A wearable ovulation monitoring device and method

Abstract

The application discloses a wearable ovulation monitoring device and method, and relates to the technical field of monitoring equipment. The device comprises a wearable main body and an ultrasonic probe. The device uses the ultrasonic probe to obtain ultrasonic images of the ovary and multiple follicles in the ovary of a measured object at different monitoring periods. An ultrasonic image processing unit extracts ovulation parameters, including the ovary volume, follicle volume, follicle liquid content and follicle wall thickness, from the ultrasonic images. An ovulation prediction unit determines the growth speed and growth stage according to the ovulation parameters, and generates and outputs ovulation monitoring results using corresponding development evaluation models and ovulation prediction models. The application uses a portable elastic bellyband as the main carrier for follicle monitoring. The ultrasonic probe is installed on the bellyband, which is used on the abdomen. The device has the characteristics of small size, portability, simple operation and easy mastery. The processor can realize accurate estimation of the ovulation period and provide guidance for planned pregnancy or contraception.

Description

Technical Field

[0001] The present invention relates to the technical field of monitoring equipment, and in particular to a wearable ovulation monitoring device and method. Background Art

[0002] The growth and development of ovarian follicles is a gradual process. During a normal menstrual cycle, women typically develop only one dominant follicle. Continuous ultrasound monitoring reveals the follicle's growth phase before ovulation, allowing for its gradual growth and development. Based on a 28-day menstrual cycle, a dominant follicle, approximately 12 mm in size and oval in shape, appears around day 10. The follicle grows at a rate of 2-3 mm per day, and ovulation is imminent when it reaches 18 mm or larger. Patients who monitor their follicles can monitor their growth and development daily to manage intercourse schedules.

[0003] For infertile patients who use ovulation-inducing drugs to stimulate follicle growth and development, the ovarian images monitored by the device can also be used to check the number of follicles, adjust the dosage of ovulation-inducing drugs, and determine the time of ovulation, thereby guiding sexual intercourse.

[0004] Traditional follicle monitoring requires the use of large equipment in hospitals, forcing patients to frequently visit hospitals throughout their menstrual cycle and face waiting in line for payment and examinations, which consumes considerable time and energy. Furthermore, multiple people using the same vaginal B-ultrasound probe can create a risk of cross-infection. Traditional vaginal B-ultrasound monitors are expensive for hospitals and require high technical skills from testing personnel. To address these issues, a wearable ovulation monitoring device and method have been developed to address them. Summary of the Invention

[0005] In view of the defects in the prior art, the present invention provides a wearable ovulation monitoring device and method to solve the problems of high cost and inconvenience of existing ovulation monitoring.

[0006] On the one hand, a wearable ovulation monitoring device is provided, comprising a wearable body and a sensor probe, wherein a button is provided on the outside of the wearable body, a processor, an Internet of Things module, and a lithium battery power supply are provided inside the wearable body, and the sensor probe comprises an ultrasonic probe, wherein the ultrasonic probe, the Internet of Things module, and the button are respectively connected to the processor;

[0007] The ultrasonic probe is used to obtain ultrasonic images of the ovary and multiple follicles contained in the ovary of the subject at different monitoring periods;

[0008] The processor includes an ultrasonic image processing unit and an ovulation prediction unit;

[0009] The ultrasonic image processing unit is configured to extract ovulation parameters from the ultrasonic image, the ovulation parameters including ovary volume, follicle volume, follicle fluid content, and follicle wall thickness.

[0010] The ovulation prediction unit is configured to determine a growth rate according to the ovulation parameters, determine a growth stage according to the growth rate parameter, retrieve a development evaluation model and an ovulation prediction model corresponding to the growth stage, and generate and output an ovulation monitoring result.

[0011] Preferably, the wearable main body comprises an elastic bellyband, both ends of the elastic bellyband are provided with a sticky elastic cloth, and the sensor probe, the Internet of Things module, the key, and the processor are arranged in the middle part of the elastic bellyband.

[0012] Preferably, the middle part of the elastic bellyband is further provided with a reminding module, the reminding module comprises an indicator light and a buzzer, and the indicator light and the buzzer are connected with the processor, respectively.

[0013] Preferably, the Internet of Things module is a WIFI communication Internet of Things module.

[0014] Preferably, the extraction of the ovulation parameters from the ultrasonic image comprises:

[0015] The ultrasonic image is preprocessed;

[0016] The preprocessed ultrasonic image is segmented to determine a follicle region map and an ovary region map;

[0017] The ovulation parameters are extracted from the follicle region map and the ovary region map.

[0018] Preferably, the extraction of the ovulation parameters from the follicle region map and the ovary region map comprises:

[0019] The follicle region map is layered to obtain a follicle hierarchical map, the outer contour of each follicle hierarchical map is refitted, and a first area of the refitted graph is calculated, and the follicle volume is determined according to the first area;

[0020] The inner contour of each follicle hierarchical map is refitted, and a second area of the refitted graph is calculated, and the follicle wall thickness is determined according to the difference between the first area and the second area;

[0021] The contour of the anechoic region in each follicle hierarchical map is refitted, and a third area of the refitted graph is calculated, and the follicle fluid content is determined according to the third area;

[0022] The ovarian region graph is layered to obtain an ovarian hierarchical graph, each ovarian hierarchical graph is refitted, and a fourth area of the refitted graph is calculated, and the ovarian volume is determined according to the fourth area.

[0023] As preferred, the extracting the ovulation parameter from the ultrasonic image further comprises: determining a segmentation parameter according to the follicle long diameter, the segmentation parameter comprising a slice thickness and a slice interval, and layering the follicle region graph according to the segmentation parameter.

[0024] As preferred, the growth speed is determined according to the ovulation parameter, the growth stage is determined according to the growth speed parameter, the development evaluation model and the ovulation prediction model corresponding to the growth stage are called, and the ovulation monitoring result is generated and outputted, comprising:

[0025] The follicle volume, the follicle liquid content and the follicle wall thickness of different periods are inputted into the follicle evaluation model to obtain a follicle change index, and the ovarian volume of different periods is inputted into the ovarian evaluation model to obtain an ovarian change index;

[0026] The growth speed is calculated according to the ovarian change index and the follicle change index;

[0027] The development stage is determined according to the growth speed, and the development evaluation model corresponding to the development stage is called;

[0028] The follicle volume, the follicle liquid content, the follicle wall thickness and the ovarian volume of different periods are respectively inputted into the development evaluation model to obtain a development evaluation value;

[0029] Whether the follicle development is normal is judged according to the development evaluation value and the development evaluation threshold value corresponding to the development stage;

[0030] When the follicle development is normal, the ovulation prediction model corresponding to the development stage is called, the follicle volume, the follicle liquid content, the follicle wall thickness and the ovarian volume of different periods are respectively inputted into the ovulation prediction model to obtain an estimated ovulation period.

[0031] In another aspect, a wearable ovulation monitoring method comprises:

[0032] Obtaining ultrasonic images of an ovary and multiple follicles wrapped by the ovary of a measured object at different monitoring periods;

[0033] Extracting an ovulation parameter from the ultrasonic image, the ovulation parameter comprising an ovarian volume, a follicle volume, a follicle liquid content and a follicle wall thickness; determining a growth speed according to the ovulation parameter, determining a growth stage according to the growth speed parameter, calling a development evaluation model and an ovulation prediction model corresponding to the growth stage, and generating and outputting an ovulation monitoring result.

[0034] As a preference, it also includes:

[0035] Displaying the ultrasound image and ovulation monitoring evaluation results via a mobile terminal;

[0036] Generate pregnancy timing prompts based on ovulation monitoring results to assist pregnancy or contraception.

[0037] The beneficial effects of the present invention are embodied in the following: The present invention provides a wearable ovulation monitoring device, comprising a wearable body and a sensor probe. The wearable body has a button, and internally houses a processor, an Internet of Things module, and a lithium battery power supply. The device uses an ultrasonic probe to acquire ultrasonic images of the subject's ovaries and multiple follicles within the ovaries at different monitoring periods. An ultrasonic image processing unit extracts ovulation parameters from the ultrasonic images, including ovarian volume, follicular volume, follicular fluid content, and follicular wall thickness. An ovulation prediction unit determines growth rate and stage based on these ovulation parameters, and uses corresponding developmental assessment models and ovulation prediction models to generate and output ovulation monitoring results. The present invention adopts a portable elastic abdominal belt as the main carrier for follicle monitoring. An ultrasonic probe is installed on it and it is attached to the abdomen for use. It is small and portable, and easy to operate and master. It can significantly reduce the number of times patients go to the hospital for treatment, reduce the relevant expenses of patients visiting the hospital, and alleviate the economic burden. It can obtain ultrasonic images of multiple periods through the ultrasonic probe, extract multiple ovulation parameters, predict ovulation through developmental assessment and ovulation prediction models, and provide corresponding monitoring results, which can help women understand their own ovulation status and play a certain guiding role in planning pregnancy or contraception.

[0038] In addition, the present invention also provides a wearable ovulation monitoring method. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] To more clearly illustrate the specific embodiments of the present invention or the technical solutions in the prior art, the following briefly describes the drawings required for the specific embodiments or the description of the prior art. Similar elements or parts are generally identified by similar reference numerals throughout the drawings. Elements or parts in the drawings are not necessarily drawn to scale.

[0040] Figure 1 A schematic structural diagram of a wearable ovulation monitoring device provided by an embodiment of the present invention;

[0041] Figure 2 A structural diagram of a wearable ovulation monitoring method provided by an embodiment of the present invention. DETAILED DESCRIPTION

[0042] The following embodiments of the technical solution of the present invention will be described in detail with reference to the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention and are therefore only examples and are not intended to limit the scope of protection of the present invention.

[0043] It should be noted that, unless otherwise specified, the technical or scientific terms used in this application should have the common meanings understood by those skilled in the art to which the present invention belongs.

[0044] Example 1

[0045] like Figure 1 As shown, an embodiment of the present invention provides a wearable ovulation monitoring device, comprising a wearable body and a sensor probe, wherein a button is provided on the outside of the wearable body, and a processor, an Internet of Things module, and a lithium battery power supply are provided inside the wearable body. The sensor probe comprises an ultrasonic probe, and the ultrasonic probe, Internet of Things module, and button are respectively connected to the processor; the ultrasonic probe is used to obtain ultrasonic images of the ovaries and multiple follicles contained in the ovaries of the subject at different monitoring periods, monitoring at least two periods. The ovulation cycle and ovulation day cannot be determined by monitoring only one period; the processor comprises an ultrasonic image processing unit and an ovulation prediction unit. The ultrasonic image processing unit is used to extract ovulation parameters from the ultrasonic image, wherein the ovulation parameters include ovarian volume, follicular volume, follicular fluid content, and follicular wall thickness; the ovulation prediction unit is used to determine the growth rate based on the ovulation parameters, determine the growth stage based on the growth rate parameters, retrieve the development assessment model and ovulation prediction model corresponding to the growth stage, and generate and output the ovulation monitoring results.

[0046] In an embodiment of the present invention, the Internet of Things module can adopt an Internet of Things module for WIFI communication. The data transmission rate of WIFI communication is relatively high, and the transmission speed of ultrasound images is fast. If WIFI is not connected to the Internet, only short-range communication can be carried out, and the monitoring information cannot be sent to the hospital or the terminal of the user being tested. If WIFI is connected to the Internet, long-range communication can be carried out.

[0047] In an embodiment of the present invention, the wearable body includes an elastic abdominal belt, both ends of the elastic abdominal belt are provided with adhesive elastic fabric, and the sensor probe, Internet of Things module, button and processor are all arranged in the middle of the elastic abdominal belt.

[0048] The design of the elastic abdominal belt can provide a comfortable wearing experience, making the user feel comfortable and free during use. Its material can be any one of soft elastic fiber materials (such as elastic fiber, elastic yarn, etc.), spandex, latex, etc., which are not shown in this embodiment. The sticky elastic fabrics set at both ends can ensure that the abdominal belt is firmly fixed on the body and is not easy to slide or loosen, thereby providing a stable wearing experience. At the same time, the sensor probe, Internet of Things module, buttons and processor are concentrated in the middle of the abdominal belt, so that users can easily operate and access related functions without the need for additional equipment or cables. Users can move freely and are not restricted to fixed positions. The operation is simple and convenient.

[0049] In order to improve the functionality and user experience of the wearable body, a reminder module is also provided in the middle of the elastic abdominal belt. The reminder module includes an indicator light and a buzzer. The indicator light and the buzzer are respectively connected to the processor. Through the real-time feedback provided by the indicator light and the buzzer, the user can immediately understand important information or reminders without relying on other external devices or checking display screens, such as information such as the predicted ovulation day.

[0050] In an embodiment of the present invention, extracting ovulation parameters from the ultrasound image includes: preprocessing the ultrasound image; wherein the preprocessing includes operations such as noise, smoothing and enhancement. By preprocessing the ultrasound image, the quality and clarity of the image are improved to provide basic support for subsequent processing. Specifically, denoising can be reduced by filtering algorithms such as median filtering, Gaussian filtering, etc. to reduce noise in the image. Enhancement can use methods such as histogram equalization and contrast enhancement; the preprocessed ultrasound image is segmented to determine the follicle area map and the ovary area map; the follicle area map is layered to obtain a follicle layer map, the outer contour of the follicle in each follicle layer map is refitted and the first area of ​​the refitted figure is calculated, and the follicle volume is determined based on the first area; the inner contour of the follicle in each follicle layer map is refitted and the second area of ​​the fitted figure is calculated, and the follicle wall thickness is determined based on the difference between the first area and the second area; the contour of the echo-free zone in each follicle layer map is refitted and the third area of ​​the refitted figure is calculated, and the follicle fluid content is determined based on the third area; the ovary area map is layered to obtain an ovary layer map, each ovary layer map is refitted and the fourth area of ​​the refitted figure is calculated, and the ovary volume is determined based on the fourth area.

[0051] In an embodiment of the present invention, extracting ovulation parameters from the ultrasonic image further includes: determining segmentation parameters according to the long diameter of the follicle, the segmentation parameters including slice thickness and slice interval, and stratifying the follicle region map according to the segmentation parameters.

[0052] The thickness of the slice can affect the accuracy, thinner slices can provide more detailed information, but may require more slices and calculations, thicker slices can speed up the calculation, but may lose some details. According to the needs, the appropriate slice thickness can be selected. And the interval between the slices will also affect the results, smaller intervals can provide more accurate volume estimates, but the amount of calculation will increase, larger intervals can speed up the calculation, but may introduce some errors. Therefore, when layering the follicle area graph and the ovary area graph, the actual ovary and follicle length needs to be considered, the target segmentation thickness of the two is determined according to the follicle length, then the segmentation interval under the same segmentation quality is determined as the target segmentation interval from the segmentation thickness-segmentation interval-segmentation quality mapping table according to the target segmentation thickness, and then layering is performed according to the target segmentation thickness and the target segmentation interval.

[0053] In the embodiment of the present application, the growth rate is determined according to the ovulation parameters, the growth stage is determined according to the growth rate parameters, the development evaluation model and the ovulation prediction model corresponding to the growth stage are called, and the ovulation monitoring result is generated and output, including: inputting the follicle volume, follicular fluid content and follicle wall thickness of different periods into the follicle evaluation model to obtain a follicle change index, and inputting the ovary volume of different periods into the ovary evaluation model to obtain an ovary change index; the growth rate is calculated by weighting the ovary change index and the follicle change index; the development stage is determined according to the growth rate, and the development evaluation model corresponding to the development stage is called; the follicle volume, follicular fluid content, follicle wall thickness and ovary volume of different periods are input into the development evaluation model respectively to obtain a development evaluation value; whether the follicle development is normal is judged according to the development evaluation value and the development evaluation threshold value corresponding to the development stage; when the follicle development is normal, the ovulation prediction model corresponding to the development stage is called, and the follicle volume, follicular fluid content, follicle wall thickness and ovary volume of different periods are input into the ovulation prediction model respectively to obtain a predicted ovulation period.

[0054] Specifically, the growth stage of the follicle can be divided into a slow growth primary growth stage and a mature stage with faster growth rate, and different stages correspond to different growth rates. The existing method indicates the growth rate of the follicle by mm / d, that is, by the average growth length. The follicle length is one of the parameters, and it is not the only factor that determines the growth rate. Therefore, the method of the present embodiment can provide more comprehensive, accurate and detailed information by comprehensively considering the follicle volume, follicular fluid content, follicle wall thickness and ovary volume to evaluate the growth rate, which helps to better understand the development of the follicle and the ovulation cycle.

[0055] Specifically, during normal ovulation, the dominant follicle grows at an average rate of 1-2 mm / day after its appearance until ovulation completes. Prior to ovulation, the average follicle diameter ranges from 18-25 mm, with an average of 22 mm. After ovulation, the follicle collapses, changing from an oval, plump shape to a shrunken one, with a small, fluid-filled dark area visible within the rectouterine fossa. In small follicle syndrome, after the dominant follicle appears, its average growth rate is ≤1 mm / day, and its morphology is essentially normal. After the follicle reaches 14-16 mm in diameter, it stops growing and disappears 24-48 hours later. During normal ovulation, the BBT increases within 48 hours after ovulation or on the day of ovulation. The BBT is biphasic, with the high-temperature phase lasting 11-13 days. In small follicle syndrome, the BBT is either atypically biphasic or uniphasic. In patients with atypical biphasic syndrome, the high-temperature phase rises slowly, reaching a plateau after 2-3 days. The BBT is elevated by 0.2-0.3°C compared to the previous phase and lasts for 9-10 days.

[0056] Therefore, in some embodiments, in order to better determine the abnormality type of the subject, the wearable ovulation monitoring device of the present application can be interconnected. If an abnormality occurs, basal body temperature monitoring is performed, and the abnormality type is determined based on the basal body temperature monitoring. Auxiliary treatment for ovulation abnormality can be performed based on the abnormality type.

[0057] In summary, the present invention provides a wearable ovulation monitoring device comprising a wearable body and a sensor probe. The wearable body has buttons, a processor, an Internet of Things module, and a lithium battery power supply. The device uses an ultrasonic probe to obtain ultrasonic images of the ovaries and multiple follicles within the ovaries of the subject at different monitoring periods. An ultrasonic image processing unit extracts ovulation parameters from the ultrasonic images, including ovarian volume, follicular volume, follicular fluid content, and follicular wall thickness. An ovulation prediction unit determines growth rate and growth stage based on these ovulation parameters, and generates and outputs ovulation monitoring results using corresponding developmental assessment models and ovulation prediction models. The present invention uses a portable elastic abdominal belt as the main carrier for follicle monitoring. By mounting an ultrasonic probe on the belt and applying it to the abdomen, the device is compact, portable, and easy to operate. It can significantly reduce the number of hospital visits for patients and reduce the associated hospital costs, alleviating the financial burden. The device can obtain ultrasonic images at multiple periods using the ultrasonic probe, extract multiple ovulation parameters, predict ovulation using developmental assessment and ovulation prediction models, and provide corresponding monitoring results, which can help women understand their ovulation status and provide guidance for pregnancy planning or contraception.

[0058] Example 2

[0059] like Figure 2As shown, an embodiment of the present invention provides a wearable ovulation monitoring method, which obtains ultrasonic images of the ovaries and multiple follicles enclosed by the ovaries of the subject at different monitoring periods; extracts ovulation parameters from the ultrasonic images, and the ovulation parameters include ovarian volume, follicular volume, follicular fluid content and follicular wall thickness; determines the growth rate according to the ovulation parameters, determines the growth stage according to the growth rate parameters, calls the development assessment model and ovulation prediction model corresponding to the generation stage, and generates and outputs the ovulation monitoring results.

[0060] In an embodiment of the present invention, the method further includes: displaying the ultrasonic image and ovulation monitoring evaluation results through a mobile terminal; and generating a pregnancy timing prompt based on the ovulation monitoring results to assist pregnancy or contraception.

[0061] The wearable ovulation monitoring method provided in an embodiment of the present invention and the wearable ovulation monitoring device provided in the above embodiment are based on the same inventive concept. For more specific working principles of each step in the embodiment of the present invention, please refer to the above embodiment and will not be repeated in the embodiment of the present invention.

[0062] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit it. Although the present invention has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some or all of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the scope of the technical solutions of the embodiments of the present invention, and they should all be included in the scope of the claims and description of the present invention.

Claims

1. A wearable ovulation monitoring device, characterized in that: The wearable device comprises a wearable body and a sensor probe, wherein a button is provided on the outside of the wearable body, a processor, an Internet of Things module and a lithium battery power supply are provided inside the wearable body, and the sensor probe comprises an ultrasonic probe, and the ultrasonic probe, the Internet of Things module and the button are respectively connected to the processor; The ultrasonic probe is used to obtain ultrasonic images of the ovary and multiple follicles contained in the ovary of the subject at different monitoring periods; The processor includes an ultrasonic image processing unit and an ovulation prediction unit; The ultrasonic image processing unit is used to extract ovulation parameters from the ultrasonic image, wherein the ovulation parameters include ovarian volume, follicular volume, follicular fluid content and follicular wall thickness; The ovulation prediction unit is used to determine the growth rate according to the ovulation parameter, determine the growth stage according to the growth rate parameter, call the development assessment model and ovulation prediction model corresponding to the growth stage, and generate and output the ovulation monitoring result; Extracting ovulation parameters from the ultrasound image includes: Preprocessing the ultrasonic image; Segmenting the pre-processed ultrasound image to determine the follicle region map and the ovary region map; Extracting ovulation parameters from the follicle region map and the ovary region map; Extracting ovulation parameters from the follicle region map and the ovary region map includes: The follicle region map is layered to obtain a follicle layer map, the outer contour of the follicle in each follicle layer map is refitted and a first area of ​​the refitted figure is calculated, and the follicle volume is determined according to the first area; Refitting the inner contour of the follicle in each follicle layer map and calculating the second area of ​​the fitted map, and determining the follicle wall thickness according to the difference between the first area and the second area; refitting the contour of the anechoic area in each follicle layer image and calculating the third area of ​​the refitted image, and determining the follicular fluid content according to the third area; The ovarian region map is layered to obtain an ovarian hierarchical map, each ovarian hierarchical map is refitted and a fourth area of ​​the refitted map is calculated, and the ovarian volume is determined according to the fourth area.

2. A wearable ovulation monitoring device according to claim 1, characterized in that: The wearable main body includes an elastic abdominal belt, both ends of which are provided with adhesive elastic fabrics, and the sensor probe, Internet of Things module, button and processor are all arranged in the middle of the elastic abdominal belt.

3. A wearable ovulation monitoring device according to claim 2, characterized in that: A reminder module is also provided in the middle of the elastic abdominal belt. The reminder module includes an indicator light and a buzzer. The indicator light and the buzzer are respectively connected to the processor.

4. A wearable ovulation monitoring device according to claim 3, characterized in that: The Internet of Things module adopts an Internet of Things module for WIFI communication.

5. A wearable ovulation monitoring device according to claim 1, characterized in that: Extracting ovulation parameters from the ultrasonic image further includes: determining segmentation parameters according to the long diameter of the follicle, the segmentation parameters including slice thickness and slice interval, and stratifying the follicle region map according to the segmentation parameters.

6. A wearable ovulation monitoring device according to claim 5, characterized in that: Determining the growth rate according to the ovulation parameter, determining the growth stage according to the growth rate parameter, retrieving the development assessment model and ovulation prediction model corresponding to the growth stage, and generating and outputting the ovulation monitoring result, including: Inputting the follicle volume, follicular fluid content and follicle wall thickness at different stages into the follicle evaluation model to obtain the follicle change index, and inputting the ovarian volume at different stages into the ovarian evaluation model to obtain the ovarian change index; Calculating the growth rate based on the weighted ovarian change index and follicle change index; determining a developmental stage according to the growth rate, and retrieving a developmental assessment model corresponding to the developmental stage; The follicle volume, follicular fluid content, follicle wall thickness and ovarian volume at different stages are input into the development assessment model to obtain a development assessment value; Determine whether the follicle development is normal according to the development assessment value and the development assessment threshold corresponding to the development stage; When the follicle development is normal, the ovulation prediction model corresponding to the development stage is called, and the follicle volume, follicular fluid content, follicle wall thickness and ovarian volume at different stages are input into the ovulation prediction model respectively to obtain the estimated ovulation period.

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