Cuff airbag, cuff, blood pressure measurement apparatus and method, and electronic device

Abstract

The present disclosure relates to a cuff airbag, a cuff, a blood pressure measurement apparatus and method, and an electronic device. The cuff airbag comprises: an airbag, an air cavity being formed inside the airbag; at least one piezoelectric sensor, wherein when two piezoelectric sensors are provided, the two piezoelectric sensors are spaced apart from each other on an inner wall of the airbag, and the two piezoelectric sensors are electrically connected; and an air pipe joint, wherein the air pipe joint is arranged on an outer wall of the airbag, and the air pipe joint comprises a first air passage in communication with the air cavity and an electrical connector electrically connected to at least two piezoelectric sensors. According to the present disclosure, the two piezoelectric sensors are spaced apart from each other on the inner wall of the airbag, thereby providing a stable environment for the piezoelectric sensors. Moreover, the blood pressure is detected by means of the air pressure and piezoelectric signals, thereby improving the detection reliability. The blood pressure measurement apparatus provided in the present disclosure comprises an air storage chamber, a piezoelectric sensor, and an air pipe joint, wherein the air storage chamber is composed of an air cavity inside an airbag or is enclosed by two cuff portions; the piezoelectric sensor is disposed inside the air storage chamber, thereby improving the detection accuracy of a Korotkoff sound signal.

Description

Cuff air bag, cuff, blood pressure measuring device, method and electronic device

[0001] The present disclosure claims priority to the following patent application, the entire contents of which are incorporated herein by reference:

[0002] Chinese patent application No. 202411391567.6, filed on September 30, 2024, entitled "Cuff air bag, cuff and blood pressure measuring device";

[0003] Chinese patent application No. 202411103115.3, filed on August 12, 2024, entitled "Blood pressure measuring device, method, electronic device, storage medium and program product". TECHNICAL FIELD

[0004] The present disclosure relates to the technical field of medical devices, and in particular to a cuff air bag, a cuff, a blood pressure measuring device, a method and an electronic device. BACKGROUND

[0005] Blood pressure can provide a basis for the diagnosis of some diseases (such as kidney disease, endocrine disease or heart disease, etc.). The blood pressure measuring device based on Korotkoff method in the related art is provided with a sensor in the cuff, specifically, the sensor is arranged outside the air bag. This structure can arrange the sensor outside the integrally formed air bag, simplifies the process, facilitates manufacturing, and improves the production efficiency of the blood pressure measuring device. However, the sensor of this structure design often collects more external noise or blood flow impact interference, resulting in a large deviation in the blood pressure measurement result. Especially, this external noise greatly interferes with the identification of Korotkoff sound, the measurement data is unstable, and the measurement result is prone to detection distortion, which seriously affects the blood pressure measurement result. SUMMARY

[0006] The purpose of the present disclosure is to at least solve the technical problem of low detection reliability of the blood pressure measuring device in the related art. The present disclosure provides a cuff air bag, a cuff, a blood pressure measuring device, a method and an electronic device, and the purpose is achieved by the following technical solutions:

[0007] The first aspect of the present disclosure provides a blood pressure measuring device, comprising: a gas storage chamber; a piezoelectric sensor arranged inside the gas storage chamber; a gas pipe joint in communication with the gas storage chamber, the gas pipe joint further comprising an electrical connector electrically connected to the piezoelectric sensor.

[0008] The second aspect of the present disclosure provides a cuff air bag for a blood pressure measuring device, the cuff air bag comprising: an air bag, an air cavity being formed in an interior of the air bag; at least one piezoelectric sensor, when the piezoelectric sensor is two, the two piezoelectric sensors are spaced apart on an inner wall of the air bag, and the two piezoelectric sensors are electrically connected; and an air tube connector, the air tube connector being arranged on an outer wall of the air bag, the air tube connector comprising a first air passage in communication with the air cavity, and an electrical connector in electrical connection with the two piezoelectric sensors.

[0009] As can be appreciated by those skilled in the art, the cuff air bag provided by the present disclosure can simultaneously detect the blood pressure of a user through air pressure and piezoelectric signals by spacing the two piezoelectric sensors on the inner wall of the air bag, thereby improving the detection reliability of the cuff air bag.

[0010] In addition, the cuff air bag can provide a relatively stable pressure measurement environment for the piezoelectric sensor, thereby reducing the phenomenon of detection distortion of the piezoelectric sensor. By placing the piezoelectric sensor on the inner wall of the air bag, noise generated outside the air bag during the measurement process can be effectively avoided. Further, the cuff air bag provided by the present disclosure also has the technical effects of simplifying the structure of the piezoelectric sensor and protecting the piezoelectric sensor.

[0011] In some embodiments, the two piezoelectric sensors are spaced apart along the length direction of the air bag, and the two piezoelectric sensors are connected in series.

[0012] In some embodiments, the cuff air bag further comprises a flat cable, the flat cable being connected to the two piezoelectric sensors, and the electrical connector being electrically connected to the flat cable.

[0013] In some embodiments, the flat cable is a flexible circuit board.

[0014] In some embodiments, the flat cable is elastic along the length direction of the air bag.

[0015] In some embodiments, the air bag comprises a first bladder sheet and a second bladder sheet that are attached to each other, the air cavity being formed between the first bladder sheet and the second bladder sheet, and the two piezoelectric sensors being arranged on an inner wall of the first bladder sheet.

[0016] In some embodiments, the second bladder sheet is provided with an air port for connecting the air cavity and the air tube connector, and an air tube base arranged on the inner wall of the second bladder sheet, the air tube base being provided with an adapter opening at a position corresponding to the air port, and the air tube connector being connected to the air tube base.

[0017] In some embodiments, the air port is arranged at a central position of two orthogonal projection positions of the two piezoelectric sensors on the second bladder sheet after the first bladder sheet and the second bladder sheet are attached.

[0018] In some embodiments, the periphery of the first capsule and the periphery of the second capsule are provided with hot melt welding portions, the first capsule and the second capsule are bonded by the hot melt welding portions and form a periphery sealing structure of the cuff airbag.

[0019] In some embodiments, the tracheal connector connects the trachea, the trachea is provided with a second airway, and the electrical connector is electrically connected with the gas-electric plug from the first airway through the second airway.

[0020] The third aspect of the present disclosure provides a cuff, comprising a cuff airbag and a cuff sleeve, the cuff airbag is arranged in the cuff sleeve, and the cuff airbag is arranged as the cuff airbag of the first aspect of the present disclosure.

[0021] The fourth aspect of the present disclosure provides a blood pressure measuring device, comprising a host, a gas-electric plug and a cuff airbag, the cuff airbag is connected with the host through the gas-electric plug, the host inflates the cuff airbag through the gas-electric plug, and the cuff airbag is arranged as the cuff airbag of the first aspect.

[0022] The fifth aspect of the present disclosure provides a blood pressure measuring device, comprising: a cuff, comprising a first cuff part and a second cuff part, the first cuff part and the second cuff part enclose a gas storage chamber, the first cuff part and the second cuff part are integrally formed or sealingly connected, the cuff is provided with an air nozzle, the air nozzle is in communication with the gas storage chamber; a piezoelectric sensor, fixed in the interior of the gas storage chamber, the piezoelectric sensor is used for collecting a Korotkoff sound signal; a trachea, having a first end and a second end, the first end is a tracheal connector, the tracheal connector is connected to the air nozzle, and the trachea is in communication with the gas storage chamber; a pressure sensor, connected to the second end, the pressure sensor is used for collecting a pressure signal, the pressure signal is used for representing the internal gas pressure of the gas storage chamber; a host, used for acquiring the Korotkoff sound signal and the pressure signal, and used for predicting a blood pressure measurement result according to the Korotkoff sound signal and the pressure signal, and the piezoelectric sensor and the pressure sensor are respectively in communication connection with the host.

[0023] In some embodiments, the piezoelectric sensor is in communication connection with the host through a connecting line built in the trachea, the piezoelectric sensor comprises a first piezoelectric sheet and a second piezoelectric sheet attached to a target inner wall of the gas storage chamber, and the target inner wall is an inner wall of the gas storage chamber close to the inner side of the cuff.

[0024] In some embodiments, the host comprises a preprocessing module, an intermediate processing module and a post-processing module connected in sequence; the preprocessing module is used for performing time-frequency transformation processing on a first time domain feature corresponding to arterial pulsation extracted from the Korotkoff sound signal to obtain a frequency domain feature, and is used for splicing the frequency domain feature with a second time domain feature extracted from the Korotkoff sound signal to obtain a target data feature; the intermediate processing module is used for inferring according to the target data feature to predict a blood pressure category classification result corresponding to the Korotkoff sound signal; and the post-processing module is used for determining a blood pressure measurement result according to the blood pressure category classification result and the pressure signal.

[0025] In some embodiments, the preprocessing module comprises a band-pass filtering unit, a signal extraction unit, a time-frequency transformation unit, a signal sampling unit and a feature splicing unit; the band-pass filtering unit is configured to perform band-pass filtering on the pressure signal to obtain a pulsatile wave signal reflecting the arterial pulse; the signal extraction unit is configured to extract a first time-domain feature corresponding to the arterial pulse from the Korotkoff sound signal with a sampling time point corresponding to a maximum value in the pulsatile wave signal as a reference time point; the time-frequency transformation unit is configured to perform time-frequency transformation on the first time-domain feature to obtain a frequency-domain feature; the signal sampling unit is configured to sample the Korotkoff sound signal to extract a second time-domain feature from the Korotkoff sound signal; and the feature splicing unit is configured to splice the frequency-domain feature and the second time-domain feature into the target data feature.

[0026] In some embodiments, the signal extraction unit is configured to determine a first preset number of first feature points before and after the reference time point extracted from the Korotkoff sound signal as the first time-domain feature; and the time-frequency transformation unit is configured to determine a second preset number of second feature points obtained by performing time-frequency transformation on the first time-domain feature as the frequency-domain feature; wherein the second preset number is less than the first preset number.

[0027] In some embodiments, the signal sampling unit is configured to determine a third preset number of third feature points sampled from the Korotkoff sound signal as the second time-domain feature; wherein the third preset number is less than the first preset number, and the third preset number is the same as or different from the second preset number; and the feature splicing unit is configured to splice the third preset number of third feature points and the second preset number of second feature points into the target data feature.

[0028] In some embodiments, the intermediate processing module is a trained convolutional bidirectional long short-term memory neural network, and the trained convolutional bidirectional long short-term memory neural network comprises a convolutional neural network and a bidirectional long short-term memory network connected in sequence; the convolutional neural network is configured to perform convolution operation on the target data feature to extract a spatial feature from the target data feature; and the bidirectional long short-term memory network is configured to output a fourth preset number of blood pressure category classification results according to the spatial feature, wherein the blood pressure category classification results comprise a classification result in the high-low pressure range and a classification result not in the high-low pressure range, and the fourth preset number is the sum of the third preset number and the second preset number.

[0029] In some embodiments, the bidirectional long short-term memory network comprises a long short-term memory network layer and a fully connected layer connected in sequence; the long short-term memory network layer is configured to extract a context feature from the spatial feature; and the fully connected layer is configured to output the fourth preset number of blood pressure category classification results according to the context feature.

[0030] In some embodiments, the post-processing module is configured to determine the pressure signal corresponding to the blood pressure category classification result of the first blood pressure between the high and low pressures as the high pressure signal, and to determine the pressure signal corresponding to the blood pressure category classification result of the last blood pressure between the high and low pressures as the low pressure signal.

[0031] In some embodiments, the host comprises an analysis module, an identification module and a judgment module connected in sequence. The analysis module is configured to extract a target time domain feature corresponding to the arterial pulsation from the Korotkoff sound signal according to the pressure signal, and to determine a signal frequency mean value and a signal frequency variance corresponding to the target time domain feature. The identification module is configured to determine a signal change trend according to the signal frequency mean value and the signal frequency variance, and to determine a high pressure change trend and a low pressure change trend according to the signal change trend. The judgment module is configured to determine the pressure signal corresponding to the high pressure change trend as the high pressure signal, and to determine the pressure signal corresponding to the low pressure change trend as the low pressure signal.

[0032] The sixth aspect of the present disclosure provides a blood pressure measurement method, comprising: acquiring a Korotkoff sound signal collected by a piezoelectric sensor fixed inside a gas storage chamber and a pressure signal collected by a pressure sensor, the gas storage chamber being surrounded by a first cuff part and a second cuff part in a cuff, the first cuff part being integrally formed or sealingly connected with the second cuff part, a gas nozzle being provided on the cuff and being in communication with the gas storage chamber, the gas nozzle being used to connect a first end of an air pipe, the air pipe being in communication with the gas storage chamber, the pressure sensor being connected to a second end of the air pipe, the pressure signal being used to represent the internal air pressure of the gas storage chamber; and predicting a blood pressure measurement result according to the Korotkoff sound signal and the pressure signal.

[0033] In some embodiments, predicting the blood pressure measurement result according to the Korotkoff sound signal and the pressure signal comprises: performing time-frequency transformation processing on a first time domain feature corresponding to the arterial pulsation extracted from the Korotkoff sound signal to obtain a frequency domain feature; splicing the frequency domain feature with a second time domain feature extracted from the Korotkoff sound signal to obtain a target data feature; performing inference according to the target data feature to predict a blood pressure category classification result corresponding to the Korotkoff sound signal; and determining the blood pressure measurement result according to the blood pressure category classification result and the pressure signal.

[0034] In some embodiments, performing time-frequency transformation processing on the first time domain feature corresponding to the arterial pulsation extracted from the Korotkoff sound signal to obtain the frequency domain feature comprises: performing band-pass filtering processing on the pressure signal to obtain an oscillation wave signal reflecting the arterial pulsation; taking a sampling time point corresponding to a maximum value in the oscillation wave signal as a reference time point to extract the first time domain feature corresponding to the arterial pulsation from the Korotkoff sound signal; and performing time-frequency transformation processing on the first time domain feature to obtain the frequency domain feature.

[0035] In some embodiments, the frequency domain feature is spliced with the second time domain feature extracted from the Korotkoff signal to obtain the target data feature, including: performing sampling processing on the Korotkoff signal to extract the second time domain feature from the Korotkoff signal; and splicing the frequency domain feature and the second time domain feature into the target data feature.

[0036] In some embodiments, the blood pressure measurement result is predicted according to the Korotkoff signal and the pressure signal, including: extracting a target time domain feature corresponding to the arterial pulsation from the Korotkoff signal according to the pressure signal, and determining a signal frequency mean value and a signal frequency variance corresponding to the target time domain feature; determining a signal change trend according to the signal frequency mean value and the signal frequency variance, and determining a high-pressure change trend and a low-pressure change trend according to the signal change trend; determining the pressure signal corresponding to the high-pressure change trend as a high-pressure signal, and determining the pressure signal corresponding to the low-pressure change trend as a low-pressure signal.

[0037] A seventh aspect of the present disclosure provides an electronic device, including: a memory and a processor, which are communicatively connected to each other, the memory stores computer instructions, and the processor executes the blood pressure measurement method in the fifth aspect by executing the computer instructions.

[0038] An eighth aspect of the present disclosure provides a computer readable storage medium, which stores computer instructions for making a computer execute the blood pressure measurement method in the fifth aspect. BRIEF DESCRIPTION OF DRAWINGS

[0039] The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and serve to explain the principles of the present disclosure, together with the description.

[0040] FIG. 1 is a structural schematic diagram of a blood pressure measurement device according to an embodiment of the present disclosure.

[0041] FIG. 2 is an axonometric view of a cuff airbag according to an embodiment of the present disclosure.

[0042] FIG. 3 is a perspective view of the cuff airbag shown in FIG. 2.

[0043] FIG. 4 is a split structural schematic diagram of a cuff airbag according to an embodiment of the present disclosure.

[0044] FIG. 5 is a cross-sectional view of a cuff airbag according to an embodiment of the present disclosure.

[0045] FIG. 6 is a partial structural cross-sectional view of the cuff airbag shown in FIG. 5.

[0046] FIG. 7 is a structural schematic diagram of a cuff according to an embodiment of the present disclosure.

[0047] FIG. 8 is a structural schematic diagram of a blood pressure measurement device according to an embodiment of the present disclosure.

[0048] FIG. 9 is a structural schematic diagram of a gas nozzle according to an embodiment of the present disclosure.

[0049] FIG. 10 is a curve schematic diagram of a pressure signal according to an embodiment of the present disclosure.

[0050] FIG. 11 is a curve schematic diagram of a Korotkoff signal according to an embodiment of the present disclosure.

[0051] FIG. 12 is a curve schematic diagram of a pressure signal in a pressure drop phase according to an embodiment of the present disclosure.

[0052] FIG. 13 is a curve schematic diagram of a dicrotic wave signal according to an embodiment of the present disclosure.

[0053] FIG. 14 is a curve schematic diagram of a Korotkoff signal in a pressure drop phase according to an embodiment of the present disclosure.

[0054] FIG. 15 is a schematic diagram of a Korotkoff signal locked according to a dicrotic wave signal according to an embodiment of the present disclosure.

[0055] FIG. 16 is a schematic diagram of a spectrum diagram of a Korotkoff signal according to an embodiment of the present disclosure.

[0056] FIG. 17 is a schematic diagram of a convolution bidirectional long short-term memory neural network according to an embodiment of the present disclosure.

[0057] FIG. 18 is a schematic diagram of a signal frequency mean and a signal frequency variance according to an embodiment of the present disclosure.

[0058] FIG. 19 is a flow schematic diagram of a blood pressure measurement method according to an embodiment of the present disclosure.

[0059] FIG. 20 is a flow schematic diagram of another blood pressure measurement method according to an embodiment of the present disclosure.

[0060] FIG. 21 is a hardware structural schematic diagram of an electronic device according to an embodiment of the present disclosure.

[0061] In the drawings, the following reference signs are used:

[0062] 100A, gas chamber; 200A, piezoelectric sensor; 300A, gas pipe joint;

[0063] 1000, cuff;

[0064] 100, cuff air bag; 101, hot melt welding part; 102, positioning structure; 103, air cavity;

[0065] 10, air bag; 11, first bag piece; 12, second bag piece; 120, air port; 121, gas pipe base; 1211, adapter port;

[0066] 20 piezoelectric sensor; 21 wire harness;

[0067] 30 air tube joint; 301 first air passage; 31 electrical connector; 311 wire harness; 312 connecting wire; 32 air tube; 321 second air passage; 33 air electrical plug;

[0068] 200 cuff cover; 300 air tube;

[0069] 11A first cuff part; 12A second cuff part; 101A air reservoir; 102A air nozzle; 40 pressure sensor; 50 main machine. DETAILED DESCRIPTION

[0070] Exemplary embodiments of the present disclosure will be described in detail below with reference to the accompanying drawings. While exemplary embodiments of the present disclosure are shown in the drawings, it is understood that the present disclosure can be implemented in various forms and should not be limited by the embodiments set forth herein. Rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the present disclosure to those skilled in the art. It should be noted that the blood pressure measuring device is only a preferred embodiment of the present disclosure, and is not a limitation on the application range of the cuff air bag. For example, the cuff air bag of the present disclosure can also be used in electronic devices such as stethoscopes, and such adjustments do not deviate from the protection scope of the cuff air bag of the present disclosure.

[0071] It should be understood that the terms used herein are for the purpose of describing particular example embodiments only and are not intended to be limiting. As used herein, the singular forms "a", "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. The terms "comprises", "comprising", "includes", "including" and "has", "having" are inclusive and therefore specify the presence of stated features, elements, components, and / or steps, but do not preclude the presence or addition of one or more other features, elements, components, steps, and / or groups thereof.

[0072] Although terms such as first, second, etc. can be used herein to describe various elements, components, regions, layers and / or sections, these elements, components, regions, layers and / or sections should not be limited by these terms. These terms can be only used to distinguish one element, component, region, layer or section from another region, layer or section. Terms such as "first", "second", and other numerical terms when used herein do not imply a sequence or order unless clearly indicated by the context. In addition, in the description of the present disclosure, unless otherwise clearly specified and limited, the terms "set", "connected" should be understood broadly, for example, can be fixed connection, can also be detachable connection, or integral connection; can be directly connected, or indirectly connected through intermediate medium. For those skilled in the art, the specific meaning of the above terms in the present disclosure can be understood according to the specific circumstances.

[0073] For ease of description, spatial relative terms can be used herein to describe the relationship of one element or feature to another element or feature as shown in the drawings, such as "end", "length", "inner", "outer", etc. Such spatial relative terms are intended to include different orientations of the mechanism in use or operation in addition to the orientation depicted in the drawings. For example, if the mechanism in the drawings is turned over, the element described as "below" or "under" the other element or feature will be subsequently oriented "above" or "over" the other element or feature. Therefore, the example term "below" can include both upward and downward orientations. The mechanism can be additionally oriented (rotated 90 degrees or in other directions) and the spatial relative relationship descriptors used herein are interpreted accordingly.

[0074] In the related art, for non-invasive blood pressure measurement, the method with more accurate measurement results is the Korotkoff method. The process of blood pressure measurement based on the Korotkoff method is generally as follows: a stethoscope is placed under the air bag of the cuff and tightly attached to the skin, the air bag is pressurized, and when the air pressure in the air bag reaches a certain pressure value, the blood flow of the upper arm artery is blocked, then the gas in the air bag is released, and the pressure slowly decreases, when the first sound of pulse beats appears in the stethoscope, the pressure value at this time is the high pressure value, and the pressure is continuously released, when the last pulse beat sound in the stethoscope disappears, the pressure value at this time is the low pressure value. With the rapid development of non-invasive blood pressure measurement technology, electronic sphygmomanometers based on the Korotkoff method have emerged as the times require. The electronic sphygmomanometer generally includes a cuff and a host, the cuff is used to collect piezoelectric signals and pressure signals, and the host is used to calculate the blood pressure measurement results according to the collected piezoelectric signals and pressure signals. The air bag needs to be provided on the conventional cuff, and the piezoelectric sensor is usually provided outside the integrally formed air bag and tightly attached to the skin. However, this kind of structure design will cause the sensor to collect more external noise, thereby interfering with the blood pressure measurement results. On the other hand, since the piezoelectric sensor is located below the air bag, the upper air bag will be continuously impacted by the blocked blood flow, and this impact is transmitted to the piezoelectric sensor through the air bag, causing the signal collected by the piezoelectric sensor to be affected by the blood flow impact (i.e. signal interference caused by the blood flow impact), thereby increasing the difficulty of judging the Korotkoff signal and affecting the accuracy of the blood pressure measurement results.

[0075] In order to solve the technical problems of the blood pressure measurement device in the related art, such as more interference data and poor measurement reliability, the present disclosure proposes to set the piezoelectric sensor on the inner wall of the air bag 10 or the sleeve part of the cuff without an air bag, so that the cuff air bag or the sleeve part can provide a relatively stable working environment for the piezoelectric sensor, thereby reducing and even eliminating the interference of external noise and blood flow impact on the piezoelectric sensor collecting the brachial artery pulse signal.

[0076] FIG. 1 is a structural schematic diagram of a blood pressure measurement device according to an embodiment of the present disclosure.

[0077] As shown in FIG. 1, the blood pressure measuring device provided by the embodiment of the present disclosure can include a gas storage chamber 100A, a piezoelectric sensor 200A, and a tracheal connector 300A. The piezoelectric sensor 200A is arranged on the inner wall of the gas storage chamber 100A, i.e., the inner wall of the gas storage chamber 100A, for collecting Korotkoff sound signals. The tracheal connector 300A can be in communication with the gas storage chamber 100A, and the tracheal connector 300A further includes an electrical connector electrically connected to the piezoelectric sensor 200A. The signals collected by the piezoelectric sensor 200A can be transmitted to the outside of the gas storage chamber 100A through the electrical connector. In this scheme, the piezoelectric sensor 200A is arranged on the inner wall of the gas storage chamber 100A, i.e., the inner surface of the gas storage chamber 100A, which effectively shields the interference of noise signals outside the gas storage chamber 100A on the signal collection of the piezoelectric sensor 200A, thereby improving the accuracy of blood pressure measurement. The gas storage chamber in this scheme is formed by the internal air cavity of the air bag or surrounded by two cuff parts.

[0078] FIG. 2 is an axonometric view of a cuff air bag according to an embodiment of the present disclosure. FIG. 3 is a perspective view of the cuff air bag shown in FIG. 2. FIG. 4 is a schematic view of a split structure of a cuff air bag according to an embodiment of the present disclosure. FIG. 5 is a sectional view of a cuff air bag according to an embodiment of the present disclosure. FIG. 6 is a sectional view of a partial structure of the cuff air bag shown in FIG. 5.

[0079] As shown in FIGS. 2 to 6, the cuff air bag 100 according to the embodiment of the present disclosure is used in a blood pressure measuring device, and includes an air bag 10, at least one piezoelectric sensor 20, and a tracheal connector 30. The air bag 10 has an air cavity 103 formed therein as a gas storage chamber. When there are two piezoelectric sensors 20, the two piezoelectric sensors 20 are arranged at intervals on the inner wall of the air bag 10, and are electrically connected in series. The tracheal connector 30 is arranged on the outer wall of the air bag 10, and includes a first air passage 301 in communication with the air cavity 103, and an electrical connector 31 electrically connected to the two piezoelectric sensors 20.

[0080] In some embodiments, the cuff air bag 100 according to the present disclosure reduces or even eliminates the interference of external noise signals on the collection of brachial artery pulsation signals by the piezoelectric sensor, so that the blood pressure measuring device obtains accurate brachial artery pulsation signals and Korotkoff sound signals, and further obtains blood pressure information of a user according to the Korotkoff sound signals and the pressure signals collected by the pressure sensor. In this scheme, the piezoelectric sensor is arranged on the inner wall of the cuff air bag, which effectively shields the interference of noise signals outside the air bag on the signal collection of the piezoelectric sensor, thereby improving the accuracy of blood pressure measurement.

[0081] The cuff air bag 100 provides a relatively stable pressure measuring environment for the piezoelectric sensor 20, so as to reduce the distortion of the piezoelectric sensor 20. In addition, the piezoelectric sensor 20 is arranged on the inner wall of the air bag 10, so as to effectively utilize the internal space of the cuff air bag 100, protect the piezoelectric sensor 20, and prolong the service life of the piezoelectric sensor.

[0082] It should be noted that the specific number of the piezoelectric sensor 20 is not limited in the embodiments of the present disclosure, because the application point of the present disclosure is to arrange the piezoelectric sensor 20 on the inner wall of the air bag 10. The specific number of the piezoelectric sensor 20 can be set according to actual needs, for example, the number of the piezoelectric sensor 20 can be two, three or four, which all belong to the protection scope of the cuff air bag 100 of the present disclosure. Other embodiments of the piezoelectric sensor 20 are not described here.

[0083] The specific structure of the cuff air bag 100 of the embodiments of the present disclosure will be described in detail below.

[0084] As shown in FIGS. 3-5, in some embodiments, two piezoelectric sensors 20 are arranged along the length direction of the air bag 10, and the two piezoelectric sensors are connected in series.

[0085] In some embodiments, by arranging the two piezoelectric sensors 20 along the length direction of the air bag 10, it is ensured that at least one piezoelectric sensor is arranged at the brachial artery position of the arm when the cuff air bag 100 is worn on the left arm or the right arm, so as to improve the effective measurement range of the two piezoelectric sensors 20.

[0086] As shown in FIGS. 2-4, in some embodiments, the cuff air bag 100 further comprises a flat cable 21 and an electrical connector 31. The flat cable 21 is connected to the two piezoelectric sensors 20, and the electrical connector 31 is electrically connected to the flat cable 21.

[0087] In some embodiments, the flat cable 21 is used to connect the two piezoelectric sensors 20, so as to improve the piezoelectric signal transmission efficiency and accuracy of the two piezoelectric sensors 20. In addition, the flat cable 21 is made of a flexible material, so that the flat cable 21 has a certain bending performance, so as to adapt to the bending working condition when the cuff air bag 100 measures blood pressure. For example, the flat cable 21 can be a flexible circuit board, so that the flat cable 21 can be bent while maintaining its circuit performance, so as to adapt to the bending working condition when the cuff air bag 100 measures blood pressure.

[0088] Further, the flat cable 21 is provided with two welding points corresponding to the two piezoelectric sensors 20, and the electrical connector 31 comprises a wire harness 311 provided with at least two connecting lines 312 connecting the two welding points.

[0089] Two connecting lines 312 are welded to two welding points of the flat cable 21, and can transmit two piezoelectric signals of the two piezoelectric sensors 20 to a host of the blood pressure measuring device, so as to improve the transmission reliability of the two piezoelectric signals of the two piezoelectric sensors 20, and reduce the phenomenon that the two connecting lines 312 and the two piezoelectric sensors 20 are separated to cause signal transmission interruption.

[0090] Further, the two welding points are provided as two welding holes on the flat cable 21, and the two connecting lines 312 are provided with two contacts respectively in electrical contact with the two welding holes. The two connecting lines 312 are first inserted into the two welding holes through the two contacts, and then welded, so as to improve the signal transmission reliability between the two connecting lines 312 and the two piezoelectric sensors 20.

[0091] As shown in FIG. 4, in some embodiments, the flat cable 21 is provided with elasticity along the length direction of the air bag 10.

[0092] In some embodiments, by providing the flat cable 21 with elasticity along the length direction of the air bag 10, the effective measurement range of the cuff air bag 100 can be improved. When the cuff air bag 100 wraps a relatively thick arm, the two piezoelectric sensors 20 can be located at the artery of the arm to measure the blood pressure of the user by stretching the flat cable 21.

[0093] When the cuff air bag 100 wraps a relatively thin arm, the two piezoelectric sensors 20 can be located at the artery of the arm to measure the blood pressure of the user by further compressing the flat cable 21.

[0094] As shown in FIGS. 4 to 6, in some embodiments, the air bag 10 includes a first bag piece 11 and a second bag piece 12 that are attached to each other, and a gas cavity 103 is formed between the first bag piece 11 and the second bag piece 12. The two piezoelectric sensors 20 are arranged on the inner wall of the first bag piece 11.

[0095] In some embodiments, by providing the air bag 10 with the first bag piece 11 and the second bag piece 12 that are attached to each other, the overall assembly efficiency of the cuff air bag 100 can be improved.

[0096] In the assembly process of the cuff air bag 100, one side of the piezoelectric sensor 20 is fixed to the inner wall of the first bag piece 11, and then the piezoelectric sensor 20 and the flat cable 21 are welded by soldering, and the flat cable 21 and the electrical connecting piece 31 in the air tube joint 30 are connected, and the air tube joint 30 is connected to the air bag 10 by hot pressing, and finally the overall assembly of the cuff air bag 100 is completed.

[0097] As shown in FIG. 4, in some embodiments, the second bladder 12 is provided with an air port 120 for connecting the air cavity 103 with the air tube joint 30, and an air tube base 121 provided on the inner wall of the second bladder 12, the air tube base 121 is provided with an adapter opening 1211 at a position corresponding to the air port 120, and the air tube joint 30 is connected with the air tube base 121.

[0098] In some embodiments, the air tube base 121 has more stable structure and mechanical properties compared with the second bladder 12, so as to reduce the tearing and damage of the air tube joint 30 at the air tube base 121.

[0099] The air tube joint 30 and the air tube base 121, and the air tube base 121 and the second bladder 12 are connected by hot pressing, so as to improve the connection stability and sealing property between the air tube joint 30 and the air tube base 121, and between the air tube base 121 and the second bladder 12, and reduce the pressure relief of the cuff air bladder 100 at the air tube joint 30.

[0100] As shown in FIG. 3 and FIG. 4, in some embodiments, the air port 120 is arranged at a central position of two projection positions of the two piezoelectric sensors 20 on the second bladder 12 after the first bladder 11 and the second bladder 12 are adhered, that is, the air tube joint 30 connected with the air port 120 is located between the two piezoelectric sensors after the first bladder 11 and the second bladder 12 are adhered, so that when the cuff air bladder 100 is wrapped around the arm, the wrinkles of the air bladder part between the two piezoelectric sensors caused by the curling of the cuff can be better eliminated, and the piezoelectric sensors can be better aligned to collect signals at the position of the brachial artery, so as to improve the accuracy of the brachial artery pulse signal collection.

[0101] Further, the part of the air bladder 10 between the two piezoelectric sensors 20 is provided with a wrinkle part distributed along the length direction of the air bladder 10.

[0102] By arranging the wrinkle part on the air bladder 10, the effective measurement range of the cuff air bladder 100 can be improved. When the user of the cuff air bladder 100 measures a relatively thick arm, the air bladder 10 of the cuff air bladder 100 can be wrapped to the artery of the arm by stretching and unfolding the wrinkle part, so that the two piezoelectric sensors 20 can measure the blood pressure at the artery of the arm.

[0103] When the user of the cuff air bladder 100 measures a relatively thin arm, the air bladder 10 of the cuff air bladder 100 can be wrapped to the artery of the arm by further folding the wrinkle part, so that the two piezoelectric sensors 20 can measure the blood pressure at the artery of the arm.

[0104] As shown in FIGS. 2-4, in some embodiments, the periphery of the first bladder sheet 11 and the periphery of the second bladder sheet 12 are provided with hot melt welding portions 101, and the first bladder sheet 11 and the second bladder sheet 12 are bonded by the hot melt welding portions 101 to form a peripheral sealing structure of the cuff air bag 100.

[0105] In some embodiments, by sealing and welding the periphery of the first bladder sheet 11 and the periphery of the second bladder sheet 12 by hot melt welding, the connection stability and sealing of the first bladder sheet 11 and the second bladder sheet 12 can be improved, and the leakage of the air cavity 103 of the air bag 10 at the connection of the first bladder sheet 11 and the second bladder sheet 12 can be reduced.

[0106] In some embodiments, the periphery of the first bladder sheet 11 and the periphery of the second bladder sheet 12 can be sealed and welded by ultrasonic vibration heat welding.

[0107] Further, the corners of the first bladder sheet 11 and the corners of the second bladder sheet 12 are provided with positioning structures 102, which are located outside the hot melt welding portions 101 and can be separated from the cuff air bag 100 after the peripheral sealing structure is formed.

[0108] The positioning structure 102 has the effect of bonding the first bladder sheet 11 and the second bladder sheet 12 at a specified position, thereby reducing the phenomenon of bonding deviation or misalignment between the first bladder sheet 11 and the second bladder sheet 12.

[0109] In some embodiments, the positioning structure 102 includes a button structure or a magnetic element, and after the first bladder sheet 11 and the second bladder sheet 12 are bonded by the positioning structure 102, the first bladder sheet 11 and the second bladder sheet 12 are connected by ultrasonic vibration heat welding. When the first bladder sheet 11 and the second bladder sheet 12 are sealed and welded by hot melt welding, the positioning structure 102 can be cut off from the air bag 10, thereby reducing the redundant structure of the positioning structure 102 on the air bag 10.

[0110] As shown in FIGS. 2 and 3, in some embodiments, the air tube joint 30 connects the air tube 32, the air tube 32 is provided with a second air passage 321, and the electrical connector 31 passes through the second air passage 321 to electrically connect with the air electrical plug 33.

[0111] In some embodiments, the piezoelectric sensor 20 is arranged on the inner wall of the air bag 10, the electrical connector 31 passes through the second air passage 321 to electrically connect with the air electrical plug 33, which can realize the transmission of the piezoelectric signal of the piezoelectric sensor 20 to the host through the electrical connector 31 in the air tube 32, and the change of the air pressure in the cuff air bag 100 is transmitted through the second air passage 321 in the air tube 32, which fully utilizes the internal space of the cuff air bag 100 and the air tube 32, and effectively reduces the wiring cost.

[0112] In some embodiments, the air tube 32 is arranged as a flexible tube, which can be bent according to the use environment, so as to improve the adaptability of the air tube 32 to the use environment.

[0113] Based on the same concept, the disclosure also provides a cuff.

[0114] FIG. 7 is a structural schematic diagram of a cuff according to an embodiment of the disclosure.

[0115] In some embodiments, as shown in FIG. 7, the cuff 1000 can include a cuff air bag 100 and a cuff sleeve 200, the cuff air bag 100 is arranged in the cuff sleeve 200, and the cuff air bag 100 is arranged as the cuff air bag 100 of the first aspect of the disclosure.

[0116] The cuff 1000 provided by the embodiments of the disclosure includes the cuff sleeve 200, which plays a role in protecting the cuff air bag 100 and preventing the cuff air bag 100 from being damaged during use to affect the blood pressure measurement result.

[0117] In some embodiments, the cuff 1000 provided by the embodiments of the disclosure has all the technical effects of the cuff air bag 100 provided by the embodiments of the first aspect of the disclosure, which will not be described here.

[0118] Based on the same concept, the disclosure also provides a blood pressure measuring device.

[0119] In some embodiments, the blood pressure measuring device includes a host, an air-electric plug 33, and a cuff air bag 100, the cuff air bag 100 is connected to the host through the air-electric plug 33, the host inflates the cuff air bag 100 through the air-electric plug 33, and the cuff air bag 100 is arranged as the cuff air bag 100 of the first aspect of the disclosure.

[0120] In some embodiments, when the host of the blood pressure measuring device is connected to the cuff air bag 100 through the air-electric plug 33, the air tube 32, and the air tube connector 30, the blood pressure measuring device inflates the air bag 10 through the second air passage 321 in the air tube 32 by the air chamber in the host, then the air pressure in the air bag 10 changes with the blood pressure measurement process, the two piezoelectric sensors 20 can detect and generate piezoelectric signals at the user's brachial artery, finally, the piezoelectric signals of the piezoelectric sensors 20 are transmitted to the host through the electrical connector 31 in the air tube 32, and the air pressure change in the cuff air bag 100 is transmitted through the second air passage 321 in the air tube 32, so as to complete the pressure measurement function of the blood pressure measuring device.

[0121] Based on the same concept, the disclosure also provides a blood pressure measuring device.

[0122] Fig. 8 is a structural schematic diagram of a blood pressure measuring device according to an embodiment of the present disclosure. Fig. 9 is a structural schematic diagram of an air nozzle according to an embodiment of the present disclosure.

[0123] In some embodiments, as shown in Fig. 8, and in combination with Fig. 9, the blood pressure measuring device according to an embodiment of the present disclosure includes, but is not limited to, a cuff 1000, a piezoelectric sensor 20, an air tube 300, a pressure sensor 40, and a host computer 50.

[0124] The cuff 1000 includes a first cuff portion 11A and a second cuff portion 12A, which enclose a gas storage chamber 101A. The first cuff portion 11A and the second cuff portion 12A are integrally formed or sealingly connected. The cuff 1000 is provided with an air nozzle 102A, which is in communication with the gas storage chamber 101A. Of course, the cuff 1000 can further include a third cuff portion (the blank area on the right side of the gas storage chamber 101A in the figure, not labeled). The third cuff portion can be a structure extended from the first cuff portion 11A or the second cuff portion 12A, or a piece of non-woven fabric fixedly connected to the first cuff portion 11A and / or the second cuff portion 12A. The third cuff portion can be used to curl the cuff 1000 over the user's arm when the cuff 1000 is used, and can ensure that the gas storage chamber 101A is attached to the user's skin (specifically, the user's arm artery) through the fixing components such as Velcro provided on the cuff 1000. The gas storage chamber 101A can be used to store air.

[0125] In this embodiment, the edges of the first cuff portion 11A and the second cuff portion 12A are pressed together to sealingly connect the edge of the first cuff portion 11A to the edge of the second cuff portion 12A, thereby forming the gas storage chamber 101A. Alternatively, the gas storage chamber 101A can be formed inside the cuff 1000 manufactured by integral molding.

[0126] The piezoelectric sensor 20 is fixed inside the gas storage chamber 101A, and is used to collect Korotkoff sound signals. The piezoelectric sensor 20 is pressed inside the cuff 1000, and the piezoelectric sheet in the piezoelectric sensor is specifically fixed inside the gas storage chamber 101A. The Korotkoff sound signals are piezoelectric signals collected by the piezoelectric sensor 20.

[0127] The number of piezoelectric sensors 20 can be one or more. One piezoelectric sensor can include at least one piezoelectric sheet. All piezoelectric sheets on the device according to this embodiment collectively collect piezoelectric signals to obtain the above-mentioned Korotkoff sound signals, and transmit the Korotkoff sound signals to the host computer 50.

[0128] In some embodiments, the piezoelectric sensor 20 is in communication connection with the host 50 through a connecting line built in the air tube 300 as an electrical connection, the piezoelectric sensor 20 can include a first piezoelectric sheet and a second piezoelectric sheet attached to the target inner wall of the air chamber 101A, which is the inner wall of the air chamber 101A close to the inner side of the cuff 1000.

[0129] The front surface of the first piezoelectric sheet and the second piezoelectric sheet is attached to the side of the air chamber 101A facing the user's skin (when using the blood pressure measuring device), and the front surface of the first piezoelectric sheet and the second piezoelectric sheet is bonded to the inner wall of the air chamber 101A (for example, bonded with 3M double-sided tape), and the piezoelectric sensor 20 can be further bonded to the inner wall of the air chamber 101A by acetic acid cloth tape, which serves as a secondary reinforcement; the back surface of the first piezoelectric sheet and the second piezoelectric sheet is attached to the sensor shell, the connecting line is extended out through the sensor shell and connected to the host 50 through the built-in air tube 300. By placing the connecting line in the air tube, the reuse of the air tube is realized, and the connecting line does not need to be separately led out, so that the host 50 and the cuff 1000 only need to be connected through the air tube, simplifying the structure of the blood pressure measuring device, and the double piezoelectric sheets attached to the inside of the air bag cuff and the air bag gas fluctuation jointly detect the Korotkoff sound signal, improving the detection accuracy of the Korotkoff sound signal.

[0130] Optionally, the first piezoelectric sheet and the second piezoelectric sheet are distributed on both sides of the air nozzle 102A and close to the air nozzle 102A, and are symmetrically arranged along the cuff axis where the air nozzle 102A is located. The distance between the first piezoelectric sheet and the second piezoelectric sheet in the present embodiment can be 100 mm.

[0131] The first piezoelectric sheet and the second piezoelectric sheet are arranged in the lower half of the cuff 1000, and during blood pressure measurement, the first piezoelectric sheet and the second piezoelectric sheet are respectively arranged on both sides of the artery.

[0132] The air tube 300 has a first end and a second end, the first end can be an air tube joint 30A, the air tube joint 30A can be connected to the air nozzle 102A, and the air tube 300 is in communication with the air chamber 101A; in the present embodiment, the second end of the air tube 300 is connected to the host 50, and the host 50 is used to control the inflation of the air chamber 101A through the air tube 300 or the deflation of the air chamber 101A through the air tube 300.

[0133] As shown in FIG. 9, the first cuff portion 11A and the second cuff portion 12A enclose the air chamber 101A which is in communication with the air tube 300 through the air nozzle 102A, the air nozzle 102A can be connected with the air tube joint 30A, and the air tube joint 30A is used to be fixedly connected with the first end of the air tube 300 and make the air tube 300 in communication with the air chamber 101A.

[0134] The pressure sensor 40 is connected to the second end, and the pressure sensor 40 is used to collect a pressure signal used to represent the internal air pressure of the air chamber 101A.

[0135] The host 50 is used to acquire the Korotkoff signal and the pressure signal, and the host 50 is used to predict the blood pressure measurement result according to the Korotkoff signal and the pressure signal. The piezoelectric sensor 20 and the pressure sensor 40 are respectively in communication connection with the host 50.

[0136] The embodiment provides a cuff design without an air bag, and the piezoelectric sensor is arranged in the cuff and specifically arranged in the air chamber surrounded by the first cuff part and the second cuff part, so as to reduce or even avoid the influence of the air bag pressure caused by the blood flow impact on the Korotkoff signal collection in the blood pressure measurement process, improve the accuracy of the Korotkoff signal collection, and improve the accuracy of the blood pressure measurement result compared with the conventional technology. Moreover, the embodiment can also help to reduce the material, reduce the device manufacturing cost, and the assembly process of the device is simpler, and the production and manufacturing of the blood pressure measurement device are facilitated.

[0137] In some embodiments, the host 50 includes a preprocessing module, an intermediate processing module and a post-processing module connected in sequence.

[0138] The preprocessing module is used to perform time-frequency transformation processing on the first time domain feature corresponding to the arterial pulsation extracted from the Korotkoff signal to obtain a frequency domain feature, and is used to splice the frequency domain feature and the second time domain feature extracted from the Korotkoff signal to obtain a target data feature.

[0139] The preprocessing module of the embodiment is used to preprocess the collected pressure signal and the Korotkoff signal to obtain a target data feature required for a subsequent inference process.

[0140] The intermediate processing module is used to infer according to the target data feature to predict a blood pressure category classification result corresponding to the Korotkoff signal.

[0141] The intermediate processing module of the embodiment is used to classify the screened Korotkoff signal according to the target data feature to infer a blood pressure category corresponding to the Korotkoff signal.

[0142] The post-processing module is used to determine a blood pressure measurement result according to the blood pressure category classification result and the pressure signal.

[0143] The post-processing module of the embodiment screens a low pressure signal and a high pressure signal from the pressure signal according to the blood pressure category to realize the measurement of high blood pressure and low blood pressure.

[0144] The disclosure can more accurately capture the change characteristics related to systolic pressure and diastolic pressure through analysis and processing of the frequency domain of the Korotkoff signal, and ensure the expression of comprehensive useful information through splicing of the frequency domain characteristics and the time domain characteristics, thereby further improving the accuracy of blood pressure measurement based on the principle of the Korotkoff method.

[0145] In some embodiments, the preprocessing module includes a band-pass filtering unit, a signal extraction unit, a time-frequency conversion unit, a signal sampling unit, and a feature splicing unit.

[0146] The band-pass filtering unit is configured to perform band-pass filtering on the pressure signal to obtain a shock wave signal reflecting the arterial pulsation.

[0147] The band-pass filtering unit is specifically configured to perform band-pass filtering on the pressure signal based on the pulse characteristics to obtain the shock wave signal, and realizes the function of signal denoising in the filtering process.

[0148] FIG. 10 is a curve diagram of a pressure signal according to an embodiment of the disclosure.

[0149] As shown in FIG. 10, the pressure signal collected by the pressure sensor 40 is shown, and the abscissa in FIG. 10 represents time, which can be in seconds (s), and the ordinate represents pressure, which can be in millimeters of mercury (mmHg). As can be seen from FIG. 10, during the process of inflating the gas chamber in the cuff, the blood flow of the user's upper arm artery is gradually blocked, and the amplitude of the pressure signal is increasing, and then during the process of slowly releasing the gas in the gas chamber at a preset speed (for example, 2-4 mmHg), the amplitude of the pressure signal is gradually decreasing.

[0150] FIG. 11 is a curve diagram of a Korotkoff signal according to an embodiment of the disclosure.

[0151] In combination with FIG. 11, the piezoelectric sensor detects the piezoelectric signal during the process of inflating the gas chamber, and detects the Korotkoff signal generated by the arterial pulsation during the process of releasing the gas.

[0152] FIG. 12 is a curve diagram of a pressure signal in a pressure drop stage according to an embodiment of the disclosure.

[0153] As shown in FIG. 12, the abscissa represents time, which can be in seconds (s), and the ordinate represents pressure, which can be in millimeters of mercury (mmHg); the embodiment focuses on the amplitude drop process of the pressure signal during blood pressure measurement, that is, the pressure curve in the pressure drop stage.

[0154] FIG. 13 is a curve diagram of a shock wave signal according to an embodiment of the disclosure.

[0155] As shown in FIG. 13, the horizontal coordinate represents time, the unit can be seconds (s), and the vertical coordinate represents the pressure change value, the unit can be millimeters of mercury (mmHg). The dots in the figure are used to represent the position of the maximum value.

[0156] The signal extraction unit is used to extract the first time domain feature corresponding to the arterial pulsation from the Korotkoff signal with the sampling time corresponding to the maximum value in the oscillatory wave signal as the reference time point.

[0157] The signal extraction unit is specifically used to lock the position of the Korotkoff signal in the double pressure sensor data (i.e. the Korotkoff signal) according to the maximum value of the oscillatory wave. In this embodiment, each pulse is taken as a time point, and 512 data points (or feature points) before and after the position of the Korotkoff signal at each time point are taken out.

[0158] FIG. 14 is a curve schematic diagram of the Korotkoff signal in the pressure drop stage according to one embodiment of the present disclosure.

[0159] As shown in FIG. 14, the horizontal coordinate represents time, the unit can be seconds (s), and the vertical coordinate represents the amplitude of the Korotkoff signal, the unit can be volts (V). On the basis of FIG. 14, the accurate position of the Korotkoff signal is locked through the time point corresponding to the maximum value in the oscillatory wave signal.

[0160] FIG. 15 is a schematic diagram of the Korotkoff signal locked according to the oscillatory wave signal according to one embodiment of the present disclosure.

[0161] As shown in FIG. 15, 25 first time domain features are shown, and each first time domain feature includes 512 data points.

[0162] The time-frequency conversion unit is used to perform time-frequency conversion processing on the first time domain feature to obtain the frequency domain feature.

[0163] The time-frequency conversion unit is specifically used to obtain 256 data points as the frequency domain feature after performing time-frequency conversion processing on the time sequence signal composed of the above-mentioned 512 data points.

[0164] The signal sampling unit is used to perform sampling processing on the Korotkoff signal to extract the second time domain feature from the Korotkoff signal.

[0165] The feature splicing unit is used to splice the frequency domain feature and the second time domain feature into the target data feature.

[0166] In this embodiment, the pressure signal is filtered to obtain an oscillation wave signal, so that the position of the Korotkoff sound signal is identified by the maximum value of the oscillation wave signal, and then time-frequency transformation can be performed on the locked Korotkoff sound signal, so that the target data feature for subsequent identification is obtained by splicing the frequency domain signal and the frequency domain signal. The processing method of the pressure signal and the Korotkoff sound signal in the above process can help to significantly improve the accuracy and reliability of the high and low pressure judgment result.

[0167] In some embodiments, the signal extraction unit is configured to determine a first preset number of first feature points before and after the reference time point extracted from the Korotkoff sound signal as the first time domain feature.

[0168] For example, the first preset number is 512.

[0169] The time-frequency transformation unit is configured to determine a second preset number of second feature points obtained by performing time-frequency transformation on the first time domain feature as the frequency domain feature.

[0170] For example, the second preset number is 256.

[0171] In this embodiment, the number of feature points is reduced during time-frequency transformation, which can reduce the hardware requirements of the subsequent processing process while retaining key information, and improve the processing efficiency of the subsequent process.

[0172] The signal sampling unit is configured to determine a third preset number of third feature points sampled from the Korotkoff sound signal as the second time domain feature. The third preset number is less than the first preset number, and the third preset number is the same as or different from the second preset number. For example, the third preset number is 256.

[0173] The signal sampling unit can specifically be used for downsampling processing of the time sequence signal composed of the above-mentioned 512 data points, thereby obtaining 256 data points.

[0174] The feature splicing unit is configured to splice the third preset number of third feature points and the second preset number of second feature points into the target data feature.

[0175] The feature splicing unit can specifically be used for splicing the frequency domain signal represented by the above-mentioned 256 data points obtained by time domain transformation and the time domain signal represented by the 256 data points obtained by downsampling, to obtain the target data feature represented by the 512 data points obtained by splicing.

[0176] In this embodiment, the splicing of the third preset number of third feature points and the second preset number of second feature points retains the time domain key information and the frequency domain key information, and provides sufficient and reliable data support for accurate identification of high and low pressure categories.

[0177] In some embodiments, the intermediate processing module is a trained convolutional bidirectional long short-term memory neural network, and the trained convolutional bidirectional long short-term memory neural network comprises a convolutional neural network and a bidirectional long short-term memory network connected in sequence.

[0178] The convolutional neural network is configured to perform a convolution operation on the target data features to extract spatial features from the target data features.

[0179] The bidirectional long short-term memory network is configured to output a fourth preset number of blood pressure category classification results according to the spatial features, the blood pressure category classification results comprising a classification result between high and low pressures and a classification result not between high and low pressures, and the fourth preset number being a sum of the third preset number and the second preset number.

[0180] In this embodiment, the extracted target data features are input into the trained convolutional bidirectional long short-term memory neural network comprising the convolutional neural network and the bidirectional long short-term memory network connected in sequence, so as to learn the deep connection between the pressure signal and the Korotkoff high-low pressure signal through the convolutional bidirectional long short-term memory neural network. This way can greatly improve the accuracy of blood pressure category classification result judgment while retaining the original features of the signal, and further improve the accuracy of high-low pressure recognition by converting the extracted Korotkoff signal to the frequency domain for high-low pressure judgment. Moreover, compared with the manual judgment method in the conventional scheme, the convolutional bidirectional long short-term memory neural network used in the present disclosure can also eliminate the problem of inaccurate blood pressure measurement results caused by human subjective factors.

[0181] In some embodiments, the bidirectional long short-term memory network comprises a long short-term memory network layer and a fully connected layer connected in sequence.

[0182] The long short-term memory network layer is configured to extract context features from the spatial features.

[0183] The fully connected layer is configured to output the fourth preset number of blood pressure category classification results according to the context features.

[0184] The present disclosure comprehensively considers the spatial features and the context features in the target data features, thereby fully analyzing and learning the conditions of the pressure signal and the Korotkoff high-low pressure signal and the connection therebetween to obtain blood pressure category classification results with higher accuracy.

[0185] In some embodiments, the post-processing module is configured to determine the pressure signal corresponding to the first blood pressure category classification result between high and low pressures as a high pressure signal, and to determine the pressure signal corresponding to the last blood pressure category classification result between high and low pressures as a low pressure signal.

[0186] The embodiment can determine the high pressure signal and the low pressure signal according to the relationship between the blood pressure category classification result and the pressure signal, that is, to realize accurate measurement of the high pressure value and the low pressure value.

[0187] In some embodiments, the host 50 comprises an analysis module, an identification module and a judgment module connected in sequence.

[0188] The analysis module is configured to extract a target time domain feature corresponding to the arterial pulse from the Korotkoff signal according to the pressure signal, and to determine a signal frequency mean and a signal frequency variance corresponding to the target time domain feature;

[0189] The identification module is configured to determine a signal change trend according to the signal frequency mean and the signal frequency variance, and to determine a high pressure change trend and a low pressure change trend according to the signal change trend;

[0190] The judgment module is configured to determine the pressure signal corresponding to the high pressure change trend as the high pressure signal, and to determine the pressure signal corresponding to the low pressure change trend as the low pressure signal.

[0191] The embodiment can also determine the signal change trend by using the signal frequency mean and the signal frequency variance corresponding to the target time domain feature extracted from the Korotkoff signal, so as to identify the high pressure signal and the low pressure signal from the pressure signal according to the signal change trend, to realize rapid and accurate determination of the high pressure value and the low pressure value, and compared with the manual identification method in the conventional scheme, the analysis module, the identification module and the judgment module used in the present disclosure can eliminate the problem of inaccurate blood pressure measurement result caused by human subjective factors.

[0192] Based on the same concept, the present disclosure also provides a blood pressure measurement method.

[0193] It should be noted that the steps shown in the flowchart of the accompanying drawings can be executed in a computer system such as a set of computer executable instructions, and although the logical order is shown in the flowchart, in some cases, the steps shown or described herein can be executed in an order different from that shown herein.

[0194] FIG. 19 is a flowchart of a blood pressure measurement method according to an embodiment of the present disclosure.

[0195] In the embodiment, the blood pressure measurement method can be used in the host described above, and FIG. 19 is a flowchart of a blood pressure measurement method according to an embodiment of the present disclosure, as shown in FIG. 19, the flowchart comprises the following steps:

[0196] Step S1201: Obtain the Korotkoff signal collected by the piezoelectric sensor fixed inside the air storage chamber and the pressure signal collected by the pressure sensor. The air storage chamber is surrounded by the first cuff part and the second cuff part in the cuff. The first cuff part is integrally formed or sealingly connected with the second cuff part. The air nozzle is arranged on the cuff and communicates with the air storage chamber. The air nozzle is used to connect the first end of the air tube. The air tube communicates with the air storage chamber. The pressure sensor is connected to the second end of the air tube. The pressure signal is used to represent the internal air pressure of the air storage chamber.

[0197] In some embodiments, the piezoelectric sensor is in communication with the host through the connecting line built in the air tube. The piezoelectric sensor includes the first piezoelectric sheet and the second piezoelectric sheet attached to the target inner wall of the air storage chamber. The target inner wall is the inner wall of the air storage chamber close to the inner side of the cuff.

[0198] The Korotkoff signal of the embodiment is the double-piezoelectric sensor data collected by the first piezoelectric sheet and the second piezoelectric sheet.

[0199] Step S1202: Predict the blood pressure measurement result according to the Korotkoff signal and the pressure signal.

[0200] The blood pressure measurement method based on the Korotkoff method selects the high pressure signal and the low pressure signal from the pressure signal according to the Korotkoff signal, so as to obtain the blood pressure measurement result, that is, the high pressure value corresponding to the high pressure signal and the low pressure value corresponding to the low pressure signal.

[0201] FIG. 20 is a flowchart of another blood pressure measurement method according to an embodiment of the present disclosure.

[0202] In the embodiment, a blood pressure measurement method is provided, which can be used for the host described above. FIG. 20 is a flowchart of the blood pressure measurement method according to an embodiment of the present disclosure. As shown in FIG. 20, the flowchart includes the following steps:

[0203] Step S1301: Obtain the Korotkoff signal collected by the piezoelectric sensor fixed inside the air storage chamber and the pressure signal collected by the pressure sensor. The air storage chamber is surrounded by the first cuff part and the second cuff part in the cuff. The first cuff part is integrally formed or sealingly connected with the second cuff part. The air nozzle is arranged on the cuff and communicates with the air storage chamber. The air nozzle is used to connect the first end of the air tube. The air tube communicates with the air storage chamber. The pressure sensor is connected to the second end of the air tube. The pressure signal is used to represent the internal air pressure of the air storage chamber. For details, please refer to step S1201 of the embodiment shown in FIG. 19, which will not be described here.

[0204] Step S1302: Predict the blood pressure measurement result according to the Korotkoff signal and the pressure signal.

[0205] The blood pressure measurement method based on the air bag cuff design scheme is provided, the piezoelectric sensor is arranged in the cuff, and is specifically arranged in the gas storage chamber surrounded by the first cuff part and the second cuff part, so that the influence of the air bag pressure on the Korotkoff sound signal collection caused by the blood flow impact in the blood pressure measurement process is reduced or even avoided, the accuracy of the Korotkoff sound collection is improved, and the accuracy of the blood pressure measurement result can be obviously improved compared with the conventional technology.

[0206] The step S1302 includes:

[0207] In step S13021, the first time domain feature corresponding to the arterial pulsation extracted from the Korotkoff sound signal is subjected to time-frequency conversion processing to obtain a frequency domain feature.

[0208] In some embodiments, the step S13021 includes but is not limited to steps a1 and a2.

[0209] In step a1, the pressure signal is subjected to band-pass filtering processing to obtain a dicrotic wave signal reflecting the arterial pulsation.

[0210] The pressure signal is subjected to band-pass filtering processing based on the pulse characteristics to obtain the dicrotic wave signal.

[0211] As shown in FIG. 10, the pressure signal collected by the pressure sensor 40 is shown, the horizontal coordinate in FIG. 10 represents time, and the unit can be seconds (s), and the vertical coordinate represents pressure, and the unit can be millimeters of mercury (mmHg). As can be seen from FIG. 10, the blood flow of the user's upper arm artery is gradually blocked during the process of inflating and pressurizing the gas storage chamber in the cuff, and the amplitude of the pressure signal is increasing, and then the amplitude of the pressure signal is gradually decreasing during the process of slowly releasing the gas in the gas storage chamber at a predetermined speed (for example, 2-4 mmHg).

[0212] In combination with FIG. 11, the piezoelectric sensor detects the piezoelectric signal during the process of inflating the gas storage chamber, and detects the Korotkoff sound signal generated by the arterial pulsation during the process of releasing the gas.

[0213] As shown in FIG. 12, the horizontal coordinate represents time, and the unit can be seconds (s), and the vertical coordinate represents pressure, and the unit can be millimeters of mercury (mmHg); the amplitude of the pressure signal during blood pressure measurement is concerned, that is, the pressure curve graph of the pressure drop section.

[0214] As shown in FIG. 13, the horizontal coordinate represents time, and the unit can be seconds (s), and the vertical coordinate represents pressure, and the unit can be millimeters of mercury (mmHg), and the points in the figure are used to represent the positions of the maximum values.

[0215] Step a2, taking the sampling time corresponding to the maximum value in the shock wave signal as a reference time point, extracts the first time domain feature corresponding to the arterial pulse from the Korotkoff sound signal.

[0216] Step a2 includes: determining the first preset number of first feature points before and after the reference time point extracted from the Korotkoff sound signal as the first time domain feature.

[0217] For example, the first preset number is 512.

[0218] The embodiment locks the position of the Korotkoff sound signal in the double pressure sensor data (i.e. the Korotkoff sound signal) according to the maximum value of the shock wave. The embodiment takes each pulse as a time point, and takes 512 data points (or feature points) before and after the position of the Korotkoff sound signal at each time point.

[0219] As shown in FIG. 14, the abscissa represents time, which can be in seconds (s), and the ordinate represents the amplitude of the Korotkoff sound signal, which can be in volts (V). Based on FIG. 14, the accurate position of the Korotkoff sound signal is locked by the time point corresponding to the maximum value in the shock wave signal.

[0220] As shown in FIG. 15, 25 first time domain features are shown, and each first time domain feature includes 512 data points.

[0221] Step a3, performing time-frequency transformation processing on the first time domain feature to obtain a frequency domain feature.

[0222] Step a3 includes: determining the second preset number of second feature points obtained by performing time-frequency transformation processing on the first time domain feature as the frequency domain feature; wherein the second preset number is less than the first preset number.

[0223] For example, the second preset number is 256.

[0224] The embodiment obtains 256 data points as the frequency domain feature by performing time-frequency transformation processing on the time sequence signal composed of the above-mentioned 512 data points. In the embodiment, the number of feature points is reduced in the time-frequency transformation process. This way can reduce the hardware requirements of the subsequent processing process on the basis of preserving key information, and can improve the processing efficiency of the subsequent process.

[0225] Step S13022, splicing the frequency domain feature and the second time domain feature extracted from the Korotkoff sound signal to obtain a target data feature.

[0226] In some embodiments, step S13022 includes:

[0227] Step b1, performing sampling processing on the Korotkoff sound signal to extract the second time domain feature from the Korotkoff sound signal.

[0228] The step b1 comprises: determining the third preset number of third feature points sampled from the click signal as the second time domain feature; wherein the third preset number is less than the first preset number, and the third preset number is the same as or different from the second preset number.

[0229] For example, the third preset number is 256.

[0230] The embodiment can also perform downsampling processing on the timing signal composed of the above-mentioned 512 data points, thereby obtaining 256 data points.

[0231] The step b2 comprises: splicing the frequency domain feature and the second time domain feature into the target data feature.

[0232] The step b2 comprises: splicing the third preset number of third feature points and the second preset number of second feature points into the target data feature.

[0233] The embodiment splices the frequency domain signal represented by the above-mentioned 256 data points obtained through time domain transformation and the time domain signal represented by the 256 data points obtained through downsampling, to obtain the target data feature represented by the 512 data points obtained through splicing.

[0234] The embodiment obtains the oscillation wave signal by filtering the pressure signal, thereby identifying the position of the click signal through the maximum value of the oscillation wave signal, and then performing time-frequency transformation on the locked click signal, thereby obtaining the target data feature for subsequent identification through the splicing of the frequency domain signal and the frequency domain signal. The processing manner of the pressure signal and the click signal in the above process can help to significantly improve the accuracy and reliability of the high-low pressure judgment result. The embodiment retains the time domain key information and the frequency domain key information by splicing the third preset number of third feature points and the second preset number of second feature points, thereby providing sufficient and reliable data support for accurate identification of the high-low pressure category.

[0235] The step S13023 comprises: performing reasoning according to the target data feature, to predict the blood pressure category classification result corresponding to the click signal.

[0236] The step S13023 comprises:

[0237] The step c1 comprises: performing convolution operation on the target data feature through the convolution neural network in the trained convolution bidirectional long short-term memory neural network, to extract the spatial feature from the target data feature.

[0238] The convolutional neural network can comprise a convolutional layer, a pooling layer, and an activation function layer; the convolutional layer is configured to perform convolutional operation on input data using a plurality of convolutional kernels to extract local features; the pooling layer is configured to perform pooling operation on the output of the convolutional layer to reduce the dimension of data while retaining important features; and the activation function layer is configured to introduce a non-linear factor to enhance the expression ability of the model.

[0239] In step c2, the bidirectional long short-term memory network in the trained convolutional bidirectional long short-term memory neural network outputs a fourth preset number of blood pressure category classification results according to the spatial features, the blood pressure category classification results include a classification result between high and low pressure and a classification result not between high and low pressure, and the fourth preset number is the sum of the third preset number and the second preset number.

[0240] FIG. 17 is a schematic diagram of a convolutional bidirectional long short-term memory neural network according to an embodiment of the present disclosure.

[0241] As shown in FIG. 17, the input target data features W correspond to a pulse number N = 25, H represents a 512-dimensional feature, i.e., the fourth preset number described above, and the channel number C is 1, which is input into the bidirectional long short-term memory network to distinguish each pulse.

[0242] The bidirectional long short-term memory network can comprise a forward long short-term memory network layer (forward LSTM layer), a backward long short-term memory network layer (backward LSTM layer), and an output layer; the forward long short-term memory network layer is configured to process the forward propagation of sequence data to capture past information; the backward long short-term memory network layer is configured to process the backward propagation of sequence data to capture future information; and the output layer is configured to perform prediction or classification according to the output of the forward LSTM layer and the backward LSTM layer. In the present embodiment, whether the Korotkoff sound signal is between high and low pressure (including high and low pressure value points) is output, and the bidirectional long short-term memory network is trained in advance, and the training samples are labeled, if it is between high and low pressure value, the output is 1, if it is not between high and low pressure value, the output is zero.

[0243] The convolutional bidirectional long short-term memory neural network (CNN-BiLSTM) is a deep learning model, which specifically combines the advantages of convolutional neural network (CNN) and bidirectional long short-term memory network (BiLSTM).

[0244] The extracted target data features are input into the trained convolutional bidirectional long short-term memory neural network including the convolutional neural network and the bidirectional long short-term memory network connected in sequence, so as to learn the deep connection between the pressure signal and the Korotkoff tone high and low pressure signal through the convolutional bidirectional long short-term memory neural network. In this way, the original features of the signal can be retained while the accuracy of the blood pressure category classification result judgment is greatly improved. The extracted Korotkoff tone signal is converted to the frequency domain for high and low pressure judgment, further improving the accuracy of high and low pressure recognition. Moreover, compared with the manual judgment method in the conventional scheme, the convolutional bidirectional long short-term memory neural network used in the present disclosure can also eliminate the problem of inaccurate blood pressure measurement results caused by human subjective factors.

[0245] The convolutional neural network and the bidirectional long short-term memory network are combined in this embodiment, which can fully utilize the advantages of the convolutional neural network in better extracting spatial features in the data, and fully utilize the advantages of the bidirectional long short-term memory network in better extracting temporal features in the data, better process the target data features in the form of sequence data, and determine more accurate blood pressure category classification results corresponding to the Korotkoff tone signal based on the time features and the space features.

[0246] Step c2 includes:

[0247] Step d1, extracting context features from the spatial features through the long short-term memory network layer in the bidirectional long short-term memory network.

[0248] Step d2, outputting a fourth preset number of blood pressure category classification results according to the context features through the full connection layer in the bidirectional long short-term memory network.

[0249] Step S13024, determining the blood pressure measurement result according to the blood pressure category classification result and the pressure signal.

[0250] Step S13024 includes: determining the pressure signal corresponding to the first blood pressure category classification result between high and low pressure as a high pressure signal, and determining the pressure signal corresponding to the last blood pressure category classification result between high and low pressure as a low pressure signal.

[0251] The present disclosure can more accurately capture the change characteristics related to systolic pressure and diastolic pressure through the analysis and processing of the frequency domain of the Korotkoff tone signal, and through the splicing of the frequency domain features and the time domain features, the comprehensive expression of useful information is ensured, thereby further improving the accuracy of blood pressure measurement based on the principle of Korotkoff tone method.

[0252] In some embodiments, in step S1302, the blood pressure measurement result is predicted according to the Korotkoff tone signal and the pressure signal, including but not limited to steps e1 to e3.

[0253] Step e1, extracting target time domain features corresponding to the arterial pulse from the ksyto sound signal according to the pressure signal, and determining the signal frequency mean and signal frequency variance corresponding to the target time domain features.

[0254] FIG. 16 is a schematic diagram of a spectrum diagram of a ksyto sound signal according to one embodiment of the present disclosure.

[0255] In this embodiment, the pressure signal is filtered, for example, a first-order Butterworth band-pass filter is used to extract the pulsatile signal, and the maximum value of the pulsatile signal is found, and the point at which the maximum value is located is the pulse time, that is, the time of each pulse is obtained, for example, as shown in FIG. 13. Next, the pulse time is used to locate the corresponding time of the ksyto sound signal, that is, the corresponding time of the piezoelectric signal. Since there may be a difference between the sampling frequencies of the piezoelectric signal and the pressure signal, in order to avoid the deviation caused by direct correspondence, this embodiment finds the position of the maximum value between the first preset time period (for example, 0.2 seconds) before and the second preset time period (for example, 0.1 seconds) after the corresponding piezoelectric signal as the position of the ksyto sound signal, for example, as shown in FIG. 14. According to the position of the ksyto sound signal, 256 points before and after are taken as target time domain features corresponding to the arterial pulse, for example, 26 target time domain features shown in FIG. 15. The extracted ksyto sound signal is processed by a window function, so that the edges of the signal are smoothed to a certain extent, and the signal will not produce too large mutation when being intercepted. Then, the ksyto sound signal processed by the window function is subjected to short-time Fourier transform to obtain the corresponding spectrum diagram. This embodiment can realize the visualization of the energy distribution of the ksyto sound signal at different frequencies through the spectrum diagram, for example, as shown in FIG. 16. Thus, the data preprocessing is completed.

[0256] FIG. 18 is a schematic diagram of signal frequency mean and signal frequency variance according to one embodiment of the present disclosure.

[0257] In this embodiment, after the target time domain features are processed by the window function and subjected to short-time Fourier transform, the frequency domain features are obtained. Through the processing of the frequency domain features, the signal frequency mean and signal frequency variance corresponding to each target time domain feature can be directly calculated. As shown in FIG. 18, the abscissa represents each target time domain feature, the ordinate represents the mean and variance, the vertical bar in the figure represents the mean, the vertical line represents the variance, and the point where the vertical bar intersects the vertical line represents the difference between the mean and the variance.

[0258] Step e2, determining the signal change trend according to the signal frequency mean and signal frequency variance, and determining the high pressure change trend and the low pressure change trend according to the signal change trend.

[0259] The embodiment determines the signal change trend according to the difference between the signal frequency mean value and the signal frequency variance or the sum of the signal frequency mean value and the signal frequency variance. In FIG. 18, the curve formed by the connection between the points where the vertical bars intersect the vertical lines refers to the change trend of the difference between the mean value and the variance.

[0260] In the embodiment, the signal change trend is the change trend of the difference between the mean value and the variance or the change trend of the sum of the mean value and the variance. The high-pressure change trend refers to the change trend between the adjacent two target time domain features with the most obvious change in the first (i.e., the first) signal frequency mean value and the signal frequency variance in the signal change trend, and the low-pressure change trend refers to the change trend between the adjacent two target time domain features with the most obvious change in the last (i.e., the last) signal frequency mean value and the signal frequency variance in the signal change trend.

[0261] In step e3, the pressure signal corresponding to the high-pressure change trend is determined as the high-pressure signal, and the pressure signal corresponding to the low-pressure change trend is determined as the low-pressure signal.

[0262] In combination with FIG. 18, according to the signal acquisition time sequence, it can be judged from the slope of the curve in the figure that the target time domain feature 13 to the target time domain feature change most obviously, and therefore, the pressure signal corresponding to the target time domain feature 14 is the high-pressure signal. After the target time domain feature 23, the mean value and the variance of the target time domain feature 24 and the target time domain feature 25 tend to be moderate, and therefore, the pressure signal corresponding to the target time domain feature 23 is the low-pressure signal.

[0263] In the embodiment, a host 50 is also provided, which is used to implement the above-described embodiments and preferred embodiments, and has been described and will not be described again. As used below, the term "module" can be a combination of software and / or hardware that implements a predetermined function. Although the device described in the following embodiments is preferably implemented in software, implementation of hardware or a combination of software and hardware is also possible and is contemplated.

[0264] The embodiment provides a host 50, which, in combination with FIG. 8, includes a preprocessing module, an intermediate processing module, and a post-processing module connected in sequence.

[0265] The preprocessing module is used to perform time-frequency transformation processing on the first time domain feature corresponding to the arterial pulsation extracted from the Korotkoff sound signal to obtain a frequency domain feature, and is used to splice the frequency domain feature with the second time domain feature extracted from the Korotkoff sound signal to obtain a target data feature.

[0266] The intermediate processing module is used to perform inference according to the target data feature to predict a blood pressure category classification result corresponding to the Korotkoff sound signal.

[0267] The post-processing module is configured to determine a blood pressure measurement result according to the blood pressure category classification result and the pressure signal.

[0268] In some embodiments, the pre-processing module includes a band-pass filtering unit, a signal extraction unit, a time-frequency transformation unit, a signal sampling unit, and a feature splicing unit.

[0269] The band-pass filtering unit is configured to perform band-pass filtering on the pressure signal to obtain a pulsatile wave signal reflecting the arterial pulsation.

[0270] The signal extraction unit is configured to extract a first time-domain feature corresponding to the arterial pulsation from the Korotkoff signal, with a sampling time point corresponding to a maximum value in the pulsatile wave signal as a reference time point.

[0271] The time-frequency transformation unit is configured to perform time-frequency transformation on the first time-domain feature to obtain a frequency-domain feature.

[0272] The signal sampling unit is configured to perform sampling on the Korotkoff signal to extract a second time-domain feature from the Korotkoff signal.

[0273] The feature splicing unit is configured to splice the frequency-domain feature and the second time-domain feature into a target data feature.

[0274] In some embodiments, the signal extraction unit is configured to determine a first preset number of first feature points before and after the reference time point extracted from the Korotkoff signal as the first time-domain feature. The time-frequency transformation unit is configured to determine a second preset number of second feature points obtained by performing time-frequency transformation on the first time-domain feature as the frequency-domain feature. The second preset number is less than the first preset number.

[0275] In some embodiments, the signal sampling unit is configured to determine a third preset number of third feature points sampled from the Korotkoff signal as the second time-domain feature. The third preset number is less than the first preset number, and the third preset number is the same as or different from the second preset number.

[0276] The feature splicing unit is configured to splice the third preset number of third feature points and the second preset number of second feature points into the target data feature.

[0277] In some embodiments, the intermediate processing module is a trained convolutional bidirectional long short-term memory neural network, and the trained convolutional bidirectional long short-term memory neural network includes a convolutional neural network and a bidirectional long short-term memory network connected in sequence.

[0278] The convolutional neural network is configured to perform convolutional operation on the target data feature to extract a spatial feature from the target data feature.

[0279] The bidirectional long short-term memory network is configured to output a fourth preset number of blood pressure category classification results from the spatial features, the blood pressure category classification results including a classification result between high and low pressure and a classification result not between high and low pressure, and the fourth preset number is a sum of the third preset number and the second preset number.

[0280] In some embodiments, the bidirectional long short-term memory network includes a long short-term memory network layer and a fully connected layer connected in sequence, the long short-term memory network layer is configured to extract context features from the spatial features, and the fully connected layer is configured to output the fourth preset number of blood pressure category classification results from the context features.

[0281] In some embodiments, the post-processing module is configured to determine a pressure signal corresponding to a first blood pressure category classification result between high and low pressure as a high pressure signal, and determine a pressure signal corresponding to a last blood pressure category classification result between high and low pressure as a low pressure signal.

[0282] In some embodiments, the host 50 includes an analysis module, an identification module, and a judgment module connected in sequence, the analysis module is configured to extract target time domain features corresponding to arterial pulsation from the Korotkoff sound signal from the pressure signal, and determine a signal frequency mean and a signal frequency variance corresponding to the target time domain features, the identification module is configured to determine a signal change trend from the signal frequency mean and the signal frequency variance, and determine a high pressure change trend and a low pressure change trend from the signal change trend, and the judgment module is configured to determine a pressure signal corresponding to the high pressure change trend as a high pressure signal, and determine a pressure signal corresponding to the low pressure change trend as a low pressure signal.

[0283] Further function descriptions of the above-mentioned modules and / or units are the same as those of the corresponding embodiments, and will not be repeated here.

[0284] The host 50 in the embodiment is presented in the form of a functional unit, where the unit refers to an ASIC (Application Specific Integrated Circuit) circuit, a processor and a memory executing one or more software or fixed programs, and / or other devices that can provide the above-mentioned functions.

[0285] FIG. 21 is a schematic diagram of a hardware structure of an electronic device according to an embodiment of the present disclosure.

[0286] Based on the same concept, the present disclosure further provides an electronic device having the host 50 shown in FIG. 21.

[0287] Referring to FIG. 21, FIG. 21 is a structural schematic diagram of an electronic device according to an optional embodiment of the present disclosure. As shown in FIG. 21, the electronic device includes one or more processors 1410, a memory 1420, and an interface for connecting various components, including a high-speed interface and a low-speed interface. The various components communicate with each other using different buses, and can be mounted on a common main board or mounted in other manners as needed. The processor can process instructions executed within the electronic device, including instructions stored in the memory or on the memory to display graphical information of a GUI on an external input / output device such as a display device coupled to the interface. In some embodiments, multiple processors and / or multiple buses can be used with multiple memories and multiple memory banks, if necessary. Also, multiple electronic devices can be connected, each device providing part of the necessary operations (for example, as a server array, a group of blade servers, or a multi-processor system). One processor 1410 is taken as an example in FIG. 21.

[0288] The processor 1410 can be a central processor, a network processor, or a combination thereof. The processor 1410 can further include a hardware chip. The hardware chip can be an application specific integrated circuit, a programmable logic device, or a combination thereof. The programmable logic device can be a complex programmable logic device, a field programmable logic device, a general array logic, or any combination thereof.

[0289] The memory 1420 stores instructions executable by the at least one processor 1410, so that the at least one processor 1410 executes the method implemented by the above-mentioned embodiments.

[0290] The memory 1420 can include a program storage area and a data storage area. The program storage area can store an operating system, application programs required by at least one function; and the data storage area can store data created according to the use of the electronic device, etc. In addition, the memory 1420 can include a high-speed random access memory, and can also include a non-transitory memory, such as at least one magnetic disk storage device, a flash memory device, or other non-transitory solid-state memory device. In some embodiments, the memory 1420 can optionally include a memory disposed remotely with respect to the processor 1410, and these remote memories can be connected to the electronic device through a network. Examples of the network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and a combination thereof.

[0291] The memory 1420 can include a volatile memory, such as a random access memory; the memory can also include a non-volatile memory, such as a flash memory, a hard disk, or a solid state disk; and the memory 1420 can also include a combination of the above-mentioned kinds of memories.

[0292] The electronic device also includes a communication interface 1430 for the electronic device to communicate with other devices or communication networks.

[0293] Based on the same concept, the present disclosure also provides a computer-readable storage medium.

[0294] The method according to the embodiments of the present disclosure described above can be implemented in hardware, firmware, or be implemented as computer code recorded in a storage medium, or be implemented through network downloading and originally stored in a remote storage medium or a non-transitory machine-readable storage medium and then stored in a local storage medium, so that the method described herein can be processed by such software on a storage medium using a general computer, a special processor, or programmable or special hardware. Among them, the storage medium can be a magnetic disk, an optical disk, a read-only memory, a random access memory, a flash memory, a hard disk or a solid state disk, etc.; further, the storage medium can also include a combination of the above types of memories. It can be understood that the computer, processor, microprocessor controller or programmable hardware includes a storage component that can store or receive software or computer code, when the software or computer code is accessed and executed by the computer, processor or hardware, the method shown in the above embodiments is implemented.

[0295] Based on the same concept, the present disclosure also provides a computer program product.

[0296] Part of the present disclosure can be applied as a computer program product, for example, computer program instructions, when executed by a computer, through the operation of the computer, the method and / or technical solutions according to the present disclosure can be invoked or provided. Those skilled in the art should understand that the form of computer program instructions in computer-readable medium includes but is not limited to source file, executable file, installation package file, etc., accordingly, the way of computer program instructions executed by computer includes but is not limited to: the computer directly executes the instructions, or the computer compiles the instructions and then executes the corresponding compiled program, or the computer reads and executes the instructions, or the computer reads and installs the instructions and then executes the corresponding installed program. Here, the computer-readable medium can be any available computer-readable storage medium or communication medium accessible to the computer.

[0297] In the description of the disclosure, it should be understood that the orientation or positional relationship indicated by the terms "center", "longitudinal", "transverse", "length", "width", "thickness", "upper", "lower", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inner", "outer", "clockwise", "counterclockwise", "axial", "radial", "circumferential" and the like are based on the orientation or positional relationship shown in the drawings, and are only for the purpose of facilitating the description of the disclosure and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed and operated in a particular orientation, and therefore cannot be understood as limiting the disclosure.

[0298] In the present disclosure, unless otherwise explicitly specified and limited, the terms "mounting", "connection", "connecting", "fixing" and the like should be understood in a broad sense, for example, can be fixed connection, can also be detachable connection, or integral; can be mechanical connection, can also be electrical connection; can be directly connected, can also be indirectly connected through an intermediate medium, can be the internal communication of two elements or the interaction relationship between two elements, unless otherwise explicitly limited. For those skilled in the art, the specific meaning of the above terms in the present disclosure can be understood according to the specific circumstances.

[0299] It should be understood that parts of the present disclosure can be realized by hardware, software, firmware or a combination thereof. In the above-mentioned embodiments, a plurality of steps or methods can be realized by software or firmware stored in a memory and executed by a suitable instruction execution system. For example, if realized by hardware, and as in another embodiment, it can be realized by any one or a combination of the following technologies known in the art: discrete logic circuit with logic gate circuit for implementing logic function on data signal, application specific integrated circuit with suitable combination logic gate circuit, programmable gate array (PGA), field programmable gate array (FPGA) and the like.

[0300] In the description of the present specification, the description of the terms "the present embodiment", "one embodiment", "some embodiments", "example", "specific example" or "some examples" and the like means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present disclosure. In the present specification, the illustrative description of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any appropriate manner in any one or more embodiments or examples. Furthermore, the skilled person in the art can combine and combine the different embodiments or examples described in the present specification and the features of the different embodiments or examples, without contradiction.

[0301] Furthermore, the terms "first", "second", etc. are used only for descriptive purposes and do not connote or imply relative importance or an ordering. Thus, a feature defined with "first", "second" etc. can include at least one of the features implicitly or explicitly. In the description of the disclosure, the meaning of "a plurality" is at least two, for example, two, three, etc., unless otherwise specifically defined.

[0302] Although embodiments of the disclosure have been described in conjunction with the drawings, various modifications and changes can be suggested by those skilled in the art, and it is intended that the appended claims encompass such modifications and changes as fall within the scope of the disclosure.

[0303] It should be understood that the present disclosure is not limited to the precise structures herein described and illustrated in the drawings, and that various modifications and changes can be made without departing from the scope thereof. The only scope of the present disclosure is defined by the appended claims.

Claims

1. A blood pressure measuring device, characterized by, The blood pressure measuring device comprises: an air reservoir (100A); a piezoelectric sensor (200A) arranged inside the air reservoir (100A); an air tube joint (300A) in communication with the air reservoir, the air tube joint further comprising an electrical connector electrically connected to the piezoelectric sensor.

2. A cuff bladder for a blood pressure measurement device, characterized in that, The cuff air bag (100) comprises: an air bag (10) having an air cavity (103) formed inside; at least one piezoelectric sensor (20), when two piezoelectric sensors (20) are provided, the two piezoelectric sensors (20) are spaced apart on the inner wall of the air bag (10) and electrically connected; an air tube joint (30) arranged on the outer wall of the air bag (10), the air tube joint (30) comprising a first air passage (301) in communication with the air cavity (103), and an electrical connector (31) electrically connected to the two piezoelectric sensors (20).

3. The cuff bladder of claim 2, wherein, The two piezoelectric sensors (20) are spaced apart along the length direction of the air bag (10) and are electrically connected in series.

4. The cuff bladder of claim 2, wherein, The cuff air bag (100) further comprises a wiring (21) connecting the two piezoelectric sensors (20), and the electrical connector (31) is electrically connected to the wiring (21).

5. The cuff bladder of claim 4, wherein, The wiring (21) is a flexible circuit board.

6. The cuff bladder of claim 4, wherein, The wiring (21) is elastic along the length direction of the air bag (10).

7. The cuff bladder of claim 2, wherein, The air bag (10) comprises a first bag piece (11) and a second bag piece (12) adhered to each other, the air cavity (103) is formed between the first bag piece (11) and the second bag piece (12), and the two piezoelectric sensors (20) are arranged on the inner wall of the first bag piece (11).

8. The cuff bladder of claim 7, wherein, The second bag piece (12) is provided with an air port (120) in communication with the air cavity (103) and the air tube joint (30), and an air tube base (121) arranged on the inner wall of the second bag piece (12), the air tube base (121) is provided with an adapter opening (1211) at a position corresponding to the air port (120), and the air tube joint (30) is connected to the air tube base (121).

9. The cuff bladder of claim 8, wherein, The air port (120) is arranged at a central position of two orthogonal projection positions of the two piezoelectric sensors (20) on the first bag piece (11) and the second bag piece (12) after being adhered to each other.

10. The cuff bladder of claim 7, wherein, The periphery of the first bag piece (11) and the periphery of the second bag piece (12) are provided with hot melt welding portions (101), and the first bag piece (11) and the second bag piece (12) are bonded by the hot melt welding portions (101) to form a peripheral sealing structure of the cuff air bag (100).

11. The cuff bladder of any one of claims 2 to 10, wherein, The air tube joint (30) is connected to an air tube (32), the air tube (32) is provided with a second air passage (321), and the electrical connector (31) is electrically connected to an air-electric plug (33) through the second air passage (321) from the first air passage (301).

12. A cuff characterized in that, The cuff includes a cuff air bag and a cuff sleeve, the cuff air bag is arranged in the cuff sleeve, and the cuff air bag is arranged as the cuff air bag (100) in any one of claims 2 to 11.

13. A blood pressure measurement device, characterized by The blood pressure measuring device includes a host, an air-electric plug (33), and a cuff air bag (100), the cuff air bag (100) is connected with the host through the air-electric plug (33), the host inflates the cuff air bag (100) through the air-electric plug (33), and the cuff air bag (100) is arranged as the cuff air bag (100) in any one of claims 2 to 11.

14. A blood pressure measuring device, characterized by, The device includes: A cuff (1000) including a first cuff part (11A) and a second cuff part (12A), the first cuff part (11A) and the second cuff part (12A) enclosing a gas storage chamber (101A), the first cuff part (11A) and the second cuff part (12A) being integrally formed or sealingly connected; the cuff (1000) is provided with an air nozzle (102A), the air nozzle (102A) being in communication with the gas storage chamber (101A); A piezoelectric sensor (20) fixed to the inside of the gas storage chamber (101A), the piezoelectric sensor (20) being used for collecting Korotkoff sound signals; An air pipe (300) having a first end and a second end, the first end being an air pipe joint (30A), the air pipe joint (30A) being connected to the air nozzle (102A), the air pipe (300) being in communication with the gas storage chamber (101A); A pressure sensor (40) connected to the second end, the pressure sensor (40) being used for collecting pressure signals, the pressure signals being used for representing the internal pressure of the gas storage chamber (101A); A host (50) used for acquiring the Korotkoff sound signals and the pressure signals, and used for predicting blood pressure measurement results according to the Korotkoff sound signals and the pressure signals, the piezoelectric sensor (20) and the pressure sensor (40) being respectively in communication connection with the host (50).

15. The device according to claim 14, wherein The piezoelectric sensor (20) is in communication connection with the host (50) through a connecting line built in the air pipe (300), the piezoelectric sensor (20) includes a first piezoelectric sheet and a second piezoelectric sheet attached to a target inner wall of the gas storage chamber (101A), the target inner wall being an inner wall of the gas storage chamber (101A) close to the inside of the cuff (1000).

16. The apparatus of claim 14 or 15, wherein, The host (50) includes a preprocessing module, an intermediate processing module, and a post-processing module connected in sequence; The preprocessing module is used for performing time-frequency transformation processing on a first time domain feature corresponding to arterial pulsation extracted from the Korotkoff sound signals, to obtain a frequency domain feature, and is used for splicing the frequency domain feature and a second time domain feature extracted from the Korotkoff sound signals, to obtain a target data feature; The intermediate processing module is used for inferring according to the target data feature, to predict a blood pressure category classification result corresponding to the Korotkoff sound signals; and The post-processing module is used for performing post-processing on the blood pressure category classification result predicted by the intermediate processing module. The post-processing module is configured to determine the blood pressure measurement result according to the blood pressure category classification result and the pressure signal.

17. The apparatus of claim 16, wherein, The preprocessing module comprises a band-pass filtering unit, a signal extraction unit, a time-frequency transformation unit, a signal sampling unit, and a feature splicing unit; The band-pass filtering unit is configured to perform band-pass filtering on the pressure signal to obtain a pulsatile wave signal reflecting arterial pulsation; The signal extraction unit is configured to extract a first time-domain feature corresponding to arterial pulsation from the Korotkoff sound signal, with a sampling time point corresponding to a maximum value in the pulsatile wave signal as a reference time point; The time-frequency transformation unit is configured to perform time-frequency transformation on the first time-domain feature to obtain a frequency-domain feature; The signal sampling unit is configured to sample the Korotkoff sound signal to extract the second time-domain feature from the Korotkoff sound signal; The feature splicing unit is configured to splice the frequency-domain feature and the second time-domain feature into the target data feature.

18. The apparatus of claim 17, wherein The signal extraction unit is configured to determine a first preset number of first feature points before and after the reference time point extracted from the Korotkoff sound signal as the first time-domain feature; The time-frequency transformation unit is configured to determine a second preset number of second feature points obtained by performing time-frequency transformation on the first time-domain feature as the frequency-domain feature; The second preset number is less than the first preset number.

19. The apparatus of claim 18, wherein The signal sampling unit is configured to determine a third preset number of third feature points sampled from the Korotkoff sound signal as the second time-domain feature; the third preset number is less than the first preset number, and the third preset number is the same as or different from the second preset number; The feature splicing unit is configured to splice the third preset number of third feature points and the second preset number of second feature points into the target data feature.

20. The apparatus of claim 19, wherein, The intermediate processing module is a trained convolutional bidirectional long short-term memory neural network, which comprises a convolutional neural network and a bidirectional long short-term memory network connected in sequence; The convolutional neural network is configured to perform convolutional operation on the target data feature to extract a spatial feature from the target data feature; The bidirectional long short-term memory network is configured to output a fourth preset number of blood pressure category classification results according to the spatial feature, the blood pressure category classification results comprising a classification result between high and low pressure and a classification result not between high and low pressure, and the fourth preset number being a sum of the third preset number and the second preset number.

21. The apparatus of claim 20, wherein, The bidirectional long short-term memory network comprises a long short-term memory network layer and a fully connected layer connected in sequence; The long short-term memory network layer is configured to extract a context feature from the spatial feature; The fully connected layer is configured to output the fourth preset number of blood pressure category classification results according to the context feature.

22. The apparatus of claim 20, wherein The post-processing module is configured to determine a pressure signal corresponding to a blood pressure category classification result of a first blood pressure between high and low pressure as a high pressure signal, and to determine a pressure signal corresponding to a blood pressure category classification result of a last blood pressure between high and low pressure as a low pressure signal.

23. The apparatus of claim 14, wherein, The host (50) comprises an analysis module, an identification module and a judgment module connected in sequence; The analysis module is configured to extract a target time domain feature corresponding to arterial pulsation from the Korotkoff sound signal according to the pressure signal, and to determine a signal frequency mean and a signal frequency variance corresponding to the target time domain feature; The identification module is configured to determine a signal change trend according to the signal frequency mean and the signal frequency variance, and to determine a high pressure change trend and a low pressure change trend according to the signal change trend; The judgment module is configured to determine a pressure signal corresponding to the high pressure change trend as a high pressure signal, and to determine a pressure signal corresponding to the low pressure change trend as a low pressure signal.

24. A method of blood pressure measurement, characterized by, The method comprises: The Korotkoff sound signal collected by the piezoelectric sensor (20) fixed inside the gas storage chamber (101A) and the pressure signal collected by the pressure sensor (40) are acquired, the gas storage chamber (101A) is surrounded by the first cuff part (11) and the second cuff part (12) in the cuff (1000), the first cuff part (11) is integrally formed or sealingly connected with the second cuff part (12), the air nozzle (102A) in communication with the gas storage chamber (101A) is arranged on the cuff (1000), the air nozzle (102A) is used to connect the first end of the air pipe (300), the air pipe (300) is in communication with the gas storage chamber (101A), the pressure sensor (40) is connected to the second end of the air pipe (300), and the pressure signal is used to represent the internal pressure of the gas storage chamber (101A); The blood pressure measurement result is predicted according to the Korotkoff sound signal and the pressure signal.

25. The method of measuring blood pressure according to claim 24, wherein, The blood pressure measurement result is predicted according to the Korotkoff sound signal and the pressure signal, comprising: The first time domain feature corresponding to arterial pulsation extracted from the Korotkoff sound signal is subjected to time-frequency transformation processing to obtain a frequency domain feature; The frequency domain feature is spliced with the second time domain feature extracted from the Korotkoff sound signal to obtain a target data feature; The blood pressure category classification result corresponding to the Korotkoff sound signal is predicted according to the target data feature; The blood pressure measurement result is determined according to the blood pressure category classification result and the pressure signal.

26. The method of measuring blood pressure according to claim 25, wherein, The first time domain feature corresponding to arterial pulsation extracted from the Korotkoff sound signal is subjected to time-frequency transformation processing to obtain a frequency domain feature, comprising: The pressure signal is subjected to band-pass filtering processing to obtain a shock wave signal reflecting arterial pulsation; The maximum value in the shock wave signal is taken as a reference time point, and the first time domain feature corresponding to arterial pulsation is extracted from the Korotkoff sound signal; The first time domain feature is subjected to time-frequency transformation processing to obtain a frequency domain feature.

27. The method of measuring blood pressure according to claim 26, wherein, The splicing the frequency domain feature with a second time domain feature extracted from the Korotkoff signal to obtain a target data feature comprises: sampling processing the Korotkoff signal to extract the second time domain feature from the Korotkoff signal; splicing the frequency domain feature and the second time domain feature into the target data feature.

28. The method of measuring blood pressure according to claim 24, wherein, The predicting a blood pressure measurement result according to the Korotkoff signal and the pressure signal comprises: extracting a target time domain feature corresponding to arterial pulsation from the Korotkoff signal according to the pressure signal, and determining a signal frequency mean and a signal frequency variance corresponding to the target time domain feature; determining a signal change trend according to the signal frequency mean and the signal frequency variance, and determining a high pressure change trend and a low pressure change trend according to the signal change trend; determining a pressure signal corresponding to the high pressure change trend as a high pressure signal, and determining a pressure signal corresponding to the low pressure change trend as a low pressure signal.

29. An electronic device, comprising: comprise: a memory and a processor, which are in communication connection with each other, and the memory stores computer instructions, and the processor executes the computer instructions to perform the blood pressure measurement method in any one of claims 24 to 28.

30. A computer-readable storage medium, characterized in that, The computer readable storage medium stores computer instructions, and the computer instructions are used to make the computer execute the blood pressure measurement method in any one of claims 24 to 28.

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