Calibration method, device and equipment of blood pressure signal and electronic equipment

Abstract

Embodiments of the present application provide a blood pressure signal calibration method, device, equipment and electronic equipment, and relate to the technical field of blood pressure signal calibration. The method comprises: obtaining a calibration signal and a biological signal, the calibration signal comprising an oscillation wave signal collected at the ear under the condition of applying pressure to the ear of the living body; the biological signal comprising at least one of a pulse wave signal and an electrocardiogram signal; processing the biological signal to obtain a blood pressure parameter used for estimating blood pressure; and obtaining a blood pressure signal according to the calibration signal and the blood pressure parameter, the blood pressure signal comprising at least one of systolic pressure and diastolic pressure. The embodiments of the present application realize sleeveless blood pressure measurement and calibration, and also ensure the accuracy of the blood pressure signal.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of blood pressure signal calibration, in particular, the present application relates to a blood pressure signal calibration method and device and electronic equipment. BACKGROUND

[0002] Blood pressure is a major risk indicator for coronary heart disease, renal failure, stroke and other diseases, so measuring blood pressure is indispensable. At present, in daily life, in order to facilitate the user to carry and quickly measure blood pressure, the wearable device often uses a sleeveless blood pressure measurement method to replace the sleeve blood pressure measurement method, but often needs the user to regularly manually calibrate the blood pressure of the wearable device with the sleeve blood pressure measurement device, which not only affects the user's use, but also cannot guarantee the accuracy of blood pressure calibration. SUMMARY

[0003] The present application provides a blood pressure signal calibration method, device, equipment and electronic equipment, which can solve the problem of inaccurate blood pressure during long-term monitoring. The technical solution is as follows:

[0004] According to an aspect of the present application, a blood pressure signal calibration method is provided, which comprises:

[0005] Obtaining a calibration signal and a biological signal, the calibration signal comprising an oscillation wave signal collected at the ear under the condition of applying pressure to the ear of the living body; the biological signal comprising at least one of a pulse wave signal and an electrocardiogram signal;

[0006] Processing the biological signal to obtain a blood pressure parameter for estimating blood pressure;

[0007] According to the calibration signal and the blood pressure parameter, a blood pressure signal is obtained, the blood pressure signal comprising at least one of systolic pressure and diastolic pressure.

[0008] As an optional embodiment, the blood pressure parameter comprises pulse wave transit time and pulse arrival time;

[0009] According to the calibration signal and the blood pressure parameter, a blood pressure signal is obtained, comprising:

[0010] Extracting the calibration signal to obtain the calibrated systolic pressure, the calibrated pulse wave transit time, the calibrated pulse arrival time and the calibrated pulse pressure;

[0011] Inputting the calibrated systolic pressure, the calibrated pulse wave transit time, the calibrated pulse arrival time and the blood pressure parameter into a first physiological mathematical model to obtain the systolic pressure output by the first physiological mathematical model;

[0012] inputting the systolic pressure, the to-be-calibrated pulse pressure, the to-be-calibrated pulse wave transit time, and the pulse wave transit time into a second physiological mathematical model to obtain the diastolic pressure output by the second physiological mathematical model.

[0013] As an optional embodiment, the blood pressure parameter comprises a pulse wave transit time.

[0014] The method further comprises:

[0015] extracting, from the calibration signal, a to-be-calibrated diastolic pressure, a to-be-calibrated systolic pressure, a to-be-calibrated pulse wave transit time, a to-be-calibrated pulse pressure, and a to-be-calibrated mean blood pressure;

[0016] inputting the to-be-calibrated mean blood pressure, the to-be-calibrated pulse wave transit time, the to-be-calibrated pulse pressure, and the blood pressure parameter into a third physiological mathematical model to obtain the diastolic pressure output by the third physiological mathematical model;

[0017] inputting the diastolic pressure, the to-be-calibrated pulse pressure, the to-be-calibrated pulse wave transit time, and the pulse wave transit time into a fourth physiological mathematical model to obtain the systolic pressure output by the fourth physiological mathematical model.

[0018] As an optional embodiment, the blood pressure parameter comprises a predicted systolic pressure and a predicted diastolic pressure.

[0019] The method further comprises:

[0020] inputting the biological signal into a pre-trained deep learning model to obtain a blood pressure parameter output by the deep learning model, the deep learning model being trained based on biological signals of biological samples and blood pressure parameters of the biological samples;

[0021] The method further comprises:

[0022] extracting, from the calibration signal, a to-be-calibrated diastolic pressure and a to-be-calibrated systolic pressure;

[0023] comparing the predicted systolic pressure and the to-be-calibrated systolic pressure at the same time, and obtaining the systolic pressure based on an error calculation model;

[0024] comparing the predicted diastolic pressure and the to-be-calibrated diastolic pressure at the same time, and obtaining the diastolic pressure based on the error calculation model.

[0025] As an optional embodiment, the calibration signal further comprises a temperature signal and an acceleration signal collected at the ear, and the method further comprises, before obtaining the blood pressure map signal based on the calibration signal and the blood pressure parameter:

[0026] determining that a temperature difference between the first time and the second time in the temperature signal reaches a first threshold, or

[0027] determining that an acceleration difference between the first time and the second time in the acceleration signal reaches a second threshold.

[0028] As an optional embodiment, if the temperature difference does not reach the first threshold and the acceleration difference does not reach the second threshold, the processing of the biological signal to obtain a blood pressure parameter for estimating blood pressure further includes:

[0029] obtaining a blood pressure map signal according to the blood pressure parameter.

[0030] According to another aspect of the embodiments of the present application, a calibration device for a blood pressure map signal is provided, and the device includes:

[0031] a signal obtaining module, configured to obtain a calibration signal and a biological signal, the calibration signal including an oscillation wave signal collected from an ear of a living body under a state of applying pressure to the ear, and the biological signal including at least one of a pulse wave signal and an electrocardiogram signal;

[0032] a first processing module, configured to process the biological signal to obtain a blood pressure parameter for estimating blood pressure;

[0033] a second processing module, configured to obtain a blood pressure map signal according to the calibration signal and the blood pressure parameter, the blood pressure map signal including at least one of a systolic pressure and a diastolic pressure.

[0034] According to another aspect of the embodiments of the present application, a calibration device for a blood pressure map signal is provided, and the device includes:

[0035] a pressure adjusting assembly arranged at the ear, configured to apply pressure to the ear to obtain an oscillation wave signal;

[0036] a measuring assembly, configured to collect a biological signal of an eye of the living body; and

[0037] a calibration device for a blood pressure map signal as described above.

[0038] According to another aspect of the embodiments of the present application, an electronic device is provided, which includes a memory, a processor, and a computer program stored in the memory, and the processor executes the computer program to implement the steps of the calibration method for a blood pressure map signal.

[0039] According to still another aspect of the embodiments of the present application, a computer readable storage medium is provided, which stores a computer program, and the computer program is executed by a processor to implement the steps of the calibration method for a blood pressure map signal.

[0040] The technical scheme provided by the embodiments of the present application has the beneficial effects that the embodiments of the present application provide a calibration method, device and equipment of a sphygmomanometer signal, an electronic device and a computer readable storage medium, the calibration signal and the biological signal are obtained, the biological signal is processed to obtain the blood pressure parameter, the sphygmomanometer signal is obtained according to the calibration signal and the blood pressure parameter, the sleeveless blood pressure measurement and calibration are realized, and the accuracy of the sphygmomanometer signal can be ensured. BRIEF DESCRIPTION OF DRAWINGS

[0041] In order to more clearly illustrate the technical scheme in the embodiments of the present application, the drawings needed in the description of the embodiments of the present application will be briefly introduced.

[0042] Figure 1 A flowchart of a calibration method of a sphygmomanometer signal provided by the embodiments of the present application;

[0043] Figure 2 A flowchart of a calibration method of a sphygmomanometer signal provided by the embodiments of the present application;

[0044] Figure 3 A flowchart of a calibration method of a sphygmomanometer signal based on a deep learning model provided by the embodiments of the present application;

[0045] Figure 4 A calibration device of a sphygmomanometer signal provided by the embodiments of the present application;

[0046] Figure 5 A calibration device of a sphygmomanometer signal provided by the embodiments of the present application;

[0047] Figure 6 A distribution diagram of a measurement assembly provided by the embodiments of the present application on a human body;

[0048] Figure 7 A calibration device of a sphygmomanometer signal provided by the embodiments of the present application;

[0049] Figure 8 A structural diagram of a pressure adjusting assembly provided by the embodiments of the present application;

[0050] Figure 9 A structural diagram of an elastomer before and after expansion provided by the embodiments of the present application;

[0051] Figure 10 A structural diagram of a pressure adjusting assembly provided by the embodiments of the present application;

[0052] Figure 11 A use diagram of a measurement assembly provided by the embodiments of the present application;

[0053] Figure 12 A structural schematic diagram of a multi-wavelength optical sensor provided for an embodiment of the present application is shown in FIG. 1.

[0054] Figure 13 A structural schematic diagram of a measurement assembly provided with an electrode for an embodiment of the present application is shown in FIG. 2.

[0055] Figure 14 A structural schematic diagram of an operation panel provided for an embodiment of the present application is shown in FIG. 3.

[0056] Figure 15 A structural schematic diagram of an electronic device for implementing a calibration method of a sphygmogram signal provided for an embodiment of the present application is shown in FIG. 4. DETAILED DESCRIPTION

[0057] Embodiments of the present application will be described below with reference to the accompanying drawings. It should be understood that the embodiments described below with reference to the accompanying drawings are exemplary descriptions of the technical solutions of the embodiments of the present application, and do not limit the technical solutions of the embodiments of the present application.

[0058] Those skilled in the art can understand that the singular forms "a", "an" and "the" used herein include plural forms unless specifically stated otherwise. It should be further understood that the terms "comprise" and "include" used in the embodiments of the present application mean that the corresponding features can be implemented as the presented features, information, data, steps, operations, elements and / or components, but do not exclude other features, information, data, steps, operations, elements, components and / or combinations thereof supported by the present technology. It should be understood that when we say that an element is "connected" or "coupled" to another element, the element can be directly connected or coupled to the other element, or it can mean that the element and the other element are connected through an intermediate element. In addition, "connected" or "coupled" used herein can include wireless connection or wireless coupling. The term "and / or" used herein means that at least one of the items defined by the term, for example, "A and / or B" can be implemented as "A", or as "B", or as "A and B".

[0059] To make the purposes, technical solutions and advantages of the present application clearer, the embodiments of the present application will be described in further detail below with reference to the accompanying drawings.

[0060] The calibration method, device, equipment, electronic equipment, computer readable storage medium and computer program product of the sphygmogram signal provided by the present application are aimed at solving the above technical problems of the prior art.

[0061] The technical solutions of the embodiments of the present application and the technical effects of the technical solutions of the present application are described below by describing several exemplary embodiments. It should be noted that the following embodiments can be mutually referenced, borrowed or combined. The same terms, similar features and similar implementation steps in different embodiments are not described repeatedly.

[0062] A calibration method of a blood pressure signal is provided in the embodiments of the present application, as shown in the following formula (1). Figure 1 The method comprises the following steps.

[0063] S100, obtaining a calibration signal and a biological signal, the calibration signal comprising an oscillatory wave signal collected at an ear under the condition of applying pressure to the ear of the living body, and the biological signal comprising at least one of a pulse wave (PPG) signal and an electrocardiogram (ECG) signal.

[0064] In this way, the accuracy of the obtained oscillatory wave signal is improved, and the normal activities of the user are not affected during the calibration of the blood pressure signal, thereby realizing long-term calibration of the blood pressure signal.

[0065] Specifically, the oscillatory wave signal refers to a curve of the change of the pressure in the blood vessel with time, which is obtained by applying a certain pressure to the blood vessel to make part of the blood vessel wall flat without causing the blood vessel to be occluded.

[0066] Optionally, the calibration signal further comprises an optical signal, a temperature signal, an acceleration signal, an electrocardiogram signal, etc.

[0067] Specifically, the pulse wave signal refers to a curve of the change of time formed by the rhythmic blood pumping of the heart, the blood propagation along the arterial blood vessels and the blood flow to the periphery.

[0068] S101, processing the biological signal to obtain a blood pressure parameter used for estimating blood pressure.

[0069] In this way, the accuracy of the obtained oscillatory wave signal is improved, and the normal activities of the user are not affected during the calibration of the blood pressure signal, thereby realizing long-term calibration of the blood pressure signal.

[0070] In this way, the accuracy of the obtained oscillatory wave signal is improved, and the normal activities of the user are not affected during the calibration of the blood pressure signal, thereby realizing long-term calibration of the blood pressure signal.

[0071] S102, obtaining a blood pressure signal according to the calibration signal and the blood pressure parameter, the blood pressure signal comprising at least one of a systolic pressure and a diastolic pressure.

[0072] The blood pressure chart signal is continuous blood pressure information, compared with the intermittent blood pressure information obtained by the existing technology through the cuff method, which only includes systolic blood pressure (SBP) and diastolic blood pressure (DBP), the blood pressure chart signal is more accurate in the evaluation of the cardiovascular system, and the accuracy of the physical health evaluation is ensured.

[0073] In combination Figure 2 As shown in the flowchart of the calibration method of the blood pressure chart signal, there are various ways to obtain the blood pressure chart signal according to the oscillation wave signal and the biological signal of the calibration signal, which can be based on at least one of a physiological mathematical model and a deep learning model. The physiological mathematical model refers to using mathematical expressions to describe the blood pressure chart signal of the human body, and the deep learning model refers to obtaining the blood pressure chart signal through the learning process according to the existing oscillation wave signal and biological signal. The present embodiment does not make specific limitations.

[0074] It can be understood that by obtaining the calibration signal and the biological signal, and processing the biological signal to obtain the blood pressure parameter, the blood pressure chart signal is obtained according to the calibration signal and the blood pressure parameter, which realizes the sleeveless blood pressure measurement and calibration, and also ensures the accuracy of the blood pressure chart signal.

[0075] On the basis of the above embodiments, as an optional embodiment, the blood pressure parameter includes pulse wave transit time and pulse arrival time;

[0076] According to the calibration signal and the blood pressure parameter, the blood pressure chart signal is obtained, including:

[0077] The to-be-calibrated systolic pressure, the to-be-calibrated pulse wave transit time, the to-be-calibrated pulse arrival time, and the to-be-calibrated pulse pressure are extracted from the calibration signal;

[0078] The to-be-calibrated systolic pressure, the to-be-calibrated pulse wave transit time, the to-be-calibrated pulse arrival time, and the blood pressure parameter are input into the first physiological mathematical model to obtain the systolic pressure output by the first physiological mathematical model;

[0079] The systolic pressure, the to-be-calibrated pulse pressure, the to-be-calibrated pulse wave transit time, and the pulse wave transit time are input into the second physiological mathematical model to obtain the diastolic pressure output by the second physiological mathematical model.

[0080] Specifically, the first physiological mathematical model includes the following formula:

[0081]

[0082] Wherein, is the to-be-calibrated systolic pressure, is the to-be-calibrated pulse wave transit time, PPTT is the pulse transit time to be calibrated, PTT is the pulse transit time, PPTT is the pulse transit time, and γ is a blood vessel information parameter.

[0083] Specifically, the second physiological mathematical model comprises the following formula:

[0084]

[0085] wherein, PPTT is the pulse pressure to be calibrated, and , PDB is the diastolic blood pressure to be calibrated.

[0086] It should be explained that the calibration method of the blood pressure signal is a factor point-to-point pairing (fPTP) calibration method, that is, to adjust and correct the BP estimation error in real time, that is, to obtain unknown parameters of a BP model before blood pressure monitoring. Once the unknown parameters are determined, they will not change in subsequent long-term blood pressure monitoring. In this embodiment, the BP model is an MK-BH model, which is composed of the first physiological mathematical model and the second physiological mathematical model, and the model can overcome the weak linear correlation between PTT and DBP.

[0087] On the basis of the above embodiments, as an optional embodiment, the blood pressure parameter comprises a pulse transit time;

[0088] According to the calibration signal and the blood pressure parameter, the blood pressure signal is obtained, comprising:

[0089] The diastolic blood pressure to be calibrated, the systolic blood pressure to be calibrated, the pulse transit time to be calibrated, the pulse pressure to be calibrated, and the mean blood pressure to be calibrated are extracted from the calibration signal;

[0090] The diastolic blood pressure to be calibrated, the systolic blood pressure to be calibrated, the pulse transit time to be calibrated, the pulse pressure to be calibrated, and the mean blood pressure to be calibrated are extracted from the calibration signal;

[0091] The diastolic blood pressure, the pulse pressure to be calibrated, the pulse transit time to be calibrated, and the pulse transit time are input into the fourth physiological mathematical model to obtain the systolic blood pressure output by the fourth physiological mathematical model.

[0092] Specifically, the third physiological mathematical model comprises the following formula:

[0093]

[0094] wherein, PDB is the diastolic blood pressure to be calibrated, PDB is the diastolic blood pressure to be calibrated, PDB is the diastolic blood pressure to be calibrated, and , to be calibrated pulse pressure, and , to be calibrated pulse wave transit time, pulse wave transit time, and γ is a blood vessel information parameter.

[0095] In particular, the fourth physiological mathematical model comprises the following formula:

[0096]

[0097] It should be explained that the calibration method of the blood pressure signal is a factor point-to-point pairing (fPTP) calibration method, that is, to adjust and correct the BP estimation error in real time, that is, to obtain the unknown parameters of a BP model before blood pressure monitoring. Once the unknown parameters are determined, they will not change in subsequent long-term blood pressure monitoring. In this embodiment, the BP model is a dMK-BH model, which is composed of the third physiological mathematical model and the fourth physiological mathematical model.

[0098] On the basis of the above embodiments, as an optional embodiment, the blood pressure parameters include predicted systolic pressure and predicted diastolic pressure;

[0099] The biological signal is processed to obtain blood pressure parameters for estimating blood pressure, including:

[0100] The biological signal is input into a pre-trained deep learning model to obtain blood pressure parameters output by the deep learning model, and the deep learning model is trained with biological signals of biological samples as samples and blood pressure parameters of biological samples as labels;

[0101] According to the calibration signal and the blood pressure parameter, a blood pressure signal is obtained, including:

[0102] The to-be-calibrated diastolic pressure and the to-be-calibrated systolic pressure are obtained from the calibration signal;

[0103] The predicted systolic pressure and the to-be-calibrated systolic pressure at the same time are compared, and the systolic pressure is obtained based on an error calculation model.

[0104] The predicted diastolic pressure and the to-be-calibrated diastolic pressure at the same time are compared, and the diastolic pressure is obtained based on an error calculation model.

[0105] It can be understood that, considering that the clinical process is dynamic, in order to ensure the accuracy of the measurement of the cuffless blood pressure measurement test, the following problems often exist: first, there is a lack of general verification standard for cuffless blood pressure measurement calibration. Second, there is a lack of mechanism for inter-individual and intra-individual blood pressure changes on cuffless measurement. Third, there is a lack of population statistics, such as the influence of blood pressure measurement accuracy by factors such as age, gender, and lifestyle. The above problems are difficult to overcome if a physiological mathematical model is used, and therefore a deep learning model can be used to avoid the above problems to ensure the accuracy of the calibration.

[0106] In combination Figure 3 As shown in the figure, an exemplary flowchart of a blood pressure signal calibration method based on a deep learning model is shown, in this example, a convolutional neural network method in the deep learning model is used for blood pressure estimation, according to the obtained pulse wave signal (PPG) and electrocardiogram signal (ECG), an automatic encoder based on U-Net is used, which includes three convolutional layers and one pooling layer, so that PPG and ECG are first analyzed by pooling down-sampling to obtain multiple blood pressure information, and then convolution up-sampling is used to combine the biological signal with the information obtained by pooling down-sampling to obtain predicted SBP and predicted DBP, and through error calculation with the same time error calculation model, accurate SBP and DBP are obtained.

[0107] On the basis of the above embodiments, as an optional embodiment, the calibration signal further includes a temperature signal and an acceleration signal collected at the ear, and before obtaining the blood pressure signal according to the calibration signal and the blood pressure parameter, the method further includes:

[0108] determining that the temperature difference between the first time and the second time in the temperature signal reaches a first threshold, or

[0109] determining that the acceleration difference between the first time and the second time in the acceleration signal reaches a second threshold.

[0110] It should be explained that, considering that human body temperature and human body position change have an impact on BP, the change of human body temperature can be determined by the temperature signal, and the change of human body position can be determined by the acceleration signal, by determining that the temperature difference reaches the first threshold or the acceleration difference reaches the second threshold, the blood pressure signal is obtained according to the calibration signal and the blood pressure parameter, so as to realize periodic calibration of the blood pressure signal.

[0111] It can be understood that the interval between the first time and the second time, the first threshold and the second threshold can be set according to actual conditions, and the present embodiment does not make specific limitation.

[0112] On the basis of the above embodiments, as an optional embodiment, when the temperature difference does not reach the first threshold and the acceleration difference does not reach the second threshold, the biological signal is processed to obtain the blood pressure parameter for estimating blood pressure, and then the method further includes:

[0113] obtaining the blood pressure signal according to the blood pressure parameter.

[0114] It can be understood that when the temperature difference does not reach the first threshold and the acceleration difference does not reach the second threshold, it means that the current change of human body temperature and body position has little impact on BP, so calibration according to the calibration signal is not needed, and the blood pressure signal can be directly obtained through the blood pressure parameter.

[0115] Specifically, the blood pressure graph signal obtained from the blood pressure parameters can be based on a physiological mathematical model or a deep learning model; this embodiment does not impose any specific limitations.

[0116] This application provides a calibration device for blood pressure graph signals, such as... Figure 4 As shown, the calibration device for the blood pressure graph signal may include: a signal acquisition module 601, a first processing module 602, and a second processing module 603. The signal acquisition module 601 is used to acquire a calibration signal and a biological signal. The calibration signal includes an oscillation wave signal collected at the ear while pressure is applied to the ear of the organism. The biological signal includes at least one of a pulse wave signal and an electrocardiogram signal. The first processing module 602 is used to process the biological signal to obtain blood pressure parameters for predicting blood pressure. The second processing module 603 is used to obtain a blood pressure graph signal based on the calibration signal and the blood pressure parameters. The blood pressure graph signal includes at least one of systolic blood pressure and diastolic blood pressure.

[0117] Based on the above embodiments, as an optional embodiment, the blood pressure parameters include pulse wave conduction time and pulse arrival time;

[0118] The second processing module obtains the blood pressure graph signal based on the calibration signal and blood pressure parameters. The specific steps include:

[0119] Extract the systolic blood pressure to be calibrated, the pulse wave conduction time to be calibrated, the pulse arrival time to be calibrated, and the pulse pressure to be calibrated from the calibration signal;

[0120] The systolic blood pressure to be calibrated, the pulse wave conduction time to be calibrated, the pulse arrival time to be calibrated, and the blood pressure parameters are input into the first physiological mathematical model to obtain the systolic blood pressure output by the first physiological mathematical model.

[0121] The systolic blood pressure, the pulse pressure to be calibrated, the pulse wave conduction time to be calibrated, and the pulse wave conduction time are input into the second physiological mathematical model to obtain the diastolic blood pressure output by the second physiological mathematical model.

[0122] Based on the above embodiments, as an optional embodiment, the blood pressure parameter includes pulse wave conduction time;

[0123] The second processing module is used to obtain the blood pressure chart signal based on the calibration signal and blood pressure parameters. The specific steps include:

[0124] Extract the diastolic blood pressure, systolic blood pressure, pulse wave transit time, pulse pressure, and mean blood pressure to be calibrated from the calibration signal;

[0125] The mean blood pressure to be calibrated, the pulse wave transit time to be calibrated, the pulse pressure to be calibrated, and the blood pressure parameters are input into the third physiological mathematical model to obtain the diastolic pressure output by the third physiological mathematical model.

[0126] inputting the diastolic pressure, the to-be-calibrated pulse pressure, the to-be-calibrated pulse wave transit time, and the pulse wave transit time into the fourth physiological mathematical model to obtain a systolic pressure output by the fourth physiological mathematical model.

[0127] On the basis of each of the above embodiments, as an optional embodiment, the blood pressure parameters include predicted systolic pressure and predicted diastolic pressure.

[0128] The second processing module is configured to process the biosignal to obtain blood pressure parameters used for estimating blood pressure, and the specific steps include:

[0129] inputting the biosignal into a pre-trained deep learning model to obtain blood pressure parameters output by the deep learning model, the deep learning model being trained by taking biosignals of biological samples as samples and taking blood pressure parameters of the biological samples as labels;

[0130] obtaining a blood pressure map signal according to the calibration signal and the blood pressure parameters, including:

[0131] obtaining to-be-calibrated diastolic pressure and to-be-calibrated systolic pressure from the calibration signal;

[0132] comparing the predicted systolic pressure and the to-be-calibrated systolic pressure at the same time, and obtaining the systolic pressure based on an error calculation model;

[0133] comparing the predicted diastolic pressure and the to-be-calibrated diastolic pressure at the same time, and obtaining the diastolic pressure based on an error calculation model.

[0134] On the basis of each of the above embodiments, as an optional embodiment, the calibration signal further includes a temperature signal and an acceleration signal collected at the ear, and the second processing module, before obtaining the blood pressure map signal according to the calibration signal and the blood pressure parameters, further includes:

[0135] determining that a temperature difference between the first time and the second time in the temperature signal reaches a first threshold, or

[0136] determining that an acceleration difference between the first time and the second time in the acceleration signal reaches a second threshold.

[0137] On the basis of each of the above embodiments, as an optional embodiment, if the temperature difference does not reach the first threshold and the acceleration difference does not reach the second threshold, the first processing module, after processing the biosignal to obtain blood pressure parameters used for estimating blood pressure, further includes:

[0138] obtaining a blood pressure map signal according to the blood pressure parameters.

[0139] Embodiments of the present application provide a calibration device for a blood pressure map signal, as shown in Figure 5As shown, an exemplary calibration device for a blood pressure graph signal is illustrated, the calibration device comprising:

[0140] A pressure adjustment component 700 is installed in the ear to apply pressure to the ear to obtain a shock wave signal;

[0141] Measurement component 701 is used to acquire biosignals from the eyes of a living organism; and

[0142] The calibration device for the blood pressure graph signal in the above embodiments.

[0143] It needs to be explained that, such as Figure 6 As shown, this example illustrates a distribution map of measurement components mounted on the human body. In other embodiments, the measurement components can also be used to measure biosignals from other body parts such as the wrist, ear, and fingers. This embodiment does not impose specific limitations. Figure 7 As shown, an exemplary device for calibrating a blood pressure signal is illustrated, with a pressure regulating component 200 disposed at the ear and a measuring component 201 disposed at the wrist.

[0144] Based on the above embodiments, as an optional embodiment, combined with Figure 8 As shown, an exemplary structural schematic diagram of a pressure regulating component is provided. The pressure regulating component includes an automatic adjustment module (not shown in the figure) and an elastic element 300. The elastic element 300 can be placed in the ear canal of the ear, and the elastic element is a column with an internal cavity.

[0145] Combination Figure 9 As shown, it exemplarily illustrates the structural diagram of the elastomer before and after expansion. An automatic adjustment module controls the expansion size of the elastic cavity to compress the arteries in the ear canal wall, thereby obtaining a shock wave signal. Furthermore, since the elastomer is placed inside the ear canal, damage to the ear canal is minimized, ensuring user comfort.

[0146] Based on the above embodiments, as an optional embodiment, combined with Figure 10 As shown, an exemplary schematic diagram of a pressure regulating assembly is illustrated. The pressure regulating assembly includes an airbag 400 and an automatic control module (not shown in the figure). The airbag 400 is disposed on the auricle or preauricular fissure of the ear. Figure 10 In (a), the airbag 400 is placed in front of the ear fissure, and in (b), the airbag 400 is placed in the auricle. That is, the expansion degree of the airbag 400 is controlled by the automatic control module to obtain the shock wave signal.

[0147] On the basis of the above embodiments, as an optional embodiment, the calibration signal further comprises an optical signal, an electrocardiogram signal, a temperature signal, an acceleration signal and a pressure signal, and the calibration device of the blood pressure chart signal further comprises a sensor module arranged on the ear, the sensor module comprising an optical sensor, an electrocardiogram electrode, a temperature sensing unit, a body position monitoring unit and a pressure sensing unit, the optical sensor being configured to obtain the optical signal, the electrocardiogram electrode being configured to obtain the electrocardiogram signal, the temperature sensing unit being configured to obtain the temperature signal, the body position monitoring unit being configured to obtain the acceleration signal, and the pressure sensing unit being configured to obtain the pressure signal.

[0148] Specifically, the body position monitoring unit can be an accelerometer, a gyroscope, etc.

[0149] On the basis of the above embodiments, as an optional embodiment, as shown in Figure 11 Fig. 8, an exemplary use diagram of a measurement assembly is shown, the measurement assembly comprising glasses and a sensor module arranged on the glasses in contact with the nose bridge, the sensor module comprising a multi-wavelength optical sensor 800 configured to obtain a pulse wave signal at blood vessels around the eye.

[0150] In combination with Figure 12 Fig. 9, an exemplary structure diagram of a multi-wavelength optical sensor is shown, the multi-wavelength optical sensor comprising a light emitter, an optical barrier and a photodetector. The light emitter is configured to emit at least two wavelengths of LED light, exemplarily, the LED light being blue light, yellow light, green light, red light and infrared light.

[0151] In combination with Figure 13 Fig. 10, an exemplary structure diagram of a measurement assembly provided with an electrode is shown, the sensor module further comprising an electrode 801 configured to obtain an electrooculogram (EOG) signal. It is to be explained that the electrooculogram (EOG) is an electrical recording of eye movements, by recognizing the movement of the eyeball to move the information of systolic pressure and diastolic pressure displayed on the glasses in real time, so that the user can obtain the blood pressure chart signal in real time. Specifically, if the horizontal movement of the eyeball is detected, a pair of electrodes are respectively arranged at the medial and lateral canthi, and if the vertical movement of the eyeball is detected, a pair of electrodes are respectively arranged on the upper and lower eyelids to record the potential difference between the two.

[0152] On the basis of the above embodiments, as an optional embodiment, in combination with Figure 14As shown, an exemplary schematic diagram of a structure of an operation panel is shown, the calibration device of the sphygmomanometer signal further comprises an operation panel, the operation panel is used for a user to view the sphygmomanometer signal and operate calibration instructions, etc., the operation panel comprises two areas, which are a calibration function setting area and a display area respectively, specifically, when the user wants to calibrate, can click the ear canal, the auricle or the preauricular fissure according to the specific position of the pressure adjusting assembly on the ear, and click the earphone, the ear ring or the watch according to the specific position of the measuring assembly on the body, and then click the button of starting calibration or the button of re-calibration, when the calibration is completed, the user can see the systolic pressure, the diastolic pressure, the BP waveform diagram and the ECG waveform diagram obtained from the sphygmomanometer signal on the display area.

[0153] The device provided in the embodiments of the present application can execute the method provided in the embodiments of the present application, and the implementation principles are similar. The actions performed by each module in the device of the embodiments of the present application are corresponding to the steps in the method of the embodiments of the present application. The detailed function description of each module of the device can be referred to the description of the corresponding method in the foregoing description, and will not be repeated here.

[0154] An electronic device is provided in the embodiments of the present application, which comprises a memory, a processor and a computer program stored in the memory. The processor executes the computer program to implement the steps of the calibration method of the sphygmomanometer signal. Compared with the related art, the calibration method can obtain a calibration signal and a biological signal, process the biological signal to obtain a blood pressure parameter, and obtain a sphygmomanometer signal according to the calibration signal and the blood pressure parameter. The calibration method not only does not need the user to manually calibrate regularly, but also can ensure that the sphygmomanometer signal is always accurate.

[0155] An electronic device is provided in an optional embodiment, which comprises a memory, a processor and a computer program stored in the memory. The processor executes the computer program to implement the steps of the calibration method of the sphygmomanometer signal. Compared with the related art, the calibration method can obtain a calibration signal and a biological signal, process the biological signal to obtain a blood pressure parameter, and obtain a sphygmomanometer signal according to the calibration signal and the blood pressure parameter. The calibration method not only does not need the user to manually calibrate regularly, but also can ensure that the sphygmomanometer signal is always accurate. Figure 15 As shown, Figure 15 The electronic device 4000 shown in the figure comprises a processor 4001 and a memory 4003. The processor 4001 and the memory 4003 are connected, for example, through a bus 4002. Optionally, the electronic device 4000 can further comprise a transceiver 4004, which can be used for data interaction between the electronic device and other electronic devices, such as data transmission and / or data reception, etc. It should be noted that in actual application, the transceiver 4004 is not limited to one, and the structure of the electronic device 4000 does not constitute a limitation on the embodiments of the present application.

[0156] The processor 4001 can be a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array) or other programmable logic device, transistor logic device, hardware component, or any combination thereof. It can implement or execute various exemplary logical blocks, modules and circuits described in connection with the disclosure. The processor 4001 can also be a combination of computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0157] The bus 4002 can include a path for transmitting information between the above-mentioned components. The bus 4002 can be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. The bus 4002 can be divided into an address bus, a data bus, a control bus, etc. For convenience of representation, Figure 15 In the figure, only one thick line is used to represent the bus, but it does not mean that there is only one bus or only one type of bus.

[0158] The memory 4003 can be a ROM (Read Only Memory) or other type of static storage device that can store static information and instructions, a RAM (Random Access Memory) or other type of dynamic storage device that can store information and instructions, an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read Only Memory) or other optical disk storage, an optical disk storage (including a compact disk, a laser disk, an optical disk, a digital versatile disk, a Blu-ray disk, etc.), a magnetic disk storage medium, other magnetic storage device, or any other medium capable of carrying or storing computer programs and capable of being read by a computer, without limitation.

[0159] The memory 4003 is configured to store a computer program for implementing the embodiments of the present application, and the processor 4001 is configured to control the execution of the computer program stored in the memory 4003. The processor 4001 is configured to execute the computer program stored in the memory 4003 to implement the steps shown in the foregoing method embodiments.

[0160] The embodiments of the present application provide a computer readable storage medium, and the computer readable storage medium stores a computer program. The computer program is executed by a processor to implement the steps and corresponding contents of the foregoing method embodiments.

[0161] The embodiments of the present application also provide a computer program product, which includes a computer program. The computer program is executed by a processor to implement the steps and corresponding contents of the foregoing method embodiments.

[0162] The terms "first", "second", "third", "fourth", "1", "2", and the like (if any) in the specification and claims of the present application and the above-described drawings are used to distinguish similar objects, and do not necessarily have to describe a specific order or sequence. It should be understood that the data thus used can be interchanged under appropriate circumstances, so that the embodiments of the present application described herein can be implemented in an order other than that illustrated or described.

[0163] It should be understood that, although the flowcharts of the embodiments of the present application indicate the respective operation steps by arrows, the implementation order of the steps is not limited to the order indicated by the arrows. Unless otherwise specified herein, in some implementation scenarios of the embodiments of the present application, the implementation steps in each flowchart can be executed in other orders as required. In addition, part or all of the steps in each flowchart can include multiple sub-steps or multiple stages based on the actual implementation scenario. Part or all of these sub-steps or stages can be executed at the same time, and each of these sub-steps or stages can also be executed at different times. In the scenario where the execution times are different, the execution order of these sub-steps or stages can be flexibly configured as required, and the embodiments of the present application do not limit this.

[0164] The above is only an optional implementation of some implementation scenarios of the present application, and it should be pointed out that, for those skilled in the art, other similar implementation means based on the technical concept of the present application can also be adopted without departing from the technical concept of the present application, and such implementation also falls within the protection scope of the embodiments of the present application.

Claims

1. A calibration method of a sphygmomanometric signal, characterized in that, The method comprises: obtaining a calibration signal and a biological signal, the calibration signal comprising an oscillation wave signal collected from an ear of a living body under a state of applying pressure to the ear, and the biological signal comprising at least one of a pulse wave signal and an electrocardiogram signal; processing the biological signal to obtain a blood pressure parameter used for estimating blood pressure; obtaining a blood pressure map signal according to the calibration signal and the blood pressure parameter, the blood pressure map signal comprising at least one of a systolic pressure and a diastolic pressure; the blood pressure parameter comprises a pulse wave transit time and a pulse arrival time; the method of obtaining the blood pressure map signal according to the calibration signal and the blood pressure parameter comprises: extracting a to-be-calibrated systolic pressure, a to-be-calibrated pulse wave transit time, a to-be-calibrated pulse arrival time, and a to-be-calibrated pulse pressure from the calibration signal; obtaining the systolic pressure based on a first physiological mathematical model; the first physiological mathematical model comprises the following formula: The is the systolic blood pressure to be calibrated, the is the pulse wave transit time to be calibrated, the is the pulse arrival time to be calibrated, the is the pulse wave transit time, the is the pulse arrival time, the γ is a blood vessel information parameter, and the SBP is the systolic blood pressure. obtaining the diastolic pressure based on a second physiological mathematical model; the second physiological mathematical model comprises the following formula: for said to be calibrated pulse pressure, said DBP is said diastolic pressure. for said to be calibrated pulse pressure, said DBP is said diastolic pressure.

2. The calibration method of a sphygmomanometric signal according to claim 1, characterized in that, the blood pressure parameter comprises a pulse wave transit time; the method of obtaining the blood pressure map signal according to the calibration signal and the blood pressure parameter comprises: extracting a to-be-calibrated diastolic pressure, a to-be-calibrated systolic pressure, a to-be-calibrated pulse wave transit time, a to-be-calibrated pulse pressure, and a to-be-calibrated mean blood pressure from the calibration signal; inputting the to-be-calibrated mean blood pressure, the to-be-calibrated pulse wave transit time, the to-be-calibrated pulse pressure, and the blood pressure parameter into a third physiological mathematical model to obtain the diastolic pressure output by the third physiological mathematical model; inputting the diastolic pressure, the to-be-calibrated pulse pressure, the to-be-calibrated pulse wave transit time, and the pulse wave transit time into a fourth physiological mathematical model to obtain the systolic pressure output by the fourth physiological mathematical model.

3. The calibration method of a sphygmomanometric signal according to claim 1, characterized in that, the blood pressure parameter comprises a predicted systolic pressure and a predicted diastolic pressure; the method of processing the biological signal to obtain a blood pressure parameter used for estimating blood pressure comprises: inputting the biological signal into a pre-trained deep learning model to obtain a blood pressure parameter output by the deep learning model, the deep learning model being trained with biological signals of living body samples as samples and blood pressure parameters of the living body samples as labels; the method of obtaining the blood pressure map signal according to the calibration signal and the blood pressure parameter comprises: obtaining a to-be-calibrated diastolic pressure and a to-be-calibrated systolic pressure from the calibration signal; comparing the predicted systolic pressure and the to-be-calibrated systolic pressure at the same time, and obtaining the systolic pressure based on an error calculation model; comparing the predicted diastolic pressure and the to-be-calibrated diastolic pressure at the same time, and obtaining the diastolic pressure based on the error calculation model.

4. A calibration method of a sphygmomanometric signal according to any one of claims 1 to 3, characterized in that, the calibration signal further comprises a temperature signal and an acceleration signal collected from the ear, and the method of obtaining the blood pressure map signal according to the calibration signal and the blood pressure parameter further comprises: determining that a temperature difference between a first time and a second time in the temperature signal reaches a first threshold, or determining that an acceleration difference between the first time and the second time in the acceleration signal reaches a second threshold.

5. The calibration method of a sphygmomanometric signal according to claim 4, characterized in that, If the temperature difference does not reach the first threshold and the acceleration difference does not reach the second threshold, the processing of the biological signal to obtain a blood pressure parameter for estimating blood pressure further comprises: obtaining a blood pressure map signal according to the blood pressure parameter.

6. A calibration device for a sphygmomanometric signal, characterized by Comprise: a signal obtaining module, configured to obtain a calibration signal and a biological signal, the calibration signal comprising an oscillation wave signal collected from an ear of a living body under a state of applying pressure to the ear, and the biological signal comprising at least one of a pulse wave signal and an electrocardiogram signal; a first processing module, configured to process the biological signal to obtain a blood pressure parameter for estimating blood pressure; a second processing module, configured to obtain a blood pressure map signal according to the calibration signal and the blood pressure parameter, the blood pressure map signal comprising at least one of a systolic pressure and a diastolic pressure; the blood pressure parameter comprises a pulse wave transit time and a pulse arrival time; the obtaining of the blood pressure map signal according to the calibration signal and the blood pressure parameter comprises: extracting a to-be-calibrated systolic pressure, a to-be-calibrated pulse wave transit time, a to-be-calibrated pulse arrival time, and a to-be-calibrated pulse pressure from the calibration signal; obtaining the systolic pressure based on a first physiological mathematical model; the first physiological mathematical model comprises the following formula: The is the systolic blood pressure to be calibrated, the is the pulse wave transit time to be calibrated, the is the pulse arrival time to be calibrated, the is the pulse wave transit time, the is the pulse arrival time, the γ is a blood vessel information parameter, and the SBP is the systolic blood pressure. obtaining the diastolic pressure based on a second physiological mathematical model; the second physiological mathematical model comprises the following formula: The For the pulse pressure to be calibrated, the DBP is the diastolic pressure.

7. A calibration device for a sphygmomanometric signal, characterized by Comprise: a pressure adjusting assembly arranged at the ear, configured to apply pressure to the ear to obtain an oscillation wave signal; a measuring assembly, configured to collect a biological signal of an eye of the living body; and The calibration device of the blood pressure map signal according to claim 6. The processor executes the computer program to implement the steps of the blood pressure map signal calibration method according to any one of claims 1-5.

8. An electronic device comprising a memory, a processor, and a computer program stored on the memory, wherein the computer program, when executed by the processor, is arranged to perform the method of any one of claims 1 to 7. ​

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