Vagina elasticity measuring and detecting device and method based on visual marker analysis

Abstract

The invention discloses a vaginal elasticity measuring and detecting device based on visual marker analysis, which comprises a black fixed array unit, a biocompatible transparent elastic silica gel layer, a transparent rigid support body, an integrated camera module, an illumination array and a gas pressure adjusting unit, and is characterized in that the gas pressure adjusting unit is used for dynamically adjusting the internal gas pressure; the invention also provides a detection method which comprises the following steps: acquiring normal data; a detection device is placed in and initialized; adjusting air pressure to make the silica gel layer fit the vaginal wall; a mark point deformation image is collected and compared with normal data; and identifying the boundary of the anatomical partition of the vaginal wall through the semantic segmentation model. The device has the advantages of being simple in structure, convenient to prepare, low in cost, high in dissection adaptability and high in detection resolution; the balance between high-precision detection and patient safety is realized, and an innovative tool is provided for quantitative evaluation of pelvic floor dysfunction.

Description

Technical Field

[0001] The present invention relates to the technical field of vaginal elasticity measurement, and in particular to a vaginal elasticity measurement and detection device and method based on visual marker analysis. Background Art

[0002] Vaginal laxity is a common problem in women after childbirth or with pelvic floor dysfunction, and is closely associated with decreased sexual quality, urinary incontinence, and pelvic organ prolapse. However, existing assessment methods have significant limitations in objectivity, functionality, and accessibility, necessitating the development of new testing technologies to fill these clinical gaps.

[0003] Currently, the assessment of vaginal relaxation mainly relies on subjective methods and imaging techniques. Subjective assessments, such as gynecological palpation and patient self-assessment scales, are simple to perform but are subject to interference from physician experience and patient psychological factors, and lack quantitative standards. Pelvic floor muscle strength tests, while able to grade muscle strength, cannot reflect the state of passive relaxation. Among imaging techniques, ultrasound and MRI can observe the pelvic floor anatomy, but the former has difficulty quantifying vaginal wall elasticity, while the latter is expensive and cannot simulate deformation under dynamic pressure loads. Functional devices, such as pressure feedback probes, can only measure active systolic pressure, while bioelectrical impedance analysis is subject to interference from physiological status, and neither can fully assess the degree of relaxation.

[0004] The core problems of the existing technology are:

[0005] First, it lacks objectivity and relies on subjective experience or static anatomical data;

[0006] Second, functional assessment is missing, ignoring the true relaxation performance in dynamic scenarios such as sexual activity and increased abdominal pressure;

[0007] Third, invasive procedures cause discomfort to patients and reduce screening compliance;

[0008] Fourth, high-cost imaging equipment makes it difficult to popularize primary medical care.

[0009] With the refinement of women's health management, especially the surge in demand for postpartum rehabilitation and sexual dysfunction treatment, the market urgently needs a precise quantitative, non-invasive, dynamic and low-cost detection tool. Summary of the Invention

[0010] In order to overcome the disadvantages of existing technologies such as lack of objectivity, lack of functional evaluation, and high cost, the present invention provides a vaginal elasticity measurement and detection device and method based on visual marker analysis, which has the advantages of strong anatomical adaptability, high detection resolution, and convenient operation, providing an innovative solution for the quantitative assessment of pelvic floor dysfunction.

[0011] To achieve the above objectives, the present invention provides the following technical solution: a vaginal elasticity measurement and detection device based on visual marker analysis, comprising:

[0012] A black fixed array unit, having a black protruding fixed structure and a biocompatible black marking layer on its surface. The biocompatible black marking layer serves as a marking point in visual imaging. The area of the marking point changes with pressure and vaginal elasticity and is used to calculate the area contacted by the black fixed array unit through an image processing module;

[0013] A biocompatible transparent elastic silicone layer forms a dynamic contact interface with the black fixed array unit and is integrally cast with the black fixed array unit through a mold;

[0014] A transparent rigid support body for integrating a camera module and an LED lighting array, wherein the camera module and the LED lighting array cooperate with each other to capture images of the interior of the vagina;

[0015] A gas pressure regulating unit is connected to the internal cavity of the silicone layer and is used to dynamically regulate the internal gas pressure.

[0016] Preferably, the black protruding structural fixing structure is an axially distributed gradually changing elastic barb in the shape of a triangular pyramid.

[0017] Preferably, the biocompatible black marking layer is made of a mixture of a medical silica gel matrix and nano-carbon powder.

[0018] Preferably, elastic fibers are embedded in the biocompatible transparent elastic silicone layer to suppress axial deformation and enhance structural stability.

[0019] Preferably, the gas pressure regulating unit includes a micro air pressure sensor, a micro air pump and a PID control module, and adopts a closed-loop dynamic control strategy to regulate the air pressure.

[0020] Preferably, the camera module includes an adjustable focus lens with a frame rate of not less than 60fps; the LED lighting array achieves uniform lighting through a light guide plate.

[0021] The present invention also provides a detection method of a vaginal elasticity measurement detection device based on visual marker analysis, comprising the following steps:

[0022] S1. Collect normal data

[0023] S2. Insert the detection device and initialize it;

[0024] S3. Adjust the air pressure so that the silicone layer fits the vaginal wall;

[0025] S4, collecting deformation images of the marker points and comparing them with normal data;

[0026] S5. Identify the anatomical boundaries of the vaginal wall through a semantic segmentation model.

[0027] Preferably, the semantic segmentation model training method comprises the following steps:

[0028] a) First, the pixel-level label data of the vaginal wall anatomical partitions are annotated to generate a dataset;

[0029] b) Apply random elastic deformation and brightness perturbation to perform data augmentation, and then use the semantic segmentation model to identify the six anatomical partition boundaries,

[0030] c) Using a hybrid loss function to optimize the model;

[0031] d) Use the semantic segmentation model and the optimizer to train and optimize the model, setting the initial learning rate and weight decay.

[0032] Compared with the prior art, the present invention has the following beneficial effects:

[0033] 1. Through modular design and manufacturing methods, the present invention realizes a vaginal elasticity measurement and detection device based on visual marker analysis with simple structure, convenient preparation, low cost, strong anatomical adaptability, and high detection resolution, providing an innovative solution for the quantitative assessment of pelvic floor dysfunction.

[0034] 2. The present invention balances detection accuracy and patient comfort through the closed-loop control strategy of the gas pressure regulating unit and the flexible fitting design of the biocompatible transparent elastic silicone layer; the internal air pressure of the silicone layer is dynamically adjusted to adapt to different vaginal morphologies and reduce measurement errors caused by individual differences; the transparent rigid support body integrates a high-frame rate camera and uniform LED lighting to avoid obstruction and interference of traditional invasive detection on tissue structures; the gradient elastic barb and elastic fiber reinforcement design ensure the fixation stability of the device while minimizing the risk of mechanical damage to the tissue. BRIEF DESCRIPTION OF THE DRAWINGS

[0035] The accompanying drawings are used to provide further understanding of the present invention and constitute a part of the specification. They are used to explain the present invention together with the embodiments of the present invention and do not constitute a limitation of the present invention.

[0036] In the attached figure:

[0037] Figure 1 It is a schematic structural diagram of the entire detection device of the present invention;

[0038] Figure 2 It is a front view of the detection device of the present invention;

[0039] Figure 3 Schematic diagram of the internal structure of the detection device of the present invention;

[0040] Figure 4 1 is a schematic diagram of the bottom structure of the detection device of the present invention;

[0041] Figure 5 It is a schematic flow chart of the detection method of the present invention;

[0042] Figure 6 This is a schematic diagram of the contact between the black fixed array unit and the inner wall of the vagina in the present invention;

[0043] Numbers in the figure: 1, black fixed array unit; 2, biocompatible transparent elastic silicone layer; 3, transparent rigid support body; 401, air path structure; 402, control module; 501, camera module; 502, lighting array. DETAILED DESCRIPTION

[0044] The preferred embodiments of the present invention are described below with reference to the accompanying drawings. It should be understood that the preferred embodiments described herein are only used to illustrate and explain the present invention, and are not used to limit the present invention.

[0045] like Figure 1-Figure 4 As shown, a vaginal elasticity measurement and detection device based on visual marker analysis includes:

[0046] The black fixed array unit 1 has a black protruding fixed structure and a biocompatible black marking layer on its surface. The biocompatible black marking layer serves as a marking point in visual imaging, and is used to calculate the area contacted by the black fixed array unit 1 through the image processing module. The black protruding fixed structure is an axially distributed, gradually changing elastic barb in the shape of a triangular pyramid with an inclination angle of no more than 30° and a preset height. The biocompatible black marking layer is made of a mixture of black carbon powder.

[0047] The biocompatible transparent elastic silicone layer 2 forms a dynamic contact interface with the black fixed array unit 1; elastic fibers are embedded in the biocompatible transparent elastic silicone layer 2 to suppress axial deformation and enhance structural stability. The biocompatible transparent elastic silicone layer 2 and the black fixed array unit 1 are integrally cast through a mold.

[0048] The transparent rigid support body 3 has a camera module 501 and an LED lighting array 502 integrated therein. The camera module 501 and the LED lighting array 502 cooperate with each other to capture images of the interior of the vagina. The camera module 501 includes an adjustable focus lens with a frame rate of not less than 60fps; the LED lighting array 502 achieves uniform lighting inside the device through a light guide plate.

[0049] A gas pressure regulating unit is connected to the internal cavity of the silicone layer and is used to dynamically regulate the internal air pressure. The gas pressure regulating unit includes a micro pressure sensor, a piezoelectric micro air pump, and a PID control module 402, and adopts a closed-loop dynamic control strategy. The gas pressure regulating unit of this device adopts a closed-loop dynamic control strategy and meets the following requirements:

[0050] 1) Basic fitting pressure: Ensure the minimum pressure for the initial contact between the silicone layer and the vaginal wall to avoid excessive pressure that may cause tissue deformation and distortion.

[0051] 2) Working pressure range: covers 95% of the resting vaginal pressure of adults, effectively transmitting muscle contraction force while maintaining patient comfort.

[0052] 3) Safety threshold: lower than the critical pressure of vaginal wall microcirculation to prevent the risk of local ischemia.

[0053] like Figure 5 and Figure 6 As shown, the present invention also provides a detection method of a vaginal elasticity measurement detection device based on visual marker analysis, comprising the following steps:

[0054] S1. Collect normal data

[0055] S2. Place the detection device and initialize it to create an initial reference image;

[0056] S3. Adjust the air pressure so that the silicone layer fits the vaginal wall;

[0057] S4. Collect the deformation image of the marker point, calculate the area of the marker point, compare it with the normal data, and determine the degree of vaginal tightness based on the area;

[0058] S5. Segment the images of each anatomical partition using a semantic segmentation model to obtain boundaries that can identify the anatomical partitions of the vaginal wall;

[0059] The semantic segmentation model training method includes the following steps:

[0060] a) First, the pixel-level label data of the vaginal wall anatomical partitions are annotated to generate a dataset;

[0061] b) Apply random elastic deformation and brightness perturbation for data augmentation, and then use the semantic segmentation model to identify the boundaries of six anatomical regions;

[0062] c) Using a hybrid loss function to optimize the model;

[0063] d) Use the semantic segmentation model and the optimizer to train and optimize the model, setting the initial learning rate and weight decay. Specific implementation method:

[0065] 1. Device structure implementation

[0066] 1. Overall structural configuration

[0067] The device adopts a split modular design. The main body is composed of a transparent rigid support body 3 and a biocompatible transparent elastic silicone layer 2. A central through cavity is integrated inside for wiring and air pressure pipelines.

[0068] 2. Flexible fixed array unit manufacturing

[0069] 1) Black protruding structure molding: The black protruding structure is manufactured using an injection molding process and a mold. The black protruding structure is in the shape of a triangular pyramid, distributed axially, and distributed in height according to a gradient. The hook inclination angle is less than 30°.

[0070] 2) Biocompatible transparent elastic silicone layer 2: Made of medical-grade silicone with a light transmittance greater than 90%, an operating temperature range of -40°C to +150°C, suitable for high-temperature sterilization, and medical-grade silicone adhesive is used to bond the flexible fixed array units.

[0071] 3. Optical imaging system

[0072] 1) Camera Module 501: Located at the bottom of the hollow cavity, the camera module is responsible for capturing images of the black protruding structure. Camera Module 501 features autofocus and high-speed acquisition, with a frame rate of ≥60 fps.

[0073] 2) Illumination array 502: Arrange 4 cold white LEDs, each with a power of about 0.5W, and achieve illumination uniformity > 90% through a light guide plate.

[0074] 4. Air pressure regulating unit

[0075] 1) Gas path structure 401: An annular cavity (volume 5±0.5 ml) is provided inside the silicone layer, which is connected to the external control module 402 via a 1.5 mm diameter fluororubber tube.

[0076] 2) Control Module 402: Core components include a pressure sensor and a micro air pump. The pressure sensor provides real-time pressure feedback, controlling the increase or decrease of air pressure. The micro air pump is used for gas transmission, suction, and pressurization. Control Module 402 uses an incremental PID control algorithm with a proportional coefficient Kp = 0.8, an integral time Ti = 2s, and a differential time Td = 0.5s.

[0077] 5. Detailed assembly methods of each component

[0078] The flexible fixing unit is bonded to the outer surface of the silicone layer through medical-grade silicone adhesive to ensure seamless fitting. Three alignment lines are set along the circumference of the silicone layer to ensure that the distribution direction of the black protruding structure is consistent, which is convenient for positioning and marking. The proximal end of the silicone layer is connected to the acrylic transparent rigid support body 3 through an interference fit with a fit tolerance of ±0.05mm. Silicone sealant is applied to the joint to prevent air pressure leakage. The camera is fixed to the front end of the acrylic transparent rigid support body 3, with the lens 8mm away from the inner surface of the silicone layer, and the lens axis coincides with the longitudinal axis of the device. 4 LEDs are arranged in a ring and installed on the periphery of the camera. Light is evenly scattered through the light guide groove of the acrylic transparent rigid support body 3. The air path interface of the silicone layer is connected to the external air pump through a long fluororubber tube. A three-way valve is set at the outlet of the air pump, one way is connected to the silicone layer, and the other way is connected to the air pressure sensor.

[0079] 2. Implementation of the test method

[0080] 1. Collect normal data

[0081] 1) First, collect the data of normal subjects under the device for comparison with the subjects, repeat 3 times and take the average value to avoid fatigue error.

[0082] 2. Clinical testing process

[0083] Step S1: Device placement

[0084] 1) Place the patient in the lithotomy position and apply medical lubricant to the surface of the device.

[0085] 2) Slowly insert the probe into the vagina to a depth of about 6 to 8 cm, ensuring that the axis of the probe is aligned with the longitudinal axis of the vagina. Secure the probe in place to prevent it from slipping during measurement.

[0086] 3) After the probe is placed, let it sit for 1 minute until the subject calms down, and then record the initial area of the spot when there is no external force.

[0087] Step S2: Gradual pressure loading

[0088] 1) Start PID control: Inflate in a step-by-step manner, and maintain the target pressure for 30 seconds until it reaches a balanced state.

[0089] 2) Pressure range: simulate light tension F1 → medium tension F2 → high tension F3.

[0090] Step S3: Data Collection

[0091] Image data was collected simultaneously from six anatomical regions (the upper, middle, and lower anterior wall; and the upper, middle, and lower posterior wall). After each pressure level stabilized, the built-in camera captured the deformation of the marker points in real time, identifying the periodic movement pattern of the vaginal muscles. The marker points were then detected during the contraction cycle, their contours were located, and an image of the contours was drawn. Finally, the area S of the marker points was calculated using the contourArea function in OpenCV.

[0092] Step S4: Data processing and image processing

[0093] 1) After each level of pressure stabilizes, record the area change of deformation under each external force (S1, S2, S3) and compare the patient's data with that of normal subjects. Under the same external force, the larger the deformation area of the marked point, the tighter the vaginal elasticity, and vice versa.

[0094] 2) Semantic Segmentation Model

[0095] Semantic segmentation model: First, the data is annotated to generate a dataset. Then, a real-time semantic segmentation model is used to identify the boundaries of six anatomical partitions. The loss function uses a combination of Dice Loss and Focal Loss, with a weight of 2:1. The model is trained using the AdamW optimizer.

[0096] The above implementation methods can be adapted to subjects of different body shapes by adjusting size parameters, pressure range, and material hardness. The specific implementation parameters should be based on clinical verification data.

[0097] Finally, it should be noted that the above description is merely a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art will be able to modify the technical solutions described in the aforementioned embodiments or substitute equivalents for some of the technical features. Any modifications, equivalent substitutions, and improvements made within the spirit and principles of the present invention shall be included within the scope of protection of the present invention.

Claims

1. A vaginal elasticity measurement and detection device based on visual marker analysis, characterized by: include: A black fixed array unit, having a black protruding fixed structure and a biocompatible black marking layer on its surface, wherein the biocompatible black marking layer serves as a marking point in visual imaging, and is used to calculate the contact area of the marking point of the black fixed array unit by an image processing module; A biocompatible transparent elastic silicone layer is integrally cast with the black fixed array unit through a mold; A transparent rigid support body for integrating a camera module and a lighting array, wherein the camera module and the lighting array cooperate with each other to capture images of the interior of the vagina; The gas pressure regulating unit is connected to the internal cavity of the silicone layer and is used to dynamically adjust the internal gas pressure so that the device can be properly placed in the vagina.

2. The vaginal elasticity measurement and detection device based on visual marker analysis according to claim 1, characterized in that: The black protruding structural fixing structure is an axially distributed gradually changing elastic barb in the shape of a triangular pyramid.

3. The vaginal elasticity measurement and detection device based on visual marker analysis according to claim 1, characterized in that: The biocompatible black marking layer is made by mixing a medical silica gel matrix with nano carbon powder.

4. The vaginal elasticity measurement and detection device based on visual marker analysis according to claim 1, characterized in that: Elastic fibers are embedded in the biocompatible transparent elastic silicone layer to inhibit axial deformation and enhance structural stability.

5. The vaginal elasticity measurement and detection device based on visual marker analysis according to claim 1, characterized in that: The gas pressure regulating unit includes a micro air pressure sensor, a micro air pump and a PID control module, and adopts a closed-loop dynamic control strategy to regulate the air pressure.

6. The vaginal elasticity measurement and detection device based on visual marker analysis according to claim 1, characterized in that: The camera module includes an adjustable focus lens, and the lighting array achieves uniform lighting through a light guide plate.

7. A method for measuring vaginal elasticity based on visual marker analysis, characterized in that: The following steps are involved: S1. Collect normal data; S2. Insert the detection device and initialize it; S3. Adjust the air pressure so that the silicone layer fits the vaginal wall; S4, collecting deformation images of the marker points and comparing them with normal data; S5. Identify the anatomical boundaries of the vaginal wall through a semantic segmentation model.

8. The method for measuring vaginal elasticity based on visual marker analysis according to claim 7, characterized in that: The semantic segmentation model training method comprises the following steps: a) First, the pixel-level label data of the vaginal wall anatomical partitions are annotated to generate a dataset; b) Apply random elastic deformation and brightness perturbation to perform data augmentation, and then use the semantic segmentation model to identify the six anatomical partition boundaries, c) Using a hybrid loss function to optimize the model; d) Use the semantic segmentation model and the optimizer to train and optimize the model, setting the initial learning rate and weight decay.

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