A dual intelligent ovulation detector and its detection method

Abstract

A dual intelligent ovulation detector and its detection method of the present invention relate to an ovulation detector and its detection method, in particular to a dual intelligent ovulation detector and its detection method. It includes a body and a sensor probe. A display screen and keys are provided outside the body, and a body control unit and a lithium battery power supply are provided inside the body; the display screen and keys are respectively connected to the body control unit; the body control unit includes a temperature detection module connected to a temperature calculation module, a conductivity detection module connected to a conductivity calculation module, and a trend judgment module; the temperature calculation module and the conductivity calculation module are respectively connected to the trend judgment module; the sensor probe is connected to the temperature detection module and the conductivity detection module; the sensor probe is placed in the mouth to detect the saliva conductivity and basal body temperature, and a conclusion is obtained by combining the dual trend analysis of the saliva conductivity and the basal body temperature. It is applicable to guiding women's natural contraception methods and selecting the best conception period.

Description

Technical Field

[0001] This invention relates to a dual-connection intelligent ovulation analyzer and its measurement method, particularly a dual-connection intelligent ovulation analyzer and its measurement method. Background Technology

[0002] Studies abroad have investigated the use of electrical resistance measurements in saliva and cervical mucus to reflect ovulation timing. These studies involved inserting electrode probes into the vagina to measure resistance, using serum LH analysis as a control. After measuring the menstrual cycles of 13 subjects over 18 months (10 patients who underwent artificial insemination, the others were volunteers), it was found that LH levels peaked on the day of ovulation, while the resistance of cervical mucus reached its minimum. Conversely, the resistance of oral saliva reached its maximum 5 to 6 days before ovulation. In my country, Qiu Xiuguang et al. from Shandong Medical University conducted research on the resistance values ​​of saliva and cervical mucus, confirming the effectiveness of this method. However, this method is complex and cannot be performed by an individual.

[0003] Basal body temperature (BBT) is the temperature measured immediately upon waking, assuming no activity. It reflects the body temperature at complete rest. In women with normal ovarian function, one follicle matures and releases an egg during each menstrual cycle, subsequently forming the corpus luteum. The follicle before ovulation produces estrogen, while the follicle after ovulation primarily produces progesterone. Progesterone has a thermogenic effect, raising body temperature by 0.3-0.5°C through the thermoregulatory center, creating a biphasic temperature pattern. When serum lactone concentration reaches 12.72 nmol / L or higher, body temperature rises significantly, and this temperature increase coincides with the luteinization time. Therefore, BBT can objectively reflect the ovulation and luteinization process in women of reproductive age. However, current measuring instruments only use a single testing pathway and cannot provide precise and effective testing and analysis for users. Therefore, the predictive results are inaccurate, and there are still many shortcomings in guiding women towards natural methods of contraception and selecting the optimal conception period. Summary of the Invention

[0004] The purpose of this invention is to overcome the shortcomings of existing detection methods and provide a dual-mode intelligent ovulation analyzer and its measurement method, which analyzes the dual trends of salivary conductivity and basal body temperature to improve the ease of use and accuracy of ovulation prediction.

[0005] This invention is achieved by the following technical solution:

[0006] The dual-connection intelligent ovulation analyzer includes a main body and a sensor probe. The main body has a display screen and buttons on the outside and a control unit and a lithium battery power supply inside. The display screen and buttons are connected to the control unit. The lithium battery power supply provides power to the display screen, sensor probe and control unit.

[0007] The display screen is used to display information such as operation prompts, test results, and historical test results;

[0008] The buttons are used to select the power on / off of the measuring instrument, the testing process, and to view information;

[0009] The body control unit includes a temperature detection module connected to the temperature calculation module, a conductivity detection module connected to the conductivity calculation module, and a trend decision module; the temperature calculation module and the conductivity calculation module are respectively connected to the trend decision module.

[0010] The sensor probe is connected to the temperature detection module and the conductivity detection module;

[0011] The sensor probe includes four detection electrodes: an NTC sensing electrode, an AC signal output electrode, and two AC signal input electrodes. The resistance of the NTC sensing electrode changes with temperature.

[0012] The trend decision module is controlled by a trend decision microcontroller. The trend decision module performs joint trend analysis on salivary conductivity and basal body temperature to obtain prediction results, which are then transmitted to the display screen for display. At the same time, the prediction results are stored in the Flash memory of the trend decision microcontroller according to the date. The trend decision microcontroller is a commercially available NRF52832 model.

[0013] The temperature detection module and the temperature calculation module are controlled by the first microcontroller. The temperature detection module samples the temperature of the NTC sensing electrode of the sensor probe and outputs the sampled value to the temperature calculation module. The temperature calculation module converts and calculates the basal body temperature and outputs the basal body temperature value to the trend judgment module. At the same time, the basal body temperature value is stored in the Flash of the first microcontroller according to the date. The first microcontroller is a commercially available BH66F5233 microcontroller, which contains a 24-bit high-precision digital-to-analog converter.

[0014] The conductivity detection module and conductivity calculation module are controlled by a second microcontroller. The conductivity detection module uses a multi-point measurement method with single-electrode output and dual-electrode input to sample saliva and outputs the sampled value to the conductivity calculation module. The conductivity calculation module converts the sampled value into conductivity and outputs it to the trend decision module. At the same time, the conductivity is stored in the Flash memory of the second microcontroller according to the date. The second microcontroller is a commercially available HT66F0185 microcontroller. The multi-point measurement method with single-electrode output and dual-electrode input means that the conductivity detection module applies a bipolar square wave pulse to the AC signal output electrode and simultaneously performs AD sampling on the input signals of the two AC signal input electrodes.

[0015] The measurement method of the dual-mode intelligent ovulation analyzer includes the following steps:

[0016] 1) The temperature detection module converts the resistance value of the NTC sensing electrode into a voltage signal, performs AD sampling on the voltage signal, and outputs the sampled value to the temperature calculation module. The temperature calculation module converts the voltage signal into a resistance value based on the principle of voltage division and calculates the basal body temperature according to the formula. The temperature calculation module calculates the basal body temperature value. The output is sent to the trend judgment module, along with the basal body temperature value. Stored in the Flash memory of the first microcontroller according to the date;

[0017] 2) The conductivity detection module applies an AC signal to the AC signal output electrode of the sensor probe. The AC signal flows through saliva to the AC signal input electrode. The conductivity detection module rectifies the AC signal at the AC signal input electrode and performs AD sampling, outputting the sampled value to the conductivity calculation module. The conductivity calculation module uses the basal body temperature obtained in step 1) according to the calculation formula. Temperature compensation was applied to the salivary conductivity, converting the sampled values ​​into conductivity to obtain the final salivary conductivity. The conductivity calculation module outputs the conductivity to the trend judgment module, and simultaneously stores the conductivity in the Flash memory of the second microcontroller according to the date.

[0018] 3) The trend judgment module combines salivary conductivity and basal body temperature to perform trend analysis, provide ovulation prediction, and display the prediction data on the display screen.

[0019] The method for temperature sampling and basal body temperature detection in step (1) includes the following steps:

[0020] 1-1) Use the temperature detection module to perform n consecutive AD samplings;

[0021] 1-2) Discard the maximum and minimum sampled values ​​from the n samples in step 1-1);

[0022] 1-3) The temperature value is calculated by averaging the remaining n-2 samples from step 1-2).

[0023] ;

[0024] 1-4) Convert the temperature value Ad obtained in step 1-3) into a resistance value Rt according to the principle of voltage division;

[0025] 1-5) Substitute the resistance value Rt obtained in step 1-4) into the polynomial fitting cubic curve formula.

[0026]

[0027] Obtain basal body temperature The accuracy reaches ±0.01℃;

[0028] 1-6) Store according to measurement date In the Flash memory of the first microcontroller;

[0029] The n≥5.

[0030] Step 2) involves a method for detecting saliva and obtaining its conductivity, comprising the following steps:

[0031] 2-1) The conductivity detection module applies a bipolar square wave pulse to the AC signal output electrode of the sensor probe, causing the AC signal output electrode to output a bipolar square wave signal.

[0032] 2-2) The conductivity detection module performs AD sampling on the input signals, i.e., the voltage signals, of the two AC signal input electrodes;

[0033] 2-3) The conductivity detection module performs a weighted average of the voltage signals from the two input electrodes and stores the sampled values;

[0034] 2-4) Repeat steps 2-1) to 2-3) n times, where n ≥ 5;

[0035] 2-5) Discard the maximum and minimum values ​​from the n samples, and take the average of the remaining n-2 samples. ,Will And substitute it into the formula:

[0036]

[0037] Saliva conductivity before compensation In the formula

[0038] , , The value of n is 2473.32 (obtained from saliva tests on 33 women of childbearing age), Rc is the constant value of the feedback resistor (10 KΩ, determined by the circuit design), Vinput is the average voltage of the input AC square wave signal, and n≥5.

[0039] 2-6) Substitute into the temperature compensation formula and replace :

[0040]

[0041] The final temperature-compensated salivary conductivity was obtained. In the formula: The temperature compensation coefficient is set to 0.142 (obtained from saliva tests on 33 women of childbearing age). Basal body temperature is The salivary conductivity before temperature compensation, k0 is the salivary conductivity value detected when the method is first used (no temperature compensation will be performed when the method is first used).

[0042] 2-7) Store according to the testing date It is stored in the Flash memory of the second microcontroller.

[0043] Step 3) includes trend analysis and ovulation prediction, comprising the following steps:

[0044] 3-1) Define the prediction window as 10 days;

[0045] 3-2) If the amount of salivary conductivity and basal body temperature data currently stored is less than 10 days, then do not perform the following steps;

[0046] 3-3) Find the peak and valley values ​​of conductivity within the prediction window, and determine whether there are data for more than 3 days on the left and right edges. If the conditions are not met, do not perform the following steps.

[0047] 3-4) Define 5 days after the date on which the current conductivity peak and trough were detected as the ovulation day. ;

[0048] 3-5) Differential calculations are performed on the basal body temperature values ​​within the prediction window to obtain the daily differential values. ,and

[0049] Find and obtain Maximum differential value Max ( );

[0050] 3-6) for Max( The system determines the action based on the basal body temperature value on the date specified. If the temperature is less than 36.5℃, the following steps are skipped; if the temperature is greater than 36.5℃, then Max(…) is defined. The date is ;

[0051] 3-7) If in step 3-6) In step 3-4) Before, then define This is the day of ovulation.

[0052] Beneficial effects: Compared with the prior art, the present invention has the following advantages: The present invention realizes the simultaneous collection of oral salivary conductivity and basal body temperature at one time, and combines the indicative role of basal body temperature and the predictive role of salivary conductivity to improve the accuracy of predicting the ovulation day. At the same time, during use, the sensor probe can be placed under the tongue in the mouth to start the measurement, which greatly facilitates the use of the user. Attached Figure Description

[0053] The present invention will be further described below with reference to the accompanying drawings:

[0054] Figure 1 This is a structural block diagram of the present invention;

[0055] Figure 2 This is a structural block diagram of the saliva conductivity detection module of the present invention;

[0056] Figure 3 This invention provides a fitting curve of resistance and temperature values, as well as the discrete value distribution of each resistance value on the curve.

[0057] In the diagram: 1. Body control unit, 2. Sensor probe, 3. Display screen, 4. Button, 5. Temperature detection module, 6. Temperature calculation module, 7. Conductivity detection module, 8. Conductivity calculation module, 9. Trend judgment module, 10. Lithium battery power supply. Detailed Implementation

[0058] The embodiments of the present invention are described in detail below. These embodiments are implemented based on the technical solution of the present invention, and provide detailed implementation methods and specific operation processes. However, the scope of protection of the present invention is not limited to the following embodiments.

[0059] like Figures 1-2 As shown, the dual-connection intelligent ovulation analyzer includes a main body and a sensor probe 2. A display screen 3 and buttons 4 are provided on the outside of the main body, and a main body control unit 1 and a lithium battery power supply 10 are provided inside the main body. The display screen 3 and buttons 4 are respectively connected to the main body control unit 1. The lithium battery power supply 10 provides power to the display screen 3, the sensor probe 2 and the main body control unit 1.

[0060] The body control unit 1 includes a temperature detection module 5 connected to the temperature calculation module 6, a conductivity detection module 7 connected to the conductivity calculation module 8, and a trend decision module 9; the temperature calculation module 6 and the conductivity calculation module 8 are respectively connected to the trend decision module 9.

[0061] Sensor probe 2 is connected to temperature detection module 5 and conductivity detection module 7;

[0062] The sensor probe 2 includes four detection electrodes: an NTC sensing electrode, an AC signal output electrode, and two AC signal input electrodes.

[0063] Upon waking, without engaging in any activity, the user connects sensor probe 2 to the main control unit 1, places sensor probe 2 under the tongue in the mouth, and presses button 4 to begin detecting basal body temperature and salivary conductivity. During this process, the control unit will execute the following steps:

[0064] (1) The temperature detection module samples the temperature of the NTC sensing electrode to detect the basal body temperature. And store according to date;

[0065] (2) The conductivity detection module applies a bipolar square wave pulse to the output electrode and simultaneously performs AD sampling on the input signals of the two electrodes. Finally, it uses the basal body temperature. Temperature compensation was applied to the conductivity to obtain the final salivary conductivity. And store them according to date;

[0066] (3) Combine salivary conductivity and basal body temperature to perform trend analysis and give ovulation prediction.

[0067] Step (1) includes the following steps:

[0068] (a) Perform 5 consecutive AD samplings;

[0069] (b) Discard the largest and smallest sampled values ​​from the 5 samples;

[0070] (c) The temperature value is calculated by averaging the remaining 3 samples, using the following formula:

[0071] ;

[0072] (d) Convert the Ad obtained in step (c) into a resistance value Rt according to the principle of voltage divider;

[0073] (e) Substitute the resistance value Rt obtained in step (d) into the polynomial fitting cubic curve formula,

[0074]

[0075] Obtain basal body temperature The accuracy can reach ±0.01℃;

[0076] (f) Store according to measurement date It is stored in the Flash memory of the first microcontroller.

[0077] The resolution of the temperature value obtained by the lookup table method is ±1℃. Generally, the linear interpolation method is used to calculate the temperature value corresponding to Rt by substituting Rt as the independent variable into the interpolation formula formed by the correspondence between the two resistance values ​​and the temperature. However, the change of NTC with temperature is not linear, which leads to a certain error when using the linear interpolation method.

[0078] This embodiment employs a polynomial curve fitting method, which better solves this problem. The normal body temperature range is set as 32℃-42℃. Using the resistance value within this temperature range as the independent variable and the temperature value as the dependent variable, a cubic curve fitting is performed. Figure 3 The figure shows the fitted curve and the discrete difference of each resistance value on the curve. It can be seen from the figure that the discrete difference is much smaller than ±0.01.

[0079] The flowchart for the execution of the conductivity detection module in step (2) is as follows: Figure 2 As shown:

[0080] (a) The AC signal output electrode outputs a 100Hz bipolar square wave signal;

[0081] (b) The input signals of the two AC signal input electrodes are rectified, filtered and amplified, and finally acquired as digital voltage signals by analog-to-digital conversion;

[0082] (c) Perform a weighted average of the voltage signals from the two AC signal input electrodes and store the sampled values;

[0083] (d) Repeat steps (a) to (c) 5 times;

[0084] (e) Discard the maximum and minimum values ​​from the 5 samples, and take the average of the remaining 3 samples. ,Will And substitute it into the formula:

[0085]

[0086] Saliva conductivity before compensation In the formula

[0087] , , Rc is the salivary conductivity coefficient (obtained from saliva tests on 33 women of childbearing age, with a value of 2473.32), Rc is the constant value of the feedback resistance (10 KΩ, determined by the circuit design), and Vinput is the average voltage of the input AC square wave signal.

[0088] (f) will Substitute into the temperature compensation formula and replace :

[0089]

[0090] The final temperature-compensated salivary conductivity was obtained. In the formula

[0091] The temperature compensation coefficient (obtained from saliva tests on 33 women of childbearing age, with a value of 0.142) is used. Basal body temperature is The salivary conductivity before time compensation, k0 is the salivary conductivity value detected when the method is first used (no temperature compensation will be performed when it is first used).

[0092] (g) Store by date It is stored in the Flash memory of the second microcontroller.

[0093] Step (3) includes the following steps:

[0094] (a) Define the prediction window as 10 days;

[0095] (b) If the amount of salivary conductivity and basal body temperature data currently stored is less than 10 days, then the following steps are not performed;

[0096] (c) Find the peak and valley values ​​of conductivity within the prediction window, and determine whether there are data for more than 3 days on the left and right edges. If the condition is not met, do not perform the following steps.

[0097] (d) Define 5 days after the date on which the current conductivity peak and trough are detected as the ovulation day. ;

[0098] (e) Differential calculations are performed on the basal body temperature values ​​within the prediction window to obtain the daily differential values. ,and

[0099] Find and obtain Maximum differential value Max ( );

[0100] (f) for Max( The system determines the action based on the basal body temperature value on the date specified. If the temperature is less than 36.5℃, the following steps are skipped; if the temperature is greater than 36.5℃, then Max(…) is defined. The date is ;

[0101] (g) exist Foreword definition This is the day of ovulation.

Claims

1. A dual-mode intelligent ovulation analyzer, comprising a body and a sensor probe, characterized in that: The machine body has a display screen and buttons on the outside, and a machine body control unit and a lithium battery power supply inside the machine body; the display screen and buttons are respectively connected to the machine body control unit; the lithium battery power supply provides power to the display screen, sensor probes and machine body control unit. The display screen is used to display operation prompts, test results, and historical test result information; The buttons are used to select the power on / off of the measuring instrument, the testing process, and to view information; The body control unit includes a temperature detection module connected to the temperature calculation module, a conductivity detection module connected to the conductivity calculation module, and a trend decision module; the temperature calculation module and the conductivity calculation module are respectively connected to the trend decision module. The sensor probe is connected to the temperature detection module and the conductivity detection module; The sensor probe includes four detection electrodes: an NTC sensing electrode, an AC signal output electrode, and two AC signal input electrodes. The temperature detection module samples the temperature from the sensor probe and then outputs the sampled value to the temperature calculation module. The temperature calculation module converts and calculates the basal body temperature, and outputs the basal body temperature value to the trend judgment module, while storing the basal body temperature value. The conductivity detection module samples saliva and outputs the sampled value to the conductivity calculation module. The conductivity calculation module converts the sampled value into conductivity and outputs it to the trend decision module, while storing the conductivity. The trend judgment module transmits the prediction results to the display screen for display, and also stores the prediction results.

2. The dual-connection intelligent ovulation analyzer according to claim 1, characterized in that: The trend decision module is controlled by a trend decision microcontroller. The trend decision module performs joint trend analysis on salivary conductivity and basal body temperature to obtain prediction results.

3. The dual-connection intelligent ovulation analyzer according to claim 1, characterized in that: The temperature detection module and the temperature calculation module are controlled by the first microcontroller. The temperature detection module samples the temperature of the NTC sensing electrode of the sensor probe; the temperature calculation module stores the baseline body temperature value in the Flash memory of the first microcontroller according to the date.

4. The dual-connection intelligent ovulation analyzer according to claim 1, characterized in that: The conductivity detection module and conductivity calculation module are controlled by a second microcontroller. The conductivity detection module uses a multi-point measurement method with single-electrode output and dual-electrode input to sample saliva. The conductivity calculation module stores the conductivity values ​​by date in the Flash memory of the second microcontroller.

5. The dual-connection intelligent ovulation analyzer according to claim 4, characterized in that: The multi-point measurement method with single-electrode output and dual-electrode input, namely the conductivity detection module, applies a bipolar square wave pulse to the AC signal output electrode and simultaneously performs AD sampling on the input signals of the two AC signal input electrodes.

6. A method for ovulation determination using the dual-unit intelligent ovulation analyzer as described in claim 1, characterized in that, Includes the following steps: 1) The temperature detection module converts the resistance of the NTC sensing electrode into a voltage signal, performs AD sampling on the voltage signal, and outputs the sampled value to the temperature calculation module. The temperature calculation module converts the voltage signal into a resistance value based on the principle of voltage division, and then calculates the basal body temperature according to the formula. The temperature calculation module calculates the basal body temperature value. The output is sent to the trend judgment module, along with the basal body temperature value. Stored in the Flash memory of the first microcontroller according to the date; 2) The conductivity detection module applies an AC signal to the AC signal output electrode of the sensor probe. The AC signal flows through saliva to the AC signal input electrode. The conductivity detection module rectifies the AC signal at the AC signal input electrode and performs AD sampling, outputting the sampled value to the conductivity calculation module. The conductivity calculation module uses the basal body temperature obtained in step 1) according to the calculation formula. Temperature compensation was applied to the salivary conductivity, converting the sampled values ​​into conductivity to obtain the final salivary conductivity. The conductivity calculation module outputs the conductivity to the trend judgment module, and simultaneously stores the conductivity in the Flash memory of the second microcontroller according to the date. 3) The trend judgment module combines salivary conductivity and basal body temperature to perform trend analysis, provide ovulation prediction, and display the prediction data on the display screen.

7. The method for ovulation determination using the dual-connection intelligent ovulation analyzer according to claim 6, characterized in that, The method for temperature sampling and basal body temperature detection in step (1) includes the following steps: 1-1) Use the temperature detection module to perform n consecutive AD samplings; 1-2) Discard the maximum and minimum sampled values ​​from the n samples in step 1-1); 1-3) The temperature value is calculated by averaging the remaining n-2 samples from step 1-2). ； 1-4) Convert the temperature value Ad obtained in step 1-3) into a resistance value Rt according to the principle of voltage division; 1-5) Substitute the resistance value Rt obtained in step 1-4) into the polynomial fitting cubic curve formula. Obtain basal body temperature The accuracy reaches ±0.01℃; 1-6) Store according to measurement date In the Flash memory of the first microcontroller; The n≥5.

8. The method for ovulation determination using the dual-connection intelligent ovulation analyzer according to claim 6, characterized in that, Step 2) involves a method for detecting saliva and obtaining its conductivity, including the following steps: 2-1) The conductivity detection module applies a bipolar square wave pulse to the AC signal output electrode of the sensor probe, causing the AC signal output electrode to output a bipolar square wave signal. 2-2) The conductivity detection module performs AD sampling on the input signals, i.e., the voltage signals, of the two AC signal input electrodes; 2-3) The conductivity detection module performs a weighted average of the voltage signals from the two input electrodes and stores the sampled values; 2-4) Repeat steps 2-1) to 2-3) n times, where n ≥ 5; 2-5) Discard the maximum and minimum values ​​from the n samples, and take the average of the remaining n-2 samples. ,Will And substitute it into the formula: Saliva conductivity before compensation In the formula , , is the salivary conductivity coefficient, with a value of 2473.32, Rc is the constant value of the feedback resistor, Vinput is the average voltage of the input AC square wave signal, and n≥5; 2-6) Substitute into the temperature compensation formula and replace : The final temperature-compensated salivary conductivity In the formula: This is the temperature compensation coefficient, with a value of 0.

142. Basal body temperature is The salivary conductivity before temperature compensation, k0 is the salivary conductivity value detected when the method is first used. No temperature compensation will be performed when the method is first used. 2-7) Store according to the testing date It is stored in the Flash memory of the second microcontroller.

9. The method for ovulation determination using the dual-connection intelligent ovulation analyzer according to claim 6, characterized in that, Step 3) involves trend analysis and ovulation prediction methods, including the following steps: 3-1) Define the prediction window as 10 days; 3-2) If the amount of salivary conductivity and basal body temperature data currently stored is less than 10 days, then do not perform the following steps; 3-3) Find the peak and valley values ​​of conductivity within the prediction window, and determine whether there are data for more than 3 days on the left and right edges. If the conditions are not met, do not perform the following steps. 3-4) Define 5 days after the date on which the current conductivity peak and trough were detected as the ovulation day. ; 3-5) Differential calculations are performed on the basal body temperature values ​​within the prediction window to obtain the daily differential values. ,and Find and obtain Maximum differential value Max ( ); 3-6) for Max( The system determines the action based on the basal body temperature value on the date specified. If the temperature is less than 36.5℃, the following steps are skipped; if the temperature is greater than 36.5℃, then Max(…) is defined. The date is ; 3-7) If in step 3-6) In step 3-4) Before, then define This is the day of ovulation.

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