Computer-implemented method and electronic system for predicting a delivery time

Abstract

A computer-implemented method for predicting the delivery time of a pregnant woman, including detecting at least one body parameter of the pregnant woman at multiple points in time, a calculation unit carrying out a pattern recognition with regard to the development of the at least one body parameter over time, and calculating a predicted delivery time or delivery period based on the pattern recognition. An electronic system for predicting the delivery time of a pregnant woman is also disclosed.

Claims

1. A computer-implemented method for predicting the delivery time of a pregnant woman, comprising the steps of: detecting at least two body parameters of said pregnant woman (1) at multiple points in time; carrying out a pattern recognition by a calculation unit with regard to the development of said at least two body parameters over time; and calculating a predicted delivery time or delivery period by the calculation unit based on said pattern recognition; wherein at least one of said at least two body parameters is a substance concentration in a body fluid of said pregnant woman; and wherein at least another of said at least two body parameters is a vital parameter.

2. The computer-implemented method according to claim 1, wherein the substance concentration is of at least one of the following substances: corticotropin-releasing hormone, adrenocorticotropic hormone, cortisol, progesterone, estrogen, inflammatory cytokines, prostaglandin, glucocorticoids, dehydroepiandrosterone, C-reactive protein, leukocytes, and/or oxytocin.

3. The computer-implemented method according to claim 1, wherein the vital parameter is, a heart rate, a blood flow, a body temperature, a breathing frequency, an electrical resistance of the skin, and/or a blood pressure, of the pregnant woman (1).

4. The computer-implemented method according to claim 1, further comprising detecting a manual input of an additionally determined body parameter wherein the additionally determined body parameter is a contraction frequency and/or at least one parameter from a cardiotocography, and wherein calculating a predicted delivery time or delivery period includes taking into account said additionally determined body parameter.

5. The computer-implemented method according to claim 1, wherein said pattern recognition comprises a recognition of correlations in the developments of the at least two body parameters.

6. The computer-implemented method according to claim 1, further comprising displaying the predicted delivery time or delivery period with a display at least three days prior to the predicted delivery time.

7. The computer-implemented method according to claim 1, further comprising selecting a body parameter or parameters for detection in dependence on a time remaining until the predicted delivery time or delivery period.

8. The computer-implemented method according to claim 1, further comprising detecting an actual delivery time in an automated manner or by manual input, and evaluating a plurality of data sets of detected body parameters in their development over time towards the actual delivery time for recognizing patterns, storing said patterns, and providing said patterns for pattern recognition.

9. The computer-implemented method according to claim 1, further comprising storing specific parameters relating to said pregnant woman or her environment, and weighting of said pattern recognition in dependence of said specific parameters.

10. An electronic system for predicting the delivery time of a pregnant woman (1), comprising: at least one sensor (2, 3, 4) configured for detecting at least two variable body parameter and a calculation unit configured to determine a predicted delivery time or delivery period on a basis of a pattern recognition in a development over time of said at least two variable body parameters detected by the at least one sensor; wherein at least one of said at least two variable body parameters is a substance concentration in a body fluid of said pregnant woman; and wherein at least another of said at least two variable body parameters is a vital parameter.

11. The electronic system according to claim 10, further comprising a wearable device (4, 5, 6) comprising a bracelet (5), wherein said at least one sensor (2, 3, 4) is arranged in said wearable device (4, 5, 6), and wherein said at least one sensor (2, 3, 4) is a heart rate sensor, a blood flow sensor, a temperature sensor, a skin resistance sensor, and/or an acceleration sensor.

12. The electronic system according to claim 10, further comprising an evaluation unit (6) in which said at least one sensor (3) is arranged, wherein the at least one sensor is a biosensor for a body fluid.

13. The electronic system according to claim 10, further comprising an input field (10) via which a measured body parameter is recordable by manual input.

14. The electronic system according to claim 10, wherein said at least one sensor (2, 3, 4) is connectable to a server (9) by way of a communication unit which is configured to transmit data corresponding to at least some of said at least two variable body parameters detected by said at least one sensor to said server (9) and to obtain from said server (9) the result of said pattern recognition regarding said transmitted data.

15. A client-server system for predicting the delivery time of a pregnant woman, comprising: a client formed by the electronic system according to claim 10, and a server (9) configured to compare data corresponding to at least some of said at least two variable body parameters detected by the client with patterns and correlations stored on said server (9) and to use said comparison to calculate the predicted delivery time or delivery period.

16. A computer-implemented method according to claim 1, wherein the substance concentration is of progesterone and the vital parameter is a body temperature of the pregnant woman (1).

17. A computer-implemented method according to claim 5, wherein the substance concentration is of progesterone and the vital parameter is a body temperature of the pregnant woman (1).

18. A computer-implemented method according to claim 1, wherein the body fluid is saliva.

19. A computer-implemented method according to claim 16, wherein the body fluid is saliva.

Description

[0035] The invention shall be explained hereafter using an exemplary embodiment with reference to the following figures:

[0036] FIG. 1 shows an embodiment of an electronic system according to the invention with a pregnant woman,

[0037] FIG. 2 shows the chronological sequence of the changes in body parameters that may be used as a basis for pattern recognition for predicting the delivery time or delivery period in embodiments of the method and the system according to the invention.

[0038] FIG. 1 shows a pregnant woman 1 with an embodiment of an electronic system for predicting the delivery time. The electronic system comprises several sensors 2, 3, 4 with which body parameters of the pregnant woman may be detected. In particular, this is a sensor 2 in a bracelet 5 for detecting vital parameters, in particular heart rate, blood flow, body temperature, electrical resistance of the skin, and/or blood pressure.

[0039] A further sensor 3 is arranged in an evaluation unit 6. This sensor may be, for example, a photo sensor which evaluates test strips inserted into the evaluation unit. The test strips in particular may have been exposed to a body fluid of the pregnant woman and may have different local color changes with regard to substance concentrations which may then be detected by the photo sensor so that one substance concentration in the body fluid or several substance concentrations may be determined. Alternatively, sensor 3 may be a biosensor with which substance concentrations in a body fluid of the pregnant woman may be determined directly.

[0040] Further sensor 4 may be arranged in a waist belt 7. It may be used to determine further vital parameters, such as breathing frequency or labor frequency, or body parameters of the unborn child.

[0041] Bracelet 5, evaluation unit 6, and/or waist belt 7 may each be provided with a radio module with which the detected body parameters may be transmitted. In particular, the detected body parameters may be transmitted to a smartphone 8 and combined there. Alternatively, however, it is also possible for the data to be received and combined in one or all of bracelet 5, evaluation unit 6, or waist belt 7. Smartphone 8, bracelet 5, evaluation unit 6, and/or waist belt 7 comprise a calculation unit which is configured to determine a predicted delivery time or delivery period based on pattern recognition from one or more detected body parameters. Alternatively, the body parameters determined may be transmitted to a server 9 and the pattern recognition can be carried out on the server. Furthermore, smartphone 8, bracelet 5, evaluation unit 6, and/or waist belt 7 may comprise a display unit 10 on which the predicted delivery time or delivery period is displayed. Alternatively or additionally, a notification may be given, for example, by audio signal or vibration of smartphone 8, waist belt 7, evaluation unit 6, and/or bracelet 5.

[0042] FIG. 2 shows the cascading sequence leading up to the start of labor, with relevant body parameters being indicated. A prediction according to the invention of the delivery time or delivery period may be carried out by detecting these body parameters at least in part, at least in the sections of the sequence in which these body parameters are relevant, in particular show significant changes. An organized equilibrium (OG) between pregnancy-maintaining and labor-promoting body parameters arises during pregnancy. Auto-, para- and endocrine processes play a role there (HH-NNR of the mother or the fetus and from the fetomaternal boundary region). Further relevant body parameters are the neurotransmitter CRH, the steroid hormones progesterone and estrogen, the glucocorticoids, oxytocin, as well as the prostaglandins, cytokines, etc.

[0043] Labor-promoting hormones are in particular CRH, ACTH, DHEA, estrogen, estradiol, cytokines IL-1β, IL-6, IL-8, prostaglandin PGE.sub.2 PGF.sub.2, and oxytocin.

[0044] Labor-inhibiting hormones and mediators are in particular progesterone and prostacyclin PGI.sub.2.

[0045] Changes in the fetal membranes (ruptured membranes), the myometrium (contraction) and the cervix (ripening) are relevant for triggering labor. The processes that lead to these changes shall be described below.

[0046] The basic process of labor induction follows a cascading process that may lead to a shift in the organized balance (OG) and may thus lead to delivery that is early, on-time or after the date. The closer the delivery, the greater the changes in the tissue (decidua, myometrium, cervix), which are mainly an expression of inflammation or infection with changes in the microbiological and macrobiological region and may be determined by way of body parameters indicative of inflammation or infection.

[0047] The following body parameters should advantageously be taken into account:

[0048] I. Release of CRH and maturation of fetal HH-NNR

[0049] II. Inflammation or infections, respectively

[0050] III. Shift in the progesterone-estrogen ratio

[0051] IV. Increased prostaglandin synthesis

[0052] V. Increase in intrauterine pressure

[0053] VI. Release of oxytocin

[0054] In the microbiological field, qualitative and quantitative changes in the spectrum of germs (bacteria, viruses, fungi, etc.) may occur. Likewise, the metabolism of the germs, e.g. the protease formation—with an effect on the arachidonic and citric acid cycle—has a significant influence. In the macrobiological field—i.e. in humans—the processes taking place in close connection with the microbiological field trigger an immunological cascade with cell-bound and humoral responses (cytokines, etc.). This may be determined by way of suitable body parameters. In detail:

[0055] I. Release of CRH and Maturation of Fetal HH-NNR

[0056] During pregnancy, corticotropin-releasing hormone (CRH) is produced in tissues of the fetomaternal boundary region, the placenta, the chorion, the cells of the amnion, and the decidua. In the fetus, this leads to maturation of the fetal HH-NMR and production of adrenocorticotropic hormone (ACTH) in the fetal anterior pituitary gland. This in turn leads to increased release of cortisol, the concentration of which may be determined as a body parameter. Furthermore, the increased cortisol level activates inflammatory cells and thereby releases more inflammatory cytokines and prostaglandins, the concentrations of which may be determined as body parameters. CRH also has a prostaglandin-enhancing effect and, at higher levels, leads to vasodilatation and an increase in myometrial contractility.

[0057] II. Inflammation or Infections, Respectively

[0058] The cortisol level increased according to the aforementioned mechanisms or as a side access due to an infection in the body (e.g. periodontal disease or the amnion due to pathogenic or potentially pathogenic germs) leads to local inflammation in infections and generally to a release of cytokines such as −1, −6, −8, −10, −12, etc. or tumor necrosis factors and factors stimulating granulocyte colonies. An increase in the number of leukocytes is one of the consequences. Together with the inflammation-induced stimulation of arachidonic acid metabolism, prostaglandin production is increased, which may be determined in the context of body parameter detection. This leads to cervical ripening and (premature) labor. The inflammation at the egg pole as part of the amnion infection also leads to damage to the egg membranes and increases the risk of ruptured membranes.

[0059] III. Shift in the Progesterone-Estrogen Ratio

[0060] The production of ACTH increases the release of the estrogen precursor dehydroepiandrosterone (DHEA). Glucocorticoids may also be indicative of the onset of labor. DHEAS increases in parallel with estrogen towards the end of pregnancy. This shifts the progesterone-estrogen ratio towards an overbalance of estrogen. This has two implications. Estrogen has a contraction-promoting effect on the α-receptors and has a positive influence on the prostaglandin and oxytocin receptors in the myometrium. Progesterone, on the other hand, activates the β-receptors, which induces a relaxing effect. Progesterone has a suppressive effect on gap junction synthesis as well as on CRH production. There is also a drop in progesterone production in the placenta towards the end of the pregnancy, which in turn is another building block that promotes delivery and also has an effect on thermogenesis.

[0061] IV. Increased Prostaglandin Synthesis

[0062] Progesterone is converted to estrogen in the placenta and stimulates the production of prostaglandin F.sub.2α (PGF.sub.2α) in the myometrium. The prostaglandins induce contractions in the myometrium, thereby increasing the intrauterine pressure and causing vasodilation of the myometrium. They also influence cervical ripening and spontaneous rupture of membranes.

[0063] V. Increase in Intrauterine Pressure

[0064] The intrauterine stretching stimulus leads to cell hyperplasia and cell hypertrophy in the myometrium and to an increase in the expression of contraction-associated proteins (GAP junctions connexin H3) as well as to impairment of the tear strength of the amnions.

[0065] VI. Release of Oxytocin

[0066] The dilation of the cervix leads to the release of oxytocin from the maternal posterior pituitary gland. The oxytocin, in turn, stimulates prostaglandin synthesis and induces additional contractions of the myometrium to fully expel the fetus from the uterus.

[0067] In particular, the following substances or their concentrations may be detected as physical parameters: CRH, ACTH, cortisol, cytokines, prostaglandins, DHEA/DHEAS, estrogen, a receptor, progesterone, β receptor, and/or oxytocin. With the onset of labor, the muscle cells of the uterus have gap junctions whereby they are connected to form a syncytium and may contract synchronously.

[0068] The processes shown in FIG. 2 lead to vasodilatation, cell hyperplasia, cell hypertrophy of the myometrium, contractility of the myometrium, cervical ripening, and/or spontaneous rupture of membranes. These events are in turn direct precursors to the onset of labor.

[0069] There are also side accesses in the labor cascade, which may also be detected by determining body parameters:

[0070] A. Stress or Hypoxic-Ischemic Lesions of the Placenta

[0071] Chronic maternal stress may prematurely activate the fetal HH-NNR axis in that CRH release is activated and cytokines are released. As the pregnancy progresses, desensitization to an increased CRH level may arise and the stress trauma may thus be reduced.

[0072] B. Effects of Circadian Rhythm on Interleukin IL-β and TNF

[0073] There is increased activity of the myometrium in the second half of the night and in the early morning, as well as an increase in progesterone and DHEAS levels, as well as maternal estradiol and progesterone fluctuations.

[0074] The aforementioned changes in the pregnant woman's body are reflected in her body parameters, either directly, for example, by the substance concentration of a hormone, or indirectly, for example, by the change in a vital parameter. An inflammatory reaction may lead to increased body temperature and/or altered heart rate values. The detection of at least one body parameter over time and/or of several different body parameters and a related pattern recognition, in particular with regard to correlations between the body parameters, may therefore enable exact prediction of the delivery time or delivery period.