts plays point detecting method two kinds.A kind of method is to detect the beat starting point by the amplitude size of calculating arterial pressure signal, this method at first utilizes signal autocorrelation or power Spectral Estimation to estimate the approximate cycle of tested arterial pressure signal, it is the power contribution maximum of the frequency correspondence at signal period place, determine the probable ranges of beat starting point then by the approximate cycle, find the point of signal amplitude minimum in this scope, promptly this as a beat starting point in the arterial pressure signal; Other method is to detect the beat starting point by the local minimum point that calculates arterial pressure signal, this method is at first to the arterial pressure signal derivative operation, obtain the extreme point of arterial pressure signal upper derivate for " 0 ", judge further that again these extreme points are maximum point or minimum point, minimum point wherein is the local minimum point of arterial pressure signal; Compare the amplitude of local minimum point at last, the point of amplitude minimum promptly is judged to be the beat starting point.These two kinds of beats play point detecting method, are used for the beat starting point of the arterial pressure signal of detection waveform profile comparison rule, and it still is reasonable detecting effect.But in clinical practice, owing to be subjected to the interaction of incident arteriogram and echo, the waveform profiles of arterial pressure signal can produce variability to a certain degree; Particularly at the wave rear place of each beat, the effect of echo strengthens gradually, and the effect of incidence wave weakens gradually, causes the fluctuation at each beat arterial pressure signal wave rear place violent, and variability strengthens.Therefore, detect in the arterial pressure signal that obtains at clinical practice, the local minimum of some beat wave rear part is the beat starting point of next beat not necessarily.For example, arterial pressure signal as shown in Figure 2, its mid point p 2Be the beat starting point of actual signal beat, some p 1It is the variability noise spot of the last beat wave rear part of this beat starting point; But no matter adopt the method for calculating amplitude still to adopt the method for calculating local minimum point, all can be with noise spot p 1Erroneous judgement is the beat starting point of arterial pressure signal, causes cutting apart by shooting of arterial pressure signal not accurate enough, thereby can have influence on arterial pressure analytical equipment accuracy of detection to heart rate, systolic pressure and diastolic pressure in subsequent process to a certain extent.In addition, feel suffocated, firmly also can cause that the arterial pressure signal generation obviously fluctuates accordingly, particularly actions such as cough, sneeze can cause that more arterial pressure signal produces corresponding violent shake; As if existing such fluctuation or shake to disturb in the arterial pressure signal, it is normal beat starting point that the detection method of employing prior art is easy to some noise spot flase drops are wherein surveyed, and causes the confusion of cutting apart by shooting of arterial pressure signal.
Summary of the invention
At the prior art above shortcomings, the technical problem that the inventive method solved is to improve the accuracy that arterial pressure signal beat by beat is cut apart.This method is applied to help to improve the detection and the analysis precision of computer or arterial pressure signal analytical equipment in computer or the cutting techniques by shooting of arterial pressure analytical equipment to successive arterial pressure signal.
The object of the present invention is achieved like this: a kind of method for dividing arterial pressure signal beat by beat, the arterial pressure signal that the arterial pressure detector is gathered is imported computer, carry out low-pass filtering and sampling pretreatment by computer, then arterial pressure signal is cut apart by shooting, the concrete steps of cutting apart by shooting comprise:
A) set up K mutually different template signal, form the template signal storehouse; Each template signal is the segment signal of each one-period before and after beat starting point in the arterial pressure signal of having discerned, and this segment signal is a N sampled point by sampling or interpolation processing; Wherein, K 〉=2, the span of N is 100～1000;
B) set up N sampled point in each template signal respectively with respect to the log-polar of its beat starting point, and carry out normalized, obtain N sampled point in each template signal with respect to the normalization log-polar of its beat starting point; The computing formula of normalized is as follows:
α k , n = ξ k , n - ξ k , min ξ k , max - ξ k , min ,
Figure BSA00000186984200022
Wherein,
Figure BSA00000186984200023
Be in k the template signal n sampled point with respect to the normalization log-polar of its beat starting point, α K, nBe normalization utmost point footpath,
Figure BSA00000186984200024
Be polar angle; (ξ K, n, ψ K, n) be in k the template signal n sampled point with respect to the log-polar of its beat starting point, ξ K, nBe utmost point footpath, ψ K, nBe polar angle; K ∈ 1,2 ..., K}, n ∈ 1,2 ..., N}; ξ K, maxAnd ξ K, minBe respectively each sampled point in k the template signal maximum and the minima in utmost point footpath in the corresponding log-polar after throwing.
C) for arterial pressure signal to be measured, extracting duration from its starting point is t 0Signal segment as detection segment; Then detection segment is carried out autocorrelation analysis, the interval in the auto-correlation function of calculating detection segment between every adjacent two local maximums is got the approximate cycle of the meansigma methods of described interval as detection segment; Wherein, t 0Span be 30～90s;
D) calculate detection segment rise in from the beginning to ε the doubly approximate cycle place all local minimum points; Wherein, the span of ε is 1.2～1.6;
E) extract the characteristic area of each local minimum point; The characteristic area of each local minimum point is the segment signal in each approximate cycle before and after this local minimum point in the arterial pressure signal to be measured, and this segment signal is a N sampled point by sampling or interpolation processing;
F) set up N sampled point in the characteristic area of each local minimum point respectively with respect to the log-polar of its local minimum point, and carry out normalized, obtain N sampled point in the characteristic area of each local minimum point with respect to the normalization log-polar of this local minimum point; The computing formula of normalized is as follows:
β i , n = ξ i , n - ξ i , min ξ i , max - ξ i , min , γ i，n＝ψ i，n；
Wherein, (β I, n, γ I, n) be in the detection segment the doubly approximate cycle of current ε with the normalization log-polar of n sampled point in the characteristic area of interior i local minimum point with respect to this local minimum point, β I, nBe normalization utmost point footpath, γ I, nBe polar angle; (ξ I, n, ψ I, n) be in the detection segment the doubly approximate cycle of current ε with the log-polar of n sampled point in the characteristic area of interior i local minimum point with respect to this local minimum point, ξ I, nBe utmost point footpath, ψ I, nBe polar angle; N ∈ 1,2 ..., N}; ξ I, minAnd ξ I, minBe respectively in the characteristic area of i local minimum point in the detection segment each sampled point with respect to the maximum and the minima in utmost point footpath in the log-polar of this local minimum point.
G) calculate the characteristic area of each local minimum point and each template signal cross-correlation coefficient respectively, with the similarity of the maximum in the cross-correlation coefficient of the characteristic area of each local minimum point and each template signal as this local minimum point based on the normalization log-polar; The computing formula of described cross-correlation coefficient is:
Figure BSA00000186984200032
And,
Figure BSA00000186984200033
Wherein, P I, kFor current ε in the detection segment doubly is similar to the cycle with the characteristic area of interior i local minimum point and the cross-correlation coefficient of k template signal; (β I, n, γ I, n) be in the detection segment the doubly approximate cycle of current ε with the normalization log-polar of n sampled point in the characteristic area of interior i local minimum point with respect to this local minimum point, β I, nBe normalization utmost point footpath, γ I, nBe polar angle;
Figure BSA00000186984200041
Be in k the template signal n sampled point with respect to the normalization log-polar of its beat starting point, α K, nBe normalization utmost point footpath,
Figure BSA00000186984200042
Be polar angle; K ∈ 1,2 ..., K}, n ∈ 1,2 ..., N}; W pThe expression weight, the span of its weight coefficient λ is 0＜λ＜1;
H) relatively draw the local minimum point of doubly approximate cycle of current ε in the detection segment with interior similarity maximum, and with the similarity and the pre-set threshold C of this local minimum point 0Compare; If its similarity is greater than threshold value C 0, judge that promptly this local minimum point is a beat starting point; Wherein, threshold value C 0Span be 0.2～0.5;
I) be starting point with the doubly approximate cycle of current ε in the detection segment with a local minimum point of interior similarity maximum, calculate thereafter the doubly approximate cycle of ε with interior all local minimums point; Repeating step e then)～i), judge beat starting points all in the detection segment thus;
J) in arterial pressure signal to be measured, be starting point with last beat starting point position in the current detection section, extracting thereafter, duration is t 0Signal segment as new detection segment; And, with the meansigma methods of last 3 normal cycle intervals in the current detection section the approximate cycle as new detection segment; Repeating step d then)～j), judge beat starting points all in the arterial pressure signal to be measured thus;
Described normal cycle interval is meant the interval that is no more than 1.5 times between adjacent two beat starting points and is not less than 0.5 times of current approximate cycle duration;
K) arterial pressure signal to be measured is cut apart by shooting, stored and show arterial pressure signal beat by beat segmentation result to be measured.
As further optimization, described step I) and j) also comprise: i1) if detected beat starting point is above 6 in the current detection section, then obtain the wherein characteristic area of 6 beat starting points of similarity maximum, add in the template signal storehouse as new template signal.
In such scheme, the cut-off frequency of described low-pass filtering is 20～50Hz; The pretreated sample frequency of described pre-sampling is 125～1000Hz.
As further optimization, the preferred value of described N is 200; Described t 0Preferred value be 60s; The preferred value of described ε is 1.5; The preferred value of weight coefficient λ is 0.8 in the described step g), described step h) middle threshold value C 0Preferred value be 0.20.
Compared to existing technology, the present invention has following beneficial effect:
1, as foundation characteristic, this foundation characteristic has translation and rotational invariance to the inventive method, can overcome the influence of the baseline drift of arterial pressure signal with between points difference vector.
2, difference vector is carried out the similarity that log-polar conversion is measured waveform, this tolerance can be caught the overall profile information of waveform simultaneously again to contiguous waveform morphology feature-sensitive, and shake has robustness to waveform.
3, only with the local minimum point in the arterial pressure signal as identification point, ignore calculating and identification to non local minimum point, simplified the data computation amount in the testing process greatly, further improved the robustness of identification.
4, respectively to giving different weights with some wave character afterwards before the local minimum point to be measured, the weight of wave character before weakening a little, strengthen the some weight of wave character afterwards, thereby weaken of the influence of arterial pressure signal beat afterbody noise spot, improve the recognition accuracy of beat starting point the identification of beat starting point.
5, by appropriate thresholds is set, can further effectively get rid of noise spot, further improve the recognition accuracy of beat starting point.
6, owing to the driving mechanism of different beats in the same arterial pressure signal to be measured is similar, similarity each other is than higher; In prioritization scheme, the higher beat starting point place characteristic area of similarity that formerly detects in the arterial pressure signal to be measured is added to new template signal, help accurate judgement in back beat starting point.
7, realized computer to the cutting apart by shooting of arterial pressure signal, and be applicable to use clinically wound method and the detected arterial pressure signal of non-invasive methods arranged.
Description of drawings
Fig. 1 is the FB(flow block) of the inventive method;
Fig. 2 is arterial pressure signal example waveform figure;
Fig. 3 is the cartesian coordinate mapping sketch map of a template signal;
Fig. 4 is sampled point a in the template signal shown in Figure 3 K, nNormalized mapping sketch map in the log-polar territory;
Fig. 5 is template signal A among the embodiment 6Oscillogram;
Fig. 6 is the oscillogram of preceding 15 seconds signals in the first detection segment of arterial pressure signal to be measured among the embodiment;
Fig. 7 is local minimum point s in the signal shown in Figure 6 1And s 2The position;
Fig. 8 is beat starting point s in the signal shown in Figure 6 2And local minimum point s 3, s 4, s 5And s 6The position;
Fig. 9 is beat starting point s in the signal shown in Figure 6 17And local minimum point s 18, s 19, s 20, s 21, s 22And s 23The position;
Figure 10 is each beat starting point position in the signal shown in Figure 6;
Figure 11 is the similarity scattergram of each local minimum point in the signal shown in Figure 6.
The specific embodiment
Below in conjunction with drawings and Examples technical scheme of the present invention is described further:
The present invention proposes a kind of method for dividing arterial pressure signal beat by beat that carries out analysis-by-synthesis in conjunction with the waveform profiles of arterial pressure signal.Corresponding by shooting the heartbeat of arterial pressure signal, and the inherent driving mechanism of each beat is identical, all is the result that tremulous pulse incidence wave and echo combined effect drive, and the waveform of adjacent beat has similarity; If can be measured and mated to similarity, just can find the point similar to the beat starting point, realize that the beat of arterial pressure signal is cut apart.The present invention extracts the point in the arterial pressure signal and the relative position relation of other point on its place waveform, and by its distribution characteristics in the log-polar territory of tolerance, measures the similarity between these points and the beat starting point; Simultaneously, the similarity measurement of point with point is converted into the similarity matching degree of waveform behind log-polar transform at a place measured, the tolerance after the conversion can be caught the overall profile information of waveform simultaneously again to contiguous waveform morphology feature-sensitive.The inventive method is applied to have the identification treatment facility (as possessing arterial pressure analyser, arterial pressure analytical system of computer function etc.) of calculation processing units such as microprocessor, in conjunction with arterial pressure signal local form structure and overall profile information are discerned, just can judge the position of beat starting point accurately, thereby improve segmentation accuracy by shooting arterial pressure signal.
The present invention adopts the arterial pressure detector to gather arterial pressure signal, these signals are by the digital signal after the A/D conversion (sample frequency of A/D conversion is 400Hz), with these signal input computers, carry out low-pass filtering and pre-sampling processing, the cut-off frequency of its filtering is 20～50Hz, and pre-sample frequency is between 125～1000Hz; Set up template by computer then, treat the side arterial pressure signal and handle, and then arterial pressure signal is cut apart by shooting by coupling.The FB(flow block) that computer is cut apart by shooting carries out as shown in Figure 1 successively as follows:
I, set up template signal, and the tolerance feature of beat starting point in the template signal:
A) set up template signal:
Under Different Individual, different condition, the cycle of the arterial pressure signal that is collected, amplitude and waveform profiles all are not quite similar, and therefore should take into full account these factors when setting up template, set up K mutually different template signal, form the template signal storehouse, K 〉=2.The process of setting up of template signal is: choose the mutually different arterial pressure signal of a plurality of waveform profiles, and its parameter such as cycle, amplitude and beat starting point separately all is retrieved as known conditions by manual detection identification or other existing detection means of identification in advance, is convenient to set up template signal.The arterial pressure signal that these are chosen, should contain the practice waveform profiles of common several arterial pressure signals clinically as far as possible, its cycle is between 0.43～1.5 second, to make these template signals can be used in the identification heart rate range at 40～140 times/minute arterial pressure signal as far as possible.Gather above-mentioned all kinds of arterial pressure signal by the arterial pressure detector, the input computer is chosen K beat starting point after carrying out low-pass filtering and pre-sampling processing then from the arterial pressure signal that this has discerned, and wherein k beat starting point is designated as O arbitrarily k, k ∈ 1,2 ..., K}.Because arterial pressure signal is a quasi-periodic signal, the signal segment in two cycles is enough to embody near the waveform profiles information of beat starting point, therefore considers from the angle that improves robustness, extracts beat starting point O kLast cycle and the back signal segment of one-period
Figure BSA00000186984200061
As the length range of setting up template signal.Yet for different arterial pressure signals, its cycle is not quite similar, thereby the sampling number in the two periodic signal sections of being extracted is also inconsistent; In order to set up unified template standard, need by sampling again or again interpolation processing be a fixed N sampled point with the length of each template signal is unified.For signal segment
Figure BSA00000186984200062
, promptly calculate the sampling number N that wherein after the sampling pretreatment, is comprised k, if N kGreater than unifying length N then to signal segment
Figure BSA00000186984200063
Sample again, if N kLess than unifying length N then to signal segment
Figure BSA00000186984200071
Carry out interpolation again, its length adjustment is a N sampled point the most at last, forms template signal A kBy above-mentioned steps K the signal segment of choosing handled, can be set up K template signal, the length of each template signal is N sampled point.The size of N has determined the precision of later stage identification to a certain extent, takes into account the consideration of accuracy of identification and robustness, and the suitable span of N is 100～1000.
B) set up N sampled point in each template signal respectively with respect to the normalization log-polar of its beat starting point:
Because influence of various factors, the waveform profiles of each beat can not fit like a glove in the arterial pressure signal, therefore can only discern the beat starting point by the similarity matching degree that compares waveform morphology.There is bigger difference between the waveform morphology of waveform morphology that the beat starting point is contiguous and non-beat starting point vicinity, if can set up a kind of metric relation, make tolerance responsive more to contiguous waveform morphology feature, with regard to easier beat starting point and non-beat starting point are significantly distinguished, reached recognition objective.The present invention is mapped to the arterial pressure signal of gathering in the log-polar territory, allow the identification point in the arterial pressure signal and the relative position relation of other point on its place waveform present the logarithm Changing Pattern, by other distribution characteristics in the log-polar territory of the identification point in the tolerance arterial pressure signal with respect to its place waveform, embody the sensitivity characteristic of identification point with its logarithm Changing Pattern, and then realize coupling identification beat starting point in the arterial pressure signal to its contiguous waveform morphology.The log-polar territory can be changed with the cartesian coordinate system mutual mapping.If the log-polar territory be (ξ, ψ), itself and cartesian coordinate system (x, transformational relation y) is as follows:
ξ = log ρ = log x 2 + y 2 ;
Figure BSA00000186984200073
Wherein, (ρ, θ) be cartesian coordinate system (utmost point footpath ξ promptly represents the logarithm value of distance between points in the log-polar territory for x, y) pairing polar coordinate, in the log-polar territory span of polar angle ψ be (π, π].
Concrete processing mode of the present invention is, for template signal A k, in order to measure and calculation template signal A kMiddle beat starting point O kWith the relative position relation of N sampled point, this N sampled point is projected with beat starting point O kIn the cartesian coordinate system for initial point, set up the Descartes relative coordinate of each sampled point, measure each sampled point and beat starting point O with Descartes's relative coordinate with respect to this beat starting point kDifference vector; The size of difference vector only with beat starting point O kRelevant with the relative position relation between its distribution characteristics point, and with beat starting point O kThe baseline of last cycle and back one-period signal waveform is irrelevant, therefore with between points difference vector as foundation characteristic, make foundation characteristic have translation and rotational invariance, this characteristic can overcome the influence of the baseline drift of arterial pressure signal.
Then, represented according to Descartes's relative coordinate again difference vector is mapped to N the sampled point of template signal Ak in the log-polar territory, obtains the log-polar of sampled point; The log-polar of this N sampled point has directly reflected itself and beat starting point O kBetween position relation, and distribute and be logarithmic parabola and change, by the log-polar of N sampled point of tolerance, this tolerance is to beat starting point O kContiguous waveform morphology feature-sensitive, the while can be caught the overall profile information of waveform again.At last, again sampled point in the template signal is carried out normalized with respect to the log-polar of its beat starting point, obtain the normalization log-polar, purpose is to eliminate template signal A kEach log-polar in incidental part personal characteristics information, simultaneously can be so that the common feature of the beat starting point that wherein contains periphery waveform profiles is kept.Sampled point with respect to the normalization log-polar of its beat starting point is in the note template signal
Figure BSA00000186984200081
For example, template signal A kIn n sampled point a K, n, n ∈ 1,2 ..., N} is with beat starting point O kFor the Descartes's relative coordinate in the cartesian coordinate system of initial point is (x K, n, y K, n), corresponding polar coordinate are (ρ K, n, θ K, n), as shown in Figure 3; Again by (ρ K, n, θ K, n) be mapped to after the log-polar territory, obtain sampled point a K, nWith respect to beat starting point O kLog-polar (ξ K, n, ψ K, n), wherein, utmost point footpath ξ K, n=log ρ K, n, polar angle ψ K, n=θ K, n, and ψ K, n∈ (π, π]; Obtain template signal A thus kIn each sampled point with respect to beat starting point O kLog-polar after, calculate the maximum ξ in the footpath of the utmost point wherein K, maxWith minima ξ K, min, between normalized to 0～1, utmost point footpath with each sampled point log-polar, keep polar angle constant, more specifically for sampled point a K, n, be:
α k , n = ξ k , n - ξ k , min ξ k , max - ξ k , min ,
Figure BSA00000186984200083
Then be template signal A kIn n sampled point a K, nWith respect to beat starting point O kThe normalization log-polar, α K, n∈ [0,1], As shown in Figure 4.
Can set up respectively by above-mentioned steps that sampled point is stored in it in memory device of computer or arterial pressure analytical equipment, as the match-on criterion of beat starting point in the arterial pressure signal to be measured with respect to the normalization log-polar of its beat starting point in each template signal.So far, test preparation is finished, next can carry out the testing procedure of arterial pressure signal to be measured.
Beat starting point in II, the identification arterial pressure signal to be measured:
Arterial pressure signal to be measured is also gathered by the arterial pressure detector, imports computer again and carries out low-pass filtering and sampling pretreatment, in order to dividing processing.Each beat starting point in the arterial pressure signal to be measured all should be a local minimum point, if only calculate as identification point with each local minimum point in the detection segment, can avoid obvious non-beat starting points a large amount of in the signal is discerned, simplify the data computation amount in the testing process greatly, can further improve the robustness of identification.In each beat, the local minimum point except that actual beat starting point is noise spot, judges that local minimum point the most similar to the beat starting point of template signal in the single beat is the actual beat starting point in this beat.But before definite beat starting point, the cycle duration of single beat can't be judged accurately, therefore needs one to judge duration, can determine to comprise at least a beat starting point in this judgement duration, can not surpass 2 beat durations again, with the accuracy that guarantees as far as possible to judge.We are used as the judgement duration benchmark of single beat in the measured signal with one " approximate cycle ".
But in the practical operation, each is variant probably for the speed of different period hearts rate, and the variation of heart rate directly causes the variation in arterial pressure signal cycle, therefore in the whole section arterial pressure signal of gathering to be measured, may have mutually different beat of cycle; If the cycle difference between the beat of difference place is excessive, but this difference is discerned with the same approximate cycle, certainly will cause recognition result to have bigger error.For this reason, the present invention has adopted arterial pressure signal to be measured with segmented mode by detecting processing, each sectional duration is set at 30～90s, and is excessive to avoid in the single split cycle difference between the different beats, thereby identification error is controlled in the limited scope.
Take all factors into consideration above-mentioned factor, the present invention is as follows to the identifying of beat starting point in the arterial pressure signal to be measured:
C) determine the first detection segment of arterial pressure signal to be measured:
For the first detection segment of arterial pressure signal to be measured, be that to extract duration from the starting point of arterial pressure signal to be measured be t 0Signal segment as detection segment; Then detection segment is carried out autocorrelation analysis, the interval in the auto-correlation function of calculating detection segment between every adjacent two local maximums is got the approximate cycle of the meansigma methods of described interval as detection segment; Wherein, t 0Span be 30～90s.
Calculate the approximate cycle of detection segment, can adopt this area auto-correlation function commonly used to find the solution, detection segment is carried out autocorrelation analysis, calculate the interval between every adjacent two local maximums in its auto-correlation function, get the approximate cycle of the meansigma methods of described interval as detection segment.For example, for detection segment
Figure BSA00000186984200091
Its signal value is the function of time, is designated as S (t), then detection segment
Figure BSA00000186984200092
Auto-correlation function R S(τ) be:
R S ( ι ) = ∫ - ∞ + ∞ S ( t ) S ( t + τ ) dt ,
Calculate its auto-correlation function R SA pairing L τZhi is designated as τ when (τ) getting local maximum l, l ∈ 1,2 ..., L}, then detection segment
Figure BSA00000186984200094
The approximate cycle
Figure BSA00000186984200095
For:
T ‾ s = 1 L - 1 Σ l = 2 L ( ι l - ι l - 1 ) .
D) determine the local minimum point in the first judgement duration in the detection segment:
In a detection segment, the duration of some beat might be greater than the length in pre-above-mentioned approximate cycle.Determine to comprise a beat starting point in order to guarantee to judge in the duration for one, the present invention is a benchmark with the length in approximate cycle, gets the judgement duration of ε times (ε＞1) approximate cycle as reality; The value of ε can not be excessive, and its span is 1.2～1.6, caused wherein comprising the beat starting point of 2 reality to avoid judging the duration that duration has surpassed 2 beats, and then produced the omission situation.
For the first judgement duration of detection segment, then be all local minimum points that calculate the cycle that doubly is similar to from section start to ε in the detection segment, judge in order to carrying out follow-up detection.Calculating local minimum point can adopt this area to use certain methods always.For example, can calculate the difference in magnitude between each neighbouring sample point,, judge that then this sampled point is the local minimum point if the difference in magnitude between a certain sampled point and its forward and backward neighbouring sample point all is not more than zero.Also can utilize method of derivation, detection segment is carried out derivative operation, obtain the extreme point of detection segment upper derivate for " 0 ", judge further that again these extreme points are maximum point or minimum point, minimum point wherein is the local minimum point of arterial pressure signal.
E) characteristic area of extraction local minimum point:
For allow each local minimum point can be respectively with template signal in the beat starting point carry out corresponding coupling and tolerance, need to extract the characteristic area of each local minimum point.The concrete grammar that extracts is, from the waveform profiles of arterial pressure signal to be measured, extract the signal segment in each each approximate cycle of local minimum point front and back, utilize and the step a) similar methods, be N sampled point (consistent) with the length of each signal segment of extracting is unified with the sampling number in the template signal, so that mate and compare, thereby form the characteristic area of each local minimum point with template signal.For example, detection segment
Figure BSA00000186984200101
The approximate cycle is
Figure BSA00000186984200102
By calculating detection segment In the doubly approximate cycle of current ε with interior I local minimum point, wherein i local minimum point is s i, i ∈ 1,2 ..., I}.From arterial pressure signal to be measured, extract local minimum point s iThe signal segment in last approximate cycle and one approximate cycle of back
Figure BSA00000186984200104
Calculate the pre-sampling number N that wherein comprises i, if N iGreater than unifying length N then to signal segment
Figure BSA00000186984200105
Sample again, if N iLess than unifying length N then to signal segment
Figure BSA00000186984200106
Carry out interpolation again, its length adjustment is a N sampled point the most at last, forms local minimum point s iCharacteristic area S iBy above-mentioned steps, from arterial pressure signal to be measured, extract detection segment
Figure BSA00000186984200107
In the doubly approximate cycle of current ε put characteristic of correspondence district separately with an interior I local minimum.
F) set up N sampled point in the characteristic area of each local minimum point respectively with respect to the normalization log-polar of its local minimum point;
Correspondingly, similar to step b), set up in the characteristic area of each local minimum point the Descartes relative coordinate of N sampled point respectively with respect to its local minimum point, represented according to Descartes's relative coordinate then difference vector, N sampled point in the characteristic area of each local minimum point is mapped in the log-polar territory, obtain its log-polar, obtain the normalization log-polar by normalized at last.Sampled point is (beta, gamma) with respect to the normalization log-polar of its local minimum point in the note characteristic area.
For detection segment
Figure BSA00000186984200108
In the doubly approximate cycle of current ε with interior i local minimum point s iCharacteristic area S i, i ∈ 1,2 ..., and I}, wherein N sampled point projects with local minimum point s iIn the cartesian coordinate system for initial point, set up each sampled point with respect to s iDescartes's relative coordinate, measure each sampled point and local minimum point s with Descartes's relative coordinate iDifference vector; Wherein, characteristic area S iIn n sampled point s I, n, n ∈ 1,2 ..., and N}, it is with local minimum point s iFor the Descartes's relative coordinate in the cartesian coordinate system of initial point is (x I, n, y I, n), corresponding polar coordinate are (ρ I, n, θ I, n); Again by (ρ I, n, θ I, n) be mapped to after the log-polar territory, obtain sampled point s I, nWith respect to local minimum point s iLog-polar (ξ I, n, ψ I, n), utmost point footpath ξ I, n=log ρ I, n, polar angle ψ I, n=θ I, nObtain local minimum point s thus iCharacteristic area S iIn each sampled point put s with respect to local minimum iLog-polar after, the maximum and the minima that calculate the footpath of the utmost point wherein are respectively ξ I, maxAnd ξ I, min, sampled point s then I, nWith respect to local minimum point s iNormalization log-polar (β I, n, γ I, n) satisfy:
β i , n = ξ i , n - ξ i , min ξ i , max - ξ i , min , γ i，n＝ψ i，n；
After normalized, β I, n∈ [0,1], γ I, n∈ (π, π].Can set up in the detection segment the doubly approximate cycle of current ε respectively with the normalization log-polar of the sampled point of the N in the characteristic area of interior each local minimum point by above-mentioned steps with respect to its local minimum point.
G) calculate the similarity of doubly approximate cycle of current ε in the detection segment respectively with interior each local minimum point:
In cycle, having only a local minimum point is real beat starting point at each beat of detection segment, and this local minimum point should be the highest with the similarity matching degree of beat starting point in the template signal.So, be incorporated herein " similarity " this notion, by calculating the similarity of local minimum point, the similarity matching degree of beat starting point in local minimum point and the template signal is described; The similarity of local minimum point is big more, represents that then the similarity matching degree of beat starting point in this local minimum point and the template signal is high more, and this local minimum point might be the actual beat starting point of detection segment more just.The present invention adopts the cross-correlation coefficient of the characteristic area of local minimum point and template signal to measure the similarity of each local minimum point in the detection segment, concrete processing mode is: the normalization log-polar of setting up based on step b) and step f), calculate the characteristic area of each local minimum point and the cross-correlation coefficient of each template signal respectively, with the similarity of the maximum in the cross-correlation coefficient of the characteristic area of each local minimum point and each template signal, thereby obtain the similarity of each local minimum point as this local minimum point.
For example, detection segment
Figure BSA00000186984200112
In the doubly approximate cycle of current ε with interior i local minimum point s iCharacteristic area S i, i ∈ 1,2 ..., and I}, n sampled point in the N of this characteristic area sampled point is s I, n, n ∈ 1,2 ..., N}, s I, nWith respect to local minimum point s iThe normalization log-polar be (β I, n, γ I, n); Simultaneously, k template signal A k, k ∈ 1,2 ..., and K}, the beat starting point in this template signal is O k, n sampled point in its N sampled point is a K, n, n ∈ 1,2 ..., N}, a K, nWith respect to beat starting point O kThe normalization log-polar be
Figure BSA00000186984200113
Local minimum point s then iCharacteristic area S iWith template signal A kCross-correlation coefficient P I, kFor:
Figure BSA00000186984200121
Wherein,
Figure BSA00000186984200122
Wherein, n ∈ 1,2 ..., N}; W pThe expression weight, the span of its weight coefficient λ is 0＜λ＜1; Because characteristic area S iN sampled point in, local minimum point s iWith the utmost point electrical path length of normalization log-polar of himself be 0, therefore, actual only have N-1 not to be that 0 inner product summation is averaged, so the coefficient before the sum term is
Figure BSA00000186984200123
Thus, can obtain detection segment
Figure BSA00000186984200124
In the doubly approximate cycle of current ε with interior i local minimum point s iCharacteristic area S iCross-correlation coefficient P with beat starting point in each template signal I, 1, P I, 2, P I, 2... P I, KWith P I, 1, P I, 2, P I, 2... P I, KIn maximum put s as local minimum iSimilarity C i, measure detection segment with this
Figure BSA00000186984200125
In the doubly approximate cycle of current ε with interior i local minimum point s iSimilarity matching degree with beat starting point in the template signal.Can see from the cross-correlation calculation formula, at characteristic area S iIn, local minimum point s iSampled point before (
Figure BSA00000186984200126
Perhaps
Figure BSA00000186984200127
) and template signal A kThe cross-correlation weight be λ (less than 1), local minimum point s iSampled point afterwards (
Figure BSA00000186984200128
) and template signal A kThe cross-correlation weight be 1, its objective is for relative reduction local minimum point s iThe matching properties of waveform profiles before.If local minimum point s iOne that is arterial pressure signal beat afterbody is disturbed minimum point, at a s iMust also there be a bit of interference shake waveform afterwards, at this moment s iWaveform profiles is relative better with the template signal coupling before the point, s iPoint back waveform profiles is relative relatively poor with the template signal coupling because of the relation of disturbing the shake waveform; But s iThe matching properties of waveform profiles is after weight coefficient λ reduction, again with s before the point iMinimum point s is disturbed in the matching properties summation of some back waveform profiles, average iCharacteristic area S iWith template signal A kCross-correlation coefficient then correspondingly reduce the corresponding local minimum point s that reduced simultaneously iSimilarity.If local minimum point s iBe a beat starting point in the arterial pressure signal to be measured, even there is a bit of interference shake waveform before, but this moment s iWaveform profiles is relative relatively poor with the template signal coupling because of the relation of disturbing the shake waveform before the point, s iPoint back waveform profiles is relative better with the template signal coupling; Even weight coefficient λ's s has weakened iThe matching properties of waveform profiles before the point, and s iThe matching properties of some back waveform profiles is kept, thereby allows local minimum point s iCharacteristic area S iWith template signal A kCross-correlation coefficient maintain higher value, correspondingly guaranteed local minimum point s iSimilarity higher relatively.Because the setting of different weights, local minimum point s relatively weakens iThe matching properties of waveform profiles before, make actual beat starting point more obvious with the similarity difference of disturbing smallest point, weaken of the influence of arterial pressure signal beat afterbody noise spot, help further to improve discrimination and cut apart accuracy rate by shooting the identification of beat starting point.Weight coefficient λ is in the span of 0＜λ＜1, and value is more little, and actual beat starting point is just obvious more with the similarity difference of disturbing smallest point.
One by one the doubly approximate cycle of current ε in the detection segment is carried out cross-correlation analysis with interior each local minimum point by this step, obtain the similarity of each local minimum point.
H) judge in the detection segment that the doubly approximate cycle of current ε is with interior beat starting point:
In each beat of detection segment, the local minimum point except that actual beat starting point is noise spot, should be got rid of in identifying.Noise spot is to produce owing to influence that arterial pressure signal is subjected to many-sided factor, these noise spots can be divided into weak jamming point and violent two kinds of noise spots from the identification angle.The weak jamming point, be near some the local minimum points the beat starting point, this noise spot may be that the disturbing wave owing to incident arteriogram and reflection interaction disturbs formation, also might be that (as the detection probe shake of arterial pressure detector etc.) causes because the of short duration instability of detection signal, but the amplitude of this noise spot is less, the beat of unlikely destruction arterial pressure signal, and this noise spot is also often little than beat starting point with the similarity of template signal, can be got rid of by comparing the similarity size.Violent noise spot, be outside the disturbing wave of penetrating arteriogram and reflection interaction, also owing to feel suffocated, exert oneself etc. to cause that arterial pressure signal produces obviously fluctuates accordingly, perhaps actions such as cough, sneeze cause arterial pressure signal acutely to be shaken, this fluctuation or violent shake have randomness, and amplitude is big, the persistent period is longer, forms one section violent disturbing wave; This violent disturbing wave just may cause superimposed interferential beat by serious destruction if overlap in the above arterial pressure signal of a beat, and this being present in by the local minimum point in the destructive beat of violent disturbing wave is regarded as violent noise spot.If have so violent interference in one section arterial pressure signal, useful information is also just destroyed in this segment signal, has in fact just lost the clinical identification meaning of arterial pressure.Therefore, the present invention is by preestablishing a threshold value C 0Beat starting point and violent noise spot are distinguished, avoid being caused cutting apart by shooting confusion for normal beat by the destructive beat flase drop survey of violent disturbing wave.
Concrete processing mode is, earlier by relatively obtaining in the detection segment the doubly approximate cycle of current ε with a local minimum point of interior similarity maximum, and other local minimum point except that this point all is regarded as weak jamming point and is got rid of; Then with the similarity and the pre-set threshold C of this local minimum point 0Compare, if its similarity is greater than threshold value C 0, judge that promptly this local minimum point is a beat starting point; If its similarity is less than threshold value C 0, judge that then this local minimum point is a violent noise spot.For example, calculate detection segment
Figure BSA00000186984200131
In current ε in the doubly approximate cycle local minimum point of similarity maximum be s i, its similarity is C iWith C iWith pre-set threshold C 0Compare, if C i≤ C 0, then local minimum is put s iBeing considered as violent noise spot excludes; If C i＞C 0, then judge local minimum point s iBe the beat starting point.
In this step, threshold value C 0Value be to get rid of the signals of violent noise spot, if threshold value C 0Value is too small, then can cause the omission of violent noise spot; If threshold value C 0Value is excessive, then the beat starting point of reality may be judged to be violent noise spot and get rid of in the lump.Usually, as the actual beat starting point of detection segment, its similarity is the highest may to reach 0.5; But under situation about existing than the large amplitude interfering signal, if the similarity of actual beat starting point is greater than 0.2 in the disturbed signal, can think that still the useful information in its beat is not destroyed fully, these useful informations clinically still can be received in the error of subsequent calculations heart rate, systolic pressure and diastolic pressure.Therefore, threshold value C 0Span get 0.2～0.5 and be advisable threshold value C 0The big more i.e. expression of value judges that the requirement of beat starting point is strict more.
I) all beat starting points in the judgement detection segment:
With the doubly approximate cycle of current ε in the detection segment be starting point with a local minimum point of interior similarity maximum, calculate thereafter the doubly approximate cycle of ε with interior all local minimums point; Repeating step e then)～i), judge beat starting points all in the detection segment thus.For example in current detection segment
Figure BSA00000186984200141
In, with the local minimum point s of doubly approximate cycle of current ε with interior similarity maximum iBe starting point, calculate detection segment
Figure BSA00000186984200142
Mid point s iThe local minimum point of ε similarity maximum in the doubly approximate cycle is judged its similarity and threshold value C then afterwards 0Between size, thereby judge whether it is the beat starting point; Be starting point with this point again, calculate ε thereafter in the doubly approximate cycle local minimum point of similarity maximum further judge ... by parity of reasoning, calculates current detection segment piecemeal
Figure BSA00000186984200143
In all beat starting points.
J) all beat starting points in the judgement arterial pressure signal to be measured:
In arterial pressure signal to be measured, be starting point with last beat starting point position in the current detection section, extracting thereafter, duration is t 0Signal segment as new detection segment, prepare to detect the beat starting point in the new detection segment.But the beat cycle may there are differences in new detection segment and the current detection section, therefore needs to upgrade earlier the approximate cycle, to avoid occurring the bigger error of calculation.The method of upgrading the approximate cycle is, with the meansigma methods of last 3 normal cycle intervals in the current detection section approximate cycle as new detection segment; Described normal cycle interval is meant the interval that is no more than 1.5 times between adjacent two beat starting points and is not less than 0.5 times of current approximate cycle duration.Repeating step d then)～j), judge beat starting points all in the arterial pressure signal to be measured thus.
III, arterial pressure signal to be measured is cut apart by shooting:
K) be cut-point with each beat starting point in the arterial pressure signal to be measured, arterial pressure signal to be measured cut apart by shooting, and the arterial pressure signal to be measured after will cutting apart shows and store, so that observe and carry out subsequent treatment by computer.
Improve as further optimization, at above-mentioned steps i) and j) between can also comprise step I 1): if the current detection section in detected beat starting point above 6, then obtain the wherein characteristic area of 6 beat starting points of similarity maximum, add in the template signal storehouse as new template signal.Because the driving mechanism of different beats is similar in the same arterial pressure signal to be measured, similarity each other is than higher; In this prioritization scheme, the higher beat starting point place characteristic area of similarity that formerly detects in the arterial pressure signal to be measured is added to new template signal, helps accurate judgement in back beat starting point.
Further specify the detailed process that this employing inventive method realizes that arterial pressure signal beat by beat is cut apart below by embodiment.
Embodiment:
In the present embodiment, by arterial pressure detector (VP-2000, Ke Lin company, Japan) gather arterial pressure signal, these signals are that sample frequency is the digital signal of 400Hz, with these signal input computers, carry out low-pass filtering and sampling pretreatment, its wave filter adopts second order Butterworth low pass filter, and cut-off frequency is 25Hz, sample frequency is 125Hz, with the signal that obtains as arterial pressure signal to be measured.Utilize the inventive method, this arterial pressure signal to be measured is cut apart by shooting, cutting procedure is carried out as follows by computer by shooting:
At first, gather a plurality of cycle differences, the representative arterial pressure signal of identification of common waveform profiles (parameters such as cycle, amplitude, beat starting point have all been discerned and known) clinically respectively by the arterial pressure detector, these signals also are that sample frequency is the digital signal of 400Hz, with these signals and relevant parameter input computer thereof, carry out low-pass filtering and sampling pretreatment, its wave filter adopts second order Butterworth low pass filter, and cut-off frequency is 25Hz, and sample frequency is 125Hz.Choose 20 beat starting points (getting K=20) the identification signal from above-mentioned each, extract each a last cycle of beat starting point and the back segment signal of one-period respectively; The 6th beat starting point O wherein 6The segment signal of last cycle with back one-period is
Figure BSA00000186984200151
Then by sampling again or the length of interpolation processing each segment signal that will extract is unified again is fixed 200 sampled points (getting N=200); For example, beat starting point O as calculated 6A last cycle and the back segment signal of one-period
Figure BSA00000186984200152
The sampling number that comprises after the middle sampling pretreatment is 236, and it is 200 sampled points that predetermined template signal is unified length, therefore with signal segment
Figure BSA00000186984200153
Be sampled as 200 sampled points again, obtain template signal A 6, its waveform profiles as shown in Figure 5; Obtain containing the template signal storehouse of 20 template signals thus.Set up in each template signal the normalization log-polar of 200 sampled points according to the described method of step b) again with respect to its beat starting point.
After finishing about the preparation of template signal, then carry out the identification of beat starting point in the arterial pressure signal to be measured.Determine earlier the first detection segment of arterial pressure signal to be measured, extracting duration from the starting point of arterial pressure signal to be measured is that the signal segment of 60s (is got t 0=60s) as first detection segment
Figure BSA00000186984200154
And obtain detection segment by autocorrelation analysis The approximate cycle
Figure BSA00000186984200156
Detection segment
Figure BSA00000186984200157
In preceding 15 seconds waveform profiles as shown in Figure 6, as can be seen from Fig. 6, between 500～600 sampled points, have one section because the violent interfering signal that cough causes, cause around here signal beat by more serious destruction.
Next, with 1.5 times of approximate cycles
Figure BSA00000186984200158
For judging duration, calculate detection segment
Figure BSA00000186984200159
In from section start extremely All local minimum points at place; But because the waveform profiles of arterial pressure signal to be measured in initial first approximate cycle is imperfect, therefore the local minimum point in initial first approximate cycle can't extract the complete signal in its last cycle, just can't utilize the inventive method to test, so the local minimum point of arterial pressure signal to be measured in initial first approximate cycle cast out, obtained detection segment
Figure BSA000001869842001511
In from section start extremely
Figure BSA000001869842001512
The place can have 2 as the local minimum point of identifying object, is respectively a s 1With a s 2, as shown in Figure 7.Then, extract the characteristic area of these 2 local minimum points respectively; With a s 1Be example, extract s 1The signal segment in last approximate cycle and one approximate cycle of back
Figure BSA00000186984200161
Calculating the sampling number that wherein comprises after the sampling pretreatment is 181, less than predetermined 200 sampled points of unified length, therefore with signal segment
Figure BSA00000186984200162
Carrying out interpolation processing is 200 sampled points, forms some s 1Characteristic area S 1Form some s in the same way 2Characteristic area S 2Set up characteristic area S respectively according to the described method of step f) again 1And S 2In 200 sampled points with respect to the normalization log-polar of local minimum point separately.Calculation level s 1Characteristic area S 1Cross-correlation coefficient (in the present embodiment, getting weight coefficient λ=0.8 when calculating cross-correlation coefficient) with 20 template signals obtains characteristic area S 120 cross-correlation coefficients in maximum be and template signal A 6Cross-correlation coefficient P 1,6=0.22, promptly determine some s 1Similarity C 1=P 1,6=0.22; Calculation level s 2Characteristic area S 2With the cross-correlation coefficient of 20 template signals, obtain characteristic area S 220 cross-correlation coefficients in maximum also be and template signal A 6Cross-correlation coefficient P 2,6=0.225, promptly determine some s 2Similarity C 2=P 2,6=0.225.Comparatively speaking, some s 2Similarity bigger, with s 2Similarity and pre-set threshold C 0Compare C 0Value is 0.20; Because C 2=0.225＞C 0, be not violent noise spot, thus local minimum point s 2Be judged as detection segment
Figure BSA00000186984200163
A beat starting point.Next, again with local minimum point s 2Be starting point, calculate detection segment
Figure BSA00000186984200164
Mid point s 2Afterwards
Figure BSA00000186984200165
Be respectively s with interior all local minimum points 3, s 4, s 5And s 6, as shown in Figure 8; Extract some s equally, respectively 3, s 4, s 5And s 6Characteristic area be S 3, S 4, S 5And S 6, set up 200 sampled points in above-mentioned each characteristic area respectively with respect to the normalization log-polar of local minimum point separately according to the described method of step f) again, respectively calculation level s 3, s 4, s 5And s 6Characteristic area S 3, S 4, S 5And S 6With the cross-correlation coefficient of each template signal based on log-polar; By calculating some s 3, s 4, s 5And s 6Characteristic area all with respect to template signal A 6The cross-correlation coefficient maximum, promptly get s 3, s 4, s 5And s 6Similarity be respectively: C 3=P 3,6=0.155; C 4=P 4,6=0.17; C 5=P 5,6=0.23; And C 6=P 6,6=0.15.By relatively learning, the similarity size is C 6＜C 3＜C 4＜C 5Thereby the local minimum point of similarity maximum is s in current 1.5 times of approximate cycles 5, and C 5=0.23＞C 0, promptly judge local minimum point s 5Be detection segment
Figure BSA00000186984200166
Another beat starting point.Then, again with local minimum point s 5Be starting point, calculate detection segment
Figure BSA00000186984200167
Mid point s 5Afterwards
Figure BSA00000186984200168
With interior all local minimum point s 6, s 7, s 8And s 9Further judge ... judge beat starting point s 17After, calculate detection segment
Figure BSA00000186984200169
Mid point s 17Afterwards
Figure BSA000001869842001610
Be respectively s with interior all local minimum points 18, s 19, s 20, s 21, s 22And s 23, as shown in Figure 9; Repeat above-mentioned steps once more and calculate the step of similarity, obtain s 18, s 19, s 20, s 21, s 22And s 23Similarity be respectively: C 18=0.09, C 19=0.13, C 20=0.155, C 21=0.185, C 22=0.14 and C 23=0.16, by relatively learning, the similarity size is C 18＜C 19＜C 22＜C 23＜C 20＜C 21Thereby the local minimum point of similarity maximum is s in current 1.5 times of approximate cycles 21, but because C 21=0.185＜C 0, promptly judge local minimum point s 21Be detection segment In a violent noise spot, therefore will put s 21Get rid of.Again with local minimum point s 21Be starting point, calculate detection segment
Figure BSA00000186984200171
Mid point s 21Afterwards
Figure BSA00000186984200172
With interior all local minimum point s 22, s 23, s 24, s 25And s 26Further judge ... recursion is determined detection segment thus
Figure BSA00000186984200173
In 82 beat starting points, be respectively s 2, s 5, s 8..., s 265, s 268, s 276, s 279And s 282Also determine detection segment in addition
Figure BSA00000186984200174
2 violent noise spots of middle existence are respectively s 21And s 272, violent noise spot s 21Be positioned at beat starting point s 17With s 25Between, violent noise spot s 272Be positioned at beat starting point s 268With s 276Between.Wherein, detection segment
Figure BSA00000186984200175
Preceding 15 seconds with interior beat starting point as shown in figure 10, detection segment
Figure BSA00000186984200176
Can see beat starting point s in the signal in conjunction with Figure 10 and 11 with the similarity scattergram of interior each local minimum point as shown in figure 11 in preceding 15 seconds 17With s 25Between the local minimum point of (comprising 500～600 sampled points) all be regarded as noise spot and exclude, therefore at a s 17With s 25Between do not have significant beat starting point.
Determine the first detection segment of arterial pressure signal to be measured
Figure BSA00000186984200177
In after all beat starting point, from these 82 beat starting points, select 6 beat starting points of similarity maximum, obtain the characteristic area of 6 beat starting points of this similarity maximum respectively, they are added to new template signal, be used for the detection of these other beat starting points of arterial pressure signal to be measured.Then, with detection segment
Figure BSA00000186984200178
In last beat starting point s 282The position is a starting point, extracts some s from arterial pressure signal to be measured 282The signal segment of 60s duration is as new detection segment afterwards
Figure BSA00000186984200179
Prepare to detect new detection segment In the beat starting point.Upgrade the value in approximate cycle this moment, with detection segment In the meansigma methods of last 3 normal cycle intervals as new detection segment
Figure BSA000001869842001712
The approximate cycle; Because beat starting point s 268With s 276Between because of existing violent interfering signal to cause interval T therebetween 79Surpass
Figure BSA000001869842001713
So T 79Be not the normal cycle interval, get beat starting point s 265With s 268Interval T 78, beat starting point s 276With s 279Interval T 80With beat starting point s 279With s 282Interval T 81Three's meansigma methods is as new detection segment
Figure BSA000001869842001714
Average period
Figure BSA000001869842001715
T ‾ s ( 2 ) = 1 3 × ( T 78 + T 80 + T 81 ) ;
Then, repeat above-mentioned steps, judge the detection segment of arterial pressure signal to be measured
Figure BSA000001869842001717
In all beat starting points.Recursion is judged the detection segment of arterial pressure signal to be measured equally thus All beat starting point in judging arterial pressure signal to be measured.At last, be cut-point with each beat starting point in the arterial pressure signal to be measured, by computer arterial pressure signal to be measured is cut apart by shooting, and the arterial pressure signal to be measured after will cutting apart shows and stores processing.
In order to assess the detection performance of the inventive method, we have made up a data base, and to play number of spots be 77190 to the beat of arterial pressure signal to be measured among the data base, and the beat starting point of these arterial pressure signals to be measured has been passed through the clinical expert manual markings.Utilize the inventive method that arterial pressure signal to be measured among the data base to be measured is carried out the identification of beat starting point, the beat starting point with testing result and expert's labelling compares then, and then assesses detection performance of the present invention.We are made as fault-tolerant interval with 8ms before and after the beat starting point of manual markings, think that this detection is correct when being not more than 8ms by the point tolerance of starting auction of starting auction a little of detecting of the present invention and expert's manual markings that is:.The inventive method is 99.04% to the identification accuracy of these 77190 beat starting points, and specificity is 98.66%, satisfies the requirement of Clinical recognition.The inventive method can finely be cut apart have wound method and the detected arterial pressure signal of non-invasive methods used clinically by shooting, effectively improves the accuracy of detection of arterial pressure checkout equipment to heart rate, systolic pressure and diastolic pressure.
The inventive method not only local messages such as the amplitude in the arterial pressure signal, local minimum points as the reference factor, the waveform profiles that more combines arterial pressure signal carries out analysis-by-synthesis, with between points difference vector as foundation characteristic, this foundation characteristic has translation and rotational invariance, can overcome the influence of the baseline drift of arterial pressure signal; Difference vector is carried out the similarity that log-polar conversion is measured waveform, and this tolerance can be caught the overall profile information of waveform again to the waveform morphology feature-sensitive of identification point vicinity, simultaneously waveform shake and distortion is had robustness; In computational process also respectively to before the local minimum point to be measured with the point after wave character give different weights, the weight of wave character before weakening a little, strengthen the some weight of wave character afterwards, thereby weaken of the influence of arterial pressure signal beat afterbody noise spot to identification, improve the recognition accuracy of beat starting point, and then realized identification accurately arterial pressure signal beat starting point; Simultaneously, also, can further effectively get rid of noise spot, help further improving the recognition accuracy of beat starting point by appropriate thresholds is set.Need benly be, in the cross-correlation coefficient that calculates local minimum point and template signal, if with weights W pThe corresponding raising of value G doubly (G be the arbitrary value greater than 0), and do not change before the local minimum point with point after weight relationship (put preceding weight less than after weight), the while is correspondingly with threshold value C 0Improve G doubly, then can not produce any influence result of calculation; Substantially identical by all schemes that numerical value is expanded or compression obtains like this with the present invention.
Explanation is at last, above embodiment is only unrestricted in order to technical scheme of the present invention to be described, although the present invention is had been described in detail with reference to preferred embodiment, those of ordinary skill in the art is to be understood that, can make amendment or be equal to replacement technical scheme of the present invention, and not breaking away from the aim and the scope of technical solution of the present invention, it all should be encompassed in the middle of the claim scope of the present invention.

Claims (8)

1. method for dividing arterial pressure signal beat by beat, it is characterized in that the arterial pressure signal input computer with the arterial pressure detector is gathered carries out low-pass filtering and sampling pretreatment by computer, then arterial pressure signal is cut apart by shooting, the concrete steps of cutting apart by shooting comprise:
A) set up K mutually different template signal, form the template signal storehouse; Each template signal is the segment signal of each one-period before and after beat starting point in the arterial pressure signal of having discerned, and this segment signal is a N sampled point by sampling or interpolation processing; Wherein, K 〉=2, the span of N is 100～1000;
B) set up N sampled point in each template signal respectively with respect to the log-polar of its beat starting point, and carry out normalized, obtain N sampled point in each template signal with respect to the normalization log-polar of its beat starting point; The computing formula of normalized is as follows:
α k , n = ξ k , n - ξ k , min ξ k , max - ξ k , min ,
Wherein,
Figure FSB00000495944700013
Be in k the template signal n sampled point with respect to the normalization log-polar of its beat starting point, α K, nBe normalization utmost point footpath,
Figure FSB00000495944700014
Be polar angle; (ξ K, n, ψ K, n) be in k the template signal n sampled point with respect to the log-polar of its beat starting point, ξ K, nBe utmost point footpath, ψ K, nBe polar angle; K ∈ 1,2 ..., K}, n ∈ 1,2 ..., N}; ξ K, maxAnd ξ K, minBe respectively each sampled point in k the template signal maximum and the minima in utmost point footpath in the corresponding log-polar after throwing;
C) for arterial pressure signal to be measured, extracting duration from its starting point is t 0Signal segment as detection segment; Then detection segment is carried out autocorrelation analysis, the interval in the auto-correlation function of calculating detection segment between every adjacent two local maximums is got the approximate cycle of the meansigma methods of described interval as detection segment; Wherein, t 0Span be 30～90s;
D) calculate in the detection segment from section start to ε doubly all local minimum points in approximate cycle; Wherein, the span of ε is 1.2～1.6;
E) extract the characteristic area of each local minimum point; The characteristic area of each local minimum point is the segment signal in each approximate cycle before and after this local minimum point in the arterial pressure signal to be measured, and this segment signal is a N sampled point by sampling or interpolation processing;
F) set up N sampled point in the characteristic area of each local minimum point respectively with respect to the log-polar of its local minimum point, and carry out normalized, obtain N sampled point in the characteristic area of each local minimum point with respect to the normalization log-polar of this local minimum point; The computing formula of normalized is as follows:
β i , n = ξ i , n - ξ i , min ξ i , max - ξ i , min , γ i，n＝ψ i，n；
Wherein, (β I, n, γ I, n) be in the detection segment the doubly approximate cycle of current ε with the normalization log-polar of n sampled point in the characteristic area of interior i local minimum point with respect to this local minimum point, β I, nBe normalization utmost point footpath, γ I, nBe polar angle; (ξ I, n, ψ I, n) be in the detection segment the doubly approximate cycle of current ε with the log-polar of n sampled point in the characteristic area of interior i local minimum point with respect to this local minimum point, ξ I, nBe utmost point footpath, ψ I, nBe polar angle; N ∈ 1,2 ..., N}; ξ I, maxAnd ξ I, minBe respectively in the characteristic area of i local minimum point in the detection segment each sampled point with respect to the maximum and the minima in utmost point footpath in the log-polar of this local minimum point;
G) calculate the characteristic area of each local minimum point and each template signal cross-correlation coefficient respectively, with the similarity of the maximum in the cross-correlation coefficient of the characteristic area of each local minimum point and each template signal as this local minimum point based on the normalization log-polar; The computing formula of described cross-correlation coefficient is:
Figure FSB00000495944700022
And,
Wherein, P I, kFor current ε in the detection segment doubly is similar to the cycle with the characteristic area of interior i local minimum point and the cross-correlation coefficient of k template signal; (β I, n, γ I, n) be in the detection segment the doubly approximate cycle of current ε with the normalization log-polar of n sampled point in the characteristic area of interior i local minimum point with respect to this local minimum point, β I, nBe normalization utmost point footpath, γ I, nBe polar angle;
Figure FSB00000495944700024
Be in k the template signal n sampled point with respect to the normalization log-polar of its beat starting point, α K, nBe normalization utmost point footpath,
Figure FSB00000495944700025
Be polar angle; K ∈ 1,2 ..., K}, n ∈ 1,2 ..., N}; W pThe expression weight, the span of its weight coefficient λ is 0＜λ＜1;
H) relatively draw the local minimum point of doubly approximate cycle of current ε in the detection segment with interior similarity maximum, and with the similarity and the pre-set threshold C of this local minimum point 0Compare; If its similarity is greater than threshold value C 0, judge that promptly this local minimum point is a beat starting point; Wherein, threshold value C 0Span be 0.2～0.5;
I) be starting point with the doubly approximate cycle of current ε in the detection segment with a local minimum point of interior similarity maximum, calculate thereafter the doubly approximate cycle of ε with interior all local minimums point; Repeating step e then)～i), judge beat starting points all in the detection segment thus;
J) in arterial pressure signal to be measured, be starting point with last beat starting point position in the current detection section, extracting thereafter, duration is t 0Signal segment as new detection segment; And, with the meansigma methods of last 3 normal cycle intervals in the current detection section the approximate cycle as new detection segment; Repeating step d then)～j), judge beat starting points all in the arterial pressure signal to be measured thus;
Described normal cycle interval is meant the interval that is no more than 1.5 times between adjacent two beat starting points and is not less than 0.5 times of current approximate cycle duration;
K) arterial pressure signal to be measured is cut apart by shooting, stored and show arterial pressure signal beat by beat segmentation result to be measured.
2. method for dividing arterial pressure signal beat by beat according to claim 1 is characterized in that: described step I) and j) also comprise:
I1) if detected beat starting point surpasses 6 in the current detection section, then obtain the wherein characteristic area of 6 beat starting points of similarity maximum, add in the template signal storehouse as new template signal.
3. method for dividing arterial pressure signal beat by beat according to claim 1 and 2 is characterized in that: the cut-off frequency of described low-pass filtering is 20～50Hz.
4. method for dividing arterial pressure signal beat by beat according to claim 1 and 2 is characterized in that: the pretreated sample frequency of described sampling is 125～1000Hz.
5. method for dividing arterial pressure signal beat by beat according to claim 1 and 2 is characterized in that: the preferred value of described N is 200.
6. method for dividing arterial pressure signal beat by beat according to claim 1 and 2 is characterized in that: described t 0Preferred value be 60s.
7. method for dividing arterial pressure signal beat by beat according to claim 1 and 2 is characterized in that: the preferred value of described ε is 1.5.
8. method for dividing arterial pressure signal beat by beat according to claim 1 and 2 is characterized in that: the preferred value of weight coefficient λ is 0.8 in the described step g), described step h) middle threshold value C 0Preferred value be 0.20.
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