High-precision pressure sensing method based on pressure detection probe

Abstract

The present application relates to the field of pressure measurement technology, and specifically to a high-precision pressure sensing method based on a pressure detection probe. The method comprises: obtaining pressure sensing data of the pressure detection probe within a preset time length; obtaining a non-stationarity index of the pressure sensing data; obtaining an unpredictability index of the pressure sensing data based on the non-stationarity index of the pressure sensing data; obtaining a detection stability index of the pressure detection probe; obtaining an accuracy compensation coefficient of the pressure sensing data based on the unpredictability index and the detection stability index; and correcting the pressure sensing data based on the accuracy compensation coefficient to obtain compensated pressure sensing data. The embodiments of the present application can improve the pressure detection accuracy of the pressure sensing method based on the pressure detection probe, thereby improving the supporting effect of the pressure detection data on medical diagnosis.

Description

Technical Field

[0001] The present application belongs to the technical field of pressure measurement, and specifically relates to a high-precision pressure sensing method based on a pressure detection probe. Background Art

[0002] With the development of modern medical technology, pressure detection is increasingly used in medical diagnosis and treatment, especially in areas involving blood pressure monitoring, ventilator management, artificial heart assistance, catheter pressure monitoring, etc. High-precision pressure detection probes can measure pressure changes inside or on the surface of the human body in real time and accurately, which plays an important role in monitoring patients' vital signs, assessing changes in their condition, and guiding clinical decision-making. Pressure sensing methods based on pressure detection probes have therefore emerged, and through advanced means such as semiconductor technology and microcomputer system technology, real-time tracking and measurement of pressure signals have been achieved.

[0003] However, the current pressure sensing method based on pressure detection probe has low detection accuracy, resulting in poor support effect of detection data for medical diagnosis. Summary of the invention

[0004] In order to solve the above problems, the embodiment of the present application provides a high-precision pressure sensing method based on a pressure detection probe, the method comprising:

[0005] Acquiring pressure sensing data of the pressure detection probe within a preset time period;

[0006] Obtaining a non-stationary index of the pressure sensing data;

[0007] Obtaining an unpredictability index of the pressure perception data according to the non-stationarity index of the pressure perception data;

[0008] Obtaining a detection stability index of the pressure detection probe;

[0009] Acquiring an accuracy compensation coefficient of the pressure sensing data according to the unpredictability index and the detection stability index;

[0010] The pressure sensing data is corrected according to the accuracy compensation coefficient to obtain compensated pressure sensing data.

[0011] Optionally, obtaining a non-stationary index of the pressure sensing data includes:

[0012] Acquiring the sharpness of the peak signal of the pressure sensing data;

[0013] Acquiring a baseline signal of the pressure sensing data;

[0014] A non-stationary index of the pressure sensing data is obtained according to the baseline signal.

[0015] Optionally, the acquiring the sharpness of the peak signal of the pressure perception data includes:

[0016] Obtaining the time interval between two adjacent valley value points on the left and right of the peak value of the peak signal;

[0017] The time interval is taken as the sharpness of the peak signal of the pressure sensing data.

[0018] Optionally, obtaining a baseline signal of the pressure perception data includes:

[0019] Performing empirical mode decomposition on the pressure sensing data to obtain a decomposition component signal set;

[0020] The last component signal in the decomposed component signal set is used as the baseline signal of the pressure perception data.

[0021] Optionally, obtaining a non-stationary index of the pressure sensing data includes:

[0022] Acquire a slope data set of the baseline signal, wherein the slope data set includes the slope of a line segment formed by any two adjacent data points in the baseline signal;

[0023] Obtaining the absolute value of the difference between any two adjacent data in the slope data set;

[0024] Obtaining the average value of the sharpness of all peak signals of the pressure sensing data;

[0025] A non-stationary index of the pressure perception data is obtained according to the absolute value and the mean value.

[0026] Optionally, obtaining an unpredictability index of the pressure perception data includes:

[0027] Acquire a pressure perception curve of the pressure perception data;

[0028] Acquire a respiratory frequency curve of the pressure sensing data;

[0029] Obtaining a mean square error between the pressure perception curve and the respiratory rate curve;

[0030] An unpredictability index of the pressure sensing data is obtained according to the non-stationary index and the mean square error.

[0031] Optionally, obtaining the detection stability index of the pressure detection probe includes:

[0032] Obtaining an environmental impact index of the pressure detection probe;

[0033] Obtaining a vibration intensity index of the pressure detection probe;

[0034] According to the environmental impact index and the vibration intensity index, a detection stability index of the pressure detection probe is obtained.

[0035] Optionally, obtaining the environmental impact index of the pressure detection probe includes:

[0036] Obtaining the standard deviation of the temperature monitoring data within the preset time period;

[0037] Obtaining the standard deviation of the humidity monitoring data within the preset time period;

[0038] The environmental impact index of the pressure detection probe is obtained according to the standard deviation of the temperature monitoring data and the standard deviation of the humidity monitoring data.

[0039] Optionally, the obtaining of the accuracy compensation coefficient of the pressure sensing data includes:

[0040] Obtaining the inverse of the unpredictability index;

[0041] Obtaining the reciprocal of the unpredictability index and the Euclidean norm of the detection stability index;

[0042] According to the Euclidean norm, an accuracy compensation coefficient of the pressure sensing data is obtained.

[0043] Optionally, the correcting the pressure perception data according to the accuracy compensation coefficient to obtain compensated pressure perception data includes:

[0044] Obtaining the product of the accuracy compensation coefficient and the pressure sensing data;

[0045] The product is used as the compensated pressure perception data.

[0046] In summary, the embodiment of the present application provides a high-precision pressure sensing method based on a pressure detection probe, the method comprising: obtaining pressure sensing data of the pressure detection probe within a preset time length; obtaining a non-stationarity index of the pressure sensing data; obtaining an unpredictability index of the pressure sensing data based on the non-stationarity index of the pressure sensing data; obtaining a detection stability index of the pressure detection probe; obtaining an accuracy compensation coefficient of the pressure sensing data based on the unpredictability index and the detection stability index; correcting the pressure sensing data based on the accuracy compensation coefficient to obtain compensated pressure sensing data. The embodiment of the present application can improve the pressure detection accuracy of the pressure sensing method based on the pressure detection probe, thereby improving the supporting effect of the pressure detection data on medical diagnosis. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] In order to more clearly illustrate the implementation scheme of the present application, the drawings required for use in the implementation scheme will be briefly introduced below. It should be understood that the drawings only show certain implementation schemes of the present application and therefore should not be regarded as limiting the scope. For ordinary technicians in this field, other relevant drawings can be obtained based on the drawings without paying creative work.

[0048] Figure 1 The present invention is a flowchart showing a high-precision pressure sensing method based on a pressure detection probe according to an exemplary embodiment.

[0049] Figure 2 The present invention is a flowchart showing a method for obtaining a non-stationary index of pressure perception data according to an exemplary embodiment.

[0050] Figure 3 The figure is a flow chart showing a method for obtaining the sharpness of a peak signal of pressure perception data according to an exemplary embodiment.

[0051] Figure 4 The present invention is a flowchart showing a method for obtaining a baseline signal of pressure perception data according to an exemplary embodiment.

[0052] Figure 5 The present invention is a flowchart of another method for obtaining a non-stationary index of pressure perception data according to an exemplary embodiment.

[0053] Figure 6 The present invention is a flowchart showing a method for obtaining an unpredictability index of pressure perception data according to an exemplary embodiment.

[0054] Figure 7 The present invention is a flow chart showing a method for obtaining a detection stability index of a pressure detection probe according to an exemplary embodiment.

[0055] Figure 8 The present invention is a flow chart showing a method for obtaining an environmental impact index of a pressure detection probe according to an exemplary embodiment.

[0056] Fig. 9 The present invention is a flowchart showing a method for obtaining a precision compensation coefficient of pressure perception data according to an exemplary embodiment.

[0057] Fig.10 The invention is a flowchart of a method for obtaining compensated pressure perception data according to an exemplary embodiment. DETAILED DESCRIPTION

[0058] In order to clearly illustrate the technical features of the present solution, the present application is described in detail below through specific implementation methods and in conjunction with the accompanying drawings.

[0059] The embodiments of the present application will be described in more detail below with reference to the accompanying drawings. Although certain embodiments of the present application are shown in the accompanying drawings, it should be understood that the present application can be implemented in various forms and should not be construed as being limited to the embodiments described herein. Instead, these embodiments are provided to provide a more thorough and complete understanding of the present application. It should be understood that the drawings and embodiments of the present application are only for exemplary purposes and are not intended to limit the scope of protection of the present application.

[0060] It should be understood that the various steps described in the method implementation of the present application can be performed in different orders and / or performed in parallel. In addition, the method implementation may include additional steps and / or omit the steps shown. The scope of the present application is not limited in this respect.

[0061] The term "including" and its variations used herein are open inclusions, i.e., "including but not limited to". The term "based on" means "based at least in part on". The term "one embodiment" means "at least one embodiment"; the term "another embodiment" means "at least one additional embodiment"; the term "some embodiments" means "at least some embodiments". The relevant definitions of other terms will be given in the following description.

[0062] It should be noted that the concepts such as "first" and "second" mentioned in this application are only used to distinguish different devices, modules or units, and are not used to limit the order or interdependence of the functions performed by these devices, modules or units.

[0063] It should be noted that the modifications of "one" and "multiple" mentioned in this application are illustrative rather than restrictive. Those skilled in the art should understand that unless otherwise clearly indicated in the context, they should be understood as "one or more". In the description of this application, unless otherwise specified, "multiple" means two or more than two, and other quantifiers are similar; "at least one item", "one or more items" or similar expressions refer to any combination of these items, including any combination of single items or plural items. For example, at least one item a can represent any number of a; for another example, one or more items of a, b and c can represent: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple; "and / or" is a kind of association relationship that describes the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone, where A and B can be singular or plural.

[0064] Although the operations or steps are described in a specific order in the drawings in the embodiments of the present application, it should not be understood that it is required to perform these operations or steps in the specific order shown or in a serial order, or to perform all the operations or steps shown to obtain the desired results. In the embodiments of the present application, these operations or steps can be performed in series; these operations or steps can also be performed in parallel; or some of these operations or steps can be performed.

[0065] At the same time, it is understandable that the data involved in this technical solution (including but not limited to the data itself, the acquisition or use of the data) shall comply with the requirements of relevant laws, regulations and relevant provisions.

[0066] First, the application scenario of the present application is explained. The pressure sensing method based on the pressure detection probe is combined with ultrasonic technology, which can not only monitor the dynamic pressure distribution of the detection part such as the spine and its surrounding soft tissue in real time, but also provide a non-invasive and radiation-free pressure detection method. Although the pressure sensing technology based on the pressure detection probe has been applied in many fields, there are still some problems and shortcomings in its application in medical ultrasonic detection. For example: although the pressure sensor of the traditional pressure detection probe can provide a certain pressure perception, the pressure distribution of the detection part such as the spine area is complex, and the small pressure changes are not easy to be detected by the pressure probe, which leads to a decrease in the pressure perception accuracy; and the influence of the environment, such as temperature, humidity, external vibration and other factors in the dynamic detection process, will also cause certain interference to the pressure sensing results of the pressure detection probe, further leading to a decrease in the pressure perception accuracy.

[0067] In view of this, it is urgent to provide a high-precision pressure sensing method based on a pressure detection probe. The present application is described below in conjunction with specific embodiments.

[0068] Figure 1 FIG. 1 is a flow chart showing a high-precision pressure sensing method based on a pressure detection probe according to an exemplary embodiment. Figure 1 As shown, the embodiment of the present application provides a high-precision pressure sensing method based on a pressure detection probe, which may include the following steps:

[0069] In step S10, the pressure sensing data of the pressure detection probe within a preset time period is obtained.

[0070] In this step, the pressure sensing data of the pressure detection probe within the preset time is obtained. For example, before using the ultrasonic pressure probe for detection, sufficient preparation can be made; first, ensure that the physical condition of the pressure probe is good, without damage or failure, and then calibrate the probe to ensure that the pressure sensor and the ultrasonic equipment work within the expected accuracy range; then guide the patient to take the correct posture according to the detection needs in order to obtain the best detection conditions; apply an appropriate amount of coupling agent to the contact part of the probe to reduce the air gap and improve the efficiency of ultrasonic transmission; place the probe in an appropriate position in the target area, and then start the ultrasonic probe to obtain data, and continuously collect pressure data and ultrasonic data during the monitoring process to ensure the integrity of the data and ensure that the pressure data is recorded synchronously with the ultrasonic data; then store the collected pressure data and ultrasonic data for subsequent analysis. Among them, the preset time can be 5 minutes.

[0071] In step S20, a non-stationary index of the pressure sensing data is obtained.

[0072] In this step, the non-stationary index of the pressure sensing data is obtained. For example, the sharpness of the peak signal of the pressure sensing data can be obtained first, and then the baseline signal of the pressure sensing data can be obtained; and then the non-stationary index of the pressure sensing data can be obtained according to the baseline signal.

[0073] In step S30, an unpredictability index of the pressure perception data is obtained according to the non-stationarity index of the pressure perception data.

[0074] In this step, the unpredictability index of the pressure perception data is obtained according to the non-stationary index of the pressure perception data. Exemplarily, the pressure perception curve of the pressure perception data can be obtained first; then the respiratory rate curve of the pressure perception data can be obtained; then the mean square error between the pressure perception curve and the respiratory rate curve can be obtained; and then the unpredictability index of the pressure perception data can be obtained according to the non-stationary index and the mean square error.

[0075] In step S40, the detection stability index of the pressure detection probe is obtained.

[0076] In this step, the detection stability index of the pressure detection probe is obtained. For example, the environmental impact index of the pressure detection probe can be obtained first, and then the vibration intensity index of the pressure detection probe can be obtained; and then the detection stability index of the pressure detection probe can be obtained according to the environmental impact index and the vibration intensity index.

[0077] In step S50, the accuracy compensation coefficient of the pressure sensing data is obtained according to the unpredictability index and the detection stability index.

[0078] In this step, the accuracy compensation coefficient of the pressure sensing data is obtained according to the unpredictability index and the detection stability index. Exemplarily, the reciprocal of the unpredictability index can be obtained first; then the Euclidean norm of the reciprocal of the unpredictability index and the detection stability index can be obtained; and then the accuracy compensation coefficient of the pressure sensing data can be obtained according to the Euclidean norm.

[0079] In step S60, the pressure sensing data is corrected according to the accuracy compensation coefficient to obtain compensated pressure sensing data.

[0080] In this step, the pressure sensing data is corrected according to the accuracy compensation coefficient to obtain the compensated pressure sensing data. Exemplarily, the product of the accuracy compensation coefficient and the pressure sensing data can be first obtained; and then the product is used as the compensated pressure sensing data.

[0081] In summary, the embodiment of the present application provides a high-precision pressure sensing method based on a pressure detection probe, the method comprising: obtaining pressure sensing data of the pressure detection probe within a preset time length; obtaining a non-stationarity index of the pressure sensing data; obtaining an unpredictability index of the pressure sensing data based on the non-stationarity index of the pressure sensing data; obtaining a detection stability index of the pressure detection probe; obtaining an accuracy compensation coefficient of the pressure sensing data based on the unpredictability index and the detection stability index; correcting the pressure sensing data based on the accuracy compensation coefficient to obtain compensated pressure sensing data. The embodiment of the present application can improve the pressure detection accuracy of the pressure sensing method based on the pressure detection probe, thereby improving the supporting effect of the pressure detection data on medical diagnosis.

[0082] Figure 2 FIG. 1 is a flow chart showing a method for obtaining a non-stationary index of pressure perception data according to an exemplary embodiment. Figure 2 As shown, the obtaining of the non-stationary index of the pressure sensing data may include the following steps:

[0083] In step S201, the sharpness of the peak signal of the pressure perception data is obtained.

[0084] In this step, the sharpness of the peak signal of the pressure sensing data is obtained. Exemplarily, the time interval between two adjacent valley points on the left and right of the peak point of the peak signal can be obtained first, and then the time interval is used as the sharpness of the peak signal of the pressure sensing data.

[0085] In step S202, a baseline signal of the pressure sensing data is acquired.

[0086] In this step, the baseline signal of the pressure sensing data is obtained. When using an ultrasonic pressure probe for spinal testing, under normal circumstances, the pressure sensing data should show some typical data change characteristics, such as the pressure signal should have a stable baseline, without obvious offset or irregular large fluctuations, etc. Pressure sensing data with such data change characteristics can reflect more accurate test results in the actual test process.

[0087] Exemplarily, empirical mode decomposition may be performed on the pressure perception data to obtain a decomposition component signal set, and then the last component signal in the decomposition component signal set is used as the baseline signal of the pressure perception data.

[0088] In step S203, a non-stationary index of the pressure perception data is obtained according to the baseline signal.

[0089] In this step, the non-stationary index of the pressure perception data is obtained according to the baseline signal. Exemplarily, the slope data set of the baseline signal can be obtained first, and the slope data set includes the slope of the line segment formed by any two adjacent data points in the baseline signal, and then the absolute value of the difference between any two adjacent data in the slope data set is obtained, and then the mean of the sharpness of all peak signals of the pressure perception data is obtained, and finally the non-stationary index of the pressure perception data is obtained according to the absolute value and the mean.

[0090] Figure 3 FIG. 1 is a flow chart showing a method for obtaining the sharpness of a peak signal of pressure perception data according to an exemplary embodiment. Figure 3 As shown, the step of obtaining the sharpness of the peak signal of the pressure perception data may include the following steps:

[0091] In step S2011, the time interval between two adjacent valley points on the left and right of the peak point of the peak signal is obtained.

[0092] In this step, the time interval between the two adjacent valley points on the left and right of the peak point of the peak signal is obtained. .

[0093] In step S2012, the time interval is used as the sharpness of the peak signal of the pressure perception data.

[0094] In this step, the time interval , as the sharpness of the peak signal of the pressure perception data. Among them, the time interval Not zero.

[0095] Figure 4 FIG. 1 is a flow chart showing a method for obtaining a baseline signal of pressure perception data according to an exemplary embodiment. Figure 4As shown, the obtaining of the baseline signal of the pressure perception data may include the following steps:

[0096] In step S2021, empirical mode decomposition is performed on the pressure sensing data to obtain a decomposition component signal set.

[0097] In this step, empirical mode decomposition, such as EMD decomposition, is performed on the pressure perception data to obtain a decomposition component signal set.

[0098] In step S2022, the last component signal in the decomposed component signal set is used as the baseline signal of the pressure perception data.

[0099] In this step, the last component signal in the decomposed component signal set is used as the baseline signal of the pressure perception data.

[0100] Figure 5 FIG. 1 is a flowchart showing another method for obtaining a non-stationary index of pressure perception data according to an exemplary embodiment. Figure 5 As shown, the obtaining of the non-stationary index of the pressure sensing data may include the following steps:

[0101] In step S2031, a slope data set of the baseline signal is obtained, where the slope data set includes the slope of a line segment formed by any two adjacent data points in the baseline signal.

[0102] In this step, a slope data set of the baseline signal is obtained, and the slope data set includes the slope of a line segment composed of any two adjacent data points in the baseline signal.

[0103] In step S2032, the absolute value of the difference between any two adjacent data in the slope data set is obtained.

[0104] In this step, get any two adjacent data in the slope data set and The absolute value of the difference .

[0105] In step S2033, the average value of the sharpness of all peak signals of the pressure perception data is obtained.

[0106] In this step, the mean value of the sharpness of all peak signals of the pressure perception data is obtained. .

[0107] In step S2034, a non-stationary index of the pressure perception data is obtained according to the absolute value and the mean value.

[0108] In this step, the absolute value and the mean , obtain the non-stationary index of pressure perception data . Exemplary non-stationary index of pressure sensing data , can be obtained by the following formula:

[0109] Formula 1

[0110] in, It represents the non-stationarity of the pressure perception data within the detection time period; It represents the e-th slope value in the baseline signal in the pressure perception data; represents the e+1th slope value adjacent to the eth slope value in the baseline signal in the pressure perception data; n is the total number of slope values ​​in the baseline signal; is a non-zero constant in the open interval (0, 0.1).

[0111] It indicates the stability of the baseline signal in the pressure perception data curve within the preset time. The smaller the average value is, the more stable the baseline signal of the actual pressure data curve is. The closer the baseline signal is to a stable straight line, the better it is in line with expectations. It represents the reciprocal of the mean of the sharpness of all peak signals in the pressure perception data curve. The larger the value, the narrower the width of the peak signal in the pressure perception data curve, that is, the sharpness of the peak signal is higher. There may be some external interference in the detection process, which may lead to abrupt peaks, that is, it does not meet expectations. The larger the value of , the more likely it is that the actual pressure perception result will deviate from the expected result, that is, the greater the non-stationarity of the pressure perception data.

[0112] Since the accuracy of pressure sensing data may be affected by the patient's breathing movements, in order to improve the accuracy of pressure sensing data, it is necessary to analyze the impact of this influencing factor. Figure 6 FIG. 1 is a flow chart showing a method for obtaining an unpredictability index of pressure perception data according to an exemplary embodiment. Figure 6 As shown, the obtaining of the unpredictability index of the pressure perception data may include the following steps:

[0113] In step S301, a pressure perception curve of the pressure perception data is obtained.

[0114] In this step, a pressure perception curve p of the pressure perception data is obtained.

[0115] In step S302, a respiratory frequency curve of the pressure sensing data is obtained.

[0116] In this step, a respiratory frequency curve h of the pressure sensing data is obtained. Exemplarily, an ultrasonic sensor can be placed on the patient's chest or abdomen to ensure that the movement caused by breathing can be detected, and then the ultrasonic reflection data is collected, the recorded reflection data is Fourier transformed, the extracted frequency data is converted into the respiratory frequency, that is, the number of breaths per minute, and then the respiratory frequency curve h is drawn according to the number of breaths per minute.

[0117] In step S303, a mean square error between the pressure perception curve and the respiratory frequency curve is obtained.

[0118] In this step, the mean square error between the pressure perception curve p and the respiratory frequency curve h is obtained. .

[0119] In step S304, an unpredictability index of the pressure perception data is obtained according to the non-stationary index and the mean square error.

[0120] In this step, according to the non-stationary index and mean square error , obtain the unpredictability index w of the pressure perception data. Exemplarily, the unpredictability index w of the pressure perception data can be obtained by the following formula:

[0121] Formula 2

[0122] in, The smaller the value is, the more it means that in the actual detection process, the change of pressure perception data and the breathing frequency of the subject have a similar or identical change cycle, which means that the "abnormal fluctuation" of pressure perception data may be due to the "interference phenomenon" caused by the breathing state of the subject; The larger the value is, the higher the instability of the pressure perception data during the detection process is, and it is not closely related to the breathing state of the subject, that is, the pressure perception data has poor predictability, indicating that the accuracy of the pressure perception data during the detection process is not very high, that is, the larger the unpredictability index w is, the less predictable the pressure perception data is, indicating that there may be real abnormalities in the detection area of ​​the subject during the actual detection process, or it may be due to the influence of other interference factors in the detection process, resulting in abnormal data, which requires further analysis.

[0123] In the process of detecting the spine using an ultrasonic pressure probe, the accuracy of the pressure sensing data may be affected by environmental factors. Unexpected changes in environmental factors have a certain impact on the stability of the detection process, thereby reducing the accuracy of the pressure sensing data. Figure 7 FIG. 1 is a flow chart showing a method for obtaining a detection stability index of a pressure detection probe according to an exemplary embodiment. Figure 7 As shown, the obtaining of the detection stability index of the pressure detection probe may include the following steps:

[0124] In step S401, the environmental impact index of the pressure detection probe is obtained.

[0125] In this step, the environmental impact index Q of the pressure detection probe is obtained. Exemplarily, the standard deviation of the temperature monitoring data within a preset time period can be obtained first, and then the standard deviation of the humidity monitoring data within a preset time period can be obtained, and then the environmental impact index Q of the pressure detection probe can be obtained based on the standard deviation of the temperature monitoring data and the standard deviation of the humidity monitoring data. Among them, the environmental impact index Q is not zero.

[0126] In step S402, the vibration intensity index of the pressure detection probe is obtained.

[0127] In this step, the vibration intensity index U of the pressure detection probe is obtained. Exemplarily, the vibration intensity index U of the pressure probe during the detection process can be obtained by a vibration sensor, and the vibration intensity index U is time series data.

[0128] In step S403, a detection stability index of the pressure detection probe is obtained according to the environmental impact index and the vibration intensity index.

[0129] In this step, the detection stability index D of the pressure detection probe is obtained according to the environmental impact index Q and the vibration intensity index U. Exemplarily, the detection stability index D of the pressure detection probe can be obtained by the following formula:

[0130] Formula 3

[0131] in, represents the vibration intensity index value at the jth time point during the movement of the pressure probe device during the test; It represents the vibration intensity index value at the yth time point during the movement of the pressure probe equipment; there is a set of difference values ​​between the vibration intensity index values ​​at any two time points, m represents one of the sets of difference values, and there are M sets of difference values ​​in the detection period.

[0132] It indicates the vibration effect of the probe device during the detection period. The smaller the value, the more stable the movement of the probe device is, which meets the expectations of medical detection. It should be noted that this value is not zero.

[0133] The larger the value is, the smaller the impact of environmental factors on the accuracy of pressure sensing results is during the detection process, and the probe device is in a stable moving state during the detection process, that is, the detection environment during the pressure sensing process is relatively stable, that is, the greater the detection stability is.

[0134] Figure 8 FIG. 1 is a flow chart showing a method for obtaining an environmental impact index of a pressure detection probe according to an exemplary embodiment. Figure 8 As shown, the obtaining of the environmental impact index of the pressure detection probe may include the following steps:

[0135] In step S4011, the standard deviation of the temperature monitoring data within the preset time period is obtained.

[0136] In this step, the standard deviation σ1 of the temperature monitoring data within a preset time period is obtained.

[0137] In step S4012, the standard deviation of the humidity monitoring data within the preset time period is obtained.

[0138] In this step, the standard deviation σ2 of the humidity monitoring data within a preset time period is obtained.

[0139] In step S4013, the environmental impact index of the pressure detection probe is obtained according to the standard deviation of the temperature monitoring data and the standard deviation of the humidity monitoring data.

[0140] In this step, the environmental impact index Q of the pressure detection probe is obtained according to the standard deviation σ1 of the temperature monitoring data and the standard deviation σ2 of the humidity monitoring data. Exemplarily, the environmental impact index Q of the pressure detection probe can be obtained by the following formula:

[0141] Q=σ1×σ2 Formula 4

[0142] Among them, σ1 and σ2 are not zero at the same time.

[0143] Fig. 9 FIG. 1 is a flow chart showing a method for obtaining an accuracy compensation coefficient of pressure perception data according to an exemplary embodiment. Fig. 9 As shown, the obtaining of the accuracy compensation coefficient of the pressure sensing data may include the following steps:

[0144] In step S501, the inverse of the unpredictability index is obtained.

[0145] In this step, the inverse of the unpredictability index is obtained .

[0146] In step S502, the inverse of the unpredictability index and the Euclidean norm of the detection stability index are obtained.

[0147] In this step, the inverse of the unpredictability index is obtained and the Euclidean norm of the detection stability index D .

[0148] In step S503, the accuracy compensation coefficient of the pressure sensing data is obtained according to the Euclidean norm.

[0149] In this step, according to the Euclidean norm , obtain the accuracy compensation coefficient of pressure perception data Exemplary, accuracy compensation coefficient of pressure sensing data It can be obtained by the following formula:

[0150] Formula 5

[0151] in, is an exponential function with the natural number e as the base; Euclidean norm The larger the value, the smaller the external interference in the detection process, the higher the reliability of the pressure sensing data obtained, and the smaller the compensation required, that is, the accuracy compensation coefficient The smaller the value of ; on the contrary, it means that the reliability of pressure perception data is low, that is, the data accuracy is low, and it is necessary to compensate for the influence of external interference with greater force, that is, the accuracy compensation coefficient The bigger.

[0152] Fig.10 FIG. 1 is a flow chart showing a method for obtaining compensated pressure perception data according to an exemplary embodiment. Fig.10 As shown, the correcting the pressure perception data according to the accuracy compensation coefficient to obtain the compensated pressure perception data may include the following steps:

[0153] In step S601, the product of the accuracy compensation coefficient and the pressure sensing data is obtained.

[0154] In this step, obtain the accuracy compensation coefficient The product ZRD of the pressure sensing data RD.

[0155] In step S602, the product is used as the compensated pressure perception data.

[0156] In this step, the product ZRD is used as the compensated pressure perception data.

[0157] In summary, the embodiment of the present application provides a high-precision pressure sensing method based on a pressure detection probe, the method comprising: obtaining pressure sensing data of the pressure detection probe within a preset time length; obtaining a non-stationarity index of the pressure sensing data; obtaining an unpredictability index of the pressure sensing data based on the non-stationarity index of the pressure sensing data; obtaining a detection stability index of the pressure detection probe; obtaining an accuracy compensation coefficient of the pressure sensing data based on the unpredictability index and the detection stability index; correcting the pressure sensing data based on the accuracy compensation coefficient to obtain compensated pressure sensing data. The embodiment of the present application can improve the pressure detection accuracy of the pressure sensing method based on the pressure detection probe, thereby improving the supporting effect of the pressure detection data on medical diagnosis.

[0158] The present application also provides a computer-readable storage medium on which computer program instructions are stored. When the program instructions are executed by a processor, the steps of the high-precision pressure sensing method based on a pressure detection probe provided in the present application are implemented.

[0159] In another exemplary embodiment, a computer program product is also provided, which includes a computer program that can be executed by a programmable electronic device, and the computer program has a code portion for executing the above-mentioned high-precision pressure sensing method based on a pressure detection probe when executed by the programmable electronic device.

[0160] The above-mentioned embodiments only express several implementation methods of the present application, and the descriptions thereof are relatively specific and detailed, but they cannot be understood as limiting the scope of the present application. It should be pointed out that, for ordinary technicians in this field, several variations and improvements can be made without departing from the concept of the present application, and these all belong to the protection scope of the present application.

Claims

1. A high-precision pressure sensing method based on a pressure detection probe, characterized in that: The method comprises: Acquiring pressure sensing data of the pressure detection probe within a preset time period; Obtaining a non-stationary index of the pressure sensing data; Obtaining an unpredictability index of the pressure perception data according to the non-stationarity index of the pressure perception data; Obtaining a detection stability index of the pressure detection probe; Acquiring an accuracy compensation coefficient of the pressure sensing data according to the unpredictability index and the detection stability index; Correcting the pressure sensing data according to the accuracy compensation coefficient to obtain compensated pressure sensing data; The step of obtaining the non-stationary index of the pressure sensing data includes: Obtaining the time interval between two adjacent valley points on the left and right of the peak point of the peak signal; using the time interval as the sharpness of the peak signal of the pressure sensing data; Performing empirical mode decomposition on the pressure perception data to obtain a decomposition component signal set; using the last component signal in the decomposition component signal set as a baseline signal of the pressure perception data; Obtaining a slope data set of the baseline signal, the slope data set including the slope of a line segment formed by any two adjacent data points in the baseline signal; obtaining an absolute value of a difference between any two adjacent data points in the slope data set; obtaining an average of the sharpness of all peak signals of the pressure sensing data; and obtaining a non-stationary index of the pressure sensing data based on the absolute value and the average; The obtaining of the unpredictability index of the pressure perception data includes: Acquire a pressure perception curve of the pressure perception data; Acquire a respiratory frequency curve of the pressure sensing data; Obtaining a mean square error between the pressure perception curve and the respiratory rate curve; Obtaining an unpredictability index of the pressure sensing data according to the non-stationary index and the mean square error; The step of obtaining the accuracy compensation coefficient of the pressure sensing data includes: Obtaining the inverse of the unpredictability index; Obtaining the reciprocal of the unpredictability index and the Euclidean norm of the detection stability index; According to the Euclidean norm, an accuracy compensation coefficient of the pressure sensing data is obtained.

2. The high-precision pressure sensing method based on a pressure detection probe according to claim 1 is characterized in that: The obtaining of the detection stability index of the pressure detection probe comprises: Obtaining an environmental impact index of the pressure detection probe; Obtaining a vibration intensity index of the pressure detection probe; According to the environmental impact index and the vibration intensity index, a detection stability index of the pressure detection probe is obtained.

3. The high-precision pressure sensing method based on a pressure detection probe according to claim 2 is characterized in that: The step of obtaining the environmental impact index of the pressure detection probe includes: Obtaining the standard deviation of the temperature monitoring data within the preset time period; Obtaining the standard deviation of the humidity monitoring data within the preset time period; The environmental impact index of the pressure detection probe is obtained according to the standard deviation of the temperature monitoring data and the standard deviation of the humidity monitoring data.

4. The high-precision pressure sensing method based on a pressure detection probe according to claim 1 is characterized in that: The step of correcting the pressure sensing data according to the accuracy compensation coefficient to obtain compensated pressure sensing data includes: Obtaining the product of the accuracy compensation coefficient and the pressure sensing data; The product is used as the compensated pressure perception data.

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