CN102525431A - Cardiovascular physiology signal detection device and method - Google Patents

Abstract

The invention provides a cardiovascular physiology signal detection device and a method, wherein the cardiovascular physiology signal detection device comprises an acquisition unit and a self-adaptive processing unit, the acquisition unit is used for collecting cardiovascular physiology signals, and the self-adaptive processing unit is used for treating the cardiovascular physiology signals in self adapting to obtain the cardiovascular physiology signals with maximum signal to interference and noise ratio. The cardiovascular physiology signal detection device in the embodiment obtains high-gain cardiovascular physiology signals by treating the cardiovascular physiology signals in self adapting, reduces influence of environment noise, and increases detection precision of the cardiovascular physiology signals. Users can complete detection of the cardiovascular physiology signals under unrestrained situation.

Description

Device and method for detecting cardiovascular physiological signals

technical field

The present invention relates to the technical field of medical devices, in particular to a detection device and method for cardiovascular physiological signals.

Background technique

Some patients with abnormal heart rhythm (atrial fibrillation) will regularly experience symptoms such as palpitations, dizziness, chest pain and dyspnea, but some patients rarely or never have symptoms, so they only rely on subjective feelings, so patients often do not receive timely diagnosis and treatment. treatment, which increases the risk of stroke.

In order to improve patients' awareness of abnormal heart rate (atrial fibrillation) and its risk of stroke, and provide an objective guarantee for patients to receive timely diagnosis and treatment and reduce the risk of stroke, it is necessary to detect heart rhythm and pulse wave velocity in time. Changes in vascular physiological signals, such as sudden rapid heart rate, too slow, irregular, short pulse (pulse frequency is less than heartbeat frequency), heartbeat ranging from strong to weak, and blood pressure changes and other symptoms. Therefore, there is a need for a device that does not rely on the patient's subjective feeling and can detect changes in cardiovascular physiological signals such as heart rate changes, pulse wave velocity, and blood pressure in time without restraint during daily activities.

However, conventional detection devices used in the prior art to detect heart rate, pulse wave, blood pressure and other cardiovascular physiological signals usually need to place, clamp or wear the detection device on the body of the person to be detected, which is likely to cause physical injury to the user. Discomfort or psychological tension, and the detected cardiovascular physiological signals are easily affected by the environment and there are too many noise signals, which makes the detected cardiovascular physiological signals inaccurate and easily causes delays in the user's condition.

Contents of the invention

In order to solve the above problems, the present invention provides a device and method for detecting cardiovascular physiological signals, which are used to solve the problem of inaccurate detection of cardiovascular physiological signals in the prior art.

To this end, the present invention provides a detection device for cardiovascular physiological signals, including: an acquisition unit and an adaptive processing unit;

The collection unit is used to collect cardiovascular physiological signals;

The adaptive processing unit is connected to the acquisition unit, and is used for adaptively processing the cardiovascular physiological signal to obtain the cardiovascular physiological signal with the largest signal-to-interference-noise ratio;

Among them, an analysis unit and an output unit are also included;

The analysis unit is connected to the adaptive processing unit, and is used to analyze and judge cardiovascular physiological parameters according to the cardiovascular physiological signal with the largest signal-to-interference-noise ratio;

The output unit is connected to the analysis unit for outputting the judgment result of the analysis unit.

Wherein, the acquisition unit includes: a heartbeat signal acquisition module and at least one pulse signal acquisition module;

The heartbeat signal collection module is used to collect heartbeat signals in cardiovascular physiological signals, and the heartbeat signal collection module includes at least two heartbeat signal collectors;

The pulse signal acquisition modules are used to acquire pulse signals in cardiovascular physiological signals, and each pulse signal acquisition module includes at least two pulse signal collectors.

Wherein, the heartbeat signal collector includes an analog-to-digital conversion channel, and the analog-to-digital conversion channel is used to convert the heartbeat signal into a digital signal;

The pulse signal collector includes an analog-to-digital conversion channel for converting the pulse signal into a digital signal.

Wherein, the adaptive processing unit includes: a heartbeat adaptive processing module and a pulse adaptive processing module;

The heartbeat adaptive processing module is used to perform adaptive processing on the heartbeat signal;

The pulse adaptive processing module is used for performing adaptive processing on the pulse signal.

Wherein, the heartbeat adaptive processing module includes: a phase adjustment submodule, an equalization processing submodule and a signal synthesis submodule;

The equalization processing submodule includes a filter channel group, which is used to perform matching filtering on the heartbeat signal collected by the heartbeat signal acquisition module with the filter coefficient set by the output of the phase adjustment module; the phase adjustment submodule The input terminals are respectively connected to the input terminal and the output terminal of the heartbeat signal of the filter bank, and are used to calculate the filter coefficient of the heartbeat signal, and the equalization filter bank is used to filter the heartbeat signal according to the filter coefficient. Perform matched filtering;

The signal synthesizing sub-module is used for summing the matched-filtered heartbeat signals to obtain the heartbeat signal with the largest signal-to-interference-noise ratio.

Wherein, the phase adjustment sub-module includes an adaptive filter and a channel selection unit;

Wherein, the pulse adaptive processing module includes: a parameter estimation algorithm submodule and a space adaptive filtering submodule;

The parameter estimation algorithm submodule is used to calculate the estimated value of the pulse signal conduction delay time and the filtering weight;

The spatial adaptive filtering sub-module performs weighted summation calculation on the pulse signal according to the filtering weight to obtain the pulse signal with the largest signal-to-interference-noise ratio.

Wherein, the parameter estimation algorithm sub-module includes: a calculation channel selection part, a channel gating part and an estimation algorithm part;

The calculation channel selection unit is used to select a calculation channel;

The estimation algorithm part is used for calculating the pulse signal propagation delay time estimation value and the filtering weight value.

Wherein, the cardiovascular physiological parameters analyzed by the analysis unit include at least one of heartbeat signal strength, pulse signal strength, pulse wave velocity and blood pressure change value.

Wherein, the collection unit is a heartbeat signal collection module, the heartbeat signal collection module is used to collect heartbeat signals in cardiovascular physiological signals, and the heartbeat signal collection module includes at least two heartbeat signal collectors.

Wherein, the acquisition unit is composed of at least one pulse signal acquisition module, and the pulse signal acquisition module is used to acquire pulse signals in cardiovascular physiological signals, and each pulse signal acquisition module includes at least two pulse signal collectors.

The present invention also provides a detection method of cardiovascular physiological signals, including:

The acquisition unit acquires cardiovascular physiological signals;

The adaptive processing unit performs adaptive processing on the cardiovascular physiological signal to obtain the cardiovascular physiological signal with the largest signal-to-interference-noise ratio.

Wherein, the analysis unit makes an analysis and judgment on the cardiovascular physiological parameters according to the cardiovascular physiological signal with the largest signal-to-interference-noise ratio;

The output unit outputs the judgment result of the analysis unit.

The present invention has following beneficial effect:

The device for detecting cardiovascular physiological signals in the embodiment of the present invention uses an adaptive processing unit to perform adaptive processing on cardiovascular physiological signals such as heartbeat signals and pulse signals to obtain high-gain cardiovascular physiological signals and reduce the impact of environmental noise. Strong anti-interference ability, which improves the detection accuracy of cardiovascular physiological signals. Users can perform detection on the bed or seat to ensure that the user can complete the detection of cardiovascular physiological signals without restraint in relaxation and without psychological or physical burden. detection.

The method for detecting cardiovascular physiological signals in the embodiment of the present invention obtains high-gain cardiovascular physiological signals by adaptively processing cardiovascular physiological signals such as heartbeat signals and pulse signals, thereby improving the detection accuracy of cardiovascular physiological signals. The user can perform detection on the bed or seat, ensuring that the user can complete the detection of cardiovascular physiological signals in a relaxed state without psychological or physical burden.

Description of drawings

FIG. 1 is a schematic structural view of a first embodiment of a detection device for cardiovascular physiological signals provided by the present invention;

2 is a schematic structural diagram of a second embodiment of a detection device for cardiovascular physiological signals provided by the present invention;

3 is a schematic structural diagram of a third embodiment of a detection device for cardiovascular physiological signals provided by the present invention;

Fig. 4 is a schematic structural diagram of the heartbeat adaptive processing module in Fig. 3;

Fig. 5 is a schematic structural diagram of the equalization processing sub-module in Fig. 4;

Fig. 6 is a schematic structural diagram of the phase synthesis module in Fig. 4;

Fig. 7 is the working flow chart of the heart beat adaptive processing module shown in Fig. 4;

Fig. 8 is a schematic structural diagram of the pulse adaptive processing module in Fig. 3;

Fig. 9 is the workflow diagram of the pulse adaptive processing module shown in Fig. 8;

Fig. 10 is a schematic structural diagram of a fourth embodiment of a device for detecting cardiovascular physiological signals provided by the present invention;

Fig. 11 is a schematic structural diagram of a fifth embodiment of a detection device for cardiovascular physiological signals provided by the present invention;

Fig. 12 is a flow chart of the first embodiment of the method for detecting cardiovascular physiological signals provided by the present invention;

Fig. 13 is a flow chart of the second embodiment of the method for detecting cardiovascular physiological signals provided by the present invention.

Detailed ways

In order to enable those skilled in the art to better understand the technical solution of the present invention, the device and method for detecting cardiovascular physiological signals provided by the present invention will be described in detail below with reference to the accompanying drawings.

FIG. 1 is a schematic structural diagram of a first embodiment of a device for detecting cardiovascular physiological signals provided by the present invention. As shown in Figure 1, the detection device of cardiovascular physiological signal of the embodiment of the present invention comprises: acquisition unit 10 and self-adaptive processing unit 20, wherein, acquisition unit 10 is used for collecting cardiovascular physiological signal, and cardiovascular physiological signal comprises pulse, cardiac The adaptive processing unit 20 is connected with the acquisition unit 10, and the adaptive processing unit 20 performs adaptive processing on the cardiovascular physiological signals collected by the acquisition unit 10. The adaptive processing helps to reduce the impact of environmental noise and improve the anti-interference ability Strong, get the cardiovascular physiological signal with the largest signal-to-interference-noise ratio.

Fig. 2 is a schematic structural diagram of a second embodiment of a device for detecting cardiovascular physiological signals provided by the present invention. As shown in FIG. 2 , on the basis of the first embodiment, the device for detecting cardiovascular physiological signals in the embodiment of the present invention further includes an analysis unit 30 and an output unit 40, wherein the analysis unit 30 is based on the information obtained by the adaptive processing unit 20. The cardiovascular physiological signal with the largest interference-to-noise ratio can analyze and judge the cardiovascular physiological parameters and physical conditions, and analyze whether the cardiovascular physiological parameters of the human body are abnormal, such as whether the heart rate is arrhythmia, arrhythmia, etc.; Sleep conditions, such as: sleep disorders, apnea and other symptoms. The output unit 40 outputs the analysis results of the analysis unit 30 , for example, to a user terminal through a digital terminal such as a mobile phone, a computer monitor or a printer.

Fig. 3 is a schematic structural diagram of a third embodiment of a device for detecting cardiovascular physiological signals provided by the present invention. As shown in FIG. 3 , in the embodiment of the present invention, the acquisition unit 10 includes a heartbeat signal acquisition module 11 and at least one pulse signal acquisition module 12, wherein the heartbeat signal acquisition module 11 is used to acquire heart rate in cardiovascular physiological signals. Heartbeat signal, including at least two heartbeat signal collectors 111 in the heartbeat signal acquisition module 11, the pulse signal acquisition module 12 is used to collect the pulse signal in the cardiovascular physiological signal, includes at least two pulse signals in the pulse signal acquisition module 12 Collector 121, in the embodiment of the present invention, heartbeat signal acquisition module 11 includes N heartbeat signal collectors 111, the number of pulse signal acquisition modules 12 is D (D>0), each pulse signal acquisition module 12 Including M pulse signal collectors 121. Both the heartbeat signal collector 111 and the pulse signal collector 121 include an analog-to-digital conversion channel, and the analog-to-digital conversion channel is used to amplify, filter and analog-to-digital convert the heartbeat signal and the pulse signal, respectively convert the heartbeat signal and the pulse signal Converted into heartbeat signals and pulse signals that can be digitally processed, heartbeat signal collector 111 and pulse signal collector 121 can adopt fiber optic collectors, piezoelectric collectors, electret capacitive collectors, air bag pressure collectors Accelerometers, micro-electro-mechanical systems (Micro-Electro-Mechanical SystemsMEMS) acceleration collectors or ultrasonic collectors, etc.

When actually collecting cardiovascular physiological signals such as heartbeat signals or pulse signals, N heartbeat signal collectors 111 and M*D pulse signal collectors 121 can be arranged in sequence according to the direction of blood flow, and the user's heart and The heartbeat signal collector 111 only needs to be in contact with the pulse signal collector 121 to contact the arteries of the user's other than the heart. In the embodiment of the present invention, N heartbeat signal collectors 111 and M*D pulse signal collectors 121 are laid on the bed or seat in sequence according to the flow direction of blood in the descending aorta, and the user can lie on the bed or Sitting on the seat, it is only necessary to contact the user's heart with the heartbeat signal collector 111 and the parts below the user's heart with the pulse signal collector 121, and it is not necessary to connect the heartbeat signal collector in the acquisition unit 111 or the pulse signal collector 121 is worn or clamped on the user's body to ensure that the user can perform detection without psychological burden and restraint in a relaxed state, which is conducive to obtaining more accurate heartbeat signals or pulse signals of the user, etc. Cardiovascular Physiological Signaling. In practical applications, the signal collection frequency f can be set to 45,000 times/second, and the distance between heartbeat signal collectors 111 or pulse signal collectors 121 can be set to 10 mm. Heartbeat signal collectors 111 or pulse signal collectors 121 It is also not necessary to arrange equidistantly, as long as the arrangement distance is smaller than the wavelength of the heartbeat signal or the pulse signal.

The adaptive processing unit 20 in the detection device of cardiovascular physiological signal shown in Figure 3 comprises a heartbeat adaptive processing module 21 and a pulse adaptive processing module 22, and the heartbeat adaptive processing module 21 is connected with the heartbeat signal acquisition module 11 , the heartbeat adaptive processing module 21 performs adaptive processing on the heartbeat signal collected by the heartbeat signal acquisition module 11, obtains the heartbeat signal with the largest signal-to-interference-noise ratio, and sends the heartbeat signal with the largest signal-to-interference-noise ratio to the Analysis unit 30, pulse adaptive processing module 22 is connected with D pulse signal acquisition modules 12, pulse adaptive processing module 22 is used to carry out adaptive processing to the pulse signal collected by D pulse signal acquisition modules, and obtains the maximum signal-to-interference-noise ratio pulse signal, and send the pulse signal with the largest signal-to-interference-noise ratio to the analyzing unit 30 .

FIG. 4 is a schematic structural diagram of the heart beat adaptive processing module in FIG. 3 . As shown in Figure 4 and in conjunction with Figure 3, the heartbeat adaptive processing module 21 includes an equalization processing submodule 211, a phase adjustment submodule 212 and a phase synthesis module 213, wherein the phase adjustment submodule 212 is used to set the heartbeat signal The filter coefficient, the input end of the phase adjustment submodule 212 are respectively connected to the input end and the output end of the heartbeat signal of the equalization processing submodule 211, and the output end of the phase adjustment submodule 212 is connected to the filter coefficient input end of the equalization processing submodule 211 , the equalization processing sub-module 211 matches the heartbeat signal according to the filter coefficient obtained by the phase adjustment sub-module 212, the signal synthesis sub-module 213 is connected with the equalization processing sub-module 211, and the signal synthesis sub-module 213 matches the heartbeat signal input by the equalization processing sub-module 211 The heartbeat signal is synthesized and summed to obtain the heartbeat signal with the largest signal-to-interference-noise ratio.

FIG. 5 is a schematic structural diagram of the equalization processing sub-module in FIG. 4 . As shown in Figure 5 and in conjunction with Figure 3, the equalization processing sub-module 211 includes N filter channels with an impulse response length of L, the filter channels are composed of an adder 2111, etc., and the input ends of the N filter channels are respectively connected to the heartbeat signal acquisition The N heartbeat signal collectors 111 in the module 11 are used to receive the heartbeat signals X ₁ ~ X _N , and the output terminals Y ₁ ~ Y _N of the N filtering channels output the equalized heartbeat signals to the signal synthesizer Module 213.

FIG. 6 is a schematic structural diagram of the phase combining module in FIG. 4 . As shown in Figure 6 and in conjunction with Figure 5, the phase adjustment sub-module 212 includes an adaptive filter 2121 and a channel selection part 2122, wherein the adaptive filter 2121 can adopt Wiener (Wiener) optimal filtering method, recursive least squares (RLS) adaptive filtering method and other adaptive filtering methods. In the embodiment of the present invention, the adaptive filter 2121 adopts a least mean square (Least Mean Squade, LMS) adaptive filtering method to form a least mean square (Least Mean Squade, LMS) adaptive filter. The convergence coefficient μ of the LMS adaptive filter satisfies the convergence condition 0<μ<2/R=λ _max , where R=λ _max is the maximum eigenvalue of the autocorrelation matrix of the input heartbeat signal Xj.

Fig. 7 is a working flow chart of the heart beat adaptive processing module shown in Fig. 4 . As shown in Figure 7 and in conjunction with Figure 5 and Figure 6, the workflow of the heartbeat adaptive processing module in the embodiment of the present invention specifically includes the following working steps:

Step 601, setting initial filter coefficients of N filter channels.

In an embodiment, the impulse response length of the N-way filter channels in the equalization processing sub-module 211 is L, and the phase adjustment sub-module 212 sets the initial filter coefficients of the N-way filter channels, and the initial filter coefficients of the N-way filter channels are: W ₁₁ ~W _1L ,...W _N1 ~W _NL .

Step 602, the channel selection sub-module selects a reference filtering channel.

In the embodiment of the present invention, the channel selection submodule 2122 selects the i-th filter channel in the equalization processing sub-module 211 as the reference filter channel, the filter coefficients of the i-th filter channel are W _i1 to W _iL , and the i-th filter channel The input and output filtered signals of the channel are X _i and Y _i , and then enter step 603

In this step, if i>N, select the first filtering channel as the reference filtering channel.

Step 603, select an adjustment filter channel.

The channel selection unit 2122 selects the jth filter channel as the adjustment filter channel, and the input and output filter signals of the jth filter channel are X _j and Y _j , wherein, if j=i, then select the j+1th filter channel As the adjustment filter channel, if j>N, select the first filter channel as the adjustment filter channel, and then go to step 604 .

Step 604, judging whether the deviation value of the heartbeat signal output by the reference filter channel and the heartbeat signal output by the adjustment filter channel converges.

The deviation value e of the heartbeat signal Y _i output by the reference filter channel and the heartbeat signal Y _j output by the adjustment filter channel, the preset maximum deviation value is ε, if e<ε, it indicates convergence, and the preset maximum deviation value is ε according to The previous deviation value e(n) diverges and converges to obtain empirical values, and then enters step 605 , otherwise, enters step 602 .

Step 605. Calculate the filter coefficients of the adjusted filter channel.

In the embodiment of the present invention, the adaptive filter 2121 adopts an LMS adaptive filter, and the adaptive filter 2121 performs the input of the received heartbeat signal Xi and the output heartbeat signal Yi of the adjustment filter channel and the output of the reference filter channel. The heartbeat signal Yj is subjected to time-domain adaptive processing to obtain filter coefficients W _j1 ˜W _jL of the adjusted filter channel, and then enter step 606 .

Step 606, updating the filter coefficients of the adjusted filter channel.

The filter coefficients W _j1 ˜W _jL of the jth filter channel as the adjustment filter channel calculated in step 605 are updated to the jth filter channel, and then step 607 is entered.

The j+1th filter channel is selected as the adjustment filter channel, and the time-domain adaptive processing of steps 603-606 is performed in a loop.

Step 607: Perform matched filtering according to the filter coefficients of the adjusted filter channel.

The equalization processing sub-module 211 performs matched filtering according to the filter coefficient of the adjusted filter channel, and then outputs the matched-filtered heartbeat signal to the signal synthesis sub-module 213 , and then enters step 608 .

Step 608, acquiring the cardiac signal with the largest SINR.

The signal synthesis sub-module 213 performs synthesis and sum calculation on the heartbeat signals input by the equalization processing sub-module 211 to obtain the heartbeat signal with the largest signal-to-interference-noise ratio.

It should be pointed out that the workflow of the heart beat adaptive processing module can also be realized by other adaptive filtering methods, and the other adaptive filtering methods will not be discussed here.

FIG. 8 is a schematic structural diagram of the pulse adaptive processing module in FIG. 3 . As shown in Figure 8 and in conjunction with Figure 3, the pulse adaptive processing module 22 includes: a parameter estimation algorithm submodule 221 and a space adaptive filtering submodule 222, wherein the parameter spectrum estimation algorithm submodule 221 calculates the filter weights and Pulse wave average velocity (pulse wave average velocity, PWV), the spatial adaptive filtering sub-module 222 carries out weighted summation calculation to the pulse signal according to the filter weight calculated by the parameter estimation algorithm sub-module 221, and obtains the pulse signal with the largest signal-to-interference-noise ratio, Then the pulse signal and the pulse conduction velocity with the largest signal-to-interference-noise ratio are output to the analysis unit 30 . The parameter estimation algorithm sub-module 221 includes: a calculation channel selection part 2211, a channel gating part 2212 and an estimation algorithm part 2213, wherein the calculation channel selection part 2211 is used for cyclically selecting the calculation channel, and the estimation algorithm part 2213 is used for calculating the pulse signal filter The weight and the pulse wave velocity, the pulse wave velocity of the d-th pulse signal is PWVd, and the channel gating unit 2212 is used to gate the transmission channel. The estimation algorithm part 2213 can adopt the minimum mean square error (Minimum Mean Squared Error, MMSE) estimation method, the constant modulus algorithm (Constant Modulus Algorithm, CMA) estimation method, the multiple signal classification (Multi Signal Classification, MUSIC) estimation method of the super-resolution spectrum estimation algorithm Method and rotation invariant technology (Estimating signal parameter via rotational invariance techniques, ESPRIT) estimation method and other parameter estimation methods for space adaptive filtering. The spatial adaptive filtering sub-module 222 includes D filtering channels, which are respectively connected to D pulse signal acquisition modules, and each filtering channel has M input terminals, which are respectively connected to M pulse signal collectors 121 .

FIG. 9 is a flowchart of the pulse adaptive processing module shown in FIG. 8 . As shown in Figure 9, the workflow of the pulse adaptive processing module specifically includes the following steps:

Step 801. Calculate the estimated value of pulse signal transmission delay time.

In the embodiment of the present invention, the estimation algorithm part 2213 calculates the estimated value of the pulse signal conduction delay time by using the multi-signal classification (Multi Signal Classification, MUSIC) calculation method of the super-resolution spectrum estimation algorithm. Firstly, the narrow-band signal required by the MUSIC calculation method is extracted from the center frequency of the pulse signal whose wavelength is greater than the arrangement distance between the two pulse signal collectors 121 when detecting the user. The calculation channel selection unit 2211 selects and connects the d-th filter channel among the D-channel filter channels, and the estimation algorithm unit 2213 receives the pulse signals _Yd1 -Y collected by the d-th pulse signal acquisition module 12 transmitted through the d-th filter channel. _dM , then extract the narrow-band signal Q and I values under the center frequencies of the M pulse signals _Yd1 ～ _YdM in the dth pulse signal acquisition module 12, generate M-dimensional signal vector X(t), pulse signal vector X and Its covariance matrix R is shown in formula (1) and formula (2) respectively:

X(t)=[X ₁ (t), . . . X _m (t), . . . X _M (t)] ^T (1)

R＝E[X(t)X(t) ^H ] (2)

Among them, T represents the vector transpose, H represents the complex conjugate transpose, the imaginary part and the real part of the element X _m (t) (1≤m≤M, m is a natural number) in the signal vector X(t) are respectively Q and I, X _m (t) is the complex value of the mth pulse signal Y _dm , and t is the sampling moment of the pulse signal at a certain time interval.

In practical applications, the maximum likelihood function of the covariance matrix R is shown in formula (3),

${\mathrm{<span\; class="notranslate">\; R</span>}}_{\mathrm{<span\; class="notranslate">\; xx</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; (</span>\frac{\mathrm{<span\; class="notranslate">\; 1</span>}}{\mathrm{<span\; class="notranslate">\; T</span>}}<span\; class="notranslate">\; )</span>{\mathrm{<span\; class="notranslate">\; \&chi;\&chi;</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 3</span>}<span\; class="notranslate">\; )</span>$

χ=[X(1), .

Calculate the eigenvalues λ ₁ ～λ _M of the maximum likelihood function R _xx of the covariance matrix R (among them, λ ₁ ≥ _{λ 2} ≥…≥ λ _M ), set according to the eigenvalues of R _xx exceeding the preset noise power Calculate the number of incident waves of the pulse signal, and calculate the eigenvectors e ₁ -e _M corresponding to the eigenvalues λ ₁ -λ _M. Then obtain the noise eigenvector E _N , E _N is the eigenvector corresponding to the (MG) eigenvalues lower than the noise power, G is the incident wave quantity of the pulse signal, that is, the number of signal sources, wherein, E _N is as the formula As shown in (4),

E _N ＝(e _G+1 ，...e _M ) (4)

According to the mathematical model of the narrow-band far field, the signal vector X(t) shown in formula (1) can be represented by formula (5),

X(t)＝AF(t)+N(t) (5)

Among them, N(t) represents the noise signal vector of M dimension, F(t) represents the spatial signal vector of G dimension, A is the steering vector matrix of M*G dimension, and A is shown in formula (6):

A=[a(τ ₁ ), a(τ ₂ ),..., a(τ _G )] (6)

Among them, the steering vector is shown in formula (7):

A(τ _i )＝[exp(-jω ₀ τ _i2 ),..., exp(-jω ₀ τ _iM )]T (7)

Wherein, ω ₀ =2πf, f is the frequency of the pulse signal, and the delay time τ _i of the pulse signal collector 121 is as shown in formula (8):

${\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; )</span>\mathrm{<span\; class="notranslate">\; sin</span>}\mathrm{<span\; class="notranslate">\; \&theta;</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 8</span>}<span\; class="notranslate">\; )</span>$

Among them, j is the serial number of the pulse signal collector, _sj is the distance between the jth pulse signal collector and the first pulse signal collector, and i is the serial number of the pulse signal source detected by the pulse signal collector , _Vi is the signal transmission speed of the pulse signal source, θ is the direction of the pulse signal, in the present embodiment, the arrangement direction of the pulse signal collector is the same as the propagation direction of the pulse signal, and θ is 90°, formula (8) It can be expressed by formulas (9) and (10):

${\mathrm{<span\; class="notranslate">\; \&tau;</span>}}_{\mathrm{<span\; class="notranslate">\; ij</span>}}<span\; class="notranslate">\; =</span><span\; class="notranslate">\; (</span>\frac{{\mathrm{<span\; class="notranslate">\; the\; s</span>}}_{\mathrm{<span\; class="notranslate">\; j</span>}}}{{\mathrm{<span\; class="notranslate">\; V</span>}}_{\mathrm{<span\; class="notranslate">\; i</span>}}}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 9</span>}<span\; class="notranslate">\; )</span>$

τ _i =[(s ₂ +...+s _j )/((j-1)*V _i )] (10)

According to the formulas (4) and (7), the evaluation function P _MU (τ) can be obtained, and the evaluation function P _MU (τ) is shown in the formula (11),

${\mathrm{<span\; class="notranslate">\; P</span>}}_{\mathrm{<span\; class="notranslate">\; MU</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; =</span>\frac{{\mathrm{<span\; class="notranslate">\; a</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; a</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; )</span>}{{\mathrm{<span\; class="notranslate">\; a</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; )</span><span\; class="notranslate">\; *</span>{\mathrm{<span\; class="notranslate">\; E.</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}{\mathrm{<span\; class="notranslate">\; E.</span>}}_{\mathrm{<span\; class="notranslate">\; N</span>}}^{\mathrm{<span\; class="notranslate">\; h</span>}}<span\; class="notranslate">\; *</span>\mathrm{<span\; class="notranslate">\; a</span>}<span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; \&tau;</span>}<span\; class="notranslate">\; )</span>}<span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; -</span><span\; class="notranslate">\; (</span>\mathrm{<span\; class="notranslate">\; 11</span>}<span\; class="notranslate">\; )</span>$

Among them, a(τ) represents the complex response of the pulse signal collector with respect to the delay time τ.

Find out the delay time corresponding to the maximum point of the evaluation function P _MU (τ) according to the formula (11), which is the estimated value τ _P of the pulse signal transmission delay time of the adjacent pulse signal collector, and then enter step 802 .

Step 802, calculating the filtering weight of the pulse signal.

The calculation formula of the filter coefficient is shown in formula (12),

W ^H = (A ^H A) ^-1 A ^H ≡ [W ₁ , W ₂ , . . . , W _M ] ^H (12)

Then calculate the filter weights W _k1 ˜W _kM of the d-th filter channel according to formula (6), formula (7) and formula (12) and the pulse signal transmission delay time estimate τ _P , and then enter step 803 .

Step 803, acquiring the pulse signal with the largest signal-to-interference-noise ratio.

According to the pulse signal Y ₁ ~ Y _M collected by the pulse signal acquisition module and the filter weight W _k1 ~ W _kM , the complex conjugate multiplication weighted sum operation is performed to obtain the pulse signal with the largest signal-to-interference-noise ratio, and then the signal-to-interference noise The pulse signal with the largest ratio is sent to the analysis unit.

Take the cardiovascular physiological signal detection device shown in Figure 3 as an example, when the analysis unit 30 receives the heartbeat signal and pulse signal with the largest signal-to-interference-noise ratio as shown in Figure 7 and Figure 9, extract the heartbeat signal per unit time and the peak times of the pulse signal are taken as the number of heartbeat signals and the number of pulse signals respectively, and the signal strength of the heartbeat signal and the pulse signal in unit time is calculated as the heartbeat signal strength and the pulse signal strength, and the pulse of the dth pulse signal is extracted Wave conduction velocity PWV _d , and then calculate the heartbeat signal and the average pulse wave velocity (PWAV) of the pulse signal according to PWV, the unit is m/s, calculate the difference between PWV and PWAV, and calculate the blood pressure change value (Press Diff, PD), the unit is mmHg, wherein, the average pulse wave velocity PWAV and blood pressure change value PD are shown in formula (13) and formula (14) respectively:

PWAV(t+1)=β*PWAV(t)+(1-β)*PWV(t)

PD=γ*(PWV(t)-PWAV(t)

Wherein, β is the moving average coefficient of the pulse wave conduction velocity (0.01<β<0.98), γ is the proportional coefficient between the change of the pulse wave conduction velocity and the blood pressure value (10<γ<60), and t is the detection time of the pulse wave conduction velocity, The detection of the pulse wave signal is usually performed at certain time intervals.

The analysis unit analyzes and judges cardiovascular physiological parameters and physical conditions according to the cardiovascular physiological signal with the largest signal-to-interference-noise ratio. In the embodiment of the present invention, according to one or more cardiovascular physiological parameters in heartbeat signal strength, pulse signal strength, pulse wave velocity and blood pressure change value, etc., it is analyzed whether the detected person has cardiovascular disease, such as abnormal heart rate, Abnormal blood pressure, etc. Then the analysis result is sent to the display terminal, which can be a digital terminal such as a mobile phone, a printer or a computer.

The embodiment of the present invention uses an adaptive processing unit to perform adaptive processing on cardiovascular physiological signals such as heartbeat signals and pulse signals, so as to obtain high-gain cardiovascular physiological signals, reduce the influence of environmental noise, and have strong anti-interference ability, and improve the Cardiovascular physiological signal detection accuracy, users can perform detection on the bed or seat, to ensure that the user can complete the detection of cardiovascular physiological signals in the case of relaxation, no psychological or physical burden.

FIG. 10 is a schematic structural diagram of a fourth embodiment of a device for detecting cardiovascular physiological signals provided by the present invention. As shown in FIG. 10 , the device for detecting cardiovascular physiological signals in the embodiment of the present invention may only include a heartbeat signal acquisition module 11 and a heartbeat adaptive processing module 21, wherein the workflow of the heartbeat adaptive processing module 21 is shown in FIG. 7 shown, and will not be repeated here.

Fig. 11 is a schematic structural diagram of a fifth embodiment of a device for detecting cardiovascular physiological signals provided by the present invention. As shown in Figure 11, the detection device of the cardiovascular physiological signal of the embodiment of the present invention may also only include the pulse signal acquisition module 12 and the pulse adaptive processing module 22, wherein, the specific work flow of the pulse adaptive processing module 22 is as shown in Figure 9 , and will not be repeated here.

Fig. 12 is a flow chart of the first embodiment of the method for detecting cardiovascular physiological signals provided by the present invention. As shown in Figure 12, the specific workflow of the method for detecting cardiovascular physiological signals in the embodiment of the present invention includes the following steps:

Step 121, collecting cardiovascular physiological signals.

In the embodiment of the present invention, the cardiovascular physiological signal detection device as shown in FIG.

Step 122, performing adaptive processing on the cardiovascular physiological signal to obtain the cardiovascular physiological signal with the largest signal-to-interference-noise ratio.

The adaptive processing unit 20 performs adaptive processing on the cardiovascular physiological signals collected by the acquisition unit 10. The adaptive processing helps to reduce the impact of environmental noise, improve anti-interference ability, and obtain cardiovascular physiological signals with the largest signal-to-interference-noise ratio.

Fig. 13 is a flow chart of the second embodiment of the method for detecting cardiovascular physiological signals provided by the present invention. As shown in Figure 13, the specific workflow of the method for detecting cardiovascular physiological signals in the embodiment of the present invention includes the following steps:

Step 131, collecting cardiovascular physiological signals;

In the embodiment of the present invention, the cardiovascular physiological signal detection device as shown in FIG.

Step 132, performing adaptive processing on the cardiovascular physiological signal to obtain the cardiovascular physiological signal with the largest signal-to-interference-noise ratio.

The adaptive processing unit 20 performs adaptive processing on the cardiovascular physiological signals collected by the acquisition unit 10 to obtain cardiovascular physiological signals with the largest signal-to-interference-noise ratio.

Step 133. Analyzing and judging the cardiovascular physiological parameters according to the cardiovascular physiological signal with the largest signal-to-interference-noise ratio;

Step 134, output the judgment result.

The embodiment of the present invention obtains high-gain cardiovascular physiological signals by adaptively processing cardiovascular physiological signals such as heartbeat signals and pulse signals, and improves the detection accuracy of cardiovascular physiological signals. Detection, to ensure that the user can complete the detection of cardiovascular physiological signals in a relaxed state without psychological or physical burden.

It can be understood that, the above embodiments are only exemplary embodiments adopted for illustrating the principle of the present invention, but the present invention is not limited thereto. For those skilled in the art, various modifications and improvements can be made without departing from the spirit and essence of the present invention, and these modifications and improvements are also regarded as the protection scope of the present invention.

Claims (14)

1. the checkout gear of a cardiovascular physiology signal is characterized in that comprising: collecting unit and self-adaptive processing unit;

Said collecting unit is used to gather the cardiovascular physiology signal;

Said self-adaptive processing unit is connected with said collecting unit, is used for said cardiovascular physiology signal is carried out self-adaptive processing, obtains the maximum cardiovascular physiology signal of Signal to Interference plus Noise Ratio.

2. the checkout gear of cardiovascular physiology signal according to claim 1 is characterized in that, also comprises: analytic unit and output unit;

Said analytic unit is connected with said self-adaptive processing unit, is used for according to the maximum cardiovascular physiology signal of said Signal to Interference plus Noise Ratio the cardiovascular physiology parameter being made analytical judgment;

Said output unit is connected with said analytic unit, is used for the judged result output with said analytic unit.

3. the checkout gear of cardiovascular physiology signal according to claim 1 and 2 is characterized in that, said collecting unit comprises: cardiac signal acquisition module and at least one pulse signal acquisition module;

Said cardiac signal acquisition module is used for gathering the cardiac signal of cardiovascular physiology signal, and said cardiac signal acquisition module comprises at least two cardiac signal harvesters;

Said pulse signal acquisition module is used for gathering the pulse signal of cardiovascular physiology signal, and each said pulse signal acquisition module comprises at least two pulse signal harvesters.

4. the checkout gear of cardiovascular physiology signal according to claim 3 is characterized in that:

Comprise the analog digital conversion passage in the said cardiac signal harvester, said analog to digital conversion passage is used for converting said cardiac signal into digital signal;

Comprise the analog digital conversion passage in the said pulse signal harvester, said analog to digital conversion passage is used for converting said pulse signal into digital signal.

5. according to the checkout gear of claim 3 or 4 described cardiovascular physiology signals, it is characterized in that said self-adaptive processing unit comprises: heartbeat self-adaptive processing module and pulse self-adaptive processing module;

Said heartbeat self-adaptive processing module is used for said cardiac signal is carried out self-adaptive processing;

Said pulse self-adaptive processing module is used for said pulse signal is carried out self-adaptive processing.

6. the checkout gear of cardiovascular physiology signal according to claim 5 is characterized in that, said heartbeat self-adaptive processing module comprises: phase place adjustment submodule, equilibrium treatment submodule and signal synthon module;

Said equilibrium treatment submodule comprises the filtering channel group, is used for the cardiac signal of said cardiac signal acquisition module collection is carried out matched filtering with the filter factor of being set by said phase adjusting module output; The input of said phase place adjustment submodule is connected with outfan with the input of the cardiac signal of said bank of filters respectively; Be used to calculate the filter factor of said cardiac signal, said equalization filter group is carried out matched filtering according to said filter factor to said cardiac signal;

Said signal synthon module is used for obtaining the maximum cardiac signal of Signal to Interference plus Noise Ratio with carrying out anded through the said cardiac signal after the matched filtering.

7. the checkout gear of cardiovascular physiology signal according to claim 6 is characterized in that, said phase place adjustment submodule comprises sef-adapting filter and channel selecting portion.

8. the checkout gear of cardiovascular physiology signal according to claim 5 is characterized in that, said pulse self-adaptive processing module comprises: parameter estimation algorithm submodule and spatially adaptive filtering submodule;

Said parameter estimation algorithm submodule is used to calculate said pulse signal conduction delay time estimated value and filter weights;

Said spatially adaptive filtering submodule carries out weighted sum according to said filter weights to said pulse signal and calculates, and obtains the maximum pulse signal of Signal to Interference plus Noise Ratio.

9. the checkout gear of cardiovascular physiology signal according to claim 8 is characterized in that, said parameter estimation algorithm submodule comprises: calculation channel selecting portion, passage gating portion and algorithm for estimating portion;

Said calculation channel selecting portion is used for selecting the calculation passage;

Said algorithm for estimating portion is used to calculate pulse signal conduction delay time estimated value and filter weights.

10. the checkout gear of cardiovascular physiology signal according to claim 2; It is characterized in that the cardiovascular physiology parameter of said analytic unit analysis comprises at least a in cardiac signal intensity, pulse signal intensity, pulse wave conduction velocity and the blood pressure value.

11. the checkout gear of 2 described cardiovascular physiology signals as requested; It is characterized in that; Said collecting unit is the cardiac signal acquisition module; Said cardiac signal acquisition module is used for gathering the cardiac signal of cardiovascular physiology signal, and said cardiac signal acquisition module comprises at least two cardiac signal harvesters.

12. the checkout gear of 2 described cardiovascular physiology signals as requested; It is characterized in that; Said collecting unit is made up of at least one pulse signal acquisition module; Said pulse signal acquisition module is used for gathering the pulse signal of cardiovascular physiology signal, and each said pulse signal acquisition module comprises at least two pulse signal harvesters.

13. the detection method of a cardiovascular physiology signal is characterized in that, comprising:

Collecting unit is gathered the cardiovascular physiology signal;

The self-adaptive processing unit carries out self-adaptive processing to said cardiovascular physiology signal, obtains the maximum cardiovascular physiology signal of Signal to Interference plus Noise Ratio.

14. the detection method of cardiovascular physiology signal according to claim 13 is characterized in that, also comprises:

Analytic unit is made analytical judgment according to the maximum cardiovascular physiology signal of said Signal to Interference plus Noise Ratio to the cardiovascular physiology parameter;

Output unit is with the judged result output of said analytic unit.

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