CN110236527A - A kind of method and device obtaining respiration information - Google Patents
A kind of method and device obtaining respiration information Download PDFInfo
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- CN110236527A CN110236527A CN201910605059.6A CN201910605059A CN110236527A CN 110236527 A CN110236527 A CN 110236527A CN 201910605059 A CN201910605059 A CN 201910605059A CN 110236527 A CN110236527 A CN 110236527A
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/24—Detecting, measuring or recording bioelectric or biomagnetic signals of the body or parts thereof
- A61B5/316—Modalities, i.e. specific diagnostic methods
- A61B5/318—Heart-related electrical modalities, e.g. electrocardiography [ECG]
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7203—Signal processing specially adapted for physiological signals or for diagnostic purposes for noise prevention, reduction or removal
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/725—Details of waveform analysis using specific filters therefor, e.g. Kalman or adaptive filters
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7235—Details of waveform analysis
- A61B5/7253—Details of waveform analysis characterised by using transforms
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/72—Signal processing specially adapted for physiological signals or for diagnostic purposes
- A61B5/7271—Specific aspects of physiological measurement analysis
Abstract
The present invention provides a kind of method and device for obtaining respiration information, and the method for the acquisition respiration information includes: to obtain electrocardiosignal sample；Filter out the interference signal in electrocardiosignal sample；The characteristic point of electrocardiosignal sample is detected and obtained according to wavelet transformation；The random noise in electrocardiosignal sample is eliminated using each histogram that the number and peak value of each characteristic point are formed；The first respiration information in electrocardiosignal sample is obtained according to characteristic point；The high-frequency noise for filtering out the respiration information obtains the second respiration information.A series of calculating is carried out by obtaining multiple characteristic points, and to multiple characteristic points, to extract the first respiration information from electrocardiosignal sample；Under the premise of filtering out the anti-jamming signal of electrocardiosignal sample, multiple characteristic points can also remove the random noise of electrocardiosignal sample by using histogram, so not only accuracy is higher for the breath signal of acquisition, but also anti-interference ability is stronger without in the case where any sensor.
Description
Technical field
The present invention relates to signal processing technology fields, particularly relate to a kind of method and device for obtaining respiration information.
Background technique
Electrocardiogram (electrocardiogram, abbreviation ECG) refers to heart in each cardiac cycle, by pacemaker, the heart
Room, ventricle are in succession excited, along with bioelectric variation, draw the potential change of diversified forms from body surface by electrocardiograph
Figure.The electrocardiosignal of electrocardiogram not only contains the functional information of heart, but also contains the information of human body other systems,
Such as the respiration information of respiratory system.With the development of technology, people have been able to extract respiration information (ECG- from electrocardiosignal
DerivedRespiration, abbreviation EDR), by analyzing breath signal, it will be appreciated that the respiratory state of user, detection breathing
Disease.
It is existing from electrocardiosignal obtain respiration information method be utilized respectively R-wave amplitude, RS amplitude, T wave amplitude,
QRS area or RR interphase equivalence obtain；But this method has only used the shape information of part electrocardiosignal, due to exhaling
Movable influence is inhaled, corresponding change can occur for P, Q, R, S, T wave in electrocardiosignal, so this obtain from electrocardiosignal
The accuracy of the method for respiration information and anti-interference ability are relatively low.
Summary of the invention
The purpose of the present invention is to provide a kind of method and devices for obtaining respiration information, to solve in the prior art from the heart
The relatively low problem of the method accuracy and anti-interference ability of the respiration information obtained in electric signal.
According in a first aspect, the embodiment of the present invention provides a kind of method for obtaining respiration information, comprising: obtain electrocardio letter
Number sample；Filter out the interference signal in the electrocardiosignal sample；It is detected according to wavelet transformation and obtains the electrocardiosignal sample
This characteristic point；It is eliminated using each histogram that the number and peak value of each characteristic point are formed random in the electrocardiosignal sample
Noise；The respiration information in the electrocardiosignal sample is obtained according to the characteristic point；Filter out the height of first respiration information
Frequency noise obtains the second respiration information.
In one embodiment, the step of filtering out the interference signal in electrocardiosignal sample, comprising: filtered using mean filter
Except the Hz noise in the electrocardiosignal sample；Flesh in the electrocardiosignal sample is filtered out using lifting wavelet transform method
Electrical interference；Baseline drift in the electrocardiosignal sample is filtered out using function-fitting method.
In one embodiment, the characteristic point includes: P crest value, Q crest value, R crest value, S crest value, T crest value with
And time value between RR；The first respiration information in the electrocardiosignal sample is obtained according to the characteristic point, comprising: according to the heart
The P crest value in multiple heart beat cycles and multiple heart beat cycles in electric signal sample, Q crest value, R crest value, S wave
Peak value, T crest value and RR interphase constitute the first matrix of m*6 dimension；Wherein, m characterizes multiple heart beat cycles；
First matrix is indicated by following formula:
X (m)=[x1(m) x2(m) x3(m) x4(m) x5(m) x6(m)],
Wherein, X (m) characterizes the first matrix；x1(m)Characterize the P wave crest of each heart beat cycle in multiple heart beat cycles
Value；x2(m)Characterize the Q crest value of each heart beat cycle in multiple heart beat cycles；x3(m)It is characterized in multiple heart beat cycles
In each heart beat cycle R crest value；x4(m)It is characterized in the S crest value of each heart beat cycle in multiple heart beat cycles；x5(m)
It is characterized in the T crest value of each heart beat cycle in multiple heart beat cycles；x6(m)It is characterized in multiple heart beat cycles every
Time value between the RR of a heart beat cycle.
In one embodiment, the first respiration information in the electrocardiosignal sample is obtained according to the characteristic point, also wrapped
It includes: according to each heartbeat in the P crest value of each heart beat cycle in the multiple heart beat cycle, multiple heart beat cycles
It is the R crest value of each heart beat cycle in the Q crest value in period, multiple heart beat cycles, each in multiple heart beat cycles
In the S crest value of heart beat cycle, multiple heart beat cycles in the T crest value and multiple heart beat cycles of each heart beat cycle
Between the RR of each heart beat cycle time value calculate separately in the multiple heart beat cycles average value of P crest value, R crest value it is flat
Mean value, the average value of S crest value, the average value of T crest value and the average value of RR interphase；
Institute is subtracted according to each P crest value in the multiple heart beat cycle in the P crest value of each heart beat cycle
State the average value of P crest value, each Q crest value in the multiple heart beat cycle in the Q crest value of each heart beat cycle
Subtract the average value of the Q crest value, each R in the multiple heart beat cycle in the R crest value of each heart beat cycle
Crest value subtracts the average value of the R crest value, in the multiple heart beat cycle in the S crest value of each heart beat cycle
Each S crest value subtract the average value of the S crest value, in the multiple heart beat cycle each heart beat cycle T wave crest
Each T crest value in value subtracts each heartbeat week in the average value and the multiple heart beat cycle of the T crest value
Time value subtracts the average value of time value between the RR between each RR between the RR of phase in time value, obtains the second matrix；Pass through following public affairs
Formula indicates second matrix:
X ' (m)=[x '1(m) x′2(m) x′3(m) x′4(m) x′5(m) x′6(m)],
Wherein, X ' (m) characterizes the second matrix；x′1(m)It is characterized in x1(m)In multiple P crest values subtract the P crest value
After average value, obtained numerical value；x′2(m)It is characterized in x2(m)In multiple Q crest values subtract the Q crest value average value it
Afterwards, the numerical value obtained；x′3(m)It is characterized in x3(m)In multiple R crest values subtract the average value of the R crest value after, obtain
Numerical value；x′4(m)It is characterized in x4(m)In multiple S crest values subtract the average value of the S crest value after, obtained numerical value；
x′5(m)It is characterized in x5(m)In multiple T crest values subtract the average value of the T crest value after, obtained numerical value；x′6(m)Characterization
In x6(m)In multiple RR between time value subtract the numerical value after the average value of time value, obtained between the multiple RR.
In one embodiment, the first respiration information in the electrocardiosignal sample is obtained according to the characteristic point, also wrapped
It includes: obtaining the covariance matrix of second matrix；The covariance matrix of second matrix is indicated by following formula:
Wherein, C characterizes the covariance matrix of the second matrix；x′j(m)Characterize the x ' in second matrix1(m)To x '6(m)'s
Numerical value.
In one embodiment, the first respiration information in the electrocardiosignal sample is obtained according to the characteristic point, also wrapped
It includes: calculating the feature vector and characteristic value of electrocardiosignal sample according to the covariance matrix of second matrix；Pass through following public affairs
Formula calculates described eigenvector and characteristic value:
λ ν=Cv,
Wherein, v characterizes described eigenvector, expression formula are as follows: v=[ν1 ν2 ν3 ν4 ν5 ν6]；λ characterizes the characteristic value,
Expression formula are as follows: λ=[λ1 λ2 λ3 λ4 λ5 λ6]；The electrocardiosignal is calculated according to second matrix and described eigenvector
First respiration information of sample；It is calculated by the following formula the first respiration information of the electrocardiosignal sample:
Wherein, EDR characterizes the respiration information of the electrocardiosignal sample；K characterizes k-th of feature vector.
In one embodiment, the first of the electrocardiosignal sample is calculated according to second matrix and described eigenvector
Respiration information, further includes: be calculated by the following formula k-th of feature vector:
Wherein, k characterizes k-th of characteristic value.
According to second aspect, the embodiment of the present invention provides a kind of device for obtaining respiration information, comprising: electrocardiosignal sample
This acquisition module, for obtaining electrocardiosignal sample；Interference signal filters out module, for filtering out in the electrocardiosignal sample
Interference signal；Characteristic point detection obtains module, for detecting and obtaining the characteristic point of the electrocardiosignal sample；Random noise disappears
Except module, each histogram for number and peak value formation using each characteristic point is eliminated random in the electrocardiosignal sample
Noise；Respiration information obtains module, for obtaining the first respiration information in the electrocardiosignal sample；High-frequency noise filters out mould
Block obtains the second respiration information for filtering out the high-frequency noise of the respiration information.
According to the third aspect, the embodiment of the present invention provides a kind of electronic equipment, comprising: memory and processor, it is described
Connection is communicated with each other between memory and the processor, computer instruction is stored in the memory, and the processor is logical
It crosses and executes the computer instruction, thereby executing the side of the acquisition respiration information as described in first aspect or its any embodiment
Method.
According to fourth aspect, the embodiment of the present invention provides a kind of computer readable storage medium, described computer-readable
Storage medium is stored with computer instruction, the computer instruction for make the computer thereby executing such as first aspect or its
The method of respiration information is obtained described in any embodiment.
The advantageous effects of the above technical solutions of the present invention are as follows:
The method for the acquisition respiration information that the embodiment of the present invention provides, comprising: obtain electrocardiosignal sample；Filter out electrocardio
Interference signal in sample of signal；The characteristic point of the electrocardiosignal sample is detected and obtained according to wavelet transformation；Utilize each spy
Each histogram that the number and peak value for levying point are formed eliminates the random noise in the electrocardiosignal sample；It is obtained according to characteristic point
The first respiration information in the electrocardiosignal sample；The high-frequency noise for filtering out first respiration information, obtains the second breathing
Information.Wherein, the multiple characteristic point includes: P crest value, Q crest value, R crest value, S crest value, between T crest value and RR
Time value.It follows that carrying out a system by obtaining above-mentioned multiple characteristic points in multiple heart beat cycles and multiple heart beat cycles
The calculating of column, to extract the first respiration information from electrocardiosignal sample；Again due to filtering out the anti-dry of electrocardiosignal sample
Under the premise of disturbing signal, multiple characteristic points are further through the random noise for using histogram to eliminate electrocardiosignal sample；In order to make
Obtained respiration information is more accurate, it is also necessary to which the high-frequency noise for filtering out first respiration information finally obtains accurate
Two respiration informations；So not only accuracy is higher for the breath signal of acquisition, but also anti-interference without in the case where any sensor
Ability is stronger.
Detailed description of the invention
Fig. 1 shows the flow charts of a specific example of the method for the acquisition respiration information of the embodiment of the present invention；
Fig. 2 indicates the flow chart of the step 2 of the method for the acquisition respiration information of the embodiment of the present invention shown in FIG. 1；
Fig. 3 indicates the flow chart of the step 5 of the method for the acquisition respiration information of the embodiment of the present invention shown in FIG. 1；
Fig. 4 indicates the schematic diagram of the device of the acquisition respiration information of the embodiment of the present invention；
Fig. 5 indicates the connection figure of electronic equipment provided in an embodiment of the present invention.
Specific embodiment
Technical solution of the present invention is clearly and completely described below in conjunction with attached drawing, it is clear that described implementation
Example is a part of the embodiment of the present invention, instead of all the embodiments.Based on the embodiments of the present invention, ordinary skill
Personnel's every other embodiment obtained without making creative work, shall fall within the protection scope of the present invention.
In the description of the present invention, it should be noted that unless otherwise clearly defined and limited, term " installation ", " phase
Even ", " connection " shall be understood in a broad sense, for example, it may be being fixedly connected, may be a detachable connection, or be integrally connected；It can
To be mechanical connection, it is also possible to be electrically connected；It can be directly connected, can also indirectly connected through an intermediary, it can be with
It is the connection inside two elements, can be wireless connection, be also possible to wired connection.For those of ordinary skill in the art
For, the concrete meaning of above-mentioned term in the present invention can be understood with concrete condition.
As long as in addition, the non-structure each other of technical characteristic involved in invention described below different embodiments
It can be combined with each other at conflict.
As shown in Figure 1, the embodiment of the present invention provides a kind of method for obtaining respiration information, comprising:
Step S1: electrocardiosignal sample is obtained；Electrocardiosignal sample refers to the real heartbeat acquired by Electrocardial signal acquisition device
The sample of signal of generation can be indicated with wave image；
Step S2: the interference signal in electrocardiosignal sample is filtered out；Interference signal specifically includes that Hz noise, myoelectricity are dry
It disturbs and baseline drift；
Step S3: the characteristic point of electrocardiosignal sample is detected and obtained according to wavelet transformation；Three are utilized based on wavelet transformation
The extreme point of original signal is converted into wavelet field zero crossing by secondary spline wavelets characteristic, utilizes the time domain of electrocardiosignal simultaneously later
Feature and small echo characteristic of field carry out characteristic point detection；Wavelet Transform, which also passes through, to be adaptively arranged threshold value, utilizes refractory period condition
Detection accuracy is improved, 98% Detection accuracy has been reached to the acquisition of characteristic points multiple in electrocardiosignal；Therefore using small
Wave conversion method obtains the detection of electrocardiosignal multi-characteristic points, and not only arithmetic speed is fast, but also detection accuracy is high.
Step S4: it is eliminated using each histogram that the number and peak value of each characteristic point are formed random in electrocardiosignal sample
Noise；Histogram is the coordinate diagram of character pair point, and abscissa represents the peak amplitude value of character pair point, ordinate representative pair
Answer the number of the identical peak amplitude value of characteristic point；When using histogram, corresponding to the maximum value of ordinate in histogram
Abscissa on the basis of, to from left to right find two threshold values, it is ensured that the data volume among the two threshold values accounts for total amount of data
98%, finally the peak amplitude value above or below the character pair point of upper lower threshold value will be corrected supreme lower threshold value, i.e., will
The smaller peak amplitude value of character pair point is adjusted to threshold range.
Step S5: the first respiration information in electrocardiosignal sample is obtained according to characteristic point.Obtain the first respiration information it
Afterwards, in order to keep the first respiration information consistent with the frequency of electrocardiosignal sample, it is also necessary to pass through the first obtained respiration information
Cubic spline interpolation is by frequency interpolation to 250HZ；
Step S6: the high-frequency noise of first respiration information is filtered out, the second respiration information is obtained；Due to the first of acquisition
All there is high-frequency noise in respiration information, in order to enable the final respiration information arrived is more accurate, so needing to remove the first breathing
The high-frequency noise of information obtains accurate second respiration information.
It follows that carrying out one by obtaining above-mentioned multiple characteristic points in multiple heart beat cycles and multiple heart beat cycles
The calculating of series, to extract the first respiration information from electrocardiosignal sample；Again due to filtering out the anti-of electrocardiosignal sample
Under the premise of interference signal, multiple characteristic points are further through the random noise for using histogram to eliminate electrocardiosignal sample；In order to
The final respiration information made is more accurate, it is also necessary to which the high-frequency noise for filtering out first respiration information obtains accurately
Second respiration information；So without in the case where any sensor, not only accuracy is higher for the breath signal of acquisition, but also anti-dry
It is stronger to disturb ability.
In one embodiment, as shown in Fig. 2, above-mentioned steps S2, the step of filtering out the interference signal in electrocardiosignal sample,
It specifically includes:
Step S21: the Hz noise in electrocardiosignal sample is filtered out using mean filter；Hz noise can be used
Value filter removal, also can be used notch filter method removal, but due in mean square error, postman than two aspect mean filters
It is superior to notch filter, and in terms of weakening R crest value, the treatment effect of mean filter is better than notch filter method, i.e.,
The weakening effect of mean filter is less than notch filter method；So selecting mean filter to filter out when filtering out Hz noise；
Step S22: the myoelectricity interference in electrocardiosignal sample is filtered out using lifting wavelet transform method；Myoelectricity interference belongs to
High-frequency Interference can be used Wavelet transformation method and be filtered out, and lifting wavelet transform method is changed on the basis of Wavelet Transform
Made of；Under the premise of identical time-frequency characteristic, lifting wavelet transform method is substantially better than wavelet transformation in terms of arithmetic speed
Method；So using lifting wavelet transform method when filtering out myoelectricity interference；
Step S23: the baseline drift in electrocardiosignal sample is filtered out using function-fitting method；The bearing calibration of baseline drift
Including shape filtering, median filtering and function-fitting method etc.；When electrocardiosignal is based on the bat of the normal heart, High-frequency Interference is less
When, the real-time and accuracy of function-fitting method are superior to shape filtering method and median filtering method；So filtering out baseline drift
Shi Caiyong uses fitting function method.
It should be noted that when executing above-mentioned steps S21 to step S23, it is not limited to above-mentioned execute sequence.
In one embodiment, features described above point includes: P crest value, Q crest value, R crest value, S crest value, T crest value with
And time value between RR；
As shown in figure 3, above-mentioned steps S5, the step of respiration information in electrocardiosignal sample is obtained according to characteristic point, tool
Body includes:
Step S51, according to the P crest value in the multiple heart beat cycles and multiple heart beat cycles in electrocardiosignal sample, Q
Crest value, R crest value, S crest value, T crest value and RR interphase constitute the first matrix of m*6 dimension；
Wherein, m characterizes multiple heart beat cycles；It generally takes m to be more than or equal to 6, that is, is not less than 6 heart beat cycles；So obtaining
When coring electric signal sample, the heart beat cycle number for including is also otherwise less than 6；
The first matrix is indicated by following formula:
X (m)=[x1(m) x2(m) x3(m) x4(m) x5(m) x6(m)],
Wherein, X (m) characterizes the first matrix that multiple characteristic points in m period are constituted；x1(m)M numerical value is characterized, i.e. m is a
The P crest value of each heart beat cycle in heart beat cycle；x2(m)M numerical value is characterized, i.e. each heart beat cycle in m heart beat cycle
Q crest value；x3(m)M numerical value is characterized, i.e. the R crest value of each heart beat cycle in m heart beat cycle；x4(m)M numerical value is characterized,
That is the S crest value of each heart beat cycle in m heart beat cycle；x5(m)Characterize m numerical value, i.e. each heartbeat in m heart beat cycle
The T crest value in period；x6(m)M numerical value is characterized, i.e. time value between the RR of each heart beat cycle in m heart beat cycle.
Step S52, according to each heartbeat in the P crest value of heart beat cycle each in m heart beat cycle, m heart beat cycle
The R crest value of each heart beat cycle in the Q crest value in period, m heart beat cycle, in m heart beat cycle each heart beat cycle S
In crest value, m heart beat cycle in the T crest value and m heart beat cycle of each heart beat cycle each heart beat cycle RR interphase
Value calculates separately the average value of the average value of P crest value, R crest value in m heart beat cycle, the average value of S crest value, T wave
The average value of peak value and the average value of RR interphase；
Step S53 subtracts P wave according to each P crest value in the P crest value of heart beat cycle each in m heart beat cycle
Each Q crest value in the average value of peak value, m heart beat cycle in the Q crest value of each heart beat cycle subtracts the flat of Q crest value
Each R crest value in mean value, m heart beat cycle in the R crest value of each heart beat cycle subtracts the average value of R crest value, m
Each S crest value in heart beat cycle in the S crest value of each heart beat cycle subtracts the average value of S crest value, m heart beat cycle
In each heart beat cycle T crest value in each T crest value subtract in the average value and m heart beat cycle of T crest value it is every
Time value subtracts the average value of time value between RR between each RR between the RR of a heart beat cycle in time value, obtains the second matrix；
The second matrix is indicated by following formula:
X ' (m)=[x '1(m) x′2(m) x′3(m) x′4(m) x′5(m) x′6(m)
Wherein, X ' (m) characterizes the second matrix；x′1(m)It is characterized in x1(m)In multiple P crest values subtract being averaged for P crest value
After value, obtained numerical value；x′2(m)It is characterized in x2(m)In multiple Q crest values subtract the average value of Q crest value after, obtain
Numerical value；x′3(m)It is characterized in x3(m)In multiple R crest values subtract the average value of R crest value after, obtained numerical value；x′4(m)Table
Sign is in x4(m)In multiple S crest values subtract the average value of S crest value after, obtained numerical value；x′5(m)It is characterized in x5(m)In
After multiple T crest values subtract the average value of T crest value, obtained numerical value；x′6(m)It is characterized in x6(m)In multiple RR between time value
Subtract the numerical value after the average value of time value, obtained between RR.
It should be noted that multiple heart beat cycles shown in Fig. 4 are above-mentioned m heart beat cycle.
Step S54 obtains the covariance matrix of the second matrix；
The covariance matrix of the second matrix is indicated by following formula:
Wherein, C characterizes the covariance matrix of the second matrix；x′j(m)Characterize the x ' in the second matrix1(m)To x '6(m)Number
Value；x′j(m) TCharacterize the transposition of the second matrix.
Step S55 calculates the feature vector and characteristic value of electrocardiosignal sample according to the covariance matrix of the second matrix；
It is calculated by the following formula feature vector and characteristic value:
λ ν=Cv,
Wherein, v characteristic feature vector, expression formula are as follows: v=[ν1 ν2 ν3 ν4 ν5 ν6]；λ characteristic feature value, expression formula
Are as follows: λ=[λ1 λ2 λ3 λ4 λ5 λ6]。
It should be noted that features described above vector v is ranked up according to the size of corresponding characteristic value.
Step S56 calculates the first respiration information of electrocardiosignal sample according to the second matrix and feature vector；
It is calculated by the following formula the first respiration information of electrocardiosignal sample:
Wherein, EDR characterizes the respiration information of electrocardiosignal sample；K characterizes k-th of feature vector.
It is calculated by the following formula k-th of feature vector:
Wherein, k characterizes k-th of characteristic value；
The value that k is obtained by above formula substitutes into k valueIt can obtain respiration information.
The embodiment of the present invention also provides a kind of device for obtaining respiration information, as shown in Figure 4, comprising: electrocardiosignal sample
Module 1 is obtained, for obtaining electrocardiosignal sample, the correlation that detailed content refers to the step S1 of above method embodiment is retouched
It states；Interference signal filters out module 2, and for filtering out the interference signal in the electrocardiosignal sample, detailed content refers to above-mentioned
The associated description of the step S2 of embodiment of the method；Characteristic point detection obtains module 3, for detecting and obtaining the electrocardiosignal sample
This characteristic point, detailed content refer to the associated description of the step S3 of above method embodiment；Random noise cancellation module 4,
Each histogram for number and peak value formation using each characteristic point eliminates the random noise in the electrocardiosignal sample, in detail
Thin content refers to the associated description of the step S4 of above method embodiment；Respiration information obtains module 5, for obtaining the heart
The first respiration information in electric signal sample, detailed content refer to the associated description of the step S5 of above method embodiment；It is high
Frequency noise filtering module 6 obtains the second respiration information, detailed content please join for filtering out the high-frequency noise of the respiration information
See the associated description of the step S6 of above method embodiment.
Module 2 is filtered out by electrocardiosignal sample acquisition module 1, interference signal, characteristic point detection obtains module 3, breathing
Data obtaining module 4 and high-frequency noise filter out module 5 and finally obtain accurate respiration information；Specifically, being detected by characteristic point
Multiple characteristic points after the acquisition acquisition filtering interference signals of module 3 in electrocardiosignal sample, multiple characteristic points pass through again makes an uproar at random
Sound cancellation module removes the random noise of electrocardiosignal sample, carries out a series of calculating to multiple characteristic points later, thus real
The first respiration information is now obtained from electrocardiosignal sample；Because all there is high-frequency noise in the first respiration information of acquisition, in order to
The first respiration information made is more accurate, so needing to remove the high-frequency noise of the first respiration information, it is accurate to finally obtain
The second respiration information.Since the first respiration information waveform of acquisition is relatively simple, in frequency set；So principle letter can be used
Single low-pass filter can filter out the high-frequency noise in respiration information；Certainly, in the case where not influencing effect of the present invention,
High-frequency noise can also be removed using other devices；So the breath signal of acquisition is not without in the case where any sensor
Only accuracy is higher, and anti-interference ability is stronger.
The embodiment of the invention also provides a kind of electronic equipment, as shown in figure 5, the electronic equipment may include processor 41
With memory 42, wherein processor 41 can be connected with memory 42 by bus or other modes, to pass through bus in Fig. 5
For connection.
Processor 41 can be central processing unit (Central Processing Unit, CPU).Processor 41 can be with
For other general processors, digital signal processor (Digital Signal Processor, DSP), specific integrated circuit
(Application Specific Integrated Circuit, ASIC), field programmable gate array (Field-
Programmable Gate Array, FPGA) either other programmable logic device, discrete gate or transistor logic,
The combination of the chips such as discrete hardware components or above-mentioned all kinds of chips.
Memory 42 is used as a kind of non-transient computer readable storage medium, can be used for storing non-transient software program, non-
Transient computer executable program and module, as the corresponding program of video data handling procedure in the embodiment of the present invention refers to
Order/module.Non-transient software program, instruction and the module that processor 41 is stored in memory 42 by operation, to hold
The various function application and data processing of row processor, the i.e. side of acquisition respiration information in realization above method embodiment
Method.
Memory 42 may include storing program area and storage data area, wherein storing program area can storage program area,
Application program required at least one function；It storage data area can the data etc. that are created of storage processor 41.In addition, storage
Device 42 may include high-speed random access memory, can also include non-transient memory, for example, at least a magnetic disk storage
Part, flush memory device or other non-transient solid-state memories.In some embodiments, it includes relative to place that memory 42 is optional
The remotely located memory of device 41 is managed, these remote memories can pass through network connection to processor 41.The reality of above-mentioned network
Example includes but is not limited to internet, intranet, local area network, mobile radio communication and combinations thereof.
Above-mentioned electronic equipment detail can correspond to refering to fig. 1 into embodiment shown in 3 corresponding associated description and
Effect is understood that details are not described herein again.
It is that can lead to it will be understood by those skilled in the art that realizing all or part of the process in above-described embodiment method
Computer program is crossed to instruct relevant hardware and complete, the program can be stored in a computer-readable storage medium
In, the program is when being executed, it may include such as the process of the embodiment of above-mentioned each method.Wherein, the storage medium can for magnetic disk,
CD, read-only memory (Read-Only Memory, ROM), random access memory (Random Access
Memory, RAM), flash memory (Flash Memory), hard disk (Hard Disk Drive, abbreviation: HDD) or solid state hard disk
(Solid-State Drive, SSD) etc.；The storage medium can also include the combination of the memory of mentioned kind.
The above is a preferred embodiment of the present invention, it is noted that for those skilled in the art
For, without departing from the principles of the present invention, it can also make several improvements and retouch, these improvements and modifications
It should be regarded as protection scope of the present invention.
Claims (10)
1. a kind of method for obtaining respiration information characterized by comprising
Obtain electrocardiosignal sample；
Filter out the interference signal in the electrocardiosignal sample；
The characteristic point of the electrocardiosignal sample is detected and obtained according to wavelet transformation；
Making an uproar in the electrocardiosignal sample at random is eliminated using each histogram that the number and peak value of each characteristic point are formed
Sound；
The first respiration information in the electrocardiosignal sample is obtained according to the characteristic point；
The high-frequency noise for filtering out first respiration information, obtains the second respiration information.
2. the method according to claim 1 for obtaining respiration information, which is characterized in that filter out dry in electrocardiosignal sample
The step of disturbing signal, comprising:
The Hz noise in the electrocardiosignal sample is filtered out using mean filter；
Myoelectricity interference in the electrocardiosignal sample is filtered out using lifting wavelet transform method；
Baseline drift in the electrocardiosignal sample is filtered out using function-fitting method.
3. the method according to claim 2 for obtaining respiration information, which is characterized in that the characteristic point includes: P wave crest
Value, Q crest value, R crest value, S crest value, time value between T crest value and RR；
The first respiration information in the electrocardiosignal sample is obtained according to the characteristic point, comprising:
According to the P crest value in the multiple heart beat cycles and multiple heart beat cycles in the electrocardiosignal sample, Q wave crest
Value, R crest value, S crest value, T crest value and RR interphase constitute the first matrix of m*6 dimension；
Wherein, m characterizes multiple heart beat cycles；
First matrix is indicated by following formula:
X (m)=[x1(m) x2(m) x3(m) x4(m) x5(m) x6(m)],
Wherein, X (m) characterizes the first matrix；x1(m)Characterize the P crest value of each heart beat cycle in multiple heart beat cycles；x2(m)
Characterize the Q crest value of each heart beat cycle in multiple heart beat cycles；x3(m)It is characterized in multiple heart beat cycles each
The R crest value of heart beat cycle；x4(m)It is characterized in the S crest value of each heart beat cycle in multiple heart beat cycles；x5(m)It is characterized in
The T crest value of each heart beat cycle in multiple heart beat cycles；x6(m)It is characterized in each heartbeat in multiple heart beat cycles
Time value between the RR in period.
4. the method according to claim 3 for obtaining respiration information, which is characterized in that according to characteristic point acquisition
The first respiration information in electrocardiosignal sample, further includes:
According to each heart in the P crest value of each heart beat cycle in the multiple heart beat cycle, multiple heart beat cycles
It is the R crest value of each heart beat cycle in the Q crest value of hop cycle, multiple heart beat cycles, every in multiple heart beat cycles
The T crest value and multiple heart beat cycles of each heart beat cycle in the S crest value of a heart beat cycle, multiple heart beat cycles
In each heart beat cycle RR between time value calculate separately in the multiple heart beat cycles average value of P crest value, R crest value
Average value, the average value of S crest value, the average value of T crest value and the average value of RR interphase；
The P wave is subtracted according to each P crest value in the multiple heart beat cycle in the P crest value of each heart beat cycle
Each Q crest value in the average value of peak value, the multiple heart beat cycle in the Q crest value of each heart beat cycle subtracts institute
State the average value of Q crest value, each R crest value in the multiple heart beat cycle in the R crest value of each heart beat cycle
Subtract the average value of the R crest value, each S in the multiple heart beat cycle in the S crest value of each heart beat cycle
Crest value subtracts the average value of the S crest value, in the multiple heart beat cycle in the T crest value of each heart beat cycle
Each T crest value subtracts the RR of each heart beat cycle in the average value and the multiple heart beat cycle of the T crest value
Between between each RR in time value time value subtract the average value of time value between the RR, obtain the second matrix；
Second matrix is indicated by following formula:
X ' (m)=[x '1(m) x′2(m) x′3(m) x′4(m) x′5(m) x′6(m)],
Wherein, X ' (m) characterizes the second matrix；x′1(m)It is characterized in x1(m)In multiple P crest values subtract being averaged for the P crest value
After value, obtained numerical value；x′2(m)It is characterized in x2(m)In multiple Q crest values subtract the average value of the Q crest value after, obtain
The numerical value arrived；x′3(m)It is characterized in x3(m)In multiple R crest values subtract the average value of the R crest value after, obtained numerical value；
x′4(m)It is characterized in x4(m)In multiple S crest values subtract the average value of the S crest value after, obtained numerical value；x′5(m)Characterization
In x5(m)In multiple T crest values subtract the average value of the T crest value after, obtained numerical value；x′6(m)It is characterized in x6(m)In
Multiple RR between time value subtract the numerical value after the average value of time value, obtained between the multiple RR.
5. the method according to claim 4 for obtaining respiration information, which is characterized in that according to characteristic point acquisition
The first respiration information in electrocardiosignal sample, further includes:
Obtain the covariance matrix of second matrix；
The covariance matrix of second matrix is indicated by following formula:
Wherein, C characterizes the covariance matrix of the second matrix；x′j(m)Characterize the x ' in second matrix1(m)To x '6(m)Number
Value.
6. the method according to claim 5 for obtaining respiration information, which is characterized in that according to characteristic point acquisition
The first respiration information in electrocardiosignal sample, further includes:
The feature vector and characteristic value of electrocardiosignal sample are calculated according to the covariance matrix of second matrix；
It is calculated by the following formula described eigenvector and characteristic value:
λ v=Cv,
Wherein, v characterizes described eigenvector, expression formula are as follows: v=[v1 v2 v3 v4 v5 v6]；λ characterizes the characteristic value, expression
Formula are as follows: λ=[λ1 λ2 λ3 λ4 λ5 λ6]。
7. the method according to claim 6 for obtaining respiration information, which is characterized in that according to characteristic point acquisition
The first respiration information in electrocardiosignal sample, further includes:
The first respiration information of the electrocardiosignal sample is calculated according to second matrix and described eigenvector；
It is calculated by the following formula the first respiration information of the electrocardiosignal sample:
Wherein, EDR characterizes the respiration information of the electrocardiosignal sample；K characterizes k-th of feature vector；
It is calculated by the following formula k-th of feature vector:
Wherein, k characterizes k-th of characteristic value.
8. a kind of device for obtaining respiration information characterized by comprising
Electrocardiosignal sample acquisition module, for obtaining electrocardiosignal sample；
Interference signal filters out module, for filtering out the interference signal in the electrocardiosignal sample；
Characteristic point detection obtains module, for detecting and obtaining the characteristic point of the electrocardiosignal sample；
Random noise cancellation module, each histogram for number and peak value formation using each characteristic point are eliminated the electrocardio and are believed
Random noise in number sample；
Respiration information obtains module, for obtaining the first respiration information in the electrocardiosignal sample；
High-frequency noise filters out module, for filtering out the high-frequency noise of first respiration information, obtains the second respiration information.
9. a kind of electronic equipment characterized by comprising
Memory and processor communicate with each other connection, are stored in the memory between the memory and the processor
Computer instruction, the processor are obtained by executing the computer instruction thereby executing claim 1-7 is described in any item
The method for taking respiration information.
10. a kind of computer readable storage medium, which is characterized in that the computer-readable recording medium storage has computer to refer to
It enables, the computer instruction is for making the computer thereby executing the described in any item acquisition respiration informations of claim 1-7
Method.
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