Non-invasive blood pressure real-time monitoring device

Abstract

The invention relates to the technical field of medical instruments, in particular to a non-invasive real-time blood pressure monitoring device which comprises a physical sign database used for storing a plurality of historical physical sign data of a user in a target time period and collection time corresponding to the historical physical sign data; the acquisition fixing module is used for periodically acquiring alternative sign data of the user and corresponding acquisition time; the data analysis module is used for determining current physical sign data of the user and updating a physical sign database; the pre-judgment and prediction module is used for performing pre-judgment according to a comparison result of the data analysis module and predicting the blood pressure data of the user in a future preset time period according to a plurality of historical sign data and the current sign data; the control module is used for adjusting the tightness degree of the acquisition fixing module worn on the arm or wrist of the user; and the data display module is used for fitting the blood pressure waveform and displaying the fitted blood pressure waveform. The accuracy of real-time blood pressure monitoring can be improved, and the prediction accuracy can be improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical devices, and in particular to a non-invasive real-time blood pressure monitoring device. Background Art

[0002] Stable blood pressure is very important for human health. Blood pressure higher or lower than normal is called hypertension or hypotension. Hypertension refers to a clinical syndrome characterized by increased systemic arterial blood pressure (systolic and / or diastolic blood pressure) (systolic blood pressure ≥ 140 mmHg, diastolic blood pressure ≥ 90 mmHg), which may be accompanied by functional or organic damage to organs such as the heart, brain, and kidneys. Hypertension is the most common chronic disease and the most important risk factor for cardiovascular and cerebrovascular diseases. If it is not controlled, it is easy to cause lesions in blood vessels and multiple target organs. Compared with hypertension, acute hypotension refers to a sudden and significant drop in blood pressure from normal or high levels, with symptoms such as dizziness, black eyes, weak limbs, cold sweats, palpitations, and oliguria. In severe cases, it manifests as syncope or shock; at the same time, it will cause insufficient blood supply to the human brain and heart, resulting in serious damage. During the course of the disease, the blood pressure of patients with hypertension or hypotension will rise or fall significantly in a short period of time. If it cannot be monitored in real time, measures cannot be taken immediately to adjust it to a normal level in time, which will cause irreversible damage.

[0003] Regular blood pressure monitoring is very important for preventing cardiovascular diseases such as hypertension. Although people at risk of hypertension need to measure their blood pressure regularly, traditional blood pressure cuff measuring devices require experienced people to accurately measure blood pressure and are inconvenient to carry. Existing wearable devices use pressure sensors to measure blood pressure, which can achieve real-time monitoring of blood pressure, but the measurement accuracy is not high and cannot achieve real-time prediction and analysis of blood pressure.

[0004] Chinese patent publication number CN115470716A discloses a non-invasive blood pressure prediction method, device and real-time monitoring system based on convolutional neural network, which collects PPG signals from the user's fingertips; preprocesses the PPG signals to obtain a first processed signal; inputs the first processed signal into a blood pressure prediction model based on a convolutional neural network to predict and generate the user's blood pressure signal; the blood pressure prediction model includes a backbone network and an information distillation network based on an attention mechanism, and uses a dual-channel encoding part to improve accuracy through dual-channel feature extraction; uses an information distillation module with an improved attention mechanism in the encoding part to obtain feature information at different scales; and the dual-channel encoding part uses an Addition connection to input into the decoding part.

[0005] It can be seen that the above invention has the following problems: predicting the user's blood pressure signal only by collecting the PPG signal from the user's fingertips is easily affected by factors such as the environment and individual physiological characteristics. Therefore, blood pressure signal monitoring will be affected, resulting in low prediction accuracy. Summary of the invention

[0006] To this end, the present invention provides a non-invasive real-time blood pressure monitoring device to overcome the problems of low accuracy of real-time monitored blood pressure signals and low prediction accuracy in the prior art.

[0007] To achieve the above object, the present invention provides a non-invasive blood pressure real-time monitoring device, comprising: A vital sign database, which is used to store a number of historical vital sign data of the user within a target time period and the collection time corresponding to each historical vital sign data; the vital sign data includes blood pressure data, pulse data, body temperature data and exercise data; A collection and fixing module, which is worn on the user's arm or wrist and is used to periodically collect the user's candidate vital sign data and the corresponding collection time; A data analysis module, which is connected to the physical sign database and the acquisition and fixing module respectively, and is used to compare the historical physical sign data with the candidate physical sign data to determine the current physical sign data of the user, and update the physical sign database; a pre-judgment and prediction module, which is respectively connected to the vital sign database and the data analysis module, and is used to make a pre-judgment according to the comparison result of the data analysis module, and to predict the blood pressure data of the user in a future preset time period according to a number of the historical vital sign data and the current vital sign data, so as to obtain predicted blood pressure data; A control module, which is connected to the pre-judgment and prediction module and the acquisition and fixing module, respectively, and is used to adjust the tightness of the acquisition and fixing module worn on the user's arm or wrist according to the predicted blood pressure data; A data display module is respectively connected to the vital sign database, the acquisition and fixation module and the pre-judgment and prediction module, and is used to fit the blood pressure waveform according to the historical vital sign data, the current vital sign data and the predicted blood pressure data, and to display the fitted blood pressure waveform.

[0008] Furthermore, the data analysis module includes: A data comparison submodule, which is connected to the vital sign database and the acquisition and fixing module respectively, and is used to compare a number of the historical vital sign data with the candidate vital sign data and determine a comparison value; The data analysis submodule is connected to the data comparison submodule, and is used to perform analysis according to the comparison value determined by the data comparison submodule and the preset standard, and determine the user's current vital sign data according to the analysis result.

[0009] Furthermore, the data analysis submodule includes: A comparison and analysis unit, which is connected to the data comparison submodule, and is used to analyze according to the comparison value determined by the data comparison submodule and the preset standard to determine whether it meets the preset standard; wherein, if the comparison value is greater than a first comparison threshold, it meets the preset standard; if the comparison value is less than or equal to the first comparison threshold, it does not meet the preset standard; A current vital sign determination unit is connected to the comparison and analysis unit, and is used to determine the user's current vital sign data based on the analysis results; wherein, if it meets the preset standards, the alternative vital sign data is determined as the current vital sign data; if it does not meet the preset standards, the alternative vital sign data is corrected according to a preset correction method to obtain the current vital sign data.

[0010] Furthermore, the pre-judgment prediction module includes: A sensitive feature determination submodule, which is connected to the physical sign database, and is used to determine a blood pressure feature segment of the user based on a number of historical physical sign data of the user, and to determine sensitive physical sign data of the user based on each physical sign data corresponding to the blood pressure feature segment; A prejudgment submodule, which is connected to the sensitive feature determination submodule and the current vital sign determination unit respectively, and is used to make a prejudgment based on the sensitive vital sign data and the current vital sign data, and determine whether to issue an early warning prompt; The prediction submodule is respectively connected to the vital sign database and the sensitive feature determination submodule, and is used to predict the user's blood pressure data in a future preset time period based on the sensitive vital sign data, a number of the historical vital sign data and the current vital sign data to obtain predicted blood pressure data.

[0011] Furthermore, the prediction submodule determines a prediction characteristic value according to the sensitive vital sign data and the current vital sign data, and issues an early warning if the prediction characteristic value is greater than a prediction comparison threshold.

[0012] Furthermore, the prediction submodule includes: a blood pressure prediction feature determination unit, which is connected to the sensitive feature determination submodule, the current physical sign determination unit and the physical sign database, respectively, and is used to determine blood pressure prediction feature data according to the sensitive physical sign data, a plurality of the historical physical sign data and the current physical sign data; A prediction model determination unit, which is connected to the feature database and is used to train an initial blood pressure prediction model according to a number of the historical physical sign data to obtain a target blood pressure prediction model; A blood pressure prediction unit is respectively connected to the blood pressure prediction feature determination unit and the prediction model determination unit, and is used to input the blood pressure prediction feature data into the target blood pressure prediction model to obtain the predicted blood pressure data output by the target blood pressure prediction model.

[0013] Furthermore, the control module includes: An adjustment ratio determination submodule, which is connected to the feature database and the pre-judgment prediction module respectively, and is used to determine the adjustment ratio according to the predicted blood pressure data and a number of the historical vital sign data; The adjusting submodule is respectively connected to the acquisition and fixing module and the adjustment ratio determining submodule, and is used to adjust the tightness of the acquisition and fixing module worn on the user's arm or wrist according to the adjustment ratio.

[0014] Furthermore, the preset correction method in the current vital sign determination unit is to determine the blood pressure offset based on the user's alternative pulse data, alternative body temperature data and alternative motion data collected periodically, and correct the alternative blood pressure data based on the blood pressure offset to obtain the current blood pressure data.

[0015] Furthermore, the acquisition and fixation module also includes a cuff, and the cuff is used to adjust the tightness of the acquisition and fixation module when worn on the user's arm or wrist.

[0016] Furthermore, the adjustment submodule determines the inflation amount or deflation amount of the cuff according to the adjustment ratio to adjust the tightness of the acquisition and fixation module worn on the arm or wrist of the user.

[0017] Compared with the prior art, the beneficial effect of the present invention is that the present invention provides data support for subsequent data analysis and blood pressure data prediction by setting a vital sign database. By setting a collection and fixing module to periodically collect the user's alternative vital sign data, the user's vital sign data can be monitored in real time, avoiding the loss of vital sign data or the interference of accidental errors that cause the reduction of the accuracy of blood pressure data monitoring. By setting a data analysis module to determine the user's current vital sign data, the accuracy of real-time monitoring can be improved. By setting a pre-judgment prediction module for pre-judgment, the user's safety can be improved, the user can be reminded in time when monitoring abnormalities, and the blood pressure data of the user in the future preset time period can be predicted based on a number of the historical vital sign data and the current vital sign data, which can improve the prediction accuracy. By setting a control module to adjust the tightness of the collection and fixing module worn on the user's arm or wrist, the interference of the collection and fixing module on the real-time monitoring of vital sign data can be reduced, and the accuracy of real-time monitoring of vital sign data can be improved. By setting a data display module to fit and display the blood pressure waveform, the user experience can be increased, which is convenient for the user to monitor the dynamic changes of blood pressure in real time.

[0018] Furthermore, the data analysis module of the present invention determines the comparison value by setting a data comparison submodule, so as to quickly determine the degree of difference between the historical vital sign data and the alternative vital sign data. By setting the data analysis submodule to perform analysis according to the comparison value and the preset standard, and determining the user's current vital sign data according to the analysis result, the data analysis efficiency can be improved. Determining the user's current vital sign data according to the analysis result can reduce errors and improve the accuracy of determining the current vital sign data.

[0019] Furthermore, the data analysis submodule of the present invention determines the alternative vital sign data whose comparison value meets the preset standard as the current vital sign data by setting the current vital sign determination unit. If the comparison value does not meet the preset standard, the alternative vital sign data is corrected to obtain the current vital sign data, which can improve the accuracy of the current vital sign data.

[0020] Furthermore, the pre-judgment prediction module of the present invention determines the user's sensitive vital signs data by setting a sensitive feature determination submodule, which can provide comparison data for subsequent pre-judgment and prediction, thereby improving the accuracy of pre-judgment and prediction. By setting a pre-judgment submodule to make a pre-judgment and determine whether to issue an early warning prompt, the user can be promptly warned when an abnormal situation occurs, thereby improving the user experience. By setting a prediction submodule to predict the user's blood pressure data in a preset time period in the future based on the sensitive vital signs data, some of the historical vital signs data, and the current vital signs data, the prediction accuracy can be improved.

[0021] Furthermore, the prediction submodule of the present invention determines the blood pressure prediction feature data by setting a blood pressure prediction feature determination unit, obtains the target blood pressure prediction model by setting a prediction model determination unit for training, and inputs the blood pressure prediction feature data into the target blood pressure prediction model by setting a blood pressure prediction unit to obtain predicted blood pressure data, thereby further improving the prediction accuracy.

[0022] Furthermore, the control module of the present invention determines the adjustment ratio by setting an adjustment ratio determination submodule; by setting the adjustment submodule to adjust the tightness of the acquisition and fixing module worn on the user's arm or wrist according to the adjustment ratio, the accuracy of the adjustment can be improved and the influence of the acquisition and fixing module on the collected vital sign data can be avoided, thereby improving the accuracy of vital sign data monitoring. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] Figure 1 It is a structural block diagram of the non-invasive blood pressure real-time monitoring device of the present invention; Figure 2 is a structural block diagram of a data analysis module according to an embodiment of the present invention; Figure 3 It is a structural block diagram of the data analysis submodule of an embodiment of the present invention; Figure 4This is a structural block diagram of a pre-judgment prediction module according to an embodiment of the present invention; Figure 5 It is a structural block diagram of the prediction submodule according to an embodiment of the present invention; Figure 6 4 is a structural block diagram of a control module according to an embodiment of the present invention. DETAILED DESCRIPTION

[0024] In order to make the objects and advantages of the present invention more clearly understood, the present invention is further described below in conjunction with embodiments; it should be understood that the specific embodiments described herein are only used to explain the present invention and are not used to limit the present invention.

[0025] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood by those skilled in the art that these embodiments are only used to explain the technical principles of the present invention and are not intended to limit the protection scope of the present invention.

[0026] It should be noted that, in the description of the present invention, terms such as "up", "down", "left", "right", "inside" and "outside" indicating directions or positional relationships are based on the directions or positional relationships shown in the drawings. This is merely for the convenience of description and does not indicate or imply that the device or element must have a specific orientation, be constructed and operated in a specific orientation. Therefore, it cannot be understood as a limitation on the present invention.

[0027] In addition, it should be noted that in the description of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the internal communication of two components. For those skilled in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0028] See also Figure 1 As shown, it is a structural block diagram of the non-invasive real-time blood pressure monitoring device of the present invention; the present invention provides a non-invasive real-time blood pressure monitoring device, comprising: A vital sign database, which is used to store a number of historical vital sign data of the user within a target time period and the collection time corresponding to each historical vital sign data; the vital sign data includes blood pressure data, pulse data, body temperature data and exercise data; In an implementation, the motion data includes the number of steps and the amount of inertia.

[0029] Specifically, the actual implementers can set the target time period according to the actual situation. If the target time period is set too long, it will lead to excessive data processing and storage, reduce data processing efficiency, and increase power consumption; if the target time period is set too short, it will lead to too little data and reduce the subsequent prediction accuracy. Preferably, the value range of the target time period is 7 days to 30 days.

[0030] A collection and fixing module, which is worn on the user's arm or wrist and is used to periodically collect the user's candidate vital sign data and the corresponding collection time; In implementation, actual implementation personnel can set the collection period according to actual conditions. Preferably, the collection period can be set in the range of 3 minutes to 10 minutes.

[0031] Specifically, the acquisition and fixation module also includes a cuff, and the cuff is used to adjust the tightness of the acquisition and fixation module when worn on the user's arm or wrist.

[0032] A data analysis module, which is connected to the physical sign database and the acquisition and fixing module respectively, and is used to compare the historical physical sign data with the candidate physical sign data to determine the current physical sign data of the user, and update the physical sign database; See also Figure 2 As shown, it is a structural block diagram of a data analysis module according to an embodiment of the present invention; specifically, the data analysis module includes: A data comparison submodule, which is connected to the vital sign database and the acquisition and fixing module respectively, and is used to compare a number of the historical vital sign data with the candidate vital sign data and determine a comparison value; In implementation, the comparison value may be determined in the following manner: The historical vital signs data are Y1, Y2, ..., Y i , …, Y n , the alternative physical sign data are E1, E2, ..., E j ,…,E m , where j = 1, 2, ..., m; i = 1, 2, ..., n; m is the number of signs; n is the number of historical collections; Y i is the vital sign data corresponding to the i-th historical collection time, Y i =Y i,1 , Y i,2 , …, Y i,j , …, Y i,m , Y i,j is the historical physical sign data corresponding to the jth physical sign at the i-th historical collection time, E j is the candidate physical sign data corresponding to the jth physical sign collected; Comparison value P = ∑ n i=1 (∑ mj=1 Y i,j ×E j ) / (sqrt(∑ m j=1 (Y i,j ) 2 )×sqrt(∑ m j=1 (E j ) 2 )) / n; sqrt() is the preset square root determination function.

[0033] The data analysis submodule is connected to the data comparison submodule, and is used to perform analysis according to the comparison value determined by the data comparison submodule and the preset standard, and determine the user's current vital sign data according to the analysis result.

[0034] The data analysis submodule of the present invention determines the alternative vital sign data whose comparison value meets the preset standard as the current vital sign data by setting the current vital sign determination unit. If the comparison value does not meet the preset standard, the alternative vital sign data is corrected to obtain the current vital sign data, which can improve the accuracy of the current vital sign data.

[0035] See also Figure 3 As shown, it is a structural block diagram of the data analysis submodule of an embodiment of the present invention; specifically, the data analysis submodule includes: A comparison and analysis unit, which is connected to the data comparison submodule, and is used to analyze according to the comparison value determined by the data comparison submodule and the preset standard to determine whether it meets the preset standard; wherein, if the comparison value is greater than a first comparison threshold, it meets the preset standard; if the comparison value is less than or equal to the first comparison threshold, it does not meet the preset standard; In implementation, actual implementers may determine the first comparison threshold according to actual conditions or based on the maximum value of comparison values ​​determined from multiple tests in historical data. Preferably, the value range of the first comparison threshold may be set to 0.7-0.9.

[0036] A current vital sign determination unit is connected to the comparison and analysis unit, and is used to determine the user's current vital sign data based on the analysis results; wherein, if it meets the preset standards, the alternative vital sign data is determined as the current vital sign data; if it does not meet the preset standards, the alternative vital sign data is corrected according to a preset correction method to obtain the current vital sign data.

[0037] Specifically, the preset correction method in the current vital sign determination unit is to determine the blood pressure offset based on the user's alternative pulse data, alternative body temperature data and alternative motion data collected periodically, and correct the alternative blood pressure data based on the blood pressure offset to obtain the current blood pressure data.

[0038] In implementation, the blood pressure offset may be determined by: Determine the corresponding preset control interval according to the collection time corresponding to the alternative vital sign data, determine the first deviation value and the second deviation value according to the mean RM of the user's pulse data, the mean RT of the body temperature data and the alternative pulse data BM and the alternative body temperature data BT in the preset control interval, respectively, determine the user's motion deviation value according to the user's current step number, the step number change characteristic value BH and the inertia amount BG, and determine the blood pressure offset PX according to the first deviation value, the second deviation value, the motion deviation value and the alternative blood pressure data BX; wherein, the step number change characteristic mean RH and the inertia amount mean RG corresponding to the user's current step number are determined based on the preset user motion comparison table; then the first deviation value PC1=(RM-BM) / RM; the second deviation value PC2=(RT-BT) / RT; the motion deviation value PC3=((RH-BH) / RH+(RG-BG) / RG) / 2; X=((PC1+PC2+PC3) / 3)×PX.

[0039] Specifically, the current blood pressure data DX=PX+X. For example: the blood pressure offset is 10 mmHg, and the alternative blood pressure data is 130 mmHg, then the current blood pressure data is 10+130=140 (mmHg); the blood pressure offset is -10 mmHg, and the alternative blood pressure data is 130 mmHg, then the current blood pressure data is -10+130=120 (mmHg).

[0040] In actual application scenarios, actual implementers can set a preset comparison interval and a preset user movement comparison table according to the actual situation of the user.

[0041] The data analysis module of the present invention determines the comparison value by setting the data comparison submodule, and can quickly determine the degree of difference between the several historical vital sign data and the alternative vital sign data. By setting the data analysis submodule to perform analysis according to the comparison value and the preset standard, and determining the user's current vital sign data according to the analysis result, the data analysis efficiency can be improved. Determining the user's current vital sign data according to the analysis result can reduce errors and improve the accuracy of determining the current vital sign data.

[0042] a pre-judgment and prediction module, which is respectively connected to the vital sign database and the data analysis module, and is used to make a pre-judgment according to the comparison result of the data analysis module, and to predict the blood pressure data of the user in a future preset time period according to a number of the historical vital sign data and the current vital sign data, so as to obtain predicted blood pressure data; See also Figure 4 As shown, it is a structural block diagram of the pre-judgment prediction module of an embodiment of the present invention; specifically, the pre-judgment prediction module includes: A sensitive feature determination submodule, which is connected to the physical sign database, and is used to determine a blood pressure feature segment of the user based on a number of historical physical sign data of the user, and to determine sensitive physical sign data of the user based on each physical sign data corresponding to the blood pressure feature segment; During implementation, the user's highest and lowest blood pressure ranges are determined based on the user's own characteristics (hypertension / hypotension / normal), and the user's historical vital signs data are longitudinally compared to determine the user's blood pressure characteristic segments. In addition, the physical sign data corresponding to the blood pressure characteristic segments are determined in the user's several historical physical sign data, and their average or maximum values ​​are determined as the user's sensitive physical sign data.

[0043] A prejudgment submodule, which is connected to the sensitive feature determination submodule and the current vital sign determination unit respectively, and is used to make a prejudgment based on the sensitive vital sign data and the current vital sign data, and determine whether to issue an early warning prompt; Specifically, the prediction submodule determines a prediction characteristic value based on the sensitive vital sign data and the current vital sign data. If the prediction characteristic value is greater than the prediction comparison threshold, an early warning prompt is issued; if the prediction characteristic value is less than or equal to the prediction comparison threshold, no early warning prompt is issued.

[0044] In implementation, according to the sensitive physical sign data A1, A2, ..., A j , …, A m With the current vital sign data B1, B2, ..., B j , …, B m Determine the predicted characteristic value Q; where j = 1, 2, ..., m; Q = sqrt (∑ m j=1 (A j -B j ) 2 );A j is the sensitive sign data corresponding to the jth sign; B j is the current sign data corresponding to the jth sign.

[0045] Specifically, the actual implementer may determine the prediction comparison threshold value according to the actual situation or based on the average of the prediction characteristic values ​​determined through multiple tests. Preferably, the value range of the prediction comparison threshold value may be set to 0.8-0.95.

[0046] The prediction submodule is respectively connected to the vital sign database and the sensitive feature determination submodule, and is used to predict the user's blood pressure data in a future preset time period based on the sensitive vital sign data, a number of the historical vital sign data and the current vital sign data to obtain predicted blood pressure data.

[0047] The pre-judgment prediction module of the present invention determines the sensitive vital signs data of the user by setting a sensitive feature determination submodule, which can provide comparison data for subsequent pre-judgment and prediction, thereby improving the accuracy of pre-judgment and prediction. By setting a pre-judgment submodule to make a pre-judgment and determine whether to issue an early warning prompt, the user can be promptly warned when an abnormal situation occurs, thereby improving the user experience. By setting a prediction submodule to predict the user's blood pressure data in a preset time period in the future based on the sensitive vital signs data, some of the historical vital signs data, and the current vital signs data, the prediction accuracy can be improved.

[0048] See also Figure 5 As shown, it is a structural block diagram of the prediction submodule of an embodiment of the present invention; specifically, the prediction submodule includes: a blood pressure prediction feature determination unit, which is connected to the sensitive feature determination submodule, the current physical sign determination unit and the physical sign database, respectively, and is used to determine blood pressure prediction feature data according to the sensitive physical sign data, a plurality of the historical physical sign data and the current physical sign data; A prediction model determination unit, which is connected to the feature database and is used to train an initial blood pressure prediction model according to a number of the historical physical sign data to obtain a target blood pressure prediction model; It should be noted that those skilled in the art are aware that any prediction model capable of predicting blood pressure in the prior art falls within the protection scope of the present invention and will not be described in detail herein.

[0049] A blood pressure prediction unit is respectively connected to the blood pressure prediction feature determination unit and the prediction model determination unit, and is used to input the blood pressure prediction feature data into the target blood pressure prediction model to obtain the predicted blood pressure data output by the target blood pressure prediction model.

[0050] The prediction submodule of the present invention determines the blood pressure prediction feature data by setting a blood pressure prediction feature determination unit, obtains the target blood pressure prediction model by setting a prediction model determination unit for training, and inputs the blood pressure prediction feature data into the target blood pressure prediction model by setting a blood pressure prediction unit to obtain predicted blood pressure data, thereby further improving the prediction accuracy.

[0051] A control module, which is connected to the pre-judgment and prediction module and the acquisition and fixing module, respectively, and is used to adjust the tightness of the acquisition and fixing module worn on the user's arm or wrist according to the predicted blood pressure data; See also Figure 6 As shown, it is a structural block diagram of a control module according to an embodiment of the present invention; specifically, the control module includes: An adjustment ratio determination submodule, which is connected to the feature database and the pre-judgment prediction module respectively, and is used to determine the adjustment ratio according to the predicted blood pressure data and a number of the historical vital sign data; In implementation, the adjustment ratio is determined by comparing the predicted collection time corresponding to the predicted blood pressure data with the historical blood pressure data of the corresponding collection time in the historical data. For example, if the predicted blood pressure data is 120 mmHg and the predicted time is 12 o'clock, the blood pressure data corresponding to each 12 o'clock in the historical blood pressure data are obtained. Assuming that they are 118, 115, 112, 120, 122, and 123 respectively, then (118+115+112+120+122+123) / 6=118.3, and the adjustment ratio is (118.3-120) / 118.3=-0.014, wherein if the adjustment ratio is a positive number, the degree to which the collection and fixing module is worn on the user's arm or wrist is loosened; if the adjustment ratio is a negative number, the degree to which the collection and fixing module is worn on the user's arm or wrist is tightened.

[0052] The adjusting submodule is respectively connected to the acquisition and fixing module and the adjustment ratio determining submodule, and is used to adjust the tightness of the acquisition and fixing module worn on the user's arm or wrist according to the adjustment ratio.

[0053] Specifically, the adjustment submodule determines the inflation amount or deflation amount of the cuff according to the adjustment ratio to adjust the tightness of the acquisition and fixation module worn on the user's arm or wrist.

[0054] In implementation, if the adjustment ratio is -0.014, the cuff is inflated to a volume that is 0.014 times the original volume.

[0055] The control module of the present invention determines the adjustment ratio by setting an adjustment ratio determination submodule; by setting the adjustment submodule to adjust the tightness of the acquisition and fixing module worn on the user's arm or wrist according to the adjustment ratio, the accuracy of the adjustment can be improved and the influence of the acquisition and fixing module on the collected vital sign data can be avoided, thereby improving the accuracy of vital sign data monitoring.

[0056] A data display module is respectively connected to the vital sign database, the acquisition and fixation module and the pre-judgment and prediction module, and is used to fit the blood pressure waveform according to the historical vital sign data, the current vital sign data and the predicted blood pressure data, and to display the fitted blood pressure waveform.

[0057] It should be noted that those skilled in the art know that any method capable of performing waveform fitting in the prior art falls within the protection scope of the present invention and will not be described in detail herein.

[0058] The present invention provides data support for subsequent data analysis and blood pressure data prediction by setting a vital sign database. By setting a collection and fixing module to periodically collect the user's alternative vital sign data, the user's vital sign data can be monitored in real time, avoiding the loss of vital sign data or the interference of accidental errors that cause the reduction of the accuracy of blood pressure data monitoring. By setting a data analysis module to determine the user's current vital sign data, the accuracy of real-time monitoring can be improved. By setting a prejudgment prediction module for prejudgment, the user's safety can be improved, the user can be reminded in time when monitoring abnormalities, and the blood pressure data of the user in the future preset time period can be predicted based on a number of the historical vital sign data and the current vital sign data, which can improve the prediction accuracy. By setting a control module to adjust the tightness of the collection and fixing module worn on the user's arm or wrist, the interference of the collection and fixing module on the real-time monitoring of vital sign data can be reduced, and the accuracy of real-time monitoring of vital sign data can be improved. By setting a data display module to fit and display the blood pressure waveform, the user experience can be increased, which is convenient for the user to monitor the dynamic changes of blood pressure in real time.

[0059] So far, the technical solutions of the present invention have been described in conjunction with the preferred embodiments shown in the accompanying drawings. However, it is easy for those skilled in the art to understand that the protection scope of the present invention is obviously not limited to these specific embodiments. Without departing from the principle of the present invention, those skilled in the art can make equivalent changes or substitutions to the relevant technical features, and the technical solutions after these changes or substitutions will fall within the protection scope of the present invention.

Claims

1. A non-invasive real-time blood pressure monitoring device, characterized in that: include: A vital sign database, which is used to store a number of historical vital sign data of the user within a target time period and the collection time corresponding to each historical vital sign data; The vital sign data include blood pressure data, pulse data, body temperature data and movement data; A collection and fixing module, which is worn on the user's arm or wrist and is used to periodically collect the user's candidate vital sign data and the corresponding collection time; A data analysis module, which is connected to the physical sign database and the acquisition and fixing module respectively, and is used to compare the historical physical sign data with the candidate physical sign data to determine the current physical sign data of the user, and update the physical sign database; a pre-judgment and prediction module, which is respectively connected to the vital sign database and the data analysis module, and is used to make a pre-judgment according to the comparison result of the data analysis module, and to predict the blood pressure data of the user in a future preset time period according to a number of the historical vital sign data and the current vital sign data, so as to obtain predicted blood pressure data; A control module, which is connected to the pre-judgment and prediction module and the acquisition and fixing module, respectively, and is used to adjust the tightness of the acquisition and fixing module worn on the user's arm or wrist according to the predicted blood pressure data; A data display module is respectively connected to the vital sign database, the acquisition and fixation module and the pre-judgment and prediction module, and is used to fit the blood pressure waveform according to the historical vital sign data, the current vital sign data and the predicted blood pressure data, and to display the fitted blood pressure waveform.

2. The non-invasive blood pressure real-time monitoring device according to claim 1, characterized in that: The data analysis module includes: A data comparison submodule, which is connected to the vital sign database and the acquisition and fixing module respectively, and is used to compare a number of the historical vital sign data with the candidate vital sign data and determine a comparison value; The data analysis submodule is connected to the data comparison submodule, and is used to perform analysis according to the comparison value determined by the data comparison submodule and the preset standard, and determine the user's current vital sign data according to the analysis result.

3. The non-invasive blood pressure real-time monitoring device according to claim 2, characterized in that: The data analysis submodule includes: A comparison and analysis unit, which is connected to the data comparison submodule, and is used to analyze according to the comparison value determined by the data comparison submodule and the preset standard to determine whether it meets the preset standard; wherein, if the comparison value is greater than a first comparison threshold, it meets the preset standard; if the comparison value is less than or equal to the first comparison threshold, it does not meet the preset standard; A current vital sign determination unit is connected to the comparison and analysis unit, and is used to determine the user's current vital sign data based on the analysis results; wherein, if it meets the preset standards, the alternative vital sign data is determined as the current vital sign data; if it does not meet the preset standards, the alternative vital sign data is corrected according to a preset correction method to obtain the current vital sign data.

4. The non-invasive blood pressure real-time monitoring device according to claim 3, characterized in that: The pre-judgment prediction module comprises: A sensitive feature determination submodule, which is connected to the physical sign database, and is used to determine a blood pressure feature segment of the user based on a number of historical physical sign data of the user, and to determine sensitive physical sign data of the user based on each physical sign data corresponding to the blood pressure feature segment; A prejudgment submodule, which is connected to the sensitive feature determination submodule and the current vital sign determination unit respectively, and is used to make a prejudgment based on the sensitive vital sign data and the current vital sign data, and determine whether to issue an early warning prompt; The prediction submodule is respectively connected to the vital sign database and the sensitive feature determination submodule, and is used to predict the user's blood pressure data within a preset time period in the future based on the sensitive vital sign data, a number of the historical vital sign data and the current vital sign data to obtain predicted blood pressure data.

5. The non-invasive blood pressure real-time monitoring device according to claim 4, characterized in that: The prediction submodule determines a prediction characteristic value according to the sensitive vital sign data and the current vital sign data, and issues an early warning if the prediction characteristic value is greater than a prediction comparison threshold.

6. The non-invasive blood pressure real-time monitoring device according to claim 5, characterized in that: The prediction submodule includes: a blood pressure prediction feature determination unit, which is connected to the sensitive feature determination submodule, the current physical sign determination unit and the physical sign database, respectively, and is used to determine blood pressure prediction feature data according to the sensitive physical sign data, a plurality of the historical physical sign data and the current physical sign data; A prediction model determination unit, which is connected to the feature database and is used to train an initial blood pressure prediction model according to a number of the historical physical sign data to obtain a target blood pressure prediction model; A blood pressure prediction unit is respectively connected to the blood pressure prediction feature determination unit and the prediction model determination unit, and is used to input the blood pressure prediction feature data into the target blood pressure prediction model to obtain the predicted blood pressure data output by the target blood pressure prediction model.

7. The non-invasive blood pressure real-time monitoring device according to claim 6, characterized in that: The control module comprises: An adjustment ratio determination submodule, which is connected to the feature database and the pre-judgment prediction module respectively, and is used to determine the adjustment ratio according to the predicted blood pressure data and a number of the historical vital sign data; The adjusting submodule is respectively connected to the acquisition and fixing module and the adjustment ratio determining submodule, and is used to adjust the tightness of the acquisition and fixing module worn on the user's arm or wrist according to the adjustment ratio.

8. The non-invasive blood pressure real-time monitoring device according to claim 7, characterized in that: The preset correction method in the current vital sign determination unit is to determine the blood pressure offset based on the user's alternative pulse data, alternative body temperature data and alternative motion data collected periodically, and correct the alternative blood pressure data based on the blood pressure offset to obtain the current blood pressure data.

9. The non-invasive blood pressure real-time monitoring device according to claim 8, characterized in that: The acquisition and fixation module also includes a cuff, and the cuff is used to adjust the tightness of the acquisition and fixation module when worn on the arm or wrist of the user.

10. The non-invasive blood pressure real-time monitoring device according to claim 9, characterized in that: The adjustment submodule determines the inflation amount or deflation amount of the cuff according to the adjustment ratio to adjust the tightness of the acquisition and fixation module worn on the arm or wrist of the user.

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