A method for intelligent nursing monitoring of pregnant women before childbirth

Abstract

The present invention relates to the technical field of fetal heart rate monitoring, and in particular to a method for intelligent nursing monitoring of pregnant women before childbirth. The method selects sudden change peak packets and non-sudden change peak packets from two aspects: sudden change of curve fluctuation and relative deviation of extreme point values ​​between adjacent peak packets, based on the change characteristics of a fetal heart rate curve that suddenly rises or falls in a fetal hypoxic state; then, the contraction time period in which the contraction occurs is selected by analyzing the change of uterine contraction pressure in the contraction pressure curve; then, the reference sudden change degree of each sudden change peak packet is improved in combination with the temporal connection between each sudden change peak packet and each uterine contraction time period, so as to obtain an effective sudden change degree that is more accurate in measuring the sudden change of the fetal heart rate; and on the basis of the effective sudden change degree, a more accurate fetal heart rate abnormality degree is determined in combination with the relatively regular characteristics of non-sudden change peaks under normal circumstances, so that the abnormal fetal heart rate monitoring is more accurate, and the accuracy of nursing monitoring of pregnant women before childbirth is indirectly improved.

Description

Technical Field

[0001] The present invention relates to the technical field of fetal heart rate monitoring, and in particular to an intelligent nursing monitoring method for pregnant women before childbirth. Background Art

[0002] Fetal heart auscultation is a very important part of prenatal check-up, which can reflect the health status of the fetus. Fetal heart auscultation usually uses a Doppler fetal heart monitor to draw the fetal heart rate curve of pregnant women before delivery, and monitors abnormal changes in fetal heart rate according to the fluctuations of the fetal heart rate curve, so as to assist pregnant women in more reasonable prenatal care based on the monitoring results, and ensure the healthy growth of the fetus before delivery.

[0003] In the traditional monitoring method of abnormal fetal heart rate curve, the abnormal fetal heart rate is usually judged based on the overall amplitude level and fluctuation of the fetal heart rate curve. If the overall amplitude of the fetal heart rate curve is too high or too low, and the standard deviation of the fetal heart rate curve is too large, that is, the fluctuation is too large, it means that the fetal heart rate is abnormal during the monitoring process. However, pregnant women may occasionally experience uterine contractions before delivery, which will squeeze the activity space of the fetus, causing the fetus to suffer from short-term hypoxia, resulting in a certain degree of mutation in the fetal heart rate. At this time, the fetal heart rate caused by uterine contractions will suddenly change to a normal fetal heart rate change. The traditional method does not analyze the relationship between the change of fetal heart rate and uterine contractions, and directly reflects the abnormal condition of the fetal heart rate based on the fluctuation of the fetal heart rate curve, which reduces the accuracy of fetal heart rate abnormality monitoring. Summary of the invention

[0004] The present application provides an intelligent nursing monitoring method for pregnant women before childbirth. The method first selects sudden change peak packages and non-sudden change peak packages from two aspects: the sudden change of curve fluctuation and the relative deviation of the extreme point values ​​between adjacent peak packages based on the change characteristics of the fetal heart rate curve that will suddenly rise or fall in the fetal hypoxia state; then, the contraction time period when the contraction occurs is selected by analyzing the contraction pressure change in the contraction pressure curve; then, the reference sudden change degree of each sudden change peak package is improved in combination with the time connection between each sudden change peak package and each contraction time period, so as to obtain a more accurate effective sudden change degree for measuring the sudden change of fetal heart rate, and on the basis of the effective sudden change degree, a more accurate fetal heart rate abnormality degree is determined in combination with the relatively regular characteristics of non-sudden change peaks under normal circumstances, which solves the problem that the traditional method does not analyze the changing relationship between the fetal heart rate and the contraction phenomenon, and directly reflects the abnormal condition of the fetal heart rate according to the fluctuation degree of the fetal heart rate curve, so that the abnormal fetal heart rate monitoring is more accurate, and indirectly improves the accuracy of nursing monitoring for pregnant women before childbirth.

[0005] The present application provides a method for intelligent nursing monitoring of pregnant women before childbirth, the method comprising:

[0006] Obtain the fetal heart rate curve and uterine contraction pressure curve within the monitoring period;

[0007] According to the fetal heart rate fluctuation in the fetal heart rate curve, at least two fetal heart rate peak packages are screened out; according to the relative deviation of the extreme value values ​​between each fetal heart rate peak package and the adjacent fetal heart rate peak package, the peak-to-valley value deviation degree of each fetal heart rate peak package is determined;

[0008] Determine the reference sudden change degree of each fetal heart rate peak package according to the fluctuation mutation corresponding to each fetal heart rate peak package and the peak-to-valley value deviation degree; filter out the sudden change peak packages and non-sudden change peak packages in all fetal heart rate peak packages according to the reference sudden change degree;

[0009] Determine the uterine cavity pressure change rate at each sampling moment according to the deviation between the uterine contraction pressure at each sampling moment and the uterine contraction pressure at the previous sampling moment on the uterine contraction pressure curve; filter out all reference uterine contraction moments according to the uterine cavity pressure change rate; determine all uterine contraction time periods according to all sequentially continuous reference uterine contraction moments;

[0010] Determine the degree of contraction in each contraction period according to the standard deviation of contraction pressure fluctuation in each contraction period; determine the effective degree of sudden change of each sudden change peak packet according to the reference degree of sudden change of each sudden change peak packet and the degree of contraction in the contraction period adjacent in time sequence;

[0011] The stability of the fetal heart rate is determined based on the similarity of fetal heart rate changes between all non-sudden change peak packets; the abnormality of the fetal heart rate is determined based on the stability of the fetal heart rate and the effective sudden change degree of all sudden change peak packets; and intelligent prenatal care monitoring of pregnant women is performed based on the abnormality of the fetal heart rate.

[0012] Furthermore, the process of obtaining the fetal heart rate peak value package includes:

[0013] Acquire all extreme points of the fetal heart rate curve; in time sequence, take the maximum point where the previous extreme point and the next extreme point are both minimum points as the peak package maximum point; take the first minimum point before the peak package maximum point as the corresponding first minimum point; take the first minimum point after the peak package maximum point as the corresponding first minimum point as the second minimum point; on the fetal heart rate curve, take the local curve between the first minimum point and the second minimum point corresponding to each peak package maximum point as the fetal heart rate peak package.

[0014] Furthermore, the process of obtaining the peak-to-valley value deviation degree includes:

[0015] In time sequence, the difference between the fetal heart rate corresponding to the peak packet maximum point of each fetal heart rate peak packet and the fetal heart rate corresponding to the peak packet maximum point of the previous fetal heart rate peak packet is taken as the adjacent maximum deviation of each fetal heart rate peak packet;

[0016] The difference between the fetal heart rate corresponding to the first minimum point of each fetal heart rate peak packet and the fetal heart rate corresponding to the first minimum point of the previous fetal heart rate peak packet is used as the adjacent first minimum deviation of each fetal heart rate peak packet;

[0017] The difference between the fetal heart rate corresponding to the second minimum point of each fetal heart rate peak packet and the fetal heart rate corresponding to the second minimum point of the previous fetal heart rate peak packet is used as the adjacent second minimum deviation of each fetal heart rate peak packet;

[0018] The product of the adjacent maximum value deviation, the adjacent first minimum value deviation and the adjacent second minimum value deviation is used as the peak-to-valley value deviation degree of each fetal heart rate peak packet.

[0019] Furthermore, the process of obtaining the reference sudden change degree includes:

[0020] In each fetal heart rate peak packet, the mean value between the fetal heart rate corresponding to the first minimum point and the fetal heart rate corresponding to the second minimum point is used as the reference minimum value; the normalized value of the difference between the fetal heart rate corresponding to the peak packet maximum point of each fetal heart rate peak packet and the reference minimum value is used as the peak mutation degree of each fetal heart rate peak packet;

[0021] The normalized value of the product of the peak mutation degree and the peak-to-valley value deviation degree is used as the reference mutation degree of each fetal heart rate peak packet.

[0022] Furthermore, the process of obtaining the reference uterine contraction time includes:

[0023] Perform k-means cluster analysis on the uterine cavity pressure change rate at all sampling moments to obtain at least two uterine cavity pressure change rate clusters; calculate the mean uterine cavity pressure change rate of all sampling moments in each uterine cavity pressure change rate cluster; take all sampling moments in the uterine cavity pressure change rate cluster with the largest mean uterine cavity pressure change rate as reference uterine contraction moments.

[0024] Furthermore, the process of obtaining the degree of uterine contraction includes:

[0025] The average of the contraction pressures at all sampling moments in the contraction pressure curve is taken as the standard pressure; the difference between the contraction pressure at each sampling moment in each contraction time period and the standard pressure is taken as the local pressure standard deviation at each sampling moment in each contraction time period; the cumulative value of the local pressure standard deviations at all sampling moments in each contraction time period is normalized to determine the degree of contraction in each contraction time period.

[0026] Furthermore, the process of obtaining the effective sudden change degree includes:

[0027] The moment at which the peak packet maximum point corresponding to each sudden change peak packet is located is used as the peak reference moment of each sudden change peak packet; the time interval between the peak reference moment and the first sampling moment of each contraction time period is used as the timing association interval between each sudden change peak packet and each contraction time period; the cumulative value of the contraction degree of all contraction time periods whose timing association interval corresponding to each sudden change peak packet is less than a preset time interval threshold is used as the contraction influence degree corresponding to each sudden change peak packet;

[0028] The product of the negative correlation mapping value of the uterine contraction influence degree and the reference sudden change degree corresponding to each sudden change peak value package is used as the effective sudden change degree corresponding to each sudden change peak value package.

[0029] Furthermore, the process of obtaining the stability of the fetal heart rate includes:

[0030] Combining each non-sudden change peak packet with each other non-sudden change peak packet in turn to form a non-sudden change peak packet binary group; obtaining all non-sudden change peak packet binary groups; using the Pearson correlation coefficient of the two local curve segments corresponding to the two non-sudden change peak packets in each non-sudden change peak packet binary group in the fetal heart rate curve as the reference correlation of each non-sudden change peak packet binary group; using the mean of the reference correlations of all non-sudden change peak packet binary groups as the stability of the fetal heart rate.

[0031] Furthermore, the process of obtaining the degree of abnormal fetal heart rate includes:

[0032] The cumulative value of the effective sudden change degrees of all sudden change peak packets is used as the overall sudden change degree; the product between the negative correlation mapping value of the fetal heart rate stability degree and the overall sudden change degree is normalized to determine the abnormal degree of the fetal heart rate.

[0033] Furthermore, the process of performing intelligent nursing monitoring of pregnant women before delivery according to the abnormal degree of fetal heart rate includes:

[0034] When the degree of fetal heart rate abnormality is greater than a preset abnormal threshold, it is determined that the fetal heart rate is abnormal during prenatal care for pregnant women; when the degree of fetal heart rate abnormality is less than or equal to the preset abnormal threshold, it is determined that the fetal heart rate is normal during prenatal care for pregnant women.

[0035] This application has the following beneficial effects:

[0036] First of all, abnormal fetal heart rate usually stems from fetal hypoxia. In this state, the fetal heart rate curve will rise or fall suddenly, and the corresponding local heart rate curve is usually relatively more prominent and presents a larger heart rate change gap. Therefore, in the dimension where the local heart rate curve is usually relatively more prominent, the present application determines the degree of peak-to-valley value deviation according to the relative deviation of the extreme point values ​​between each fetal heart rate peak package and the adjacent fetal heart rate peak package. Based on the degree of peak-to-valley value deviation, in the dimension presenting a larger heart rate change gap, combined with the fluctuation mutation corresponding to each fetal heart rate peak package, the reference sudden change degree of each fetal heart rate peak package is determined, and combined with the reference sudden change degree, the sudden change peak packages with more abnormal fetal heart rate and the non-sudden change peak packages with relatively normal fetal heart rate are screened out.

[0037] For the sudden change peak in the fetal heart rate curve, that is, the curve segment where the fetus may be in an abnormal hypoxic state, the lower the sudden change degree of the sudden change peak package, the more normal the fetal heart rate; and since the hypoxic state may be a normal hypoxic state caused by uterine contractions, it may also be an abnormal hypoxic state caused by poor uterine blood circulation; only the abnormal hypoxic state can reflect the abnormality of the fetal heart rate, so it is necessary to correct the sudden change degree of each sudden change peak package in combination with the uterine contractions, so as to determine a more accurate effective sudden change degree.

[0038] In addition, the better the similarity between the non-sudden change peaks in the fetal heart rate curve, the more regular the fetal heart rate state is, and the corresponding fetal heart rate is healthier or more normal. Therefore, based on the effective sudden change degree, the fetal heart rate stability that characterizes the similarity between non-sudden change peaks is combined to comprehensively measure the degree of fetal heart rate abnormality, so that the obtained fetal heart rate abnormality degree is more accurate, which improves the accuracy of fetal heart rate abnormality monitoring and makes the accuracy of prenatal care monitoring of pregnant women higher. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the drawings required for use in the embodiments or the prior art descriptions are briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0040] Figure 1 A flow chart of a method for intelligent nursing and monitoring of pregnant women before childbirth provided by one embodiment of the present invention. DETAILED DESCRIPTION

[0041] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following is a detailed description of the specific implementation method, structure, characteristics and effects of a prenatal pregnant woman intelligent nursing monitoring method proposed by the present invention in combination with the accompanying drawings and preferred embodiments. In the following description, different "one embodiment" or "another embodiment" does not necessarily refer to the same embodiment, and the specific features, structures or characteristics in one or more embodiments may be combined in any suitable form. In addition, the terms "first" and "second" are used for descriptive purposes only and cannot be understood as implying or suggesting relative importance or implicitly indicating the number of technical features indicated. Therefore, the features defined as "first" and "second" may explicitly or implicitly include one or more of the features.

[0042] Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.

[0043] The specific scheme of the intelligent nursing monitoring method for pregnant women before childbirth provided by the present invention is described in detail below with reference to the accompanying drawings.

[0044] This application embodiment provides a method for intelligent nursing monitoring of pregnant women before childbirth. Figure 1 , which shows a flow chart of a method for intelligent nursing monitoring of pregnant women before childbirth provided by an embodiment of the present invention, the method comprising:

[0045] Step S101: Obtaining the fetal heart rate curve and uterine contraction pressure curve within the monitoring time period.

[0046] In a specific implementation of the embodiment of the present invention, a medical ultrasonic coupling agent is applied at the fetal heart position to facilitate the ultrasonic penetration of the Doppler fetal heart rate monitor; then the Doppler fetal heart rate monitor is placed at the fetal heart and the device is turned on to collect the fetal heart rate curve and the uterine contraction pressure curve within 20 minutes before the current moment, and the fetal heart rate at each sampling moment and the uterine contraction pressure curve at each sampling moment are obtained according to the fetal heart rate curve. The time interval between adjacent sampling moments is set to 0.1s, which can be adjusted according to the specific implementation environment; that is, the monitoring time period is set to 20 minutes before the current moment. It should be noted that in order to make the subsequent analysis of the fetal heart rate curve more accurate, the collected fetal heart rate curve is processed by the Douglas-Peucker algorithm, so as to smooth the redundant curve burrs while retaining the contour features of the fetal heart rate curve, that is, the fetal heart rate curves used in the embodiment of the present invention are all curves processed by the Douglas-Peucker algorithm; and the Douglas-Peucker algorithm is a technical means well known to those skilled in the art, and will not be further described here.

[0047] Step S102: Filter out at least two fetal heart rate peak packages according to the fetal heart rate fluctuation in the fetal heart rate curve; determine the peak-to-valley value deviation degree of each fetal heart rate peak package according to the relative deviation of the extreme point values ​​between each fetal heart rate peak package and the adjacent fetal heart rate peak package.

[0048] First, the abnormal fetal heart rate usually stems from the fetal hypoxia. In the hypoxic state, the fetal heart rate curve will rise or fall suddenly, and the corresponding local heart rate curve is usually more prominent and presents a large heart rate change gap. Therefore, in the dimension where the local heart rate curve is usually more prominent, the present application first extracts the fetal heart rate peak package representing the heart rate fluctuation in the fetal heart rate curve, and determines the peak-to-valley value deviation degree according to the relative deviation of the extreme value value between each fetal heart rate peak package and the adjacent fetal heart rate peak package.

[0049] Preferably, in some possible implementations of the embodiments of the present invention, the process of acquiring the fetal heart rate peak package includes:

[0050] Acquire all extreme points of the fetal heart rate curve; in time sequence, take the maximum point where both the previous extreme point and the next extreme point are minimum points as the peak package maximum point; take the first minimum point before the peak package maximum point as the corresponding first minimum point; take the first minimum point after the peak package maximum point as the corresponding first minimum point as the second minimum point; on the fetal heart rate curve, take the local curve between the first minimum point and the second minimum point corresponding to each peak package maximum point as the fetal heart rate peak package; the fetal heart rate peak package, that is, the local curve segment corresponding to each prominent peak on the fetal heart rate curve, usually corresponds to the maximum point as the peak point, and the two minimum points on both sides of the maximum are peak-valley points, the peak point and the peak-valley points on both sides together constitute a peak, that is, the fetal heart rate peak package; when the fetal heart rate is abnormal, the corresponding abnormality will be reflected in the peak package, so that the peak package has a larger fetal heart rate span and a larger amplitude change relative to the adjacent peak package.

[0051] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the peak-to-valley value deviation degree includes:

[0052] In time sequence, the difference between the fetal heart rate corresponding to the peak package maximum point of each fetal heart rate peak package and the fetal heart rate corresponding to the peak package maximum point of the previous fetal heart rate peak package is used as the adjacent maximum deviation of each fetal heart rate peak package; the difference between the fetal heart rate corresponding to the first minimum point of each fetal heart rate peak package and the fetal heart rate corresponding to the first minimum point of the previous fetal heart rate peak package is used as the adjacent first minimum deviation of each fetal heart rate peak package; the difference between the fetal heart rate corresponding to the second minimum point of each fetal heart rate peak package and the fetal heart rate corresponding to the second minimum point of the previous fetal heart rate peak package is used as the adjacent second minimum deviation of each fetal heart rate peak package. The sudden change peak generated under hypoxia will suddenly rise or fall, so the corresponding fetal heart rate peak packet will have a sudden change in amplitude in the fetal heart rate value. Therefore, for each fetal heart rate peak packet, the greater the deviation between the fetal heart rate of its corresponding feature point and the fetal heart rate of the feature point corresponding to the previous fetal heart rate peak packet, the greater the amplitude change of the corresponding fetal heart rate peak, and the more likely it is to have an abnormal change of sudden rise or sudden fall. Therefore, with the maximum point and two minimum points as feature points, the greater the corresponding adjacent maximum deviation, the greater the adjacent first minimum deviation, and the greater the adjacent second minimum deviation, the more likely the corresponding fetal heart rate peak packet will have an abnormal amplitude mutation, that is, the more likely it is a sudden change peak, and further the product of the adjacent maximum deviation, the adjacent first minimum deviation, and the adjacent second minimum deviation is used as the peak-to-valley deviation of each fetal heart rate peak packet, so that when the peak-to-valley deviation is greater, the corresponding fetal heart rate peak packet has a greater sudden change degree, and the more likely it is a sudden change peak.

[0053] In a specific implementation of the embodiment of the present invention, the process of obtaining the peak-to-valley value deviation degree is expressed by the formula: ;in, For the The degree of deviation of the peak-to-valley value of each fetal heart rate peak packet; For the The fetal heart rate corresponding to the peak value of the peak packet of the fetal heart rate peak packet For the The fetal heart rate corresponding to the first minimum point of the fetal heart rate peak package; For the The fetal heart rate corresponding to the second minimum point of the fetal heart rate peak package; For the The previous fetal heart rate peak packet, i.e., the The fetal heart rate corresponding to the peak value point of the fetal heart rate peak value package; For the The previous fetal heart rate peak packet, i.e., the The fetal heart rate corresponding to the first minimum point of the fetal heart rate peak package; For the The previous fetal heart rate peak packet, i.e., the The fetal heart rate corresponding to the second minimum point of the fetal heart rate peak package; For the The adjacent maximum deviation of each fetal heart rate peak packet; For the The deviation of the first adjacent minimum value of each fetal heart rate peak packet; For the It should be noted that, considering that the first fetal heart rate peak packet does not have the previous fetal heart rate peak packet, the peak-to-valley deviation degree of the first fetal heart rate peak packet is not calculated, and the corresponding peak-to-valley deviation degree is set to 0.

[0054] Step S103: Determine the reference sudden change degree of each fetal heart rate peak package according to the fluctuation mutation and peak-to-valley value deviation corresponding to each fetal heart rate peak package; and screen out sudden change peak packages and non-sudden change peak packages in all fetal heart rate peak packages according to the reference sudden change degree.

[0055] The peak-to-valley deviation degree characterizes the degree of sudden change of each fetal heart rate peak packet in the dimension where the local heart rate curve is relatively more prominent, thereby indirectly characterizing the corresponding abnormal fetal heart rate characteristics. At the same time, the sudden rise or fall of the fetal heart rate curve under hypoxia is usually accompanied by a large difference in fetal heart rate change. Therefore, based on this feature, on the basis of the calculated peak-to-valley deviation degree that characterizes the degree of sudden change, combined with the fluctuation mutation that characterizes the difference in fetal heart rate change corresponding to each fetal heart rate peak packet, the reference sudden change degree of each fetal heart rate peak packet is comprehensively determined; thereby, combined with the reference sudden change degree, the sudden change peak packets with more abnormal fetal heart rate and the non-sudden change peak packets with relatively normal fetal heart rate are screened out.

[0056] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the reference sudden change degree includes:

[0057] In each fetal heart rate peak packet, the mean value between the fetal heart rate corresponding to the first minimum point and the fetal heart rate corresponding to the second minimum point is used as the reference minimum value; the normalized value of the difference between the fetal heart rate corresponding to the peak packet maximum point of each fetal heart rate peak packet and the reference minimum value is used as the peak mutation degree of each fetal heart rate peak packet. For each peak packet, the greater the difference between its corresponding peak and valley values, the more it conforms to the peak packet sudden change characteristics. Therefore, the greater the difference between the fetal heart rate corresponding to the peak packet maximum point and the reference minimum value, the greater the corresponding peak mutation degree, and the greater the corresponding sudden change degree. Further combined with the characteristic that the greater the peak-to-valley deviation degree, the greater the sudden change degree of the corresponding fetal heart rate peak packet, the normalized value of the product between the peak mutation degree and the peak-to-valley deviation degree is used as the reference sudden change degree of each fetal heart rate peak packet; through normalization, the value of the reference sudden change degree is limited to 0 to 1, which is convenient for screening sudden change peak packets and non-sudden change peak packets.

[0058] In a specific implementation of the embodiment of the present invention, the process of obtaining the peak mutation degree is expressed by the formula: ;in, For the The peak mutation degree of each fetal heart rate peak package: For the The fetal heart rate corresponding to the peak value of the peak packet of the fetal heart rate peak packet For the The fetal heart rate corresponding to the first minimum point of the fetal heart rate peak package; For the The fetal heart rate corresponding to the second minimum point of the fetal heart rate peak package; For the The reference minimum value of each fetal heart rate peak packet; is the linear normalization function, is the absolute value symbol.

[0059] In a specific implementation of the embodiment of the present invention, the process of obtaining the reference sudden change degree is expressed by the formula: ;in, For the The reference sudden change degree of each fetal heart rate peak package; For the The degree of deviation of the peak-to-valley value of each fetal heart rate peak packet; For the The peak mutation degree of each fetal heart rate peak packet; is a linear normalization function.

[0060] As the reference sudden change degree increases, the corresponding fetal heart rate peak packet is more likely to have a sudden change, that is, it is more likely to be a hypoxic state curve segment where the fetal heart rate may be abnormal under a hypoxic state; therefore, the sudden change peak packet under abnormal fetal heart rate and the non-sudden change peak packet under normal fetal heart rate can be screened out according to the reference sudden change degree.

[0061] In a specific implementation of the embodiment of the present invention, the fetal heart rate peak packets whose corresponding reference sudden change degree is greater than the preset sudden change threshold are regarded as sudden change peak packets; other fetal heart rate peak packets other than the sudden change peak packets are regarded as non-sudden change peak packets. The preset sudden change threshold is set to 0.68, which can be adjusted according to the specific implementation environment.

[0062] Step S104: Determine the uterine cavity pressure change rate at each sampling moment based on the deviation between the uterine contraction pressure at each sampling moment and the uterine contraction pressure at the previous sampling moment on the uterine contraction pressure curve; filter out all reference uterine contraction moments based on the uterine cavity pressure change rate; determine all uterine contraction time periods based on all sequentially continuous reference uterine contraction moments.

[0063] For the sudden change peak in the fetal heart rate curve, that is, the curve segment where the fetus may have an abnormal hypoxia state, the lower the sudden change degree of the sudden change peak packet, the more normal the fetal heart rate; and since the hypoxia state may be a normal hypoxia state caused by uterine contraction, or an abnormal hypoxia state caused by poor uterine blood circulation; only the abnormal hypoxia state can reflect the abnormality of the fetal heart rate, it is necessary to correct the sudden change degree of each sudden change peak packet in combination with the uterine contraction phenomenon, so as to determine a more accurate effective sudden change degree. The time period when the uterine contraction phenomenon occurs can be determined based on the uterine contraction pressure curve; the uterine contraction phenomenon will cause a sudden increase in the pressure in the uterine cavity, so for each sampling moment, the greater the corresponding instantaneous change speed of the uterine cavity pressure, the higher the possibility of the occurrence of the uterine contraction phenomenon at the corresponding sampling moment, so according to the deviation between the uterine contraction pressure at each sampling moment on the uterine contraction pressure curve and the uterine contraction pressure at the previous sampling moment, the uterine cavity pressure change rate at each sampling moment is determined, so that when the uterine cavity pressure change rate is greater, the corresponding sampling moment is more likely to have a uterine contraction phenomenon. In a specific implementation of the embodiment of the present invention, on the uterine contraction pressure curve, the difference between the uterine contraction pressure at each sampling moment and the uterine contraction pressure at the previous sampling moment is normalized to determine the uterine cavity pressure change rate at each sampling moment; the corresponding uterine cavity pressure change rate acquisition process is expressed by the formula: ;in, The first The difference between the uterine contraction pressure at a sampling moment and the uterine contraction pressure at the previous sampling moment; is the maximum value of the difference between the uterine contraction pressure at each sampling moment on the uterine contraction pressure curve and the uterine contraction pressure at the previous sampling moment, that is, the maximum value of the difference corresponding to all sampling moments; right Normalize so that The value is limited to 0 to 1, which is convenient for subsequent reference to the screening of contraction timing.

[0064] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the reference uterine contraction time includes:

[0065] Perform k-means cluster analysis on the uterine cavity pressure change rate at all sampling moments to obtain at least two uterine cavity pressure change rate clustering clusters; calculate the mean of the uterine cavity pressure change rate at all sampling moments in each uterine cavity pressure change rate clustering cluster; use all sampling moments in the uterine cavity pressure change rate clustering cluster with the largest mean of the uterine cavity pressure change rate as reference contraction moments. In a specific implementation of an embodiment of the present invention, the number of clusters in the k-means clustering algorithm is set to 3, which can be adjusted according to the specific implementation environment, but should be a positive integer of at least 2; the uterine cavity pressure change rate clustering cluster with the largest mean of the uterine cavity pressure change rate is usually the sampling moment with a large uterine cavity pressure change rate and a relatively concentrated value, so it is analyzed as a reference contraction moment. It should be noted that the object of the k-means clustering analysis is only the uterine contraction pressure change rate at each sampling moment, and does not include the time dimension, which will not be further elaborated here. Further, all the contraction time periods are determined according to all the sequentially continuous reference contraction moments, that is, the sequentially adjacent reference contraction moments are combined into one contraction time period, indicating that there is a contraction phenomenon in the corresponding time period.

[0066] Step S105: Determine the contraction degree of each contraction time period according to the standard deviation of the contraction pressure fluctuation in each contraction time period; determine the effective sudden change degree of each sudden change peak packet according to the reference sudden change degree of each sudden change peak packet and the contraction degree of the contraction time period adjacent in time sequence.

[0067] Furthermore, in terms of correcting the sudden change degree of each sudden change peak package in combination with the uterine contraction phenomenon, it is necessary to quantify the degree of contraction in each contraction time period, and based on the degree of contraction, correct the reference sudden change degree of the sudden change peak package that may have an impact on the timing, so as to determine the effective sudden change degree.

[0068] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the degree of uterine contraction includes:

[0069] The average contraction pressure of all sampling moments in the contraction pressure curve is used as the standard pressure; the difference between the contraction pressure at each sampling moment in each contraction time period and the standard pressure is used as the standard deviation of the local pressure at each sampling moment in each contraction time period; the cumulative value of the standard deviation of the local pressure at all sampling moments in each contraction time period is normalized to determine the degree of contraction in each contraction time period. For the contraction time period that characterizes the contraction phenomenon, the greater the contraction degree, the greater the corresponding contraction pressure performance is usually. Therefore, the average contraction pressure of all sampling moments in the contraction pressure curve is used as the standard, and the degree of contraction is quantified according to the deviation of the contraction pressure at each moment in each contraction time period from the standard pressure, so that the greater the cumulative value of the standard deviation of the local pressure at all sampling moments in each contraction time period, the greater the corresponding contraction pressure performance, that is, the greater the degree of contraction.

[0070] In a specific implementation of the embodiment of the present invention, the process of obtaining the degree of uterine contraction is expressed by the formula: ;in, For the The degree of uterine contractions during each contraction period; For the The number of sampling moments in each contraction time period is also the corresponding number of reference contraction moments; For the The first contraction in the Uterine contraction pressure at each sampling moment; is the average value of uterine contraction pressure at all sampling moments in the uterine contraction pressure curve, i.e., standard pressure; For the The first contraction in the The standard deviation of the local pressure at each sampling moment; is the linear normalization function, is the absolute value symbol.

[0071] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the effective sudden change degree includes:

[0072] The moment at which the peak packet maximum point corresponding to each sudden change peak packet is located is used as the peak reference moment of each sudden change peak packet; the time interval between the peak reference moment and the first sampling moment of each contraction time period is used as the timing association interval between each sudden change peak packet and each contraction time period; the cumulative value of the contraction degree of all contraction time periods whose timing association interval corresponding to each sudden change peak packet is less than the preset time interval threshold is used as the contraction influence degree corresponding to each sudden change peak packet. In a specific implementation of the embodiment of the present invention, the preset time interval threshold is set to 1min, which can be adjusted at will.

[0073] For each sudden change peak packet, if it is affected by uterine contraction, the time interval between the time period when the uterine contraction phenomenon occurs and the time period when the sudden change peak packet occurs is small. Therefore, after determining the peak reference time representing the time when the sudden change peak packet occurs and the first sampling time corresponding to the time when the uterine contraction time period occurs, the size of the timing correlation interval determined by the time interval between the peak reference time and the first sampling time of each uterine contraction time period is used to determine whether there is a correlation influence; when the timing correlation interval is small, it means that the time interval between the corresponding uterine contraction time period and the corresponding sudden change peak packet is small, indicating that the corresponding sudden change peak packet may be affected by the uterine contraction phenomenon; therefore, by setting a preset time interval threshold, all the uterine contraction time periods of each sudden change peak packet with a timing correlation interval less than the preset time interval threshold are used as the uterine contraction time period that affects the sudden change of the sudden change peak packet, so the uterine contraction degrees of all the uterine contraction time periods that have an impact are accumulated to determine the comprehensive influence degree of each sudden change peak packet affected by the uterine contraction, that is, the uterine contraction influence degree. The greater the corresponding uterine contraction influence degree, the greater the sudden change phenomenon of the sudden change peak packet is affected by the uterine contraction, and the corresponding sudden change degree should be smaller. Therefore, the product of the negative correlation mapping value of the degree of influence of uterine contraction and the reference sudden change degree corresponding to each sudden change peak package is further taken as the effective sudden change degree corresponding to each sudden change peak package, so that the process of obtaining the effective sudden change degree can be combined with the influence of uterine contraction phenomenon, making the subsequent analysis more accurate; and the greater the effective sudden change degree, the more obvious the abnormal hypoxia state caused by poor uterine blood circulation is, and the more abnormal the corresponding fetal heart rate is.

[0074] In a specific implementation of the embodiment of the present invention, the process of obtaining the effective sudden change degree is expressed by the formula: ;in, For the The effective sudden change degree of each fetal heart rate peak packet; For the The reference sudden change degree of each fetal heart rate peak package; For the The number of all uterine contraction time periods corresponding to the timing correlation intervals that are smaller than the preset time interval threshold among all timing correlation intervals corresponding to the fetal heart rate peak packets; For the The first time series correlation interval corresponding to all time series correlation intervals corresponding to the fetal heart rate peak package that is smaller than the preset time interval threshold The degree of uterine contractions during each contraction period; For the The degree of influence of uterine contraction corresponding to each fetal heart rate peak package; is a linear normalization function.

[0075] Step S106: Determine the stability of the fetal heart rate based on the similarity of fetal heart rate changes between all non-sudden change peak packets; determine the degree of fetal heart rate abnormality based on the stability of the fetal heart rate and the effective sudden change degree of all sudden change peak packets; and perform intelligent prenatal nursing monitoring of pregnant women based on the degree of fetal heart rate abnormality.

[0076] In addition, the better the similarity between the non-sudden change peaks in the fetal heart rate curve, the more regular the fetal heart rate state is, and the corresponding fetal heart rate is healthier or more normal. Therefore, based on the effective sudden change degree, the fetal heart rate stability that characterizes the similarity between non-sudden change peaks is combined to comprehensively measure the degree of fetal heart rate abnormality, so that the obtained fetal heart rate abnormality degree is more accurate, which improves the accuracy of fetal heart rate abnormality monitoring and makes the accuracy of prenatal care monitoring of pregnant women higher.

[0077] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the stability of the fetal heart rate includes:

[0078] Each non-sudden change peak packet is sequentially combined with each other non-sudden change peak packet to form a non-sudden change peak packet binary group; all non-sudden change peak packet binary groups are obtained; the Pearson correlation coefficient of the two non-sudden change peak packets in each non-sudden change peak packet binary group corresponding to the two local curve segments in the fetal heart rate curve is used as the reference correlation of each non-sudden change peak packet binary group; the mean of the reference correlation of all non-sudden change peak packet binary groups is used as the stability of the fetal heart rate. The non-sudden change peak packet represents the change of the fetal heart rate under normal conditions, and the corresponding fetal heart rate is usually more regular under normal conditions. Therefore, the higher the similarity between the two non-sudden change peaks, that is, the larger the overall Pearson correlation coefficient of the two non-sudden change peak packets in each non-sudden change peak packet binary group corresponding to the two local curve segments in the fetal heart rate curve, the more normal the corresponding fetal heart rate is. Therefore, the smaller the mean of the reference correlation of all non-sudden change peak packet binary groups, that is, the smaller the stability of the fetal heart rate, the more unstable the fetal heart rate, and the more abnormal the corresponding fetal heart rate.

[0079] Preferably, in some possible implementations of the embodiments of the present invention, the process of obtaining the degree of abnormal fetal heart rate includes:

[0080] Since the smaller the stability of the fetal heart rate, the greater the effective sudden change degree of each sudden change peak, the more abnormal the corresponding fetal heart rate; therefore, the cumulative value of the effective sudden change degree of all sudden change peak packets is further used as the overall sudden change degree; the product between the negative correlation mapping value of the fetal heart rate stability and the overall sudden change degree is normalized to determine the abnormal degree of the fetal heart rate. In a specific implementation of an embodiment of the present invention, the process of obtaining the abnormal degree of the fetal heart rate is expressed by the formula: ;in, The degree of abnormal fetal heart rate; is the number of non-sudden peak packet pairs; For the The Pearson correlation coefficient of the two local curve segments corresponding to the two non-sudden change peak packets in the non-sudden change peak packet binary group in the fetal heart rate curve, that is, The reference correlation of the non-sudden peak packet pairs; The stability of fetal heart rate; is the number of sudden peak packets; For the The effective sudden change degree of each sudden change peak packet; is the overall degree of sudden change; is an exponential function with a natural constant as base; is a linear normalization function.

[0081] The greater the degree of fetal heart rate abnormality, the more abnormal the corresponding fetal heart rate; therefore, intelligent prenatal care monitoring of pregnant women is further performed according to the degree of fetal heart rate abnormality, specifically including: when the degree of fetal heart rate abnormality is greater than the preset abnormal threshold, it is determined that the fetal heart rate is abnormal during the prenatal care of pregnant women; when the degree of fetal heart rate abnormality is less than or equal to the preset abnormal threshold, it is determined that the fetal heart rate is normal during the prenatal care of pregnant women. In a specific implementation of an embodiment of the present invention, the preset abnormal threshold is set to 0.53, which can be adjusted according to the specific implementation environment. When the fetal heart rate is normal during the prenatal care of pregnant women, it indicates that the fetus is in good health; conversely, when the fetal heart rate is abnormal during the prenatal care of pregnant women, it indicates that the fetus is in poor health and a comprehensive examination of the physical condition of the pregnant women is required.

[0082] In summary, an intelligent nursing monitoring method for antenatal pregnant women selects sudden change peak packages and non-sudden change peak packages from two aspects: the sudden change of curve fluctuation and the relative deviation of the extreme point values ​​between adjacent peak packages based on the change characteristics of the fetal heart rate curve that will suddenly rise or fall under the fetal hypoxia state; then the contraction time period when the contraction occurs is selected by analyzing the change of the contraction pressure in the contraction pressure curve; then, the reference sudden change degree of each sudden change peak package is improved in combination with the temporal connection between each sudden change peak package and each contraction time period, so as to obtain a more accurate effective sudden change degree for measuring the sudden change of the fetal heart rate, and on the basis of the effective sudden change degree, a more accurate fetal heart rate abnormality degree is determined in combination with the relatively regular characteristics of the non-sudden change peak under normal circumstances, which solves the problem that the traditional method does not analyze the changing relationship between the fetal heart rate and the contraction phenomenon, and directly reflects the abnormal condition of the fetal heart rate according to the fluctuation degree of the fetal heart rate curve, so that the abnormal fetal heart rate monitoring is more accurate, and the accuracy of antenatal nursing monitoring of pregnant women is indirectly improved.

[0083] It should be noted that the sequence of the above embodiments of the present invention is only for description and does not represent the advantages and disadvantages of the embodiments. The processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0084] The various embodiments in this specification are described in a progressive manner, and the same or similar parts between the various embodiments can be referenced to each other, and each embodiment focuses on the differences from other embodiments.

Claims

1. A method for intelligent nursing monitoring of pregnant women before childbirth, characterized in that: The method comprises: Obtain the fetal heart rate curve and uterine contraction pressure curve within the monitoring period; According to the fetal heart rate fluctuation in the fetal heart rate curve, at least two fetal heart rate peak packages are screened out; according to the relative deviation of the extreme value values ​​between each fetal heart rate peak package and the adjacent fetal heart rate peak package, the peak-to-valley value deviation degree of each fetal heart rate peak package is determined; Determine the reference sudden change degree of each fetal heart rate peak package according to the fluctuation mutation corresponding to each fetal heart rate peak package and the peak-to-valley value deviation degree; filter out the sudden change peak packages and non-sudden change peak packages in all fetal heart rate peak packages according to the reference sudden change degree; Determine the uterine cavity pressure change rate at each sampling moment according to the deviation between the uterine contraction pressure at each sampling moment and the uterine contraction pressure at the previous sampling moment on the uterine contraction pressure curve; filter out all reference uterine contraction moments according to the uterine cavity pressure change rate; determine all uterine contraction time periods according to all sequentially continuous reference uterine contraction moments; Determine the degree of contraction in each contraction period according to the standard deviation of contraction pressure fluctuation in each contraction period; determine the effective degree of sudden change of each sudden change peak packet according to the reference degree of sudden change of each sudden change peak packet and the degree of contraction in the contraction period adjacent in time sequence; Determine the stability of the fetal heart rate according to the similarity of fetal heart rate changes between all non-sudden change peak packets; determine the abnormality of the fetal heart rate according to the stability of the fetal heart rate and the effective sudden change degree of all sudden change peak packets; perform intelligent nursing monitoring of pregnant women before delivery according to the abnormality of the fetal heart rate; The process of obtaining the fetal heart rate peak value package includes: Acquire all extreme points of the fetal heart rate curve; in time sequence, take the maximum point where the previous extreme point and the next extreme point are both minimum points as the peak package maximum point; take the first minimum point before the peak package maximum point as the corresponding first minimum point; take the first minimum point after the peak package maximum point as the corresponding first minimum point as the second minimum point; on the fetal heart rate curve, take the local curve between the first minimum point and the second minimum point corresponding to each peak package maximum point as the fetal heart rate peak package; The process of obtaining the peak-to-valley value deviation degree includes: In time sequence, the difference between the fetal heart rate corresponding to the peak packet maximum point of each fetal heart rate peak packet and the fetal heart rate corresponding to the peak packet maximum point of the previous fetal heart rate peak packet is taken as the adjacent maximum deviation of each fetal heart rate peak packet; The difference between the fetal heart rate corresponding to the first minimum point of each fetal heart rate peak packet and the fetal heart rate corresponding to the first minimum point of the previous fetal heart rate peak packet is used as the adjacent first minimum deviation of each fetal heart rate peak packet; The difference between the fetal heart rate corresponding to the second minimum point of each fetal heart rate peak packet and the fetal heart rate corresponding to the second minimum point of the previous fetal heart rate peak packet is used as the adjacent second minimum deviation of each fetal heart rate peak packet; The product of the adjacent maximum value deviation, the adjacent first minimum value deviation and the adjacent second minimum value deviation is used as the peak-to-valley value deviation degree of each fetal heart rate peak packet.

2. The method for intelligent nursing and monitoring of pregnant women before childbirth according to claim 1, characterized in that: The process of obtaining the reference sudden change degree includes: In each fetal heart rate peak packet, the mean value between the fetal heart rate corresponding to the first minimum point and the fetal heart rate corresponding to the second minimum point is used as the reference minimum value; the normalized value of the difference between the fetal heart rate corresponding to the peak packet maximum point of each fetal heart rate peak packet and the reference minimum value is used as the peak mutation degree of each fetal heart rate peak packet; The normalized value of the product of the peak mutation degree and the peak-to-valley value deviation degree is used as the reference mutation degree of each fetal heart rate peak packet.

3. The method for intelligent nursing and monitoring of pregnant women before childbirth according to claim 1, characterized in that: The process of obtaining the reference uterine contraction time comprises: Perform k-means cluster analysis on the uterine cavity pressure change rate at all sampling moments to obtain at least two uterine cavity pressure change rate clusters; calculate the mean uterine cavity pressure change rate of all sampling moments in each uterine cavity pressure change rate cluster; take all sampling moments in the uterine cavity pressure change rate cluster with the largest mean uterine cavity pressure change rate as reference uterine contraction moments.

4. The method for intelligent nursing and monitoring of pregnant women before childbirth according to claim 1, characterized in that: The process of obtaining the degree of uterine contraction includes: The average of the contraction pressures at all sampling moments in the contraction pressure curve is taken as the standard pressure; the difference between the contraction pressure at each sampling moment in each contraction time period and the standard pressure is taken as the local pressure standard deviation at each sampling moment in each contraction time period; the cumulative value of the local pressure standard deviations at all sampling moments in each contraction time period is normalized to determine the degree of contraction in each contraction time period.

5. The method for intelligent nursing and monitoring of pregnant women before childbirth according to claim 1, characterized in that: The process of obtaining the effective sudden change degree includes: The moment at which the peak packet maximum point corresponding to each sudden change peak packet is located is used as the peak reference moment of each sudden change peak packet; the time interval between the peak reference moment and the first sampling moment of each contraction time period is used as the timing association interval between each sudden change peak packet and each contraction time period; the cumulative value of the contraction degree of all contraction time periods whose timing association interval corresponding to each sudden change peak packet is less than a preset time interval threshold is used as the contraction influence degree corresponding to each sudden change peak packet; The product of the negative correlation mapping value of the uterine contraction influence degree and the reference sudden change degree corresponding to each sudden change peak value package is used as the effective sudden change degree corresponding to each sudden change peak value package.

6. The method for intelligent nursing and monitoring of pregnant women before childbirth according to claim 1, characterized in that: The process of obtaining the fetal heart rate stability includes: Combining each non-sudden change peak packet with each other non-sudden change peak packet in turn to form a non-sudden change peak packet binary group; obtaining all non-sudden change peak packet binary groups; using the Pearson correlation coefficient of the two local curve segments corresponding to the two non-sudden change peak packets in each non-sudden change peak packet binary group in the fetal heart rate curve as the reference correlation of each non-sudden change peak packet binary group; using the mean of the reference correlations of all non-sudden change peak packet binary groups as the stability of the fetal heart rate.

7. The method for intelligent nursing and monitoring of pregnant women before childbirth according to claim 1, characterized in that: The process of obtaining the degree of fetal heart rate abnormality includes: The cumulative value of the effective sudden change degrees of all sudden change peak packets is used as the overall sudden change degree; the product between the negative correlation mapping value of the fetal heart rate stability degree and the overall sudden change degree is normalized to determine the abnormal degree of the fetal heart rate.

8. The method for intelligent nursing and monitoring of pregnant women before childbirth according to claim 1, characterized in that: The process of performing intelligent nursing monitoring of pregnant women before delivery according to the abnormal degree of fetal heart rate includes: When the degree of fetal heart rate abnormality is greater than a preset abnormal threshold, it is determined that the fetal heart rate is abnormal during prenatal care for pregnant women; when the degree of fetal heart rate abnormality is less than or equal to the preset abnormal threshold, it is determined that the fetal heart rate is normal during prenatal care for pregnant women.

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