Blood pressure measurement methods, devices, data processing equipment, and head-mounted devices

Abstract

This application discloses a blood pressure measurement method, device, data processing equipment, and head-mounted device, belonging to the field of wearable device technology. The method includes: acquiring a target pressure signal; selecting at least one channel's pressure pulse wave signal as the target pulse wave signal from multiple channels; acquiring the wearer's composite physiological parameters; and calculating the wearer's blood pressure data based on the target pulse wave signal and the wearer's composite physiological parameters. In this scheme, the head-mounted device can calculate the wearer's blood pressure data based on the pressure pulse wave signal from at least one channel acquired by the pressure sensor and the composite physiological parameters, thereby enabling more accurate acquisition of the user's blood pressure data based on the head-mounted device.

Description

Technical Field

[0001] This application relates to the field of wearable device technology, and in particular to a blood pressure measurement method, device, data processing equipment, and head-mounted device. Background Technology

[0002] Existing non-invasive blood pressure monitors include cuff-type and wristwatch-type models, which typically rely on air pumps or motors to mechanically pressurize the blood pressure to obtain pressure change signals. However, these blood pressure monitors can cause discomfort during the pressurization process, are not suitable for continuous monitoring, and their size and noise limit their application in portable and wearable scenarios.

[0003] While ring-type and watch-type blood pressure monitors have become more portable in recent years, their measurement principle still relies on micro-bladders or piezoelectric structures to pressurize and detect changes in the pulse wave, which is essentially still a mechanical pressurization method. In addition, blood vessels in the hand and wrist area are easily affected by posture and motion artifacts, resulting in poor signal stability and limited measurement accuracy. Therefore, there is an urgent need for a wearable device that can accurately collect blood pressure. Summary of the Invention

[0004] Therefore, it is necessary to provide a blood pressure measurement method, device, data processing equipment, and head-mounted device to address the above problems, which can accurately collect the wearer's blood pressure data based on the head-mounted device.

[0005] This application provides a blood pressure measurement method applied to a head-mounted device. The head-mounted device includes a pressure sensor array for acquiring pressure values ​​at the superficial temporal artery of the head from multiple locations. The method includes: Acquire a target pressure signal; the target pressure signal includes pressure pulse wave signals from multiple channels collected by the pressure sensor array from the wearer. From the pressure pulse wave signals of the multiple channels, at least one channel's pressure pulse wave signal is selected as the target pulse wave signal; The composite physiological parameters of the wearer are obtained; the composite physiological parameters are obtained by calibration based on an external reference blood pressure value and pressure pulse wave signals from at least two channels; Based on the target pulse wave signal and the wearer's composite physiological parameters, the wearer's blood pressure data is calculated.

[0006] In another aspect, a blood pressure measuring device is provided, the device being disposed in a head-mounted device, the head-mounted device having a pressure sensor array for acquiring pressure values ​​at the superficial temporal artery of the head from multiple locations, the device comprising: A signal acquisition module is used to acquire a target pressure signal; the target pressure signal includes pressure pulse wave signals from multiple channels collected by the pressure sensor array from the wearer. The signal selection module is used to select at least one channel's pressure pulse wave signal as the target pulse wave signal from the multiple channels of pressure pulse wave signals. The parameter acquisition module is used to acquire the composite physiological parameters of the wearer; the composite physiological parameters are obtained by calibration based on an external reference blood pressure value and pressure pulse wave signals from at least two channels. The blood pressure calculation module is used to calculate the blood pressure data of the wearer based on the target pulse wave signal and the composite physiological parameters of the wearer.

[0007] In another aspect, a data processing device is provided, which includes a processor and a memory; the memory stores computer instructions; and the processor executes the computer instructions to perform the aforementioned blood pressure measurement method.

[0008] In another aspect, a head-mounted device is provided, wherein a pressure sensor array is provided, the pressure sensor array being used to acquire pressure values ​​at the superficial temporal artery of the head from multiple locations; The head-mounted device is also equipped with a data processing device to perform the blood pressure measurement method described above.

[0009] Compared with the prior art, the technical solution provided in this application has the following advantages: When a user wears the head-mounted device, the pressure sensor array within the device collects pressure values ​​from the superficial temporal artery at multiple locations, generating multi-channel pressure pulse wave signals. At least one channel of these signals is then selected as the target pulse wave signal. The head-mounted device then acquires the user's composite physiological parameters and calculates their blood pressure based on the target pulse wave signal and these parameters. This approach, by deploying a pressure sensor array at the superficial temporal artery to collect multi-channel pressure wave signals, allows users to quickly calibrate their composite physiological parameters using an external reference blood pressure value and multiple channel pressure pulse wave signals. During subsequent wear, the head-mounted device calculates the user's blood pressure data based on the pressure pulse wave signal from at least one channel collected by the pressure sensors and the composite physiological parameters, thus enabling relatively accurate blood pressure data collection. Attached Figure Description

[0010] Figure 1 A flowchart of a blood pressure measurement method according to an embodiment of this application is shown.

[0011] Figure 2 A schematic flowchart of a blood pressure measurement method according to an embodiment of this application is shown.

[0012] Figure 3 The diagram illustrates the relationship between the amplitude of blood pressure at three adjacent points on an artery and the blood pressure on a coordinate system.

[0013] Figure 4 A logical diagram illustrating a blood pressure measurement and parameter update according to an embodiment of this application is shown.

[0014] Figure 5 This is a diagram showing the results of array pressure pulse wave signal acquisition in an embodiment of this application.

[0015] Figure 6 This is a diagram showing the channel filtering results involved in the embodiments of this application.

[0016] Figure 7 It is a comparison chart of estimated blood pressure and reference blood pressure.

[0017] Figure 8 This is a graph showing the difference in average systolic blood pressure.

[0018] Figure 9 This is a graph showing the difference in mean diastolic blood pressure.

[0019] Figure 10 This is a schematic diagram of the structure of a blood pressure measuring device provided in an embodiment of this application.

[0020] Figure 11 A schematic diagram of the sensing unit of the pressure sensor array involved in this application embodiment is shown.

[0021] Figure 12 A schematic diagram of a circuit module according to an embodiment of this application is shown. Detailed Implementation

[0022] To make the above-mentioned objectives, features, and advantages of this application more apparent and understandable, the specific embodiments of this application are described in detail below with reference to the accompanying drawings. Many specific details are set forth in the following description to provide a thorough understanding of this application. However, this application can be implemented in many other ways different from those described herein, and those skilled in the art can make similar modifications without departing from the spirit of this application. Therefore, this application is not limited to the specific embodiments disclosed below.

[0023] First, a unified definition is provided for all terms and abbreviations used in the embodiments of this application: ALA (Arterial Lumen Area): Area of ​​the arterial lumen; CDC (cuff deflation curve): Cuff deflation pressure; CP (cuff pressure): Cuff static pressure; OMW (oscillometric waveform): Pressure pulse wave; where OMW = CDC - CP; Pa(t) (arterial pressure): arterial pressure; Pc(t) (Cuff pressure): Cuff pressure; Pt(t) (transmural pressure): transmural pressure, where Pt(t) = Pa(t) - Pc(t); SBP: Systolic blood pressure, i.e., continuous arterial pressure Pa(t) curve (e.g.) Figure 3 Arterial pressure at the peak of the wave; DBP: Diastolic blood pressure, i.e., continuous arterial pressure Pa(t) curve (e.g.) Figure 3 Arterial pressure at the trough; SSBP (suprasystolic BP): Supersystolic blood pressure, indicating blood pressure higher than systolic blood pressure; SDBP (subdiastolic BP): Low diastolic blood pressure, indicating blood pressure below diastolic level; Simulated OMW: OMWsim is a mathematical model of the pulse wave derived from the ALA model; Actual pulse wave: OMWact, which is the pulse wave waveform obtained from actual experiments.

[0024] Non-invasive blood pressure monitors, including cuff and wristwatch types, typically rely on an air pump or motor to mechanically pressurize the blood pressure to obtain a signal of pressure change. While these devices avoid the risk of incisions, the pressurization process can be uncomfortable, making them unsuitable for uninterrupted, continuous monitoring. Furthermore, their size and noise limit their application in portable and wearable scenarios.

[0025] While ring-type and watch-type blood pressure monitors have become more portable in recent years, their measurement principle still relies on miniature air bladders or piezoelectric structures to pressurize and detect changes in the pulse wave, which is essentially still a mechanical pressurization method. In addition, blood vessels in the hand and wrist area are easily affected by posture and motion artifacts, resulting in poor signal stability and limited measurement accuracy.

[0026] To reduce the impact of posture and motion artifacts on measurements, spectacle-type blood pressure monitoring devices, such as the Glabella glasses-type blood pressure monitoring device, attempt to estimate blood pressure using signals from head vessels. This requires placing three optical PPG sensors on the bridge and temples of the glasses, combined with a 3-axis accelerometer, to collect pulse reflection signals from the superficial temporal artery, angular artery, and posterior auricular artery, as well as head motion signals. However, using optical PPG sensors for blood pressure acquisition lacks a clear hemodynamic basis, resulting in poor accuracy. This method not only suffers from complex system structure, hindering lightweight wear and commercialization, but also has the following significant drawbacks: 1. It can only fit the trend of systolic blood pressure; 2. Measuring only optical reflection signals instead of direct vascular pressure waveforms lacks a clear hemodynamic basis; 3. Data processing relies on multi-channel phase stability and is extremely sensitive to motion artifacts; 4. The multi-sensor synchronization structure is complex, has high wearability, and the signal quality is significantly affected by position.

[0027] 5. The sensor is difficult to place precisely above the blood vessel.

[0028] Therefore, in order to solve the above problems, this application provides a method for measuring blood pressure. Figure 1 A flowchart of a blood pressure measurement method according to an embodiment of this application is shown. The method is applied to a head-mounted device, which includes a pressure sensor array. For ease of understanding, smart glasses are used as an example of the head-mounted device in subsequent embodiments. The head-mounted device can also be a virtual reality or augmented reality headset, etc. In the smart glasses, a pressure sensor array can be installed on the frame to collect pressure values ​​at the superficial temporal artery of the head from multiple locations, such as... Figure 1 As shown, the method includes: Step 101: Obtain the target pressure signal.

[0029] The target pressure signal includes pressure pulse wave signals from multiple channels collected by the pressure sensor array from the wearer. Specifically, in this embodiment, the sensor array includes M rows and N columns of sensor units; wherein, the M rows and N columns of sensor units are arranged in a rectangular pattern; the M rows and N columns of sensor units are respectively used to collect pressure pulse wave signals from M*N channels at the superficial temporal artery of the head.

[0030] In this embodiment, the pressure sensor array can be located on the inside of the temple of the smart glasses or near the user's temple, so that the pressure sensor array can form stable contact with the user's scalp when the user wears the smart glasses.

[0031] Since the superficial temporal artery is located on the surface of the skin and has obvious blood flow signals, by placing multiple pressure sensors near the direction of the superficial temporal artery, the pulse pressure changes of the superficial temporal artery can be collected synchronously from multiple spatial locations, thereby obtaining pressure pulse wave signals at M*N spatial locations (i.e., pressure pulse wave signals as M*N channels).

[0032] Specifically, when a user wears smart glasses, each pressure sensor in the pressure sensor array can sense the periodic pressure changes in the superficial temporal artery driven by the heartbeat and convert these pressure changes into corresponding electrical signals. Subsequently, the data acquisition circuit inside the smart glasses samples and performs analog-to-digital conversion on these electrical signals to generate corresponding digital signals. Since the pressure sensor array includes multiple pressure sensors distributed at different locations, each pressure sensor can generate a corresponding pressure pulse wave signal, thus forming pressure pulse wave signals at M*N spatial locations.

[0033] In some embodiments, the smart glasses can also preprocess the collected pressure pulse wave signals from M*N spatial locations, such as filtering the signals of each channel to remove influencing factors such as environmental noise, muscle movement interference, and baseline drift, thereby improving the stability of subsequent pulse wave analysis. After preprocessing, the obtained pressure pulse wave signals from M*N spatial locations are used as the target pressure signal.

[0034] Step 102: Select at least one channel of pressure pulse wave signal as the target pulse wave signal from multiple channels of pressure pulse wave signal.

[0035] Because the relative positions of the various sensors in the pressure sensor array to the superficial temporal artery differ, the pressure pulse wave signals acquired by different channels may vary in signal amplitude, signal-to-noise ratio, and waveform integrity. Therefore, in this embodiment, at least one channel with higher signal quality needs to be selected from the pressure pulse wave signals of multiple channels as the target pulse wave signal for subsequent blood pressure calculation.

[0036] Specifically, the smart glasses can analyze the pressure pulse wave signals of each channel within a preset time window, calculating characteristic parameters of each channel's pulse wave signal, such as pulse wave amplitude, signal-to-noise ratio, main wave energy, or waveform stability. Based on these characteristic parameters, the quality of the multi-channel pulse wave signals can be evaluated, and at least one channel that meets preset conditions can be selected as the target pulse wave signal. For example, channels with larger pulse wave amplitude and higher signal-to-noise ratio can be preferentially selected to ensure that the selected target pulse wave signal can accurately reflect the blood pressure changes in the superficial temporal artery.

[0037] By using the above methods, signal distortion caused by poor local contact, skin slippage, or sensor position misalignment can be effectively avoided, thereby improving the accuracy of subsequent blood pressure calculations.

[0038] Step 103: Obtain the composite physiological parameters of the wearer.

[0039] The composite physiological parameters are obtained by calibration based on external reference blood pressure values ​​and pressure pulse wave signals at the M*N spatial locations.

[0040] In this embodiment, due to individual differences in vascular elasticity, vascular diameter, and tissue structure among different users, it is difficult to directly and accurately estimate blood pressure values ​​solely based on pressure pulse wave signals. Therefore, before calculating blood pressure, it is necessary to obtain the composite physiological parameters corresponding to the wearer through a calibration process to establish a user-specific blood pressure estimation model.

[0041] Specifically, when using smart glasses for blood pressure monitoring for the first time, users can obtain reference blood pressure values ​​through standard blood pressure measurement devices (such as electronic blood pressure monitors or medical blood pressure meters). These reference blood pressure values ​​may include parameters such as systolic blood pressure, diastolic blood pressure, and mean arterial pressure. Simultaneously, the smart glasses use a pressure sensor array to synchronously collect pressure pulse wave signals from the user at M*N spatial locations within the same time period.

[0042] Subsequently, the smart glasses can calibrate relevant parameters reflecting vascular characteristics based on the reference blood pressure value and the corresponding target pulse wave signal to obtain the wearer's composite physiological parameters. These composite physiological parameters can be used to characterize the user's vascular compliance, vascular cross-sectional area change characteristics, and the mapping relationship between sensor signals and actual blood pressure. Through this calibration process, an individualized blood pressure estimation model suitable for the user can be established, thereby improving the accuracy of subsequent blood pressure measurements.

[0043] In subsequent use, composite physiological parameters can be stored in smart glasses or connected terminal devices and retrieved during blood pressure calculation.

[0044] Step 104: Calculate the blood pressure data of the wearer based on the target pulse wave signal and the composite physiological parameters of the wearer.

[0045] After obtaining the target pulse wave signal and the wearer's composite physiological parameters, the smart glasses can estimate the user's blood pressure based on a blood pressure estimation model.

[0046] Specifically, smart glasses can first extract pulse wave features related to blood pressure changes from the target pulse wave signal, such as pulse wave peak value, pulse wave trough value, and peak-trough difference. Then, combining these composite physiological parameters, the pulse wave features are substituted into a preset blood pressure estimation model for calculation, thereby obtaining blood pressure data corresponding to the current pulse wave signal. Blood pressure data may include parameters such as systolic blood pressure, diastolic blood pressure, and mean arterial pressure (or mean arterial pressure).

[0047] In this embodiment, an arterial lumen area model can be established as the aforementioned blood pressure estimation model. By comparing the differences between theoretical pulse wave characteristics and actual collected pulse wave characteristics, and optimizing the blood pressure parameters, a blood pressure value that best matches the current pulse wave signal can be obtained. The specific principle of this arterial lumen area model can be found in [reference needed]. Figure 2 The illustrated embodiment.

[0048] Using the above method, blood pressure can be estimated solely based on the pressure pulse wave signal at the superficial temporal artery without the need for mechanical pressurization, thereby enabling continuous monitoring of the user's blood pressure.

[0049] Furthermore, the calculated blood pressure data can be displayed through the display module of the smart glasses or a connected mobile terminal, or stored in the system for subsequent health analysis or trend monitoring.

[0050] In summary, when a user wears the head-mounted device, the pressure sensor array within the device can collect pressure values ​​from the superficial temporal artery at multiple locations, generating multi-channel pressure pulse wave signals. Then, at least one channel of the pressure pulse wave signal is selected as the target pulse wave signal. The head-mounted device then acquires the user's composite physiological parameters and calculates the user's blood pressure data based on the target pulse wave signal and composite physiological parameters. This solution, by deploying a pressure sensor array at the superficial temporal artery to collect multi-channel pressure wave signals, allows the user to quickly calibrate their composite physiological parameters based on an external reference blood pressure value and multiple channel pressure pulse wave signals. During subsequent wear, the head-mounted device can calculate the user's blood pressure data based on the pressure pulse wave signal from at least one channel collected by the pressure sensors and the composite physiological parameters, thus enabling relatively accurate blood pressure data collection.

[0051] Based on the above embodiments, in order to further explain the underlying principle of the technical solution shown in this application, the mathematical relationship between blood pressure data, pulse wave signal and composite physiological parameters involved in the embodiments of this application will be introduced below: In the embodiments of the present application, the smart glasses collect the pressure value at the superficial temporal artery through a pressure sensor. To estimate the blood pressure of a wearing user based on the pressure value at the superficial temporal artery, it is necessary in the embodiments of the present application to construct a relationship between the change in arterial cross-sectional area (i.e., pulse) and vascular blood pressure.

[0052] In the embodiments of the present application, an ALA (Arterial Lumen Area) model is constructed, that is, a blood pressure estimation model based on the variation relationship of the arterial lumen area with the transmural pressure Pt(t). The core of this model is to connect blood pressure with the dynamic change of arterial cross-sectional area, establish a mathematical relationship between theoretical prediction and actual pulse waveform, allow continuous pressure application within a low pressure range and compare simulated waveforms with actually measured waveforms, thereby estimating key blood pressure parameters such as systolic blood pressure (SBP), diastolic blood pressure (DBP) and mean arterial pressure (MAP). The introduction of the ALA model provides an interpretable theoretical basis for cuff-less continuous blood pressure monitoring, that is, it improves the estimation stability and credibility based on physiological and mechanical principles.

[0053] Specifically, the ALA model adopts a piecewise exponential form to describe the deformation characteristics of blood vessels under different transmural pressures, including two parts: the compressed state of blood vessels (systole) and the dilated state of blood vessels (diastole), which are respectively represented as follows: (1) (2) Wherein, is the arterial lumen area; is the arterial lumen area when = 0, is the transmural pressure; is the arterial lumen area when the arterial lumen is fully dilated ( ); represents the average value of ALA when the arterial lumen area is 0. When the arterial lumen area at the center of the cuff is 0, the average arterial lumen area within the entire width of the cuff is still a small non-zero value , which is used to correct modeling errors caused by "uneven cuff pressure".

[0054] Since the arterial stiffness index needs to be considered separately in the systolic pressure phase (i.e. > ) and the diastolic pressure phase ( < ), a and c are set as the vascular compliance parameters (equivalent characterization indicators of arterial stiffness index) for systole and diastole respectively. The smart glasses involved in the embodiments of the present application only work under the low external pressure condition of <DBP, at this time Since the value is ≥0, the subsequent derivation only uses the diastolic segment model.

[0055] To further solve the above model, the embodiments of this application make the following mathematical assumptions based on actual physiological conditions: Hypothesis 1: Since the tissue surrounding the artery is instantaneously incompressible, the periodic changes in the arterial lumen volume are transmitted through the tissue to the skin interface, causing periodic fluctuations in skin surface pressure and resulting in deformation. Sensors placed on the skin surface collect this pressure change signal, which is ultimately presented as a pressure pulse wave. Therefore, it can be considered that the measured pressure pulse wave (i.e., OMW) is positively correlated with the change in arterial lumen area.

[0056] Assumption 2: Due to external pressure (such as cuff pressure) The change in arterial pressure within a heartbeat cycle is much smaller than the change in arterial pressure, therefore within a heartbeat cycle It can be assumed to be constant (the contact pressure of the sensor changes even less, almost unchanged, so it can be considered more constant), and the peak value of the pulse wave OMW corresponds to the arterial pressure. = Systolic blood pressure (SBP), arterial pressure corresponding to the trough of OMW =Diastolic blood pressure (DBP).

[0057] Based on the two assumptions above, the embodiments of this application can decompose ALA, ALA (that is... It consists of two main components: the slow-changing component caused by the deflation of the cuff. and the oscillation component of arterial lumen area caused by arterial pressure pulsation The slow-varying component should only reflect slow changes in cuff pressure; therefore, we need to eliminate the amount of arterial pressure pulsation. That is, the arterial pressure in equation (1) Replacing it with the average arterial pressure (MAP), we obtain the following formula: (3) (4) in, It is the oscillation component of the arterial lumen area. = - .

[0058] Based on the oscillatory component of the arterial lumen area during diastole in ALA Based on the relationship between OMW and the oscillating components obtained from Assumption 1, the theoretical pulse wave (i.e., the simulated pulse wave OMWsim) is as follows: (5) Since the sensor detects pressure on the skin surface, rather than direct ALA (alpha pressure), a proportionality coefficient φ is defined, which is related to skin thickness and fit. If it is assumed that the tissue state remains unchanged during the same wear, then φ is a constant.

[0059] For formula (5), when the left side equals the peak value (Peaks), the right side... When the left side equals the systolic blood pressure (SBP), and the right side equals the trough value (Troughs),... Equal to diastolic pressure DBP, therefore, by replacing Pa(t) on the right side of formula (5) with SBP and DBP, we can obtain the peak values, trough values, and peak-trough difference PP of OMWsim, which are respectively related to cuff pressure. The relationship between (t): (6) (7) (8) Based on the above theoretically derived relationship between simulated pulse waves and blood pressure data Figure 2 A flowchart illustrating a blood pressure measurement method according to an embodiment of this application is shown, as follows: Figure 2 As shown, the method flow includes: Step 201: Obtain the target pressure signal.

[0060] Optionally, in this embodiment of the application, in order for the smart glasses to accurately convert the voltage signal generated by the pressure sensor array into the actual pressure value, it is necessary to calibrate the pressure sensor of the smart glasses (for example, during the production stage). The pressure sensor array is pressurized according to a standard pressure device, and the calibration pressure parameters corresponding to the calibrated pressure sensor are obtained.

[0061] During the wearing process, the smart glasses can first acquire the various voltage signals generated by the pressure sensor array; then, according to the pressure calibration parameters corresponding to the pressure sensor array, convert the various voltage signals into target pressure signals.

[0062] To convert electrical signals into physically meaningful pressure signals, pressure calibration of the sensors is required during system initialization. Specifically, a known pressure is applied using an airbag (a standard pressure device) and a standard pressure sensor is used as a reference to establish the correspondence between the sensor's output voltage and the actual pressure, thus obtaining pressure calibration parameters. Based on these calibration parameters, the voltage signals acquired by each channel can be converted into equivalent external pressure. (Unit: mmHg). After this conversion, each channel in the pressure sensor array receives a pressure pulse wave signal that changes over time, providing input data for subsequent array channel selection and blood pressure calculation.

[0063] Step 202: Based on the pulse wave amplitude in the direction perpendicular to the blood vessel, select at least one channel of pressure pulse wave signal from multiple channels as the target pulse wave signal.

[0064] In this embodiment, the sensor array includes M rows and N columns of sensor units arranged in a rectangular pattern. Each of the M rows and N columns of sensor units is used to collect pressure pulse wave signals from M*N channels at the superficial temporal artery in the head. Therefore, within the same time window, according to the magnitude of the pulse wave amplitude, candidate channels of pressure pulse wave signals can be selected from the N channels of pressure pulse wave signals collected by each row of sensor units to determine M candidate channels. Then, based on the main wave energy of the pressure pulse wave signals from the M candidate channels, the signal-to-noise ratio of the pressure pulse wave signals from the M candidate channels, and the pulse wave amplitude of the adjacent channels of the M candidate channels, at least one channel of pressure pulse wave signal is selected as the target pulse wave signal from the pressure pulse wave signals of the M candidate channels.

[0065] The above steps essentially involve performing feature calculations on the pressure pulse wave signals of each channel of the array within the same time window to obtain the pulse wave amplitude of each channel. Since the pulse wave amplitude near the superficial temporal artery is typically large, meaning the peak region in the normal amplitude distribution of the vessel usually corresponds to the location of the vessel, the above scheme compares the pressure pulse wave signals collected by each row of sensor units in the sensor array. From the N channels of pressure pulse wave signals collected by each row of sensors, the channel with the largest pulse wave amplitude is selected as the candidate channel, thus obtaining M candidate channels. The sensor locations corresponding to these M candidate channels can then characterize the location of the superficial temporal artery.

[0066] Then, in this embodiment of the application, the signal-to-noise ratio, signal strength, and amplitude distribution of the signals collected by the M candidate channels themselves are used to make a judgment, thereby selecting the pressure pulse wave signal of the channel that best represents the characteristics of the superficial temporal artery from the M candidate channels as the target pulse wave signal.

[0067] For example, the signal-to-noise ratio, signal strength, and amplitude distribution of neighboring channels can be compared with the corresponding thresholds to select the target pulse wave signal from M candidate channels that meets the thresholds for signal-to-noise ratio, signal strength, and amplitude distribution of neighboring channels. Alternatively, the M candidate channels can be scored according to the order of signal-to-noise ratio, signal strength, and amplitude distribution of neighboring channels, and the pressure pulse wave signals with the highest scores can be selected as the target pulse wave signal.

[0068] Step 203: Obtain the composite physiological parameters of the wearer.

[0069] The composite physiological parameters are obtained by calibration based on external reference blood pressure values ​​and pressure pulse wave signals from the multiple channels.

[0070] Before explaining the specific principles of calibration, let's first clarify the principles involved in composite physiological parameters: After obtaining the above formulas (6), (7), and (8), we can take the logarithm of the above three formulas to obtain the following formula: (9) (10) (11) Where c is the vascular compliance parameter and φ is the skin tissue parameter. yes Arterial lumen area when =0, It is the area of ​​the arterial lumen when the arterial lumen is fully dilated.

[0071] Then, in the above formulas (9)-(11) Differentiation yields: (12) (13) (14) The above mathematical derivation reveals that c represents the slopes of Peaks, Troughs, and PP. Therefore, Peaks and Troughs can be directly extracted from the collected pulse wave data, and the logarithm of the values ​​can be used to calculate the slopes. Calculate the vascular compliance parameter c by taking the derivative.

[0072] Suppose that there are three points A, B, and C on the artery that are close to each other. Due to the influence of skin tissue, the skin tissue parameter φ is different at each point. Substituting φ into formula (11), the relationship between the amplitudes PP of the three points is as follows: (15) Will Move to the left to get: (16) Figure 3 The diagram illustrates the relationship between the amplitude of blood pressure at three adjacent points on an artery and the blood pressure on a coordinate system.

[0073] Once the skin tissue parameter φ is calibrated, the influence of skin tissue characteristics at different measurement locations on the signal amplitude can be eliminated, allowing different measurement points in the array (e.g., A, B, C, etc.) to be equivalent to the same location under different external pressures in the model calculation. Measurement results under the given conditions. Because the pressure sensor array is in contact with the skin at the same time, but the tissue transmission path and contact state differ at each measurement point, the equivalent external pressure corresponding to each measurement point varies. The differences exist, therefore it can be equivalent to applying different external pressures at different times (t1, t2, t3) at the same location. The measurement process. Based on this, this application achieves the measurement of different equivalent external pressures by synchronously sampling at multiple points in space using a pressure sensor array. The conditions are obtained simultaneously, thus replacing the traditional mechanical pressurization process with a "space-for-time" approach.

[0074] Under actual measurement conditions, and Both are related to individual vascular structure and blood pressure status, making independent measurement under non-invasive conditions difficult. Furthermore, during model derivation, φ and ( The two terms appear only together in the form of a product, and therefore cannot be independently identified mathematically. Therefore, in this application, ( φ is considered as a global constant parameter (i.e., the aforementioned composite physiological parameter), which can be obtained through a single external blood pressure calibration. Because... and The combined parameter exhibits minimal variation during short-term blood pressure measurements and effectively characterizes the overall response of the tissue-vascular-sensor system, thus not affecting subsequent blood pressure calculations.

[0075] In one optional implementation, the composite physiological parameters can be calibrated using the following steps: calculating vascular compliance parameters based on pressure pulse wave signals from at least two channels of the user; acquiring standard blood pressure data; the standard blood pressure data being collected by the user using a standard blood pressure monitor; the standard blood pressure data including the user's systolic blood pressure, diastolic blood pressure, and mean blood pressure; and calibrating the user's composite physiological parameters based on the standard blood pressure data, the vascular compliance parameters, and pressure pulse wave signals from at least two channels.

[0076] In simple terms, extract the peaks, troughs, and static pressure of at least two channels of the pressure pulse wave signal. The blood pressure of the human body at this time is measured using a commercial blood pressure monitor, including systolic pressure SBP, diastolic pressure DBP and mean pressure MAP. The vascular compliance parameter c is obtained by formula (12)-(14). That is, at least one of the peak value, trough value and peak-trough difference PP of the pressure pulse wave signal of at least two channels is selected as the target parameter. Then the logarithm of the target parameter is taken and the slope of its logarithm and static pressure is calculated as the vascular compliance parameter c.

[0077] After obtaining the vascular compliance parameter c, the following parameters are used: c, blood pressure data measured by a standard blood pressure monitor (systolic blood pressure SBP, diastolic blood pressure DBP, and mean systolic blood pressure MAP), and waveform parameters (peaks, troughs, and static pressure) collected from multiple points using a pressure sensor array. Substituting into formula (15) will yield the differences at the points. This allows for the calibration of the wearer's composite physiological parameters.

[0078] Step 204: Calculate the blood pressure data of the wearer based on the target pulse wave signal and the wearer's composite physiological parameters.

[0079] Furthermore, in the embodiments of this application, the target pulse wave signal includes the target pulse wave peak value, the target pulse wave trough value, and the target pulse wave peak-trough difference value; the blood pressure data includes systolic pressure, diastolic pressure, and mean pressure; the mean pressure is calculated based on the systolic pressure and diastolic pressure.

[0080] At this point, based on the target pulse wave signal and the composite physiological parameters of the user wearing the device, the user's blood pressure data is calculated, including: The blood pressure data of the wearer is optimized to minimize the function value of the objective function; the objective function is the sum of pulse wave peak error, pulse wave trough error, and pulse wave peak-trough difference error. The pulse wave peak value error is used to characterize the difference between the target pulse wave peak value and the theoretical pulse wave peak value; the theoretical pulse wave peak value is calculated based on the composite physiological parameters and the systolic blood pressure and mean blood pressure to be optimized. The pulse trough error is used to characterize the difference between the target pulse trough value and the theoretical pulse trough value; the theoretical pulse trough value is calculated based on the composite physiological parameters and the diastolic blood pressure and mean blood pressure to be optimized. The pulse wave peak-valley difference error is used to characterize the difference between the target pulse wave peak-valley difference and the theoretical pulse wave peak-valley difference.

[0081] In simple terms, the theoretical peak and trough values ​​of the pulse wave can be obtained using the following formula: (17) (18) in, This represents the theoretical peak value of the pulse wave. This is the theoretical trough value of the pulse wave; These are composite physiological parameters; This is the scaling factor corresponding to the i-th channel, which is also the skin tissue parameter φ corresponding to the i-th channel; This represents the area of ​​the arterial lumen when the transmural pressure is 0. This represents the area of ​​the arterial lumen when the transmural pressure is infinite. 1 represents vascular compliance parameters; MAP is the mean pressure calculated from systolic and diastolic blood pressure; SBP is the systolic blood pressure to be optimized; DBP is the diastolic blood pressure to be optimized. Let be the static pressure value of the sensor corresponding to the i-th channel.

[0082] in:

[0083] The target pulse wave peak value measured and screened by the pressure sensor array is The target pulse wave trough value measured and screened by the pressure sensor array is The peak-to-valley difference of the target pulse wave measured and screened by the pressure sensor array is... .

[0084] At this time, the peak value error of the pulse wave Pulse trough error and pulse wave peak-to-trough difference error They respectively satisfy the following formulas: (19) (20) (twenty one) By minimizing the objective function The goal of minimizing the difference between the model-derived results and the actual measured results is to minimize the difference between the two. Minimization essentially involves solving equations, but due to measurement noise and interference in actual pulse wave signals, direct analytical solutions are extremely sensitive to noise, leading to unstable results. Optimization methods can improve stability and accuracy by constructing an objective function and searching for a physiologically reasonable optimal solution within the feasible region. Therefore, optimization algorithms can be used to minimize the above objective function to obtain the final SBP and DBP.

[0085] Figure 4 A logical diagram illustrating a blood pressure measurement and parameter update method according to an embodiment of this application is shown. Figure 4 As shown, during the wearing of smart glasses, the pressure sensor array in the smart glasses first detects data in real time. At this time, the signal acquisition and processing module in the smart glasses collects the data from the pressure sensor array and performs preprocessing. Then, the sensor data with the largest amplitude of the vascular normal pulse wave is selected as the judgment basis. Then, the waveform characteristics of the target pulse wave data corresponding to the sensor data are extracted, and the blood pressure data measured by the external blood pressure monitor is obtained. Based on the above data, the calibration of c and φ is realized.

[0086] The smart glasses can then detect data in real time based on the above parameters and the pressure sensor array, and obtain SBP and DBP by optimizing the above objective function.

[0087] After obtaining SBP and DBP during this measurement process, in this embodiment of the application, the composite physiological parameters and vascular compliance parameters of the wearer can be updated based on the wearer's blood pressure data (i.e., SBP and DBP) and the target pulse wave signal.

[0088] After obtaining SBP and DBP by minimizing the objective function using the current c and φ, this application obtains a more accurate blood pressure estimate for the current moment. At this point, the newly estimated SBP and DBP can be regarded as "virtual reference values" (similar to performing a new calibration). Combined with the pulse wave characteristics (peak value, trough value, and static pressure) of at least two channels currently being collected, they are re-substituted into the model (as shown in Equations 12-15) to fit c and φ. Even if there are small errors in the initial calibration, through multiple iterations, the parameters will gradually converge to the true values ​​that better match the current state. Furthermore, with the user's use, it will increasingly match the actual physiological condition of the wearer.

[0089] In one optional implementation, if the number of target pulse wave signals selected during the current measurement is 1, the composite physiological parameters are not updated; if the number of target pulse wave signals is greater than 1 (that is, when the accuracy of the data obtained in the current measurement is high), the composite physiological parameters and vascular compliance parameters of the wearer can be updated using the blood pressure data obtained in the current measurement and the target pulse wave signals.

[0090] In summary, when a user wears the head-mounted device, the pressure sensor array within the device can collect pressure values ​​from the superficial temporal artery at multiple locations, generating multi-channel pressure pulse wave signals. Then, at least one channel of the pressure pulse wave signal is selected as the target pulse wave signal. The head-mounted device then acquires the user's composite physiological parameters and calculates the user's blood pressure data based on the target pulse wave signal and composite physiological parameters. This solution, by deploying a pressure sensor array at the superficial temporal artery to collect multi-channel pressure wave signals, allows the user to quickly calibrate their composite physiological parameters based on an external reference blood pressure value and multiple channel pressure pulse wave signals. During subsequent wear, the head-mounted device can calculate the user's blood pressure data based on the pressure pulse wave signal from at least one channel collected by the pressure sensors and the composite physiological parameters, thus enabling relatively accurate blood pressure data collection.

[0091] Furthermore, the technical solution shown in the embodiments of this application has the following advantages compared to existing endoscopic blood pressure monitoring devices: First, since the scheme shown in the embodiments of this application is based on array pressure pulse wave signals and ALA model for blood pressure inversion, by extracting peak value, trough value, equivalent external pressure Pc and vascular compliance parameter c, a joint solution model for systolic blood pressure SBP and diastolic blood pressure DBP is established to solve SBP and DBP, so SBP and DBP are output simultaneously; secondly, the ALA model has been theoretically derived for systolic and diastolic periods respectively, so the scheme shown in the embodiments of this application can obviously overcome the defect of "only fitting the trend of systolic blood pressure".

[0092] Secondly, since the head-mounted device in this application embodiment explicitly uses a pressure sensor array to directly collect pressure pulse waves on the skin surface, this signal can be regarded as the surface response after the change in arterial lumen area is transmitted through the tissue. It can establish a clear correspondence with transmural pressure, change in arterial lumen area and ALA model. The entire ALA model is constructed based on the mechanical properties of the blood vessel wall. Therefore, the scheme shown in this application embodiment has a solid hemodynamic theoretical foundation, based on the mechanism of vascular compliance and change in arterial lumen area, and no longer relies solely on empirical fitting.

[0093] Third, the scheme shown in this application does not use the precise phase difference across channels as the core measurement basis. Instead, it utilizes the idea of ​​"trading space for time" and uses the amplitude characteristics, peak and valley characteristics, and corresponding equivalent external pressure Pc of the pressure pulse waves collected by each channel at the same time as the main calculation basis. Different channels in the array mainly reflect spatial position differences, rather than having to maintain a strictly stable phase relationship. Therefore, it is less sensitive to slight movements and local contact disturbances.

[0094] Fourth, traditional solutions aim for perfect contact between all sensors and blood vessels to obtain consistent high-quality signals, thus requiring complex sensor structures and resulting in significant variations in fit among different users. In contrast, the embodiments in this application utilize the inherent differences in the contact pressure between each sensor unit in the sensor array and the skin. Sensor units at different locations generate pressure pulse wave data for different channels, eliminating the need to deploy different types of sensors at multiple anatomical locations or rely on complex cross-location synchronous time difference analysis. The array itself can perform multi-point detection within a local area and obtain blood pressure results through channel selection and model calculation. Therefore, the structure is more compact, the signal chain is simpler, and the integration is higher, which is more conducive to lightweight design and engineering implementation.

[0095] Fifth, the embodiments of this application use an array-type sensing structure to cover the area adjacent to the superficial temporal artery, eliminating the need to precisely align a single sensing unit with the center of the blood vessel each time it is worn. The system can compare the amplitude distribution, signal quality, and neighborhood consistency of multiple channels within the same time window, automatically identifying the optimal channel or region as input for subsequent calculations, thereby significantly reducing the dependence on precise wearing. Furthermore, different individuals have differences in blood vessel orientation, depth, and tissue structure; the array structure can adaptively match these individual differences, avoiding customization for different users.

[0096] To verify the feasibility of the above method, the following describes the test process corresponding to the technical solution involved in the embodiments of this application. That is, by arranging an 8×8 array sensor in the superficial temporal artery region, pressure pulse wave signals are collected under constant wearing pressure conditions, and reference blood pressure data is obtained in combination with a continuous blood pressure monitoring device. The signal acquisition capability, channel screening effectiveness and blood pressure calculation performance of the method involved in the embodiments of this application in continuous blood pressure estimation are evaluated.

[0097] The expected results of this test are: the array sensor can stably acquire pressure pulse wave signals with obvious pulse characteristics in the superficial temporal artery region, can select effective channels corresponding to the vascular coverage area from the array signal, can output continuous systolic and diastolic blood pressure results, and maintain a small error with the measurement results of the reference device.

[0098] Specifically, the test subject was one healthy participant. During the test, the participant remained supine, minimizing head movement to reduce the impact of motion interference on the acquisition of the superficial temporal artery pressure pulse wave. The test environment was kept quiet and the room temperature was stable.

[0099] Specifically, the testing system involved in the embodiments of this application includes: The head-mounted device (e.g., smart glasses integrating an 8×8 array pressure sensor) involved in the embodiments of this application is used to collect pressure pulse wave signals in the superficial temporal artery region; the continuous non-invasive blood pressure monitoring device (CNAP) and its matching monitor serve as reference blood pressure acquisition devices; and the host computer data acquisition system is used to synchronously record the smart glasses signal and the CNAP reference signal.

[0100] Before the test, the smart glasses were worn on the subject's head, ensuring stable contact between the array sensor and the superficial temporal artery region. Simultaneously, the CNAP finger sensor was worn on the subject, and the monitor was zeroed. After the CNAP output stable blood pressure data, the data recording programs of both the smart glasses and the monitor were simultaneously initiated for synchronized data acquisition.

[0101] During the test, the subjects performed the following actions in sequence to induce blood pressure fluctuations within a certain range: Rest for 3 minutes; Warburg respiration for 0.5 minutes; Rest for 5 minutes; Passive leg raises for 1 minute; Rest for 5 minutes; 2 minutes of aerial bicycle riding; Rest for 5 minutes; Take a deep breath for 1 minute; Rest for 3 minutes.

[0102] After the test is completed, both recording programs are shut down simultaneously.

[0103] Figure 5 This is a diagram showing the results of array pressure pulse wave signal acquisition in an embodiment of this application. Figure 5 As shown, the array channels can acquire obvious periodic pressure pulse wave signals, with the signals in columns 2 to 6 being more significant, indicating that the corresponding sensor covers the vicinity of the superficial temporal artery in this area. The array signals also show that adjacent channels in the axial direction of the vessel exhibit good waveform continuity and amplitude consistency, verifying the effectiveness of the array arrangement and vessel localization method.

[0104] Figure 6 This is a diagram showing the channel filtering results involved in an embodiment of this application. For example... Figure 6 As shown, based on array signal analysis, a screening strategy based on amplitude and neighborhood consistency was adopted to further select four effective channels from the candidate channels as inputs for subsequent blood pressure calculation. The selected channels outperformed other channels in terms of waveform amplitude, signal-to-noise ratio, and spatial consistency, and were able to better reflect the pulse wave changes at the superficial temporal artery.

[0105] Figure 7 It's a comparison chart of estimated blood pressure and reference blood pressure. For example... Figure 7 As shown, pulse wave features are extracted based on the selected effective channels, and the model parameters are calibrated by combining them with reference blood pressure to obtain continuous blood pressure estimation results. Figure 8 This is a graph showing the difference in average systolic blood pressure. Figure 9 This is a graph showing the difference in mean diastolic blood pressure.

[0106] like Figure 8 and Figure 9 As shown, the estimated results were compared with the CNAP reference blood pressure, and the following error statistics were obtained (including mean error and standard deviation): For SBP: mean error = 0.72, std = 7.11 For DBP: mean error = -2.74, std = 5.28 The above error statistics show that the method can achieve continuous blood pressure estimation in the initial test of a single subject, and the average error of systolic and diastolic blood pressure is controlled within a small range.

[0107] This test, based on an 8×8 array pressure sensor, successfully completed the acquisition of superficial temporal artery pressure pulse waves and the verification of continuous blood pressure estimation under smart glasses wearing conditions. Experimental results show that: The array sensor can effectively cover the superficial temporal artery region and acquire pressure signals with obvious pulse characteristics; the channel screening method based on amplitude and neighborhood consistency can stably select effective vascular channels; in the preliminary test with a single subject, the proposed method achieved continuous estimation of systolic and diastolic blood pressure with a small average error; in summary, this test preliminarily verifies the feasibility of the smart glasses blood pressure measurement scheme based on array pressure pulse wave and ALA model.

[0108] This application also provides a blood pressure measuring device for implementing the above embodiments and preferred embodiments, which will not be repeated hereafter. As used below, the term "module" can refer to a combination of software and / or hardware that performs a predetermined function. Although the device described in the following embodiments is preferably implemented in software, hardware implementation, or a combination of software and hardware, is also possible and contemplated.

[0109] This application provides a blood pressure measuring device. Figure 10 This is a schematic diagram of a blood pressure measuring device provided in an embodiment of this application. The device includes: Signal acquisition module 1001 is used to acquire target pressure signal; the target pressure signal includes pressure pulse wave signals from multiple channels collected by the pressure sensor array from the wearer. The signal selection module 1002 is used to select at least one channel's pressure pulse wave signal as the target pulse wave signal from the multiple channels of pressure pulse wave signals. The parameter acquisition module 1003 is used to acquire the composite physiological parameters of the wearer; the composite physiological parameters are obtained by calibration based on an external reference blood pressure value and pressure pulse wave signals from at least two channels. The blood pressure calculation module 1004 is used to calculate the blood pressure data of the wearer based on the target pulse wave signal and the composite physiological parameters of the wearer.

[0110] In summary, when a user wears the head-mounted device, the pressure sensor array within the device can collect pressure values ​​from the superficial temporal artery at multiple locations, generating multi-channel pressure pulse wave signals. Then, at least one channel of the pressure pulse wave signal is selected as the target pulse wave signal. The head-mounted device then acquires the user's composite physiological parameters and calculates the user's blood pressure data based on the target pulse wave signal and composite physiological parameters. This solution, by deploying a pressure sensor array at the superficial temporal artery to collect multi-channel pressure wave signals, allows the user to quickly calibrate their composite physiological parameters based on an external reference blood pressure value and multiple channel pressure pulse wave signals. During subsequent wear, the head-mounted device can calculate the user's blood pressure data based on the pressure pulse wave signal from at least one channel collected by the pressure sensors and the composite physiological parameters, thus enabling relatively accurate blood pressure data collection.

[0111] This application also provides a head-mounted device, which includes a pressure sensor array for collecting pressure values ​​at the superficial temporal artery of the head from multiple locations.

[0112] Optionally, this application employs an iontronic sensor array based on an interdigitated electrode (IDE) structure to detect minute pressure changes caused by the pulse of the superficial temporal artery. This sensor utilizes the electric double layer (EDL) effect formed between the ionogel and the interdigitated electrodes to achieve signal conversion, and controls sensitivity and linearity through spacer layers between the structural layers.

[0113] Figure 11 A schematic diagram of the sensing unit of the pressure sensor array involved in an embodiment of this application is shown. Figure 11 As shown, a single sensing unit comprises, from bottom to top: 21-Interdigitated Electrode Layer: Fabricated on a flexible polyimide (PI) substrate, employing a two-set interlaced finger electrode structure. The electrode material can be gold (Au), copper (Cu), or carbon-based conductive ink, with finger widths of 50–150 μm and spacing of 50–200 μm. The electrodes are connected to the signal acquisition circuit via flexible ribbon cables to achieve multi-channel synchronous measurement.

[0114] 22-Spacer layer (double-sided adhesive frame layer): This layer is made of medical double-sided adhesive or polyimide frame, with a thickness of 50–150 μm, forming a closed frame along the electrode edge. Its functions are: (1) to form a stable micro-gap cavity and control the initial distance between the electrode and the ion gel layer; (2) to prevent the gel material from penetrating into the electrode area and causing a short circuit; (3) to limit the gel spreading range and improve device repeatability and signal linearity.

[0115] 23-Ionogel Layer: The ionogel is made of ionic liquid and polymer matrix composite ([EMIM][TFSI]+PVDF-HFP), with a thickness of 100-300 micrometers. It contains migratable ions, which redistribute under external pressure, causing changes in the electrical double-layer capacitance formed between the interdigitated electrodes and generating a measurable electrical signal.

[0116] The entire sensor has an "electrode-spacer-ion gel" structure. When there is no external force, the ion gel maintains a fixed distance from the electrode; when subjected to a pulse wave, the gel deforms in a local area and contacts the electrode surface, inducing a change in the electrobial capacitance, thus achieving high-sensitivity detection.

[0117] The fabrication steps of the above sensor are as follows: 1. Electrode fabrication: Interdigitated electrode patterns are formed on a PI flexible substrate by photolithography or screen printing; the metal layer is deposited by sputtering (thickness 100-300nm); after forming, a uniform interdigitated structure is formed and signal ports are brought out.

[0118] 2. Spacer layer formation: Use medical double-sided tape to cut a border shape that matches the electrode pattern; attach it around the electrode surface to form a closed ring border; the border thickness is controlled at 50–150 μm to ensure a balance between sensitivity and mechanical stability.

[0119] 3. Preparation and coating of ion gel: The ion liquid and polymer matrix are mixed at a mass ratio of 1:4 and stirred evenly; the mixture is spin-coated onto the spacer layer in an inert gas atmosphere to cover the entire sensing area; and cured at 60–80°C for 1 hour to form a flexible ion gel film.

[0120] 4. Packaging and lead connection: The outer layer is covered with a breathable PDMS protective film and bonded by plasma activation; flexible flat cable (FPC) is used to connect each unit to the signal acquisition module; forming a complete array sensing unit module.

[0121] Figure 12 A schematic diagram of a circuit module according to an embodiment of this application is shown. Figure 12 As shown in this application, taking a head-mounted device as smart glasses as an example, the circuit module of the smart glasses is entirely encapsulated inside the temple of the glasses, including the following modules: Signal acquisition and processing module 31: The signal acquisition and processing module 31 is electrically connected to the sensor array. It includes a capacitor-to-voltage conversion unit, a preamplifier circuit, an analog filter unit, a multi-channel sampling control unit, a multi-channel A / D converter, and a data processing device, which are used to complete the acquisition, conditioning, conversion and processing of multi-channel signals.

[0122] Optionally, the data processing device includes a processor and memory, and the processor may be a microcontroller unit (MCU) or a system-on-a-chip (SoC).

[0123] Specifically, the capacitance change signal from the pressure sensor array is first converted into a corresponding analog voltage signal in the capacitance-to-voltage conversion unit; then, the analog voltage signal is amplified by the preamplifier circuit and suppressed by the analog filter unit (such as a low-pass filter) to suppress high-frequency noise and interference signals; the conditioned analog signal is channel-selected and time-managed under the control of the multi-channel sampling control unit, and input to the multi-channel A / D converter to realize synchronous digital sampling of signals from each channel.

[0124] After analog-to-digital conversion, the resulting multi-channel digital signals can be stored in the memory of the data processing device, and read, cached, and processed by the microcontroller unit (MCU) or system on chip (SoC) within the module.

[0125] The memory stores computer instructions, and the MCU / SoC is used to read these instructions to control the signal acquisition process, synchronize multi-channel data, and execute subsequent signal preprocessing, feature extraction, and blood pressure calculation algorithms, thereby performing tasks such as... Figure 1 or Figure 2 The blood pressure measurement method is shown in the corresponding embodiment.

[0126] Wireless communication module 32: It adopts Bluetooth Low Energy (BLE) or Wi-Fi module to realize data transmission with mobile terminal or host computer; it supports real-time waveform display, historical data upload and downlink of individual calibration parameters; the communication protocol is compatible with mainstream smart device systems.

[0127] Power module 33: Composed of a micro lithium battery, voltage regulator circuit and charging management chip; provides a stable operating voltage of 3.3V to 5V; has overcharge, over-discharge and short circuit protection functions; can be replenished through Type-C interface or wireless charging.

[0128] Electrode interface 34: used to connect the sensor array signal line to the main control circuit board; it adopts a flexible FFC and pluggable connector structure for easy assembly and maintenance; the signal interface adopts a shielded wire design to reduce external electromagnetic interference.

[0129] The aforementioned circuit module is centered around the signal acquisition and processing module 31. It interacts with external devices through the wireless communication module 32, is powered by the power supply module 33, and is connected to the sensor array via the electrode interface 34. The entire module is embedded in the temple cavity of the glasses, featuring a compact layout and good heat dissipation, meeting the lightweight and low-power requirements of wearable devices.

[0130] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0131] The embodiments described above are merely illustrative of several implementation methods of this application, and while the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the invention patent. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of this application, and these all fall within the protection scope of this application. Therefore, the protection scope of this patent application should be determined by the appended claims.

Claims

1. A method for measuring blood pressure, characterized in that, The method is applied to a head-mounted device, which includes a pressure sensor array for acquiring pressure values ​​at the superficial temporal artery in the head from multiple locations. The method includes: Acquire a target pressure signal; the target pressure signal includes pressure pulse wave signals from multiple channels collected by the pressure sensor array from the wearer. From the pressure pulse wave signals of the multiple channels, at least one channel's pressure pulse wave signal is selected as the target pulse wave signal; The composite physiological parameters of the wearer are obtained; the composite physiological parameters are obtained by calibration based on an external reference blood pressure value and pressure pulse wave signals from at least two channels; the composite physiological parameters are used to characterize the user's vascular compliance characteristics, vascular cross-sectional area change characteristics, and the mapping relationship between sensor signals and actual blood pressure. Based on the target pulse wave signal and the composite physiological parameters of the wearer, the blood pressure data of the wearer is calculated. The acquisition of the composite physiological parameters of the wearer includes: Vascular compliance parameters are calculated based on the pressure pulse wave signals from at least two channels of the wearer; the pressure pulse wave signals from at least two channels are acquired by a pressure sensor array within the same time period; the measurement results of the pressure sensor array at different measurement points at the same time are equivalent to the measurement results of applying different external pressures at the same location at different times. Obtain standard blood pressure data; the standard blood pressure data is collected by the wearer using a standard blood pressure monitor; the standard blood pressure data includes the wearer's systolic blood pressure, diastolic blood pressure, and mean blood pressure; The composite physiological parameters of the wearer are calibrated based on the standard blood pressure data, the vascular compliance parameters, and the pressure pulse wave signals of at least two channels.

2. The method according to claim 1, characterized in that, The target pulse wave signal includes the target pulse wave peak value, the target pulse wave trough value, and the target pulse wave peak-trough difference value; the blood pressure data includes systolic pressure, diastolic pressure, and mean pressure; the mean pressure is calculated based on the systolic pressure and diastolic pressure. Based on the target pulse wave signal and the wearer's composite physiological parameters, the wearer's blood pressure data is calculated, including: The blood pressure data of the wearer is optimized to minimize the function value of the objective function; the objective function is the sum of pulse wave peak error, pulse wave trough error, and pulse wave peak-trough difference error. The pulse wave peak value error is used to characterize the difference between the target pulse wave peak value and the theoretical pulse wave peak value; the theoretical pulse wave peak value is calculated based on the composite physiological parameters and the systolic blood pressure and mean blood pressure to be optimized. The pulse trough error is used to characterize the difference between the target pulse trough value and the theoretical pulse trough value; the theoretical pulse trough value is calculated based on the composite physiological parameters and the diastolic blood pressure and mean blood pressure to be optimized. The pulse wave peak-valley difference error is used to characterize the difference between the target pulse wave peak-valley difference and the theoretical pulse wave peak-valley difference.

3. The method according to claim 2, characterized in that, The theoretical peak and trough values ​​of the pulse wave can be obtained using the following formula: in, This is the theoretical peak value of the pulse wave. This is the theoretical trough value of the pulse wave. These are composite physiological parameters; This is the scaling factor corresponding to the i-th channel. This represents the area of ​​the arterial lumen when the transmural pressure is 0. This represents the area of ​​the arterial lumen when the transmural pressure is infinite. The parameters are: vascular compliance parameters; MAP is the mean pressure calculated from systolic and diastolic blood pressure; SBP is the systolic blood pressure to be optimized; and DBP is the diastolic blood pressure to be optimized. Let be the static pressure value of the sensor corresponding to the i-th channel.

4. The method according to claim 3, characterized in that, The method further includes: The composite physiological parameters and vascular compliance parameters of the wearer are updated based on the wearer's blood pressure data and pressure pulse wave signals from at least two channels.

5. The method according to claim 4, characterized in that, The sensor array includes M rows and N columns of sensor units; wherein the M rows and N columns of sensor units are arranged in a rectangular pattern; the M rows and N columns of sensor units are used to collect pressure pulse wave signals of M*N channels at the superficial temporal artery of the head. Selecting at least one channel's pressure pulse wave signal as the target pulse wave signal from the plurality of channels includes: Within the same time window, according to the magnitude relationship of the pulse wave amplitude, the pressure pulse wave signals of candidate channels are selected from the pressure pulse wave signals of N channels collected by each row of sensor units to determine M candidate channels; Based on the main wave energy of the pressure pulse wave signals of the M candidate channels, the signal-to-noise ratio of the pressure pulse wave signals of the M candidate channels, and the pulse wave amplitude of the adjacent channels of the M candidate channels, at least one channel's pressure pulse wave signal is selected as the target pulse wave signal from the pressure pulse wave signals of the M candidate channels.

6. The method according to any one of claims 1 to 5, characterized in that, The acquisition of the target pressure signal includes: Acquire the voltage signals generated by the pressure sensor array; According to the pressure calibration parameters corresponding to the pressure sensor array, each voltage signal is converted into the target pressure signal; the pressure calibration parameters are obtained by pressurizing and calibrating the pressure sensor array according to a standard pressure device.

7. A blood pressure measuring device, characterized in that, The device is mounted on a head-mounted device, which includes a pressure sensor array for acquiring pressure values ​​at the superficial temporal artery in the head from multiple locations. The device comprises: A signal acquisition module is used to acquire a target pressure signal; the target pressure signal includes pressure pulse wave signals from multiple channels collected by the pressure sensor array from the wearer. The signal selection module is used to select at least one channel's pressure pulse wave signal as the target pulse wave signal from the multiple channels of pressure pulse wave signals. The parameter acquisition module is used to acquire the composite physiological parameters of the wearer; the composite physiological parameters are obtained by calibration based on an external reference blood pressure value and pressure pulse wave signals from at least two channels; the composite physiological parameters are used to characterize the user's vascular compliance characteristics, vascular cross-sectional area change characteristics, and the mapping relationship between sensor signals and actual blood pressure; The blood pressure calculation module is used to calculate the blood pressure data of the wearer based on the target pulse wave signal and the composite physiological parameters of the wearer. The acquisition of the composite physiological parameters of the wearer includes: Vascular compliance parameters are calculated based on the pressure pulse wave signals from at least two channels of the wearer; the pressure pulse wave signals from at least two channels are acquired by a pressure sensor array within the same time period; the measurement results of the pressure sensor array at different measurement points at the same time are equivalent to the measurement results of applying different external pressures at the same location at different times. Obtain standard blood pressure data; the standard blood pressure data is collected by the wearer using a standard blood pressure monitor; the standard blood pressure data includes the wearer's systolic blood pressure, diastolic blood pressure, and mean blood pressure; The composite physiological parameters of the wearer are calibrated based on the standard blood pressure data, the vascular compliance parameters, and the pressure pulse wave signals of at least two channels.

8. A data processing device, characterized in that, The data processing device includes a processor and a memory; the memory stores computer instructions; the processor executes the computer instructions to perform the blood pressure measurement method as described in any one of claims 1 to 6.

9. A head-mounted device, characterized in that, The head-mounted device is equipped with a pressure sensor array, which is used to collect pressure values ​​at the superficial temporal artery of the head from multiple locations. The head-mounted device is further provided with a data processing device to perform the blood pressure measurement method according to any one of claims 1 to 6.

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