CN112998678A - Wearable device boosting type blood pressure measurement and calculation method - Google Patents
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Abstract
The invention discloses a wearable device boosting type blood pressure measurement and calculation method, which comprises an inflation control stage and a blood pressure calculation stage, and is characterized in that: the control inflation phase comprises: carrying out quick inflation, and carrying out open-loop control on the PWM through setting a speed threshold when the pressure value is lower than the set threshold; or linear inflation, when the static pressure value reaches a set threshold value, a stable linear inflation process is realized by using closed-loop control to adjust PWM; the invention provides a pressure-boosting blood pressure measurement and calculation method, which achieves a stable inflation process through a pid control algorithm, collects pulse wave signals in the inflation process for processing, preliminarily calculates a blood pressure value by adopting an amplitude coefficient method, and calculates the blood pressure value by combining an amplitude normalization method and a characteristic compensation method, so that the average pressure deviation caused by other factors is compensated, the discomfort caused by a pressure-reducing blood pressure measurement method is avoided, the measurement efficiency is improved, and the comfort level and the convenience of the blood pressure measurement of wearable equipment are increased.
Description
Technical Field
The invention belongs to a blood pressure detection method, and particularly relates to a wearable device which extracts pulse wave signals to detect blood pressure in a boosting process and calculates heart rate according to the pulse waves.
Background
Cardiovascular disease is one of the most common diseases in the world, and with increasing age, more and more people suffer from hypertension. Blood pressure is an important physiological parameter index reflecting cardiovascular function, and has very important clinical diagnosis value. The blood pressure detection method comprises invasive blood pressure detection and noninvasive blood pressure detection. Invasive blood pressure belongs to a direct measurement method, although the prior art is mature, the invasive blood pressure has some pains and is currently applied to critical patients or patients needing surgical treatment. Therefore, the non-invasive blood pressure measurement method is widely used. The oscillometric blood pressure measurement has two modes of pressure rise measurement and pressure reduction measurement. The blood pressure reduction measurement comprises two stages, namely an inflation stage and a deflation stage, wherein the part to be measured is inflated and pressurized to be in an artery closing state, and then a pressure shock wave signal generated by artery pulsation is collected in the deflation stage to be analyzed to finish measurement. The pressure-boosting measurement mode is to acquire the oscillation wave signals and process the signals in real time during the pressurization process, and the gas is quickly released once the test is finished. The pressure reduction measurement mode needs to preset the pressure value of the end of inflation, if the preset pressure value is too high, the discomfort of the testee can be increased, and if the preset pressure value is too low, the measurement efficiency is low.
Oscillography measurement is generally that a curve fitting method is matched with an amplitude coefficient method to calculate an actual blood pressure value, pulse shock waves are collected in the boosting process, then a peak value sequence and a valley value sequence of the pulse shock waves are identified, some curve fitting is carried out according to the peak value sequence, and some curve fitting is carried out according to the amplitude value sequence. The pressure value corresponding to the maximum amplitude or peak value of the pulse wave is the average pressure; and then calculating the systolic pressure amplitude and the diastolic pressure amplitude by using the maximum amplitude and the amplitude coefficient, and finding out the corresponding static pressure value by combining the fitting curve, namely the corresponding systolic pressure and diastolic pressure. If the original pressure value has deviation, the test result is influenced.
Disclosure of Invention
In order to overcome the defects of the prior art, the invention aims to provide a pressure-boosting blood pressure measuring device and a pressure-boosting blood pressure measuring method. And adjusting the PWM of the air pump to achieve a stable inflation process through a pid control algorithm, acquiring a pulse wave signal in a boosting process to perform real-time analysis, calculating systolic pressure and diastolic pressure by utilizing curve fitting in combination with an amplitude coefficient method and a compensation method, and calculating heart rate.
In order to achieve the purpose, the technical scheme of the invention is as follows:
a wearable equipment boost blood pressure measurement calculation method comprises a control inflation stage and a blood pressure calculation stage, and is characterized in that: the control inflation phase comprises:
carrying out quick inflation, and carrying out open-loop control on the PWM through setting a speed threshold when the pressure value is lower than the set threshold;
or linear inflation, when the static pressure value reaches a set threshold value, a stable linear inflation process is realized by using closed-loop control to adjust PWM;
the blood pressure calculation stage comprises the following steps:
s1, obtaining pulse oscillation wave signals, removing noise such as baseline drift and the like through the combination of Butterworth high-pass filtering and low-pass filtering, and extracting relatively pure pulse wave signals; simultaneously, extracting a direct current component in the signal by using a Butterworth low-pass filter to be used as a static pressure reference value;
and S2, peak/valley detection, namely detecting the peak and valley values of the processed pulse wave signals, searching the original pulse wave signal sequence one by one in a one-by-one searching mode, judging the ascending and descending processes of the sequence, identifying a peak point if the ascending process reaches a certain length and the amplitude reaches a set threshold value, and identifying the point at which the ascending starts as a valley point and the difference value of the two as the amplitude. The peak value point corresponds to the valley value point, the amplitude value point corresponds to the pulse frequency, and the heart rate is calculated according to the pulse frequency;
s3, smoothing and fitting the amplitude curve, firstly carrying out filtering processing on the amplitude curve by using median filtering and mean filtering, and then fitting the processed amplitude curve by using linear interpolation fitting to obtain a smoother and more complete pulse wave amplitude curve;
s4, calculating a blood pressure value, identifying a static pressure value corresponding to the maximum value of the amplitude curve as an average pressure, calculating the amplitudes of diastolic pressure and systolic pressure by an amplitude coefficient method, and acquiring the corresponding static pressure value as a corresponding blood pressure value;
s5, blood pressure compensation, namely compensating diastolic pressure by using a coefficient method and compensating systolic pressure by using an amplitude normalization proportion method;
and S6, finishing the measurement, wherein the condition for judging the end of the measurement comprises that the corresponding diastolic pressure and systolic pressure or the pressure of the measured part exceed the preset maximum pressure value or the measurement duration exceeds the preset maximum measurement duration, finishing the measurement and quickly deflating.
Optionally, the step of linear aeration is: using a pid control method, wherein the pid control method formula is as follows:
where Kp is a proportional coefficient, Ki is an integral coefficient, Kd is a differential coefficient, and e (t) is a deviation signal. The Pid control method controls a controlled object by forming a deviation between a target value and an actual output value and linearly combining the proportion, integral, and differential of the deviation to form a control amount.
Optionally, the butterworth high-pass filtering processing in step S1 specifically includes the following steps:
setting the pass band cut-off frequency, pass band maximum attenuation, stop band minimum attenuation and sampling frequency
Design of analog Butterworth high-pass/Low-pass Filter (prototype Filter H (s))
Bilinear transformation:
high-pass:
low-pass:
obtaining the system function h (z) of the digital filter: denominator a (n), numerator b (m)
Solving a linear difference equation of the constant coefficients to obtain a filtered signal y (n):
optionally, the step S3 includes the following specific steps:
setting the length of a filter, namely the number of sequence elements transmitted into the filter each time;
sorting the incoming sequences from large to small;
and returning the intermediate value of the sorted sequence.
Optionally, the step S3 includes the following specific steps:
setting the length of a filter, namely the number of sequence elements transmitted into the filter each time;
the average of the incoming sequence is calculated and returned.
Optionally, in the step S3, the linear interpolation fitting method mainly performs numerical estimation according to data near left and right of a point to be interpolated in the one-dimensional data sequence, where the point (x) is known0,y0)、(x1,y1) And solving a y value corresponding to the interpolation point x by an equal proportion method, wherein the formula is as follows:
optionally, in step S4, the initial systolic pressure and the diastolic pressure are calculated by a magnitude coefficient method.
Optionally, in step S5, the initial blood pressure value is compensated by a coefficient method and an amplitude normalization ratio method, so as to obtain a more accurate result.
Optionally, in step S6, the condition for ending the measurement includes that the calculated result exceeds a preset maximum pressure value or exceeds a maximum measurement time. The preset maximum pressure value is 256mmHg and the maximum measurement time is preset to 70 s.
The invention provides a pressure-boosting blood pressure measurement and calculation method, which achieves a stable inflation process through a pid control algorithm, collects pulse wave signals in the inflation process for processing, preliminarily calculates a blood pressure value by adopting an amplitude coefficient method, and calculates the blood pressure value by combining an amplitude normalization method and a characteristic compensation method, so that the average pressure deviation caused by other factors is compensated, the discomfort caused by a pressure-reducing blood pressure measurement method is avoided, the measurement efficiency is improved, and the comfort level and the convenience of the blood pressure measurement of wearable equipment are increased.
Drawings
FIG. 1 is a general flow diagram of the present invention.
Fig. 2 is a rapid inflation flow chart.
FIG. 3 is a pid control schematic.
Fig. 4 is a graph of inflation.
Fig. 5 is a diagram showing the effect of extracting and filtering pulse waves.
Fig. 6 is a graph of fft spectra before and after filtering.
Fig. 7 shows a dc component in the extracted signal.
Fig. 8 is a peak/valley detection flow chart.
Fig. 9 is a graph of the measurement results.
Detailed Description
The invention is described in further detail below with reference to the accompanying examples.
The specific embodiment provides a wearable device up-pressure type blood pressure measurement and calculation method, and a flow chart of the method is shown in fig. 1. The blood pressure measuring method is divided into an inflation stage and a calculation stage, the inflation stage can collect pulse wave signals, and the key point is to control the efficiency and stability of the inflation process; the key point of the calculation stage is that amplitude curve processing, a proportionality coefficient method and various compensation methods are combined to improve the accuracy of blood pressure measurement.
The first stage is an inflation stage, which is divided into rapid inflation and linear inflation, and the rapid inflation can improve the measurement efficiency.
When the pressure value is lower than the set threshold value of 25mmHg, a rapid inflation method is adopted, several groups of speed threshold values are set, and open-loop adjustment is directly carried out on PWM, and the rapid inflation process is shown in figure 2.
4 speed thresholds were set, including 15mmHg/s, 10mmHg/s, 8mmHg/s, and 3 mmHg/s. The inflation speed is preferably 3-8mmHg/s, so when the actual inflation speed is more than 15mmHg/s, the PWM duty ratio is directly increased, and the increase amplitude is 5; similarly, when the actual inflation speed is greater than 10mmHg/s, the PWM duty ratio is directly increased, and the increase amplitude is 2; when the actual inflation speed is more than 8mmHg/s, directly increasing the PWM duty ratio, wherein the increase amplitude is 1; when the actual inflation speed is less than 3mmHg/s, the PWM duty ratio is directly reduced, and the reduction amplitude is 2.
When the pressure value reaches a set threshold value, in order to ensure the stability of the inflation phase and facilitate the acquisition of more stable pulse wave signals, PWM is regulated and controlled in real time through a pid control method so as to further control the inflation process. The control principle is as shown in fig. 3, the target rate is set to 3.7mmHg/s, and the deviation signal e (t) indicates that the difference between the actual rate and the target rate is a proportional control part corresponding to the proportional coefficient Kp; the last deviation signal e (t-1) is an integral control part and corresponds to an integral coefficient Ki; the difference of the deviation signals, i.e., e (t) -e (t-1), is a differential control section corresponding to a differential coefficient Kd. The Pid control result is shown in equation (7):
pid_result＝e(t)Kp+e(t-1)Ki+[e(t)-e(t-1)]Kd (7)
the pid control regulates the PWM variation amplitude, which is the result obtained by the formula (7).
The inflation phase is complete and the actual inflation curve is shown in figure 4. The inflation process is basically stable, the rising rate is basically stable, and the pressure value basically shows linear increase.
The second phase is a calculation phase, and firstly, pulse wave signals are acquired.
The pulse wave signals are extracted from the original inflation signals through the Butterworth high-pass filter, because the inflation signals belong to time domain signals, baseline wander can be removed through the high-pass filter to obtain the pulse wave signals, the 3-order Butterworth high-pass filter with the cutoff frequency of 0.5Hz is designed, the baseline wander is removed, and the extracted pulse wave signals are shown in figure 5.
The extracted pulse wave signals also have a plurality of high-frequency noise signals, and the extracted pulse wave signals are processed through a Butterworth low-pass filter, so that the signals are purer and smoother. And a 7-order low-pass filter with the cut-off frequency of 3.5Hz is designed to further process the signals, filter redundant high-frequency noise and extract a purer pulse wave signal. The filtering effect is shown in fig. 5, and the spectrogram before and after filtering is shown in fig. 6.
The direct current signal is obtained through the Butterworth low-pass filter, the cut-off frequency is set to be 0.4Hz due to the fact that the human pulse wave signal is about 0.7H-3Hz, and the direct current component in the original signal can be effectively extracted to serve as a reference static pressure value, as shown in figure 7.
Next, peak/valley detection is performed, and a detection starting point is determined first, and the previous inflation process may not acquire a pulse wave signal or the acquired pulse wave signal is weak, so that the detection starting point needs to be determined before peak/valley detection is performed. The minimum detection position is set to 170, and when the inflation pressure value reaches 35mmHg from this detection position, peak/bottom detection is started. And searching one by utilizing the distribution characteristics of the peak value/valley value. The peak/bottom values are detected, and the amplitude and the number of pulse waves are calculated. Two thresholds are set, one being a rise length threshold of 5 and the other being an amplitude threshold of 20. As shown in fig. 8, where data is raw signal data, up _ cnt denotes a rise length, and amp is a change in amplitude from a valley to a peak, i.e., data (i) -data (i-up _ cnt); the position corresponding to the peak value is i, and the peak value is data (i); the position corresponding to the valley value is i-up _ cnt, and the valley value is data (i-up _ cnt). And recording the amplitude of the current pulse wave every time the peak value/valley value is recorded, and increasing the number of the pulse waves one by one.
The heart rate is the number of beats per minute of the heart, and the pulse is the number of beats per minute. The values of both are generally equal. Therefore, the calculation method of the heart rate is calculated by the pulse wave detection condition. The ratio of the sum of the time distances to the number of pulse waves is obtained by calculating the time distance between every two adjacent pulse waves (from the starting position to the ending position). And finally, calculating the pulse beating times per minute by combining the signal sampling frequency of 50Hz, and further obtaining the heart rate value. Namely, Bmp (60 × 50)/average pulsation, where average pulsation is the time distance/pulse number.
In the actual detection process, some oscillation phenomena may exist, the amplitude is not very stable, and the filtering smoothing processing is performed on the original amplitude by adopting a median filtering mode and a mean filtering mode.
And (4) median filtering, wherein the window length is set to 5, namely, the median is sorted and screened every 5 amplitude sequences. The amplitudes of the first and last bits in the sequence remain unchanged and the amplitudes of the second and penultimate bits are calculated using the average of the three amplitudes. Assuming that the original amplitude sequence is data, the total sequence length is N, and the filtered sequence is data1, the filtering process is performed according to the following rules.
data1(0)＝data(0)；
data1(1)＝(data(0)+data(1)+data(2))/3；
data1(N-2)＝(data(N-3)+data(N-2)+data(N-1))/3；
data1(N-1)＝data(N-1)
data1(i) is two amplitudes around point i, and if the 5 values are sorted from large to small, data1(i) is the middle value of the 5 sorted amplitudes.
And (4) mean filtering, namely smoothing the original data by using a mean mode. The window length is set to 3 and the initial and end values remain unchanged. Others are processed by averaging every 3 numbers. Assuming that the original sequence is data, the sequence length is N, and the filtered sequence is data1, the average filtering rule is as follows:
data1(0)＝data(0)；
data1(N-1)＝data(N-1)；
data1(i)＝(data(i-1)+data(i)+data(i+1))/3
the amplitude curve after the filtering treatment is smoother, and the oscillation phenomenon of the pulse wave is improved.
The linear interpolation fitting can make the original curve more complete, the estimation of unknown data points through the known data sequence can play a role in compensating missing data, and the proportion is distributed mainly according to the distance of the known points. Firstly, extending an original amplitude sequence, wherein the initial position is 1, and the initial amplitude is 0; the end position is the length of the original data sequence and the end amplitude is also 0. Then, a scaling factor k and an offset b are determined. The magnitude sequence is y (n), the magnitude position sequence is x (n), and i represents a sequence point.
distance＝x(i)-x(i-1)
value＝y(i)-y(i-1)
k(i-1)＝value/distance
b(i-1)＝y(i-1)-k(i-1)*x(i-1)
The filtered and fitted linear interpolation amplitude curve is smoother and more complete than the original amplitude curve, and better presents the envelope shape of the pulse wave, such as the diamond connection curve in fig. 9, the diamond marked points on the curve are the amplitude points of the original amplitude after the median filtering and the mean filtering, and the original amplitude sequence is the five-pointed star connection line in fig. 9. The original amplitude sequence has a certain oscillation phenomenon, is smoother after filtering processing, can reflect the oscillation change trend of the original pulse wave, and has a more complete amplitude curve after linear interpolation, thereby realizing the pulse wave envelope in the whole measurement process.
The position where the pulse wave amplitude is the maximum is the mean arterial pressure abp, so the mean pressure position is determined by the amplitude, the mean pressure position is determined by obtaining the maximum pulse wave amplitude, and the pressure value corresponding to the current position is the magnitude of the mean pressure, as shown in the blue five-pointed star label of fig. 9.
And calculating a blood pressure value by combining a proportionality coefficient method and a plurality of compensation methods, detecting initial dbp and sbp by the proportionality coefficient method, and setting thresholds of the dbp and the sbp by using the proportionality coefficient with the abp position as a reference point. The amplitude coefficients are referred to in the literature, but are empirical values, and the different test equipment configurations may vary greatly. In connection with the study of the present invention, the sbp amplitude coefficient was set to 0.69 and the dbp amplitude coefficient was set to 0.33. Therefore, the amplitude threshold of sbp is 0.69 times of the amplitude of abp; the threshold amplitude value of dbp is 0.33 times the amplitude value of abp.
The reference value is the average pressure, the reference position is the average pressure position, and the detection positions of the reference value and the reference position are different. The detection of sbp is the detection after the position of the average pressure, and the detection is carried out after the position of the average pressure is searched backwards until the detection is finished. And dbp is detected from the start point to the end of the average pressure position. When the first blood pressure value is lower than the amplitude threshold value, the corresponding blood pressure value is the corresponding initial sbp or dbp, the sbp and dbp are distributed on two sides of abp, as shown in the dark five-pointed star marked position in fig. 9, and the dark origin is the corresponding sbp and dbp position in the amplitude curve.
Sbp and dbp obtained by the initial scale factor method may have a certain error with an actual value, so that the error needs to be compensated, a threshold coefficient compensation method is adopted for dbp, and an amplitude normalization compensation method is adopted for sbp.
The threshold coefficient compensation method is used for compensating by setting a reference value, the compensation position takes a dbp position as a reference, the compensation reference value is about 70 basically, the compensation reference value is set to be 68 in the embodiment, and a proportionality coefficient of 0.67 is set to realize the compensation effect on dbp by calculating the difference between the original dbp value and the reference threshold value. The compensation reference values are as indicated by the light colored five pointed stars in fig. 9.
The amplitude normalization compensation method obtains normalization parameters by utilizing the relationship between the pulse wave oscillation amplitude and the pressure value, obtains the average value of 7 maximum amplitudes, determines the blood pressure value corresponding to the average value by utilizing the normalization parameters, and finally obtains the final sbp value by utilizing linear transformation, wherein the linear parameter is linerparameter ═ 0.5685,29.9947 }. Namely, it is
Normalized parameter is maximum amplitude value/maximum blood pressure value of pulse wave
Normalized blood pressure value as amplitude average value/normalized parameter
Final blood pressure value (normalized blood pressure value) (linerparameter [0] + linerparameter [1]
Outputting the result, as shown in fig. 9, where the actual reference blood pressure of the measurement data is sbp-110, dbp-68; the original amplitude coefficient method measures sbp 139, sbp 82, abp 124, the whole is shifted upwards, and the compensated measurement results sbp 110 and dbp 76.
The above examples are further detailed descriptions of the present invention in conjunction with specific scenario implementations, and the present invention is not considered to be limited thereto. For those skilled in the art to which the invention pertains, several simple deductions or substitutions can be made without departing from the spirit of the invention, and all of them belong to the protection scope of the invention.
Claims (9)
1. A wearable equipment boost blood pressure measurement calculation method comprises a control inflation stage and a blood pressure calculation stage, and is characterized in that: the control inflation phase comprises:
carrying out quick inflation, and carrying out open-loop control on the PWM through setting a speed threshold when the pressure value is lower than the set threshold;
or linear inflation, when the static pressure value reaches a set threshold value, a stable linear inflation process is realized by using closed-loop control to adjust PWM;
the blood pressure calculation stage comprises the following steps:
s1, obtaining pulse oscillation wave signals, removing noise such as baseline drift and the like through the combination of Butterworth high-pass filtering and low-pass filtering, and extracting relatively pure pulse wave signals; simultaneously, extracting a direct current component in the signal by using a Butterworth low-pass filter to be used as a static pressure reference value;
and S2, peak/valley detection, namely detecting the peak and valley values of the processed pulse wave signals, searching the original pulse wave signal sequence one by one in a one-by-one searching mode, judging the ascending and descending processes of the sequence, identifying a peak point if the ascending process reaches a certain length and the amplitude reaches a set threshold value, and identifying the point at which the ascending starts as a valley point and the difference value of the two as the amplitude. The peak value point corresponds to the valley value point, the amplitude value point corresponds to the pulse frequency, and the heart rate is calculated according to the pulse frequency;
s3, smoothing and fitting the amplitude curve, firstly carrying out filtering processing on the amplitude curve by using median filtering and mean filtering, and then fitting the processed amplitude curve by using linear interpolation fitting to obtain a smoother and more complete pulse wave amplitude curve;
s4, calculating a blood pressure value, identifying a static pressure value corresponding to the maximum value of the amplitude curve as an average pressure, calculating the amplitudes of diastolic pressure and systolic pressure by an amplitude coefficient method, and acquiring the corresponding static pressure value as a corresponding blood pressure value;
s5, blood pressure compensation, namely compensating diastolic pressure by using a coefficient method and compensating systolic pressure by using an amplitude normalization proportion method;
and S6, finishing the measurement, wherein the condition for judging the end of the measurement comprises that the corresponding diastolic pressure and systolic pressure or the pressure of the measured part exceed the preset maximum pressure value or the measurement duration exceeds the preset maximum measurement duration, finishing the measurement and quickly deflating.
2. The wearable device boost blood pressure measurement calculation method of claim 1, wherein: the steps of linear inflation are as follows: by the pid control method, a deviation is formed by a target value and an actual output value, and a proportional, integral, and differential linearity of the deviation is combined to form a control amount, thereby controlling the controlled object.
3. The wearable device boost blood pressure measurement calculation method of claim 1, wherein: in the step S1, the butterworth high-pass filtering and the low-pass filtering are combined to obtain the pulse oscillation signal in the original inflation signal, and the specific steps are as follows:
setting indexes: pass-band cut-off frequency, pass-band maximum attenuation, stop-band minimum attenuation, and sampling frequency;
designing an analog butterworth high/low pass filter (prototype filter);
bilinear transformation: obtaining a system function of the digital filter;
linear difference equation of solution coefficients: a filtered signal is obtained.
4. The wearable device boost blood pressure measurement calculation method of claim 1, wherein: the specific steps of the median filtering in step S3 are as follows:
1) setting the length of a filter, namely the number of sequence elements transmitted each time;
2) sorting the incoming sequences from large to small;
3) and returning the intermediate value of the reordered sequence.
5. The wearable device boost blood pressure measurement calculation method of claim 1, wherein: the specific steps of the mean filtering in step S3 are as follows:
setting the length of a filter, namely the number of sequence elements transmitted into the filter each time;
the average of the incoming sequence is calculated and returned.
6. The wearable device boost blood pressure measurement calculation method of claim 1, wherein: the linear interpolation fitting method in step S3 is to perform numerical estimation mainly based on data near left and right of a point to be interpolated in the one-dimensional data sequence, and the point (x) is known0,y0)、(x1,y1) And calculating the corresponding y value at the interpolation point x by using an equal proportion method, wherein x belongs to (x)0,x1)。
7. The wearable device boost blood pressure measurement calculation method of claim 1, wherein: the step S4 calculates the initial systolic pressure and diastolic pressure by the amplitude coefficient method.
8. The wearable device boost blood pressure measurement calculation method of claim 1, wherein: the step S5 compensates the initial blood pressure value by a coefficient method and an amplitude normalization ratio method to obtain a more accurate result.
9. The wearable device boost blood pressure measurement calculation method of claim 1, wherein: in step S6, the condition for ending the measurement includes that the calculated result exceeds a preset maximum pressure value or exceeds a maximum measurement time. The preset maximum pressure value is 256mmHg and the maximum measurement time is preset to 70 s.
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