CN103071236A - Method and device for detecting electric shock signal - Google Patents
Method and device for detecting electric shock signal Download PDFInfo
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- CN103071236A CN103071236A CN2012105934530A CN201210593453A CN103071236A CN 103071236 A CN103071236 A CN 103071236A CN 2012105934530 A CN2012105934530 A CN 2012105934530A CN 201210593453 A CN201210593453 A CN 201210593453A CN 103071236 A CN103071236 A CN 103071236A
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Abstract
The invention discloses a method and a device for detecting an electric shock signal. The method comprises the following steps of: 1, intercepting an input electrocardiosignal datum D by sliding a window of which the time duration is m according to the input electrocardiosignal datum D to obtain a plurality of first window signals yi(m), and delaying and reconstructing the first window signals yi(m) to obtain a first reconstruction point so as to obtain a first parameter P of the electrocardiosignal datum D; 2, setting a window function, partitioning the input electrocardiosignal datum D into a plurality of segments according to a sliding window, multiplying each segment with the window function, normalizing an amplitude, converting into a binary character string, and calculating another parameter T of the electrocardiosignal datum D by counting the percentage of characters of which the normalized binary character string amplitude are larger than a first amplitude threshold value; and 3, judging whether a signal is an electric shock signal or not by judging whether P and T fall into a plurality of preset parameter threshold value ranges or not.
Description
Technical field
The present invention relates to the medical electronics technical field, be specifically related to a kind of electric shock signal detection method and device.
Background technology
Ventricular fibrillation (Ventricular Fibrillation, VF) be the most pernicious a kind of in the arrhythmia, be the main cause that causes Sudden Cardiac Death, and ventricular tachycardia (Ventricular Tachycardia, VT) and ventricular flutter can worsen transformation for quivering the chamber.Electric defibrillation is the unique effective termination chamber method of quivering now.Above three kinds of signal overwhelming majority finally all the chamber of showing as quiver, can end by electric shock, so quiver in our chamber of general designation, pounce on the chamber, the chamber speed of heart rate more than 160bpm is electric shock signal, electric shock signal belongs to the average information that is used for the treatment of.Automatically the research of the method for the electric shock signal of the above-mentioned average information of detection is most important.
The method that detects at present the identification electric shock signal emerges in an endless stream, and these methods mainly are classified as time domain, frequency domain and Nonlinear Dynamics three major types.Time Domain Analysis mainly is to be based upon on the basis that the parameters such as slope, amplitude analyze, although this class methods computing is fast, accuracy rate is inadequate, detects error large, to single or carry out on a small quantity ripple and detect effectively, a large amount of continuous implementation ripples is detected poor effect.Typical Time Domain Analysis has: sequential hypothesis detection algorithm, auto-correlation function detection algorithm etc.Frequency-domain analysis method mainly carries out transform domain analysis to electrocardiogram, detects electric shock signal according to corresponding parameter, and this class methods operand is large, be unfavorable for real-time processing.Typical frequency domain method has: Spectral Analysis Method, EMD analytical method, Algorithms of Discrete Wavelet Transform.Nonlinear Dynamics is to detect electric shock signal by certain non-linear parameter threshold value is set mostly, and its detection speed is fast, degree of accuracy is also higher, but single fixing threshold value so that algorithm is lower to variability electric shock signal verification and measurement ratio, has limited sensitivity and specific raising greatly.
Summary of the invention
The present invention for solve in the prior art detect identification electric shock signal accuracy rate not, detect the large technical problem of error, a kind of detection method and device of electric shock signal is provided.
Technical scheme provided by the invention is as follows:
An object of the present invention is to provide a kind of electric shock signal detection method, may further comprise the steps:
1.1) according to input ecg signal data D, be that the window of the m described input ecg signal data D of intercepting that slides obtains some the first window signal y with time span
i(m), to described the first window signal y
i(m) carry out Delay reconstruction and obtain the first reconstruction point, obtain first parameter P of described ecg signal data D;
1.2) window function of setting, input ecg signal data D is divided into some sections by sliding window, every section multiply by window function, with amplitude normalization and convert string of binary characters to, by the number of characters percentage ratio of statistics normalization string of binary characters amplitude greater than the first amplitude threshold, calculate another parameter T of ecg signal data D;
1.3) whether fall into corresponding default parameter threshold range according to P and T, determine whether electric shock signal.Further, as preferably, described step 1.1) specifically may further comprise the steps:
2.1) with described the first window signal y
i(m) resampling obtains resampling signal z
i(m
1);
2.2) to described resampling signal z
i(m
1) adopt in the following method reconstruct: with z
i(m
1) as the x axial coordinate, with z
i(m
1+ τ) as y axle vertical coordinate, draw the first reconstruction point, wherein, 0＜m
1＜m-τ;
3.3) covering all described first reconstruction point with one 40 * 40 grid, the grid number that is occupied by described the first reconstruction point and the ratio of possessive case subnumber are first parameter P of described ecg signal data D.
Further, as preferably, described step 1.2) specifically comprise the steps:
3.1), to set both sides be to be the window data data_parat_w of constant in the middle of the cosine;
3.2), take width as t7 second, sliding time divides ecg signal data D as the first sliding window of t8 second, and ecg signal data D is divided into some groups of data segments;
3.3), multiply by window data data_parat_w for every group of data segment;
3.4), multiply by the data segment normalization of window data data_parat_w and be converted into string of binary characters above-mentioned;
3.5), the statistics above-mentioned string of binary characters greater than the second amplitude threshold V
0Number of characters percentage ratio;
3.6), above-mentioned all data segment number of characters percentage ratios are accumulated, obtain parameter T.
Further, as preferably, in described step 1.1) further comprising the steps of before:
4.1) if the noise of ecg signal data D disturbs greater than the first power frequency threshold value greater than the first noise threshold or power frequency, then being judged to can not electric shock signal, finishes; Otherwise enter next step.
Further, as preferably, described 4.1) also comprise after the step: whether judge pretreatment electrocardiosignal amplitude A less than the 3rd default amplitude threshold A1, if so, being classified as can not electric shock signal, finishes; Otherwise enter next step.
Further, as preferably, described the 3rd amplitude threshold A1 is 0.15～0.25mV.
Further, as preferably, the concrete calculation procedure of described electrocardiosignal amplitude A is as follows:
7.1) to get time span be T0 the second sliding window, obtains the amplitude upper limit ATmaxi that signal reaches in each sliding window;
7.2) A is the maximum of ATmaxi in all sliding windows.
Further, as preferably, described T0 is 1～3 second.
Further, as preferably, in described step 1.1) also comprise before: ecg signal data D is divided into k wicket take the t1 duration as unit, amplitude and the 4th amplitude threshold A2 contrast with wicket, if the wicket signal amplitude, thinks then that this wicket is the horizontal segment wicket less than the 4th amplitude threshold A2; The number sn of statistics horizontal segment wicket if greater than first number threshold value N1, then be judged to be can not electric shock signal for sn, finishes; Otherwise enter next step.
Further, as preferably, described the 4th amplitude threshold A2 is 0.01～0.03mV.
Further, as preferably, described step 1.3) further comprise:
The first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1 are set, satisfy P0＜P1, T0＜T1; If P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step.
Further, as preferably, further comprise:
The first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1, the 5th parameter threshold P2, the 6th parameter threshold P3, the 7th parameter threshold T2, the 8th parameter threshold T3 are set, satisfy P0＜P2＜P3＜P1, T0＜T2＜T3＜T1; If P＜P2 and T＜T2 or P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P3 and T＞T3 or P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step.
Further, as preferably, described heart rate detection step is specially: judge whether heart rate surpasses 160bpm, if, then be judged to electric shock signal, finish; Otherwise being judged as can not electric shock signal, finishes.
Further, as preferably, the obtaining step of described heart rate is as follows:
14.1) setting the 5th amplitude threshold CF1 initial value;
14.2) if the ecg signal data difference greater than the 5th amplitude threshold CF1, simultaneously amplitude is then thought the R ripple greater than default the 6th amplitude threshold A3; Automatically upgrade the 5th amplitude threshold CF1 according to the R wave amplitude;
14.3) after ecg signal data D detect to finish, calculate the R wave spacing, if the R wave spacing, then judges have undetectedly in the described R wave spacing zone greater than very first time threshold value t5, undetected R wave spacing zone is detected according to above-mentioned steps again;
14.4) number of statistics R ripple, calculate and obtain described heart rate.
The invention also discloses a kind of checkout gear of electric shock signal, comprise that the first parameter obtains module, the second parameter obtains module and judge module;
Described the first parameter obtains module, according to input ecg signal data D, is that the window of the m described input ecg signal data D of intercepting that slides obtains some the first window signal y with time span
i(m), to described the first window signal y
i(m) carry out Delay reconstruction and obtain the first reconstruction point, obtain first parameter P of described ecg signal data D; Described the second parameter obtains module, by setting a window function, input ecg signal data D is divided into some sections by sliding window, every section multiply by window function, with amplitude normalization and convert string of binary characters to, by the number of characters percentage ratio of statistics normalization string of binary characters amplitude greater than the first amplitude threshold, calculate another parameter T of ecg signal data D;
Whether described judge module falls into default a plurality of parameter threshold ranges according to parameter P and parameter T, determines whether electric shock signal.
Further, as preferably, the acquisition that described the first parameter obtains first parameter P in the module specifically comprises:
With described the first window signal y
i(m) resampling obtains resampling signal z
i(m
1);
To described resampling signal z
i(m
1) adopt in the following method reconstruct: with z
i(m
1) as the x axial coordinate, with z
i(m
1+ τ) as y axle vertical coordinate, draw the first reconstruction point, wherein, 0＜m
1＜m-τ;
Cover all described first reconstruction point with one 40 * 40 grid, the grid number that is occupied by described the first reconstruction point and the ratio of possessive case subnumber are first parameter P of described ecg signal data D.
Further, as preferably, the acquisition that described the second parameter obtains another parameter T in the module specifically comprises:
Set window data data_parat_w (t);
Take width as t7 second, sliding time divides ecg signal data D as the first sliding window of t8 second, then
Ecg signal data D is divided into some groups of data segments;
Multiply by window data data_parat_w for every group of data segment;
Multiply by the data segment normalization of window data data_parat_w and be converted into string of binary characters above-mentioned;
The statistics string of binary characters is greater than the second amplitude threshold V
0Number of characters percentage ratio;
Above-mentioned number of characters percentage ratio is accumulated, obtained parameter T.
Further, as preferably, described judge module specifically comprises:
The first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1 are set, satisfy P0＜P1, T0＜T1; If P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step.
Further, as preferably, described judge module specifically comprises:
The first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1, the 5th parameter threshold P2, the 6th parameter threshold P3, the 7th parameter threshold T2, the 8th parameter threshold T3 are set, satisfy P0＜P2＜P3＜P1, T0＜T2＜T3＜T1; If P＜P2 and T＜T2 or P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P3 and T＞T3 or P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step.
Further, as preferably, further comprise the heart rate detection module: judge whether heart rate surpasses 160bpm, if then be judged to electric shock signal, end.
Further, as preferably, further comprise the heart rate acquisition module: set the 5th amplitude threshold CF1 initial value, if the ecg signal data difference is greater than the 5th amplitude threshold CF1; After ecg signal data D detect to finish, calculate the R wave spacing, if the R wave spacing, then judges have undetectedly in the described R wave spacing zone greater than very first time threshold value t5, undetected R wave spacing zone is detected according to above-mentioned steps again; The number of statistics R ripple is calculated and is obtained described heart rate.
Can find out from technique scheme, utilize the nonlinear method threshold value first click signal to be done preliminary judgement, then utilize waveform frequency further to judge again, not only arithmetic speed is high, and detect effective to a large amount of continuous implementation ripples, satisfy the condition of processing in real time, also have simultaneously higher degree of accuracy.
Description of drawings
In order to be illustrated more clearly in the embodiment of the invention or technical scheme of the prior art, the below will do to introduce simply to the accompanying drawing of required use in embodiment or the description of the Prior Art, apparently, accompanying drawing in the following describes only is some embodiments of the present invention, for those of ordinary skills, under the prerequisite of not paying creative work, can also obtain according to these accompanying drawings other accompanying drawing.
Fig. 1 is the embodiment of the invention 1 electric shock detection algorithm schematic flow sheet.
Fig. 2 is the embodiment of the invention 2 electric shock detection algorithm schematic flow sheets.
Fig. 3 is the embodiment of the invention 3 electric shock checkout gear block diagrams.
The specific embodiment
Below in conjunction with the accompanying drawing in the embodiment of the invention, the technical scheme in the embodiment of the invention is clearly and completely described, obviously, described embodiment only is the present invention's part embodiment, rather than whole embodiment.Based on the embodiment among the present invention, those of ordinary skills belong to the scope of protection of the invention not making all other embodiment that obtain under the creative work prerequisite.
Be elaborated respectively below in conjunction with accompanying drawing.
Embodiment 1
As shown in Figure 1, a kind of electric shock signal detection method may further comprise the steps:
First parameter P of S100, ecg signal data D obtains step: be that the window of the m described input ecg signal data D of intercepting that slides obtains some the first window signal y with time span
i(m), to described the first window signal y
i(m) carry out Delay reconstruction and obtain the first reconstruction point, obtain first parameter P of described ecg signal data D;
Another parameter T of S200, ecg signal data D obtains step: set a window function, input ecg signal data D is divided into some sections by sliding window, every section multiply by window function, with amplitude normalization and convert string of binary characters to, by the number of characters percentage ratio of statistics normalization string of binary characters amplitude greater than the first amplitude threshold, calculate another parameter T of ecg signal data D;
S300, whether be the electric shock signal determining step: whether fall into corresponding default parameter threshold range according to P and T, determine whether electric shock signal.
Utilize the nonlinear method threshold value first click signal to be done preliminary judgement, then utilize waveform frequency further to judge again (namely adopt two parameters＜parameter P, parameter T＞), not only arithmetic speed is high, and detect effective to a large amount of continuous implementation ripples, satisfy the condition of processing in real time, also have simultaneously higher degree of accuracy.
Embodiment 2
Be elaborated below in conjunction with 2 pairs of embodiment of the invention of accompanying drawing.
As shown in Figure 2, a kind of electric shock signal detection method may further comprise the steps:
S1, according to sample rate smprate, acquisition time t electrocardiosignal is sampled, obtaining data length is the ecg signal data D0 of smprate*t;
S2, judge according to the amplitude of ecg signal data D0 whether this data segment contains large noise (being whether noise is greater than the first noise threshold), if contained would enter S3, being judged as can not electric shock signal, finish; Otherwise enter next step;
S4, judge according to the frequency characteristic of ecg signal data D0 whether this data segment contains a large amount of power frequencies and disturb, if contained would enter S5, being judged as can not electric shock signal, finish; Otherwise enter next step;
S6, ECG Signal Analysis data D0 is carried out trap, high pass and low-pass filtering pretreatment obtain ECG Signal Analysis data D;
S7, judge ECG Signal Analysis data D amplitude A whether greater than default the 3rd amplitude threshold A1, if so, then enter next step S9, otherwise enter S8, be judged to be the electrocardiosignal of stopping rich or moribund condition, being judged as can not electric shock signal, finishes; General preferred the 3rd amplitude threshold A1 is 0.15～0.25mV.The present embodiment the 3rd amplitude threshold A1 is 0.20mV.
The concrete calculation procedure of this electrocardiosignal amplitude A is as follows:
7.1) to get time span be T0 the second sliding window, obtains the amplitude upper limit ATmaxi that signal reaches in each sliding window; Preferred 1～3 second of this T0, the present embodiment is specially elects 1 second as.
7.2) A is the maximum of ATmaxi in all sliding windows.
S9: judge according to the amplitude of ecg signal data D whether these data contain a large amount of horizontal segments, ecg signal data D is divided into k wicket take the t1 duration as unit, difference in magnitude and the 4th amplitude threshold A2 contrast with wicket, if the difference in magnitude of wicket, thinks then that this wicket is the horizontal segment wicket less than the 4th amplitude threshold A2; The number sn of statistics horizontal segment wicket if greater than first number threshold value N1, then be judged to be can not electric shock signal for sn, finishes; Otherwise enter next step.
Concrete, take a sample take 0.1S as window, if difference in magnitude (be window in amplitude maximum amplitude minima) less than 0.02mV, if satisfy the window number sn of above condition greater than N1 (N1 is clinical experience numerical value), S10, then being judged to be can not electric shock signal, S11 otherwise enter next step; The adding of this step is conducive to reduce erroneous judgement, namely because the amplitude that careless manipulation or other errors are brought is higher and the interfering signal of level accesses and causes being mistaken for electric shock signal, has improved accuracy of detection.S11, be that the window of the m described input ecg signal data D of intercepting that slides obtains some the first window signal y with time span
i(m) (wherein m, t1 can get respectively 4 seconds and 1 second; First first window signal y for example
1(m) time is scope (0,4), second the first window signal y
2(m) time is scope (1,5), by that analogy.), to described the first window signal y
i(m) carry out Delay reconstruction and obtain the first reconstruction point, obtain first parameter P of described ecg signal data D; Set window function, ecg signal data be multiply by window function, normalization also converts string of binary characters to, by the number of characters percentage ratio of statistics string of binary characters greater than threshold value, calculates another parameter T of ecg signal data D;
S12, S13, S14, S15, judge whether it is electric shock signal, specifically comprise: the first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1 are set, satisfy P0＜P1, T0＜T1; If P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step;
Among another more excellent embodiment of the present invention, this S12, S13, S14, S15, judge whether it is electric shock signal, specifically comprise: the first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1, the 5th parameter threshold P2, the 6th parameter threshold P3, the 7th parameter threshold T2, the 8th parameter threshold T3 are set, satisfy P0＜P2＜P3＜P1, T0＜T2＜T3＜T1; If P＜P2 and T＜T2 or P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P3 and T＞T3 or P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step; Further, the determining step among this embodiment is, at first adopts the determination methods among the embodiment 2 to judge, the signal between the signal between P0 and the P1 or T0 and the T1 then adopts P2 to be combined T2 and T3 with P3 and judges.By the judgement of two steps, improved accuracy of detection.
Wherein: P0:0.06～0.1, P2:0.08～0.12, P3:0.12～0.15, P4:0.13～0.17T0:8～12, T2:12～16, T3:30～36, T1:39～44.
S16, further judge according to the heart rate of ecg signal data D, if heart rate greater than 160bpm (beating 160 times in namely 1 minute), S18, then is judged to be electric shock signal, S17 otherwise be electric shock signal not finishes.
The obtaining step of this heart rate is as follows:
14.1) setting the 5th amplitude threshold CF1 initial value;
14.2) if the ecg signal data difference greater than the 5th amplitude threshold CF1, simultaneously amplitude is then thought the R ripple greater than default the 6th amplitude threshold A3; Automatically upgrade the 5th amplitude threshold CF1 according to the R wave amplitude; For example the proportional example of the 5th amplitude threshold CF1 and last R wave amplitude concerns.
14.3) after ecg signal data D detect to finish, calculate the R wave spacing, if the R wave spacing, then judges have undetectedly in the described R wave spacing zone greater than very first time threshold value t5, undetected R wave spacing zone is detected according to above-mentioned steps again;
14.4) number of statistics R ripple, calculate and obtain described heart rate.
Calculating P among the described step S11 specifically comprises the steps:
With the first window signal y
i(m) reduce sample rate to 50Hz, resampling obtains signal z
i(m
1); To signal z
i(m
1) carrying out following reconstructing method: x axle abscissa is z
i(m
1), y axle vertical coordinate is z
i(m
1+ τ), wherein the phase space reconfiguration point is drawn in τ=0.9; Determine whether and can shock by electricity by the zone that is reconstructed filling point, the grid that produces in the drawings 40 * 40 extends, and this grid has covered all reconstruction point, and calculates the total Psnum of the grid of being filled by these points.Calculate according to formula
Calculating T among the described step S11 specifically comprises the steps:
3.1), set the window data according to formula
3.2), take 3 seconds as unit, sliding window is 1 second dividing data D, then D is divided into data segment SD1
i(j), i=1,2 ... SDnum, j=1,2 ... (3 * smprate), SDnum=(t-3)+1 wherein;
3.3), multiply by window data data_parat_w, SD2 for every segment data
i(j)=SD1
i(j) .*tcsc_w (j);
3.4), with segment data SD2
iNormalization also is converted into string of binary characters b={b (1), b (2), and b (3) ...;
3.5), the statistics string of binary characters greater than threshold value V
0Number of characters percentage ratio
3.6), according to the formula calculating parameter
Embodiment 3
As shown in Figure 3, the invention also discloses a kind of electric shock signal checkout gear, comprise that the first parameter obtains module 100, the second parameter obtains module 200 and judge module 300;
Described the first parameter obtains module 100, according to input ecg signal data D, is that the window of the m described input ecg signal data D of intercepting that slides obtains some the first window signal y with time span
i(m), to described the first window signal y
i(m) carry out Delay reconstruction and obtain the first reconstruction point, obtain first parameter P of described ecg signal data D; Described the second parameter obtains module 200, by setting a window function, input ecg signal data D is divided into some sections by sliding window, every section multiply by window function, with amplitude normalization and convert string of binary characters to, by the number of characters percentage ratio of statistics normalization string of binary characters amplitude greater than the first amplitude threshold, calculate another parameter T of ecg signal data D;
Whether described judge module 300 falls into default parameter threshold range according to parameter P and parameter T, determines whether electric shock signal.
The acquisition that this first parameter obtains first parameter P in the module 100 specifically comprises:
With described the first window signal y
i(m) resampling obtains resampling signal z
i(m
1);
To described resampling signal z
i(m
1) adopt in the following method reconstruct: with z
i(m
1) as the x axial coordinate, with z
i(m
1+ τ) as y axle vertical coordinate, draw the first reconstruction point, wherein, 0＜m
1＜m-τ;
Cover all described first reconstruction point with one 40 * 40 grid, the grid number that is occupied by described the first reconstruction point and the ratio of possessive case subnumber are first parameter P of described ecg signal data D.
The acquisition that this second parameter obtains another parameter T in the module 200 specifically comprises:
Set window data data_parat_w;
Take width as t7 second, sliding time divides ecg signal data D as the first sliding window of t8 second, then
Ecg signal data D is divided into some groups of data segments;
Multiply by window data data_parat_w for every group of data segment;
Multiply by the data segment normalization of window data data_parat_w and be converted into string of binary characters above-mentioned;
The statistics string of binary characters is greater than the second amplitude threshold V
0Number of characters percentage ratio;
Above-mentioned number of characters percentage ratio is accumulated, obtained parameter T.
This judge module 300 specifically comprises:
The first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1 are set, satisfy P0＜P1, T0＜T1; If P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step.
Among another embodiment, this judge module 300 specifically comprises:
The first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1, the 5th parameter threshold P2, the 6th parameter threshold P3, the 7th parameter threshold T2, the 8th parameter threshold T3 are set, satisfy P0＜P2＜P3＜P1, T0＜T2＜T3＜T1; If P＜P2 and T＜T2 or P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P3 and T＞T3 or P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step.
This heart rate detection module: judge whether heart rate surpasses 160bpm, if, then be judged to electric shock signal, finish; Otherwise being judged as can not electric shock signal, finishes.Further comprise the heart rate acquisition module in this heart rate detection module: set the 5th amplitude threshold CF1 initial value, if the ecg signal data difference is greater than the 5th amplitude threshold CF1; After ecg signal data D detect to finish, calculate the R wave spacing, if the R wave spacing, then judges have undetectedly in the described R wave spacing zone greater than very first time threshold value t5, undetected R wave spacing zone is detected according to above-mentioned steps again; The number of statistics R ripple is calculated and is obtained described heart rate.
The above scheme that the embodiment of the invention is provided is described in detail, and has used specific case herein principle of the present invention and embodiment are set forth, and the explanation of above embodiment just is used for helping to understand method of the present invention and core concept thereof; Simultaneously, for one of ordinary skill in the art, according to thought of the present invention, all will change in specific embodiments and applications, in sum, this description should not be construed as limitation of the present invention.
Claims (21)
1. an electric shock signal detection method is characterized in that, may further comprise the steps:
1.1) according to input ecg signal data D, be that the window of the m described input ecg signal data D of intercepting that slides obtains some the first window signal y with time span
i(m), to described the first window signal y
i(m) carry out Delay reconstruction and obtain the first reconstruction point, obtain first parameter P of described ecg signal data D;
1.2) window function of setting, input ecg signal data D is divided into some sections by sliding window, every section multiply by window function, with amplitude normalization and convert string of binary characters to, by the number of characters percentage ratio of statistics normalization string of binary characters amplitude greater than the first amplitude threshold, calculate another parameter T of ecg signal data D;
1.3) whether fall into corresponding default parameter threshold range according to P and T, determine whether electric shock signal.
2. described electric shock signal detection method according to claim 1 is characterized in that described step 1.1) specifically may further comprise the steps:
2.1) with described the first window signal y
i(m) resampling obtains resampling signal z
i(m
1);
2.2) to described resampling signal z
i(m
1) adopt in the following method reconstruct: with z
i(m
1) as the x axial coordinate, with z
i(m
1+ τ) as y axle vertical coordinate, draw the first reconstruction point, wherein, 0＜m
1＜m-τ;
3.3) covering all described first reconstruction point with one 40 * 40 grid, the grid number that is occupied by described the first reconstruction point and the ratio of possessive case subnumber are first parameter P of described ecg signal data D.
3. described electric shock signal detection method according to claim 1 is characterized in that described step 1.2) specifically comprise the steps:
3.1) to set both sides be to be the window data data_parat_w of constant in the middle of the cosine;
3.2) take width as t7 second, sliding time divides ecg signal data D as the first sliding window of t8 second, and ecg signal data D is divided into some groups of data segments;
3.3) multiply by window data data_parat_w for every group of data segment;
3.4) multiply by the data segment normalization of window data data_parat_w and be converted into string of binary characters above-mentioned;
3.5) add up above-mentioned string of binary characters greater than the second amplitude threshold V
0Number of characters percentage ratio;
3.6) above-mentioned all data segment number of characters percentage ratios are accumulated, obtain parameter T.
4. described electric shock signal detection method according to claim 1 is characterized in that, in described step 1.1) further comprising the steps of before:
4.1) if the noise of ecg signal data D disturbs greater than the first power frequency threshold value greater than the first noise threshold or power frequency, then being judged to can not electric shock signal, finishes; Otherwise enter next step.
5. described electric shock signal detection method according to claim 4 is characterized in that, described 4.1) also comprise after the step: whether judge pretreatment electrocardiosignal amplitude A less than the 3rd default amplitude threshold A1, if so, being classified as can not electric shock signal, finishes; Otherwise enter next step.
6. described electric shock signal detection method according to claim 5 is characterized in that, described the 3rd amplitude threshold A1 is 0.15～0.25mV.
7. described electric shock signal detection method according to claim 5 is characterized in that, the concrete calculation procedure of described electrocardiosignal amplitude A is as follows:
7.1) to get time span be T0 the second sliding window, obtains the amplitude upper limit ATmaxi that signal reaches in each sliding window;
7.2) A is the maximum of ATmaxi in all sliding windows.
8. described electric shock signal detection method according to claim 7 is characterized in that, described T0 is 1～3 second.
9. described electric shock signal detection method according to claim 1, it is characterized in that, in described step 1.1) also comprise before: ecg signal data D is divided into k wicket take the t1 duration as unit, difference in magnitude and the 4th amplitude threshold A2 contrast with wicket, if the difference in magnitude of wicket, thinks then that this wicket is the horizontal segment wicket less than the 4th amplitude threshold A2; The number sn of statistics horizontal segment wicket if greater than first number threshold value N1, then be judged to be can not electric shock signal for sn, finishes; Otherwise enter next step.
10. described electric shock signal detection method according to claim 9 is characterized in that, described the 4th amplitude threshold A2 is 0.01～0.03mV.
11. described electric shock signal detection method is characterized in that according to claim 1, described step 1.3) further comprise:
The first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1 are set, satisfy P0＜P1, T0＜T1; If P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step.
12. described electric shock signal detection method is characterized in that according to claim 1, described step 1.3) further comprise:
The first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1, the 5th parameter threshold P2, the 6th parameter threshold P3, the 7th parameter threshold T2, the 8th parameter threshold T3 are set, satisfy P0＜P2＜P3＜P1, T0＜T2＜T3＜T1; If P＜P2 and T＜T2 or P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P3 and T＞T3 or P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step.
13. according to claim 11 or 12 described electric shock signal detection methods, it is characterized in that, described heart rate detection step is specially: judge whether heart rate surpasses 160bpm, if, then be judged to electric shock signal, finish; Otherwise being judged as can not electric shock signal, finishes.
14. described electric shock signal detection method is characterized in that according to claim 13, the obtaining step of described heart rate is as follows:
14.1) setting the 5th amplitude threshold CF1 initial value;
14.2) if the ecg signal data difference greater than the 5th amplitude threshold CF1, simultaneously amplitude is then thought the R ripple greater than default the 6th amplitude threshold A3; Automatically upgrade the 5th amplitude threshold CF1 according to the R wave amplitude;
14.3) after ecg signal data D detect to finish, calculate the R wave spacing, if the R wave spacing, then judges have undetectedly in the described R wave spacing zone greater than very first time threshold value t5, undetected R wave spacing zone is detected according to above-mentioned steps again;
14.4) number of statistics R ripple, calculate and obtain described heart rate.
15. the checkout gear of an electric shock signal is characterized in that, comprises that the first parameter obtains module, the second parameter obtains module and judge module;
Described the first parameter obtains module, according to input ecg signal data D, is that the window of the m described input ecg signal data D of intercepting that slides obtains some the first window signal y with time span
i(m), to described the first window signal y
i(m) carry out Delay reconstruction and obtain the first reconstruction point, obtain first parameter P of described ecg signal data D; Described the second parameter obtains module, by setting a window function, input ecg signal data D is divided into some sections by sliding window, every section multiply by window function, with amplitude normalization and convert string of binary characters to, by the number of characters percentage ratio of statistics normalization string of binary characters amplitude greater than the first amplitude threshold, calculate another parameter T of ecg signal data D;
Whether described judge module falls into default parameter threshold range according to parameter P and parameter T, determines whether electric shock signal.
16. the checkout gear of described electric shock signal is characterized in that according to claim 15, the acquisition that described the first parameter obtains first parameter P in the module specifically comprises:
With described the first window signal y
i(m) resampling obtains resampling signal z
i(m
1);
To described resampling signal z
i(m
1) adopt in the following method reconstruct: with z
i(m
1) as the x axial coordinate, with z
i(m
1+ τ) as y axle vertical coordinate, draw the first reconstruction point, wherein, 0＜m
1＜m-τ;
Cover all described first reconstruction point with one 40 * 40 grid, the grid number that is occupied by described the first reconstruction point and the ratio of possessive case subnumber are first parameter P of described ecg signal data D.。
17. the checkout gear of described electric shock signal is characterized in that according to claim 15, the acquisition that described the second parameter obtains another parameter T in the module specifically comprises:
Set window data data_parat_w;
Take width as t7 second, sliding time divides ecg signal data D as the first sliding window of t8 second, then ecg signal data D is divided into some groups of data segments;
Multiply by window data data_parat_w for every group of data segment;
Multiply by the data segment normalization of window data data_parat_w and be converted into string of binary characters above-mentioned;
The statistics string of binary characters is greater than the second amplitude threshold V
0Number of characters percentage ratio;
Above-mentioned number of characters percentage ratio is accumulated, obtained parameter T.
18. the checkout gear of described electric shock signal is characterized in that according to claim 15, described judge module specifically comprises:
The first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1 are set, satisfy P0＜P1, T0＜T1; If P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step.
19. the checkout gear of described electric shock signal is characterized in that according to claim 15, described judge module specifically comprises:
The first parameter threshold P0, the second parameter threshold P1, the 3rd parameter threshold T0, the 4th parameter threshold T1, the 5th parameter threshold P2, the 6th parameter threshold P3, the 7th parameter threshold T2, the 8th parameter threshold T3 are set, satisfy P0＜P2＜P3＜P1, T0＜T2＜T3＜T1; If P＜P2 and T＜T2 or P＜P0 or T＜T0, then being judged to can not electric shock signal, finishes; If P＞P3 and T＞T3 or P＞P1 or T＞T1 are judged to electric shock signal, finish; Otherwise, carry out the heart rate detection step.
20. the checkout gear of described electric shock signal is characterized in that according to claim 15, further comprises the heart rate detection module: judge whether heart rate surpasses 160bpm, if, then be judged to electric shock signal, finish; Otherwise being judged as can not electric shock signal, finishes.
21. the checkout gear of described electric shock signal is characterized in that according to claim 20, further comprises the heart rate acquisition module: set the 5th amplitude threshold CF1 initial value, if the ecg signal data difference is greater than the 5th amplitude threshold CF1; After ecg signal data D detect to finish, calculate the R wave spacing, if the R wave spacing, then judges have undetectedly in the described R wave spacing zone greater than very first time threshold value t5, undetected R wave spacing zone is detected according to above-mentioned steps again; The number of statistics R ripple is calculated and is obtained described heart rate.
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