CN116269274B - Blood pressure monitoring intelligent patch, dynamic blood pressure monitoring method, device and storage medium - Google Patents
Blood pressure monitoring intelligent patch, dynamic blood pressure monitoring method, device and storage medium Download PDFInfo
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- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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Abstract
The invention relates to an intelligent patch for blood pressure monitoring and a method, equipment and a storage medium for dynamic blood pressure monitoring, wherein the method comprises the following steps: obtaining core impact data through a pressure sensing patch module and an LED-photodiode module; judging the body position through the heart attack data; acquiring a blood pressure calculation model corresponding to the body position; extracting heart attack data of the strongest pressure sensing patch of the signal, and calculating waveform characteristic points and frequency domain characteristics; summarizing the time domain features and the main component features as the input of a blood pressure calculation model to calculate blood pressure; and obtaining stable blood pressure measurement results through a voting mechanism by using the blood pressures obtained by two different paths. The invention measures the ballistocardiogram through the LED-photodiode module and the BCG through the pressure sensing patch module, and has the advantages of ventilation and comfort; meanwhile, the LED-photodiode module and the pressure sensing patch module are started to realize multimode sensing, and acquisition of an optimal signal and measurement of dynamic characteristics during body position change can be realized in annular light source switching.
Description
Technical Field
The invention relates to the technical field of blood pressure measurement, in particular to an intelligent patch for blood pressure monitoring and a dynamic blood pressure monitoring method, equipment and a storage medium.
Background
Blood pressure is one of important vital signs, is closely related to the prognosis of cardiovascular diseases, and can effectively reduce the risk of cardiovascular accidents through early screening of hypertension. The wearable dynamic blood pressure monitoring technology has the advantages of forward movement of a screening window, detection outside a clinical environment, comfort in no sense and the like, and has positive significance in promoting the knowledge, treatment and long-term management of hypertension. However, the related innovative technologies at present have some inherent problems, mainly focused on the aspects of body position instability (unstable information transmission), contact pressure, measurement comfort and price.
1. The body position is not fixed: sleep blood pressure is typically measured by an upper arm cuff sphygmomanometer or wristwatch. The upper arm cuff sphygmomanometer is fixed relative to the heart, but when inflated, sleep is easily affected, so that the measured blood pressure value is in an interfered state and cannot reflect the real sleep blood pressure. Wrist watch type sphygmomanometers are extremely susceptible to body position. Even in the sleeping state, the relative positions of the wristwatch and the heart are not fixed under different sleeping postures due to the flexibility of the upper limbs. During the blood flow transmission from the heart to the extremities, the inconsistent paths lead to unstable deviations of most of the blood pressure related information, resulting in a large overall blood pressure assessment error.
2. Contact pressure: when wearing the wristwatch, even in the night quiet environment, different contact pressures are generated due to water metabolism and other reasons, so that the error is far larger than that of the traditional sphygmomanometer, and the development of the technology is restricted. In the process of taking off and re-wearing the wristwatch, the problems of inconsistent wearing positions and calibration failure also exist. In too lean people, poor contact easily causes light leakage, and causes excessive noise.
3. Comfort and price: the upper arm cuff sphygmomanometer is large in size, uncomfortable to wear and can influence sleeping due to inflation and deflation. Although the intelligent wristwatch can be used for measuring blood oxygen, heart rate and the like, the wristwatch with high accuracy and medical instrument registration card can only be measured intermittently by adopting a micro-air bag technology, and has certain problems in air permeability, comfort and measurement continuity and higher price.
Disclosure of Invention
To achieve the above and other advantages and in accordance with the purpose of the present invention, a first object of the present invention is to provide a dynamic blood pressure monitoring method, comprising the steps of:
respectively acquiring the heart impact data through the pressure sensing patch module and the LED-photodiode module;
judging the body position through the obtained ballistocardiogram data;
acquiring a corresponding blood pressure calculation model through the judged body position;
extracting heart attack data of the strongest pressure sensing patch of the signal, dividing each beat of heart according to the feature points, marking the feature points, calculating positive and negative amplitude values and arrival time of each feature point, and obtaining a plurality of time domain features;
the method comprises the steps of intercepting data of preset time each time in a sliding window mode, performing wavelet transformation to form an intensity diagram of a series of frequencies, and performing Fourier frequency domain transformation on each frequency to form a two-dimensional spectrogram;
reducing the dimension of the two-dimensional spectrum into a plurality of main component characteristics by a main component analysis method;
summarizing the time domain features and the main component features as the input of a corresponding blood pressure calculation model to calculate blood pressure;
and obtaining a stable blood pressure measurement result through a voting mechanism by using the blood pressure calculated by the ballistocardiogram data obtained through the pressure sensing patch module and the blood pressure calculated by the ballistocardiogram data obtained through the LED-photodiode module.
Further, obtaining ballistocardiogram data through the LED-photodiode module comprises the steps of:
controlling the fabric LEDs to emit pulsed light;
pulse light measurement is performed through a photodiode;
converting the obtained transmural pressure into blood volume, wherein the conversion formula is as follows:
wherein->To specify the transmutation pressure->Corresponding blood volume, < > or>Is->The corresponding blood volume is then calculated,for maximum blood volume, ++>Is->Maximum compliance at that time.
Further, the obtaining the ballistocardiographic data through the LED-photodiode module further comprises the steps of:
controlling the fabric LEDs which are annularly arranged to alternately emit light in a time-sharing multiplexing mode;
pulsed light measurement by cyclic time-division multiplexing is performed by photodiodes.
Further, the obtaining the ballistocardiographic data through the LED-photodiode module further comprises the steps of:
and (3) reducing the dimension of the two-dimensional spectrum into a plurality of principal component characteristics by a principal component analysis method, and then calculating to obtain a weighted principal component evaluation value, and obtaining a signal with the highest fundamental frequency content of the weighted principal component as an optimal signal.
Further, acquiring the heart attack data and the photoplethysmography data simultaneously through the LED-photodiode module; the method comprises the steps of obtaining ballistocardiogram data through pulse intensity change caused by periodical contact pressure change, and obtaining photoelectric volume pulse data through intravascular pressure pulsation and perfusion; based on the ballistocardiogram data, calculating the vascular elasticity and the blood pressure fluctuation through the photoelectric volume pulse data, and specifically comprising the following steps of:
acquiring pulse wave recovery time through the photoplethysmography pulse data;
calculating the elasticity of blood vessels and the fluctuation of blood pressure according to the pulse wave recovery time;
the blood pressure calculation model is modified by vascular elasticity and blood pressure fluctuations.
Further, the step of determining the body position from the obtained ballistocardiogram data includes the steps of:
sequentially sequencing a plurality of pressure sensing patches according to the placement positions;
if the ballistocardiogram measured by the pressure sensing patch is descending according to the sequence from small to large, judging the ballistocardiogram as a first side position;
if the ballistocardiogram measured by the pressure sensing patch is increased according to the sequence from small to large, judging the ballistocardiogram as a second side position;
if the pressure sensing patches corresponding to the maximum value of the measured ballistocardiogram data are positioned at the central position in a descending manner according to the sequence from small to large, and the ballistocardiogram data measured by the pressure sensing patches at the two sides are all descending, the supine position is judged;
if the signal intensity measured by the pressure sensing patch does not meet the preset intensity or does not contain heart rate information, the pressure sensing patch is judged to fall;
if the signal intensity measured by the pressure sensing patch meets the preset intensity or contains heart rate information and does not belong to the first side position, the second side position and the supine position, the prone position is determined.
Further, the step of summarizing the time domain features and the principal component features as inputs of a corresponding blood pressure calculation model, and further includes the steps of:
selecting a pressure sensing patch with the similarity of the signal to noise ratio and the strongest pressure sensing patch reaching a preset value, jumping to extract heart impact data of the pressure sensing patch, dividing each beat of heart beat according to characteristic points, marking the characteristic points, calculating positive and negative amplitude values and arrival time for each characteristic point, and continuously executing the steps of obtaining a plurality of time domain characteristics;
judging whether the difference between the calculated blood pressure and the blood pressure calculation result corresponding to the signal strongest pressure sensing patch is within a preset range;
if yes, taking the average value of the blood pressure calculation results of the selected pressure sensing patches as a blood pressure calculation result;
otherwise, outputting a blood pressure calculation result corresponding to the intensity of the strongest pressure sensing patch of the signal, and simultaneously giving out a confidence degree mark.
A second object of the present invention is to provide an electronic device including: a memory having program code stored thereon; a processor coupled with the memory and when the program code is executed by the processor, implementing a dynamic blood pressure monitoring method.
A third object of the present invention is to provide a computer readable storage medium having stored thereon program instructions that when executed implement a dynamic blood pressure monitoring method.
The invention provides an intelligent patch for blood pressure monitoring, which comprises a pressure sensing patch module and an LED-photodiode module, wherein the pressure sensing patch module comprises a plurality of pressure sensing patches, connecting wires, a battery and a signal processing module, the LED-photodiode module comprises a plurality of fabric LEDs and photodiodes, the pressure sensing patches are sequentially connected and then are connected with a power supply and the signal processing module through the connecting wires, the signal processing module is used for transmitting data or locally storing the data in a wireless communication mode, the fabric LEDs and the photodiodes are embedded in fabric fibers, the fabric LEDs alternately emit light in a time-sharing multiplexing mode, the photodiodes are used for converting optical signals of the fabric LEDs irradiated to the photodiodes into electric signals, the pressure sensing patches are embedded in a silica gel cushion, and the pressure sensing patches embedded in the silica gel cushion are externally hung on fabrics embedded with the fabric LEDs and the photodiodes.
Further, a plurality of the fabric LEDs are annularly arranged in the fabric fiber, and the photodiode is positioned in the center of an annular shape formed by the arrangement of the fabric LEDs.
Compared with the prior art, the invention has the beneficial effects that:
aiming at the defects of low sampling rate and discomfort of the traditional sphygmomanometer and the problems of body position (unstable information transmission), contact pressure and measurement comfort of the wearable wristwatch, the invention performs blood pressure measurement by designing the intelligent patch for shoulder blood pressure monitoring, and measures BCG (Ballistocardiograph) through an LED-photodiode module and a pressure sensing patch module respectively. Because the fabric LEDs and the photodiodes are buried in the fabric fibers, the pressure sensing patch is not in direct contact with the skin, and the fabric LED/photodiode composite patch has the advantages of ventilation and comfort; meanwhile, the LED-photodiode module and the pressure sensing patch module are started, so that multimode sensing can be realized, and the acquisition of an optimal signal and the measurement of dynamic characteristics during body position change can be realized in annular light source switching; through mutual verification of a plurality of pressure sensing patches, signal reliability is improved, and output blood pressure reliability is higher.
The foregoing description is only an overview of the present invention, and is intended to provide a better understanding of the present invention, as it is embodied in the following description, with reference to the preferred embodiments of the present invention and the accompanying drawings. Specific embodiments of the present invention are given in detail by the following examples and the accompanying drawings.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this application, illustrate embodiments of the invention and together with the description serve to explain the invention and do not constitute a limitation on the invention. In the drawings:
fig. 1 is a schematic diagram of a blood pressure monitoring smart patch of example 1;
fig. 2 is a top view of the blood pressure monitoring smart patch of example 1;
FIG. 3 is a schematic diagram of an LED-photodiode module embedding design according to embodiment 1;
fig. 4 is a schematic diagram of a placement position of a pressure-sensitive patch module in embodiment 1;
FIG. 5 is a schematic diagram of a human body elastic damping model of example 1;
FIG. 6 is a flow chart of the dynamic blood pressure monitoring method of embodiment 2;
FIG. 7 is a schematic diagram of the definition of OS and HW of example 2;
FIG. 8 is a graph showing the relationship between the dynamic response and the hemodynamic parameters of example 2;
FIG. 9 is a ballistocardiogram extraction schematic diagram of example 2;
FIG. 10 is a schematic diagram of the impact graph of example 2 with characteristic points;
FIG. 11 is a process diagram of a two-dimensional spectrogram formed by performing Fourier transform on each frequency after wavelet transform in example 2;
fig. 12 is a schematic diagram showing the two-dimensional spectrogram reduced to 9 principal component features by principal component analysis according to example 2;
FIG. 13 is a Bayesian network diagram of embodiment 2;
fig. 14 is a schematic view of an electronic device of embodiment 3;
fig. 15 is a schematic view of a storage medium of embodiment 4.
In the figure: 1. a pressure sensing patch; 2. fabric LEDs; 3. a photodiode; 4. a silica gel cushion; 5. a conductive wire; 6. a fabric fiber.
Detailed Description
The present invention will be further described with reference to the accompanying drawings and detailed description, wherein it is to be understood that, on the premise of no conflict, the following embodiments or technical features may be arbitrarily combined to form new embodiments.
Example 1
The intelligent patch for blood pressure monitoring is used for obtaining the ballistocardiogram signal and calculating the blood pressure. The intelligent patch for blood pressure monitoring is mainly inlaid below the collar of the back and can be fixed on the personal clothing, and meanwhile, the intelligent patch for blood pressure monitoring can be designed in a detachable mode. As shown in fig. 1 and 2, the pressure sensing patch module comprises a pressure sensing patch module and an LED-photodiode module, wherein the pressure sensing patch module comprises a plurality of pressure sensing patches 1, connecting wires, a battery and a signal processing module, and in the embodiment, the pressure sensing patches adopt EMFi pressure sensing sheets, so that the pressure sensing patch has the advantages of light and thin texture and pressure sensitivity, and the measurement of a stable ballistocardiogram based on neck and shoulder EMFi is realized in the prior study. As shown in fig. 3, the LED-photodiode module includes a plurality of fabric LEDs 2 and photodiodes 3, and the fabric LEDs 2 and photodiodes 3 are embedded by conductive wires 5 to form a soft, skin-friendly, and non-inductive breathable optical measurement. The pressure sensing patches are sequentially connected, as shown in fig. 4, the EMFi pressure sensing patches with the marks of 1 to 5 are sequentially connected, the pressure sensing patches are sequentially connected and then connected with a power supply and a signal processing module through connecting wires, and the signal processing module is used for transmitting data in a wireless communication mode or locally storing the data, such as transmitting data in a Bluetooth mode. Since the shoulder is not related to the cervical vertebrae, the cervical vertebrae are less affected by the elasticity of the neck. A plurality of fabric LEDs 2 and photodiodes 3 are embedded in fabric fibers 6, so that the fabric is very skin-friendly. The fabric LEDs alternately emit light in a time-sharing multiplexing mode, the photodiodes are used for converting optical signals of the fabric LEDs irradiated to the photodiodes into electric signals, the pressure sensing patches 1 are embedded in the silica gel cushion 4, and the pressure sensing patches embedded in the silica gel cushion are externally hung on fabrics embedded with the fabric LEDs and the photodiodes and are detachable.
The intelligent patch for blood pressure monitoring can collect two signals of photoplethysmography (PPG) data and BCG at the same time, and can form a patch module, preferably 5 pressure sensing patches. Too small a patch area will affect the strength of the signal, reduce the signal to noise ratio, and too large a patch will cause discomfort in wearing and the number of sampling points. The 5 pressure sensing patches not only can mutually verify the reliability of signals, but also can judge sleeping positions, namely left lying position, right lying position, supine position or prone position. Compared with the sensor arranged under the pillow, the intelligent patch for blood pressure monitoring has the advantages that the heart attack chart signal of the whole neck is generally measured under the pillow, and the intelligent patch is affected by the body position and the relative position of the neck and the pillow. Most importantly, the neck belongs to an elastic component in mechanical modeling, as shown in fig. 5, the measurement of the neck needs to consider the influence of elastic parameters, and the individuation difference is large.
As shown in fig. 2, a plurality of fabric LEDs are circularly arranged in the fabric fiber, and a photodiode is located at the center of the loop formed by the arrangement of the fabric LEDs. Different light sources adopt a time-sharing multiplexing mode to alternately emit light, so that the mutual noninterference of signals can be realized, and the selection of the optimal signals can be realized.
According to the invention, through the annularly arranged fabric LEDs, the pulse light measurement of cyclic time-sharing multiplexing is realized, and the stable extraction of the ballistocardiogram and the PPG signal is realized. Particularly in the case of body position changes, due to local pressure changes, there is a lag response of reperfusion in the PPG signal, and accurate measurement of the time sequence thereof will help to evaluate the vascular elasticity (poor elasticity with less lag), thereby improving the accuracy of blood pressure evaluation.
According to the invention, the mechanical measurement of the ballistocardiogram is realized through the pressure sensing patch embedded by the silica gel soft pad, and the blood pressure is obtained through the modes of feature extraction, two-dimensional spectrum information compression and Bayesian network fitting.
The invention adopts the fabric LEDs and the photodiodes to realize flexible and breathable photoelectric volume pulse wave measurement, and realizes PPG-based ballistocardiogram measurement (0.3-18 Hz frequency band) through the change of the ballistocardiogram force during respiration and heartbeat on the contact pressure. At the sensor end, the skin-fabric LED-pressure sensing patch compound sensing realizes the blood pressure evaluation of two measuring paths, and more stable blood pressure measurement can be obtained through a voting mechanism.
The detailed description of the dynamic blood pressure monitoring method based on the blood pressure monitoring intelligent patch can refer to the corresponding description in the following method embodiments, and will not be repeated here.
Example 2
Based on the dynamic blood pressure monitoring method of the blood pressure monitoring intelligent patch provided in embodiment 1, the detailed description of the blood pressure monitoring intelligent patch may refer to the corresponding description in the above-mentioned blood pressure monitoring intelligent patch embodiment, and will not be repeated here. The dynamic blood pressure monitoring method is shown in fig. 6, and comprises the following steps:
respectively acquiring the heart impact data through the pressure sensing patch module and the LED-photodiode module;
judging the body position through the obtained ballistocardiogram data; the method specifically comprises the following steps:
sequentially sequencing a plurality of pressure sensing patches according to the placement positions; as shown in fig. 4, taking 5 pressure-sensitive patches as an example, the pressure-sensitive patches are sequentially ordered from left to right into 1, 2, 3, 4, 5.
If the ballistocardiogram measured by the pressure sensing patch is descending according to the sequence from small to large, judging the ballistocardiogram as a first side position; in this embodiment, the first side position is a left side position.
If the ballistocardiogram measured by the pressure sensing patch is increased according to the sequence from small to large, judging the ballistocardiogram as a second side position; in this embodiment, the second side position is the right side position.
If the pressure sensing patches corresponding to the maximum value of the measured ballistocardiogram data are positioned at the central position in a descending manner according to the sequence from small to large, and the ballistocardiogram data measured by the pressure sensing patches at the two sides are all descending, the supine position is judged;
if the signal intensity measured by the pressure sensing patch does not meet the preset intensity or does not contain heart rate information, the pressure sensing patch is judged to fall;
if the signal intensity measured by the pressure sensing patch meets the preset intensity or contains heart rate information and does not belong to the first side position, the second side position and the supine position, the prone position is determined.
The ballistocardiogram measurement data based on the LED-photodiode module and the ballistocardiogram measurement data of the neck and shoulder EMFi pressure sensing sheet are equivalent data of different path measurements, only the difference of signal to noise ratio exists, the EMFi data is better in general, and the difference is larger in special cases. Such as: in the case that the neck and shoulder EMFi pressure sensing piece is separated from the skin, the ballistocardiogram measurement data based on the LED-photodiode module is only poor, but the ballistocardiogram based on the EMFi pressure sensing piece does not contain effective information. The signal quality of an EMFi pressure sensitive sheet depends on contact, there being no signal once out of contact; the optical signal is only a light spot which is large, and the signal to noise ratio is poor, but can also be used.
Acquiring a corresponding blood pressure calculation model through the judged body position; i.e. the blood pressure calculation is classified according to body position and different training data are formed. The bayesian network of preset body positions can form targeted parameters. When in blood pressure prediction, body position prediction is performed first, and test data are input into a Bayesian model trained by the same body position data.
As shown in fig. 9, the heart attack data of the pressure sensing patch with the strongest signal is extracted, each beat of heart is segmented according to the characteristic points, the characteristic points are marked, as shown in fig. 10, I, J, K and L4 characteristic points are total, positive and negative amplitude values and arrival time are calculated for each characteristic point, and 12 time domain characteristics are obtained;
the wavelet transformation is performed by cutting out the data of the preset time each time in a sliding window mode, the intensity diagram of a series of frequencies is formed as shown in the diagram of the lower left position in fig. 11, the intensity diagram of the series of frequencies is formed as shown in the diagram of the upper left position in fig. 11, the Fourier frequency domain transformation is performed on each frequency, the two-dimensional spectrogram is formed as shown in the diagram of the upper right position in fig. 11, and the two-dimensional spectrogram is formed as shown in the diagram of the lower right position in fig. 11. The sliding window method of this embodiment is to shift the window of 5 seconds back for a period of time each time, and this embodiment takes 5 seconds as an example. The final fitted blood pressure was the blood pressure averaged over a 5 second sliding window, with a sampling time of 1 second.
The two-dimensional spectrum was reduced in dimension to 9 principal component features by principal component analysis, as shown in fig. 12. The high frequency principal component does not contribute to blood pressure monitoring and is not considered in the model. The two-dimensional spectrum will greatly compress the original data volume while not damaging the blood pressure information contained in the data. For example, at a sampling rate of 100Hz, a 20s measurement yields 2000 BCG data points, which after 2-14Hz wavelet spectrum splitting form a 13x2000 matrix, which is also the data volume of the traditional two-dimensional spectrum. The present embodiment is based on the first fourier analysis of each band, assuming that the fourier reserves 15 frequencies around the center frequency, the data will be compressed to 13x15. After principal component analysis, further compression was 13x9. Despite the extreme compression of the data, blood pressure related information, namely body vibrations from cardiac ejection, is fully preserved.
By means of wavelet transformation and Fourier transformation of each wavelet frequency band, two-dimensional spectrograms of two frequency domain axes are realized, and different from the traditional method that frequency domain decomposition is realized only in the wavelet transformation direction to form a frequency domain-time domain distribution map, the two-dimensional frequency domain (wavelet base) -frequency domain (long-time correlation) distribution not only realizes lossless compression of data, but also realizes extraction of main components.
Summarizing the time domain features (namely the 12 features) and the principal component features (namely the 9 features) as the input of a corresponding blood pressure calculation model (namely a Bayesian network), and carrying out blood pressure calculation through an artificial intelligent model formed by pre-data training;
selecting a pressure sensing patch with the similarity of the signal to noise ratio and the strongest pressure sensing patch reaching a preset value, if the similarity of the signal to noise ratio is set to be more than 70%, jumping to extract heart impact data of the pressure sensing patch, dividing each beat of heart according to characteristic points, marking the characteristic points, calculating positive and negative amplitude values and arrival time of each characteristic point, and continuously executing the steps of obtaining a plurality of time domain characteristic points;
judging whether the difference between the calculated blood pressure and the blood pressure calculation result corresponding to the signal strongest pressure sensing patch is within a preset range; such as: the preset range is set to be within 5 mmHg.
If yes, taking the average value of the blood pressure calculation results of the selected pressure sensing patches as a blood pressure calculation result;
otherwise, outputting a blood pressure calculation result corresponding to the strongest pressure sensing patch intensity of the signal, and simultaneously giving out a confidence degree label, wherein the confidence degree is inversely proportional to the variance of the blood pressure output by the selected sensor.
And obtaining a stable blood pressure measurement result through a voting mechanism by using the blood pressure calculated by the ballistocardiogram data obtained through the pressure sensing patch module and the blood pressure calculated by the ballistocardiogram data obtained through the LED-photodiode module.
Ballistocardiogram measurement based on an LED-photodiode module belongs to indirect measurement, and a conversion relation between contact pressure and blood volume (PPG or V) is needed. Specifically, obtaining ballistocardiogram data through an LED-photodiode module comprises the steps of:
controlling the fabric LEDs to emit pulsed light;
pulse light measurement is performed through a photodiode;
converting the obtained transmural pressure into blood volume, wherein the conversion formula is as follows:
wherein->To specify the transmutation pressure->Corresponding blood volume, < > or>Is->The corresponding blood volume is then calculated,for maximum blood volume, ++>Is->The maximum compliance at the time of the manufacture,right upper corner->To the negative power.
Through the annular arrangement of the fabric LEDs, the pulse light measurement of cyclic time-sharing multiplexing is realized, and the stable extraction of the ballistocardiogram and the PPG signal is realized. Particularly in case of body position changes, due to local pressure changes, there is a lag response of reperfusion in the PPG signal, and accurate measurement of the time sequence of the lag response will help to evaluate the vascular elasticity (poor elasticity, less lag), thereby improving the accuracy of blood pressure evaluation. Specifically, obtaining the ballistocardiographic data through the LED-photodiode module further comprises the steps of:
controlling the fabric LEDs which are annularly arranged to alternately emit light in a time-sharing multiplexing mode;
pulsed light measurement by cyclic time-division multiplexing is performed by photodiodes.
The two-dimensional spectrum is reduced to a plurality of principal component characteristics by a principal component analysis method, and then weighted principal component evaluation values are obtained by calculation, for example, after signal decomposition, the weighted principal component evaluation values are obtained when the energy distribution of 9 principal components is Ei.And acquiring a signal with the highest fundamental frequency content of the weighted main component as an optimal signal.
The change in contact pressure P will cause a change in V and thus a corresponding fluctuation in PPG from which the ballistocardiogram can be measured. The measurement, due to the pressure-volume conversion involved, allows an estimation of the vessel elasticity at the time of the body position change. As shown in fig. 7 and 8. When sleeping posture and body position are changed, the pressure will have a stepwise change, and if the blood vessel elasticity is poor, the buffering time is short, and the fluctuation of blood pressure is aggravated. The blood vessel elasticity and blood pressure fluctuation can be calculated from the time when the blood volume reaches balance, and the blood pressure fitting algorithm is corrected. When the sleeping posture and the body position are changed, the OS (pulse wave) is inversely proportional to the blood vessel elasticity (experimental data), and the blood vessel elasticity is inversely proportional to the blood pressure difference (common sense of physiology). Thus, OS is proportional to the blood pressure differential, i.e. systolic minus diastolic. HW (half-width), pulse wave recovery time) is proportional to peripheral resistance and inversely proportional to heart displacement. The pulse wave recovery time can thus be used to evaluate the average blood pressure change amplitude when the peripheral resistance changes due to body position changes.
The LED-photodiode module can acquire the heart impact data and the photo-volume pulse data at the same time; namely, the LED-photodiode module in the embodiment not only can measure the heart attack data, but also can measure the photoelectric volume pulse data at the same time, so that the robustness of the algorithm is improved. The pulse intensity change caused by the periodical contact pressure change can obtain ballistocardiogram data, and the intravascular pressure pulsation, perfusion and the like can obtain photoelectric volume pulse data; therefore, based on the ballistocardiogram data, the blood vessel elasticity and the blood pressure fluctuation can be calculated through the photoelectric volume pulse data, and the method specifically comprises the following steps of:
acquiring pulse wave recovery time through the photoplethysmography pulse data;
calculating the elasticity of blood vessels and the fluctuation of blood pressure according to the pulse wave recovery time;
the blood pressure calculation model is corrected by the blood vessel elasticity and the blood pressure fluctuation.
Aiming at the defects of low sampling rate and discomfort of the traditional sphygmomanometer and the problems of body position (unstable information transmission), contact pressure and measurement comfort of the wearable wristwatch, the invention performs blood pressure measurement by designing the intelligent patch for shoulder blood pressure monitoring, and measures BCG (Ballistocardiograph) through an LED-photodiode module and a pressure sensing patch module respectively. Because the fabric LEDs and the photodiodes are buried in the fabric fibers, the pressure sensing patch is not in direct contact with the skin, and the fabric LED/photodiode composite patch has the advantages of ventilation and comfort; meanwhile, the LED-photodiode module and the pressure sensing patch module are started, so that multimode sensing can be realized, and the acquisition of an optimal signal and the measurement of dynamic characteristics during body position change can be realized in annular light source switching; through mutual verification of a plurality of pressure sensing patches, signal reliability is improved, and output blood pressure reliability is higher.
Example 3
An electronic device 200, as shown in fig. 14, includes, but is not limited to: a memory 201 having program codes stored thereon; a processor 202 coupled to the memory and which when executed by the processor implements a dynamic blood pressure monitoring method. For detailed description of the method, reference may be made to corresponding descriptions in the above method embodiments, and details are not repeated here.
Example 4
A computer readable storage medium having stored thereon program instructions that when executed implement a method of dynamic blood pressure monitoring, as shown in fig. 15. For detailed description of the method, reference may be made to corresponding descriptions in the above method embodiments, and details are not repeated here.
It should also be noted that the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus. Without further limitation, an element defined by the phrase "comprising one … …" does not exclude the presence of other like elements in a process, method, article or apparatus that comprises an element.
In this specification, each embodiment is described in a progressive manner, and identical and similar parts of each embodiment are all referred to each other, and each embodiment mainly describes differences from other embodiments.
The foregoing is illustrative of the embodiments of the present disclosure and is not to be construed as limiting the scope of the one or more embodiments of the present disclosure. Various modifications and alterations to one or more embodiments of this description will be apparent to those skilled in the art. Any modifications, equivalent substitutions, improvements, or the like, which are within the spirit and principles of one or more embodiments of the present disclosure, are intended to be included within the scope of the claims of one or more embodiments of the present disclosure.
Claims (7)
1. A method for dynamic blood pressure monitoring, comprising the steps of:
respectively acquiring the heart impact data through the pressure sensing patch module and the LED-photodiode module; wherein obtaining the ballistocardiogram data by the LED-photodiode module comprises the steps of:
controlling the fabric LEDs to emit pulsed light;
pulse light measurement is performed through a photodiode;
converting the obtained transmural pressure into blood volume, wherein the conversion formula is as follows:
，
wherein V is a specified wall penetration pressureCorresponding blood volume, < > or>Is->Corresponding blood volume, ->For maximum blood volume, ++>Is->Maximum compliance at time;
the obtaining of the ballistocardiographic data by means of the LED-photodiode module further comprises the steps of:
controlling the fabric LEDs which are annularly arranged to alternately emit light in a time-sharing multiplexing mode;
pulse light measurement of cyclic time-sharing multiplexing is performed through a photodiode;
the two-dimensional spectrum is reduced to a plurality of principal component characteristics through a principal component analysis method, then a weighted principal component evaluation value is obtained through calculation, and a signal with the highest fundamental frequency content of the weighted principal component is obtained to be used as an optimal signal;
judging the body position through the acquired ballistocardiogram data, specifically comprising the following steps:
sequentially sequencing a plurality of pressure sensing patches according to the placement positions;
if the ballistocardiogram measured by the pressure sensing patch is descending according to the sequence from small to large, judging the ballistocardiogram as a first side position;
if the ballistocardiogram measured by the pressure sensing patch is increased according to the sequence from small to large, judging the ballistocardiogram as a second side position;
if the pressure sensing patches corresponding to the maximum value of the measured ballistocardiogram data are positioned at the central position in a descending manner according to the sequence from small to large, and the ballistocardiogram data measured by the pressure sensing patches at the two sides are all descending, the supine position is judged;
if the signal intensity measured by the pressure sensing patch does not meet the preset intensity or does not contain heart rate information, the pressure sensing patch is judged to fall;
if the signal intensity measured by the pressure sensing patch meets the preset intensity or contains heart rate information and does not belong to the first side position, the second side position and the supine position, the prone position is judged;
acquiring a corresponding blood pressure calculation model through the judged body position;
extracting heart attack data of the strongest pressure sensing patch of the signal, dividing each beat of heart according to the feature points, marking the feature points, calculating positive and negative amplitude values and arrival time of each feature point, and obtaining a plurality of time domain features;
the method comprises the steps of intercepting data of preset time each time in a sliding window mode, performing wavelet transformation to form an intensity diagram of a series of frequencies, and performing Fourier frequency domain transformation on each frequency to form a two-dimensional spectrogram;
reducing the dimension of the two-dimensional spectrum into a plurality of main component characteristics by a main component analysis method;
summarizing the time domain features and the main component features as the input of a corresponding blood pressure calculation model to calculate blood pressure;
and obtaining a stable blood pressure measurement result through a voting mechanism by using the blood pressure calculated by the ballistocardiogram data obtained through the pressure sensing patch module and the blood pressure calculated by the ballistocardiogram data obtained through the LED-photodiode module.
2. The dynamic blood pressure monitoring method of claim 1, wherein: acquiring the heart impact data and the photo-volume pulse data simultaneously through an LED-photodiode module; the method comprises the steps of obtaining ballistocardiogram data through pulse intensity change caused by periodical contact pressure change, and obtaining photoelectric volume pulse data through intravascular pressure pulsation and perfusion; based on the ballistocardiogram data, calculating the vascular elasticity and the blood pressure fluctuation through the photoelectric volume pulse data, and specifically comprising the following steps of:
acquiring pulse wave recovery time through the photoplethysmography pulse data;
calculating the elasticity of blood vessels and the fluctuation of blood pressure according to the pulse wave recovery time;
the blood pressure calculation model is modified by vascular elasticity and blood pressure fluctuations.
3. The method for dynamic blood pressure monitoring according to claim 1, wherein the step of summarizing the time-domain features and the principal component features as inputs to a corresponding blood pressure calculation model further comprises the steps of, after the step of calculating the blood pressure:
selecting a pressure sensing patch with the similarity of the signal to noise ratio and the strongest pressure sensing patch reaching a preset value, jumping to extract heart impact data of the pressure sensing patch, dividing each beat of heart beat according to characteristic points, marking the characteristic points, calculating positive and negative amplitude values and arrival time for each characteristic point, and continuously executing the steps of obtaining a plurality of time domain characteristics;
judging whether the difference between the calculated blood pressure and the blood pressure calculation result corresponding to the signal strongest pressure sensing patch is within a preset range;
if yes, taking the average value of the blood pressure calculation results of the selected pressure sensing patches as a blood pressure calculation result;
otherwise, outputting a blood pressure calculation result corresponding to the intensity of the strongest pressure sensing patch of the signal, and simultaneously giving out a confidence degree mark.
4. An electronic device, comprising: a memory having program code stored thereon; a processor coupled to the memory and which, when executed by the processor, implements the method of claim 1.
5. A computer readable storage medium, having stored thereon program instructions which, when executed, implement the method of claim 1.
6. The blood pressure monitoring smart patch for implementing the method of claim 1, wherein: the LED-photodiode module comprises a plurality of pressure sensing patches, a connecting wire, a battery and a signal processing module, wherein the LED-photodiode module comprises a plurality of fabric LEDs and photodiodes, the pressure sensing patches are sequentially connected and then connected with a power supply and the signal processing module through the connecting wire, the signal processing module is used for transmitting data or locally storing data in a wireless communication mode, the fabric LEDs and the photodiodes are embedded in fabric fibers, the fabric LEDs alternately emit light in a time-sharing multiplexing mode, the photodiodes are used for irradiating the fabric LEDs with optical signals of the photodiodes to convert the optical signals into electric signals, the pressure sensing patches are embedded in a silica gel cushion, and the pressure sensing patches embedded in the silica gel cushion are externally hung on fabrics embedded with the fabric LEDs and the photodiodes.
7. The blood pressure monitoring smart patch of claim 6, wherein: the fabric LEDs are annularly arranged in the fabric fibers, and the photodiodes are positioned in the center of an annular shape formed by the arrangement of the fabric LEDs.
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