WO2020045745A1 - Dispositif informatique pour vérifier l'authenticité du sang menstruel, et coupelle menstruelle intelligente - Google Patents

Dispositif informatique pour vérifier l'authenticité du sang menstruel, et coupelle menstruelle intelligente Download PDF

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Publication number
WO2020045745A1
WO2020045745A1 PCT/KR2018/013940 KR2018013940W WO2020045745A1 WO 2020045745 A1 WO2020045745 A1 WO 2020045745A1 KR 2018013940 W KR2018013940 W KR 2018013940W WO 2020045745 A1 WO2020045745 A1 WO 2020045745A1
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data
verification
smart
menstrual
cup
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PCT/KR2018/013940
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English (en)
Korean (ko)
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황룡
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주식회사 룬랩
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    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/14—Devices for taking samples of blood ; Measuring characteristics of blood in vivo, e.g. gas concentration within the blood, pH-value of blood
    • A61B5/1405—Devices for taking blood samples
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B10/00—Other methods or instruments for diagnosis, e.g. instruments for taking a cell sample, for biopsy, for vaccination diagnosis; Sex determination; Ovulation-period determination; Throat striking implements
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/15—Devices for taking samples of blood
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/70—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for mining of medical data, e.g. analysing previous cases of other patients
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B10/00—Other methods or instruments for diagnosis, e.g. instruments for taking a cell sample, for biopsy, for vaccination diagnosis; Sex determination; Ovulation-period determination; Throat striking implements
    • A61B10/0045—Devices for taking samples of body liquids
    • A61B2010/0074—Vaginal or cervical secretions

Definitions

  • the present disclosure relates to a device capable of determining the authenticity of menstrual blood data obtained from a menstrual cup. More particularly, the authenticity of menstrual blood data based on whether or not the data obtained from a sensor in a menstrual cup meets a predetermined verification range. It relates to a device capable of determining.
  • Menstrual blood is blood that is periodically discharged along with the endometrium, and may include a lot of biological information such as genetic information, protein information, health information, and the like, like general blood. Therefore, when the menstrual blood is periodically discharged to check the biometric information without a separate blood collection can be used for health care.
  • the smart menstrual cup can grasp information such as the amount of menstruation, menstrual blood, or menstrual cycle even before removing the menstrual cup, and can check the health state of the corresponding female through this information.
  • an apparatus for determining the authenticity of surrounding environment and menstrual blood data obtained from menstrual blood received in a menstrual cup is provided.
  • an environment capable of correcting a predetermined verification range for a corresponding verification item as a surrounding environment and menstrual blood data accumulated from menstrual blood received in a menstrual cup is accumulated.
  • a computing device for verifying authenticity of menstrual blood is configured to receive first data representing a surrounding environment of a smart menstrual cup and second data representing a characteristic of menstrual blood measured from the smart menstrual cup.
  • a configured communication unit a storage device configured to store the first data and the second data, a first verification result indicating whether the measured first data meets a predetermined verification range for the verification item of the first set of first data, and the measured
  • a controller configured to determine the authenticity of menstrual blood based on at least one of the second verification results indicating whether the second data conforms to a predetermined verification range for the verification item of the second set of second data, and the authenticity of menstrual blood It may include an output configured to output the information indicating the.
  • the first group sensor module configured to measure the first data representing the environment of the smart menstrual cup when the smart menstrual cup is worn, smart A second group sensor module configured to measure second data characteristic of menstrual blood when the menstrual cup is worn, a storage device configured to store measured first data and measured second data, the first measured data being first A first verification result indicating whether the first verification result for the verification item of the first set of data is in compliance with the predetermined verification range for the verification item of the second set of the second data; A control unit configured to determine the authenticity of menstrual blood and the authenticity of menstrual blood based on at least one of the verification results;
  • the information may include a constructed output to output.
  • the present disclosure it is possible to build an accurate big data or database related to menstrual blood, thereby providing a more accurate medical examination to a user using a smart menstrual cup.
  • the corresponding information may be provided to not only a smart menstrual cup user but also many hospitals and research institutes that need blood information.
  • FIG. 1 is a schematic diagram of a computing device for verifying the authenticity of menstrual blood according to one embodiment of the present disclosure.
  • FIG. 2 is a block diagram showing in detail the configuration of the smart menstrual cup according to an embodiment of the present disclosure.
  • 3 to 6 are cross-sectional views illustrating examples of various positions in which a sensor of the smart menstrual cup 110 may be disposed according to an embodiment of the present disclosure.
  • FIG. 7 is a block diagram illustrating in detail a configuration of a computing device according to an exemplary embodiment.
  • FIG. 8 is a schematic diagram of a smart menstrual cup according to another embodiment of the present disclosure.
  • FIG. 9 is a flowchart illustrating a method of determining whether menstrual blood is true or not according to an embodiment of the present disclosure.
  • FIG. 10 is a flowchart illustrating a process of verifying the authenticity of menstrual blood by a computing device according to an exemplary embodiment of the present disclosure.
  • FIG. 11 is a schematic diagram illustrating a process of generating and correcting a verification range by collecting menstrual blood data from each of the plurality of smart menstrual cups.
  • FIG. 12 is a graph for deriving a verification range according to a probabilistic distribution of values of a verification item.
  • FIG. 13 is a structural diagram showing an artificial neural network according to another embodiment of the present disclosure.
  • FIG. 1 is a schematic diagram of a computing device 130 for verifying the authenticity of menstrual blood according to one embodiment of the present disclosure.
  • Smart menstrual cup 110 is inserted into the vagina of the user is configured to receive the menstrual blood into the storage.
  • the smart menstrual cup 110 may include various sensors, and may generate first data representing a surrounding environment of the smart menstrual cup 110 and second data representing a surrounding environment of menstrual blood using the sensors. .
  • the smart menstrual cup 110 may request the computing device 130 to verify the authenticity of menstrual blood through the network 120 based on the generated first data and the second data. In this case, the generated first data and second data may be provided to the computing device 130 via the network 120.
  • Network 120 may include a local area network and / or a long distance network. According to an embodiment, the network 120 may be configured in a wireless Internet scheme such as Bluetooth, Wi-Fi, WiBro, and ultra-wideband. In addition, the network 120 may include a wired Internet scheme such as IEEE 1394, Ethernet, and the like.
  • a wireless Internet scheme such as Bluetooth, Wi-Fi, WiBro, and ultra-wideband.
  • the network 120 may include a wired Internet scheme such as IEEE 1394, Ethernet, and the like.
  • the computing device 130 receives the first data and the second data of the smart menstrual cup 110 from the smart menstrual cup 110 through the network 120, and based on the received first data and the second data, the menstrual blood It may be configured to determine the authenticity of.
  • the computing device 130 is a device capable of communicating with another device through a wired or wireless network, and may include one of a central processing unit (CPU), a graphic processing unit (GPU), a digital signal processor (DSP), and the like. It may be a computing device capable of performing a calculation operation using any one, but is not limited thereto.
  • computing device 130 may be a server device or a smartphone device.
  • the smart menstrual cup 110 may be configured to include a sensor module 210 of a first group, a sensor module 220 of a second group, a communication unit 230, and a storage device 240. Data measured by the sensor module 210 of the first group and / or the sensor module 220 of the second group may be stored in the storage device 240, and the data may be stored in the computing device 230 through the communication unit 230. 130).
  • the first group sensor module 210 may be configured to measure first data representing the surrounding environment of the smart menstrual cup 110.
  • the sensor module 210 of the first group includes a gyro sensor 252, an acceleration sensor 254, a pH sensor 256, a light sensor 258, a temperature sensor 260, and a pressure sensor ( 262).
  • the sensor module 210 of the first group is illustrated to include six sensors 252-262, but may further include any sensor capable of predicting the surrounding environment of the smart menstrual cup 110. .
  • the first group of sensor modules 210 may be configured to include at least one of the six sensors 252-262 shown in FIG. 2.
  • each sensor of the first group sensor module 210 in real time to the surrounding environment of the smart menstrual cup 110 Measure data in real time.
  • each sensor of the first group sensor module 210 may measure data about the surrounding environment of the smart menstrual cup 110 at regular intervals, that is, periodically.
  • the gyro sensor 252 may be configured to measure the rotational angular velocity of the smart menstrual cup 110.
  • the position and direction of the smart menstrual cup 110 may be determined through the measured angular velocity of the smart menstrual cup.
  • the vaginal position and direction of the smart menstrual cup 110 can be measured.
  • the acceleration sensor 254 may be configured to measure dynamic force of acceleration, vibration, shock, and the like of the smart menstrual cup 110.
  • the acceleration sensor 254 may be an electronic acceleration sensor configured to measure by the electromotive force of the magnet and the coil the amount of movement of the movable portion having a suitable mass.
  • the acceleration sensor 254 may be a voltage accelerometer configured to measure acceleration by the applied pressure, using a piezoelectric element that generates a voltage upon application of pressure.
  • the pH sensor 256 may be configured to measure the pH value around the smart menstrual cup 110. According to one embodiment, when the user wears the smart menstrual cup 110 in the vagina, it may be configured to measure the pH value in the vagina. According to one embodiment, pH sensor 256 may be disposed on the outer surface of the menstrual cup to measure the pH value in the vagina.
  • the light sensor 258 may be configured to detect light around the smart menstrual cup 110.
  • the light sensor 258 may be an illuminance sensor.
  • the temperature sensor 260 may be configured to detect a temperature around the smart menstrual cup 110. According to one embodiment, the temperature sensor 260 may be configured to measure the body temperature of the user when the user wears the smart menstrual cup 110 in the vagina. For example, the temperature sensor 260 may be arranged on the outer surface of the smart menstrual cup 110 and configured to measure constant temperature.
  • the pressure sensor 262 may be configured to sense the pressure around the smart menstrual cup 110. According to one embodiment, the pressure sensor 262 may be configured to measure the barometric air pressure when the user wears the smart menstrual cup 11 in the vagina.
  • the second group sensor module 220 may be configured to measure second data indicating characteristics of menstrual blood received in the smart menstrual cup 110.
  • the second group of sensor module 220 is a color sensor 272, pH sensor 274, dielectric constant measuring sensor 276, dissolved gas amount measuring sensor 278 ), A SpO 2 measurement sensor 280, and a physiological blood flow measurement sensor 282.
  • the sensor module 220 of the second group is shown to include six sensors 272-282, but further includes any sensor capable of measuring characteristics of menstrual blood contained in the smart menstrual cup 110. can do.
  • the second group of sensor modules 220 may be configured to include at least one of the six sensors 272-282 shown in FIG. 2.
  • each sensor of the second group sensor module 220 in order to generate the second data representing the characteristics of the menstrual blood received in the smart menstrual cup 110, is a menstrual blood received in the smart menstrual cup 110 in real time Data representing the characteristics of can be measured in real time.
  • each sensor of the second group sensor module 220 may measure data about characteristics of menstrual blood received in the smart menstrual cup 110 at regular intervals, that is, periodically.
  • the color sensor 272 may be configured to detect the color of menstrual blood contained in the smart menstrual cup 110. According to one embodiment, when the smart menstrual cup 110 is worn in the vagina by the user, by measuring the color value (eg, RGB value) of menstrual blood received in the smart menstrual cup 110, the color of the menstrual blood Can be determined.
  • the color value eg, RGB value
  • the pH sensor 274 may be configured to measure the pH value of menstrual blood contained in the smart menstrual cup 110. According to one embodiment, when the user wears the smart menstrual cup 110 in the vagina, it may be configured to measure the pH value of menstrual blood. According to one embodiment, the pH sensor 256 may be disposed on the inner surface of the menstrual cup to measure the pH value in the vagina.
  • the dielectric constant measuring sensor 276 may be configured to measure the dielectric constant of menstrual blood received in the smart menstrual cup 110. According to one embodiment, when the user wears the smart menstrual cup 110 in the vagina, it may be configured to measure the dielectric constant of menstrual blood.
  • Dissolved gas amount sensor 278 may be configured to measure the dissolved amount of a specific component contained in the menstrual blood contained in the smart menstrual cup (110). According to an embodiment, when the user wears the smart menstrual cup 110 in the vagina, the dissolved gas amount sensor 278 may measure the dissolved amount of at least one of oxygen and carbon dioxide contained in the menstrual blood.
  • SpO 2 measurement sensor 280 may be configured to measure the oxygen saturation contained in the menstrual blood contained in the smart menstrual cup (110). According to an embodiment, when the user wears the smart menstrual cup 110 in the vagina, the SpO 2 measuring sensor 280 may measure the oxygen saturation level of menstrual blood.
  • the menstrual blood flow measurement sensor 282 may be configured to measure data indicative of characteristics for the menstrual blood volume received in the smart menstrual cup 110. According to an embodiment, when the user wears the smart menstrual cup 110 in the vagina, the menstrual blood flow measurement sensor 282 may measure at least one value of the total amount of menstrual blood and the amount of discharge per hour.
  • the smart menstrual cup 110 transmits the first data and the second data measured from the first group sensor module 210 and the second group sensor module 220 to an external device (eg, the computing device 130). It may include a communication unit 230 capable of. According to an embodiment, the communicator 230 may be disposed at various positions of the smart menstrual cup 110.
  • the communication unit 230 may be formed in the form of a straight line or a curve, and may be manufactured in the shape of an antenna made of a material such as metal.
  • the communicator 230 may transmit a signal for the first data and the second data to the external device.
  • a signal for the first data and the second data may be provided to the external device through the communication unit 230.
  • the communication unit 230 may include a component for communicating with an external device using a communication means such as Bluetooth, infrared, Zigbee, Wi-fi, and the like.
  • signals for the first data and the second data may be provided to the server device configured to collect and analyze / process such data through the communication unit 230.
  • the signal for the first data and the second data may be transmitted to the server device through the smart phone of the user wearing the smart menstrual cup 110.
  • the smart menstrual cup 110 may include a storage device 240 configured to store first data and second data measured from the first group sensor module 210 and the second group sensor module 220. According to an embodiment, the first data and the second data may be classified according to types of each data and stored in the storage device 240.
  • 3 to 6 are cross-sectional views illustrating examples of various positions in which a sensor of the smart menstrual cup 110 may be disposed according to an embodiment of the present disclosure.
  • the smart menstrual cup 110 may be formed with a storage unit 340 in which one side (for example, the upper side) is opened to receive the menstrual blood therein.
  • the smart menstrual cup 110 may be manufactured in a form in which the upper diameter becomes narrower toward the lower side. That is, for correct insertion and fixation, the smart menstrual cup 110 may have a circumference at a portion close to the opening at least in some areas than a circumference at the portion far from the opening.
  • the smart menstrual cup 110 according to the present disclosure is not limited to this form, and may be manufactured in various shapes.
  • a form in which the circumference in the upper portion is longer than the circumference in the lower portion will be described as an example.
  • each sensor of the first group sensor module 210 or the second group sensor module 220 is installed in the smart menstrual cup 110 to provide the surrounding environment or the smart menstrual cup 110 of the menstrual cup. Various kinds of data on the menstrual blood contained in can be measured. Each sensor may be disposed at various positions of the smart menstrual cup 110.
  • the sensors 310, 320, and 330 may be disposed on an inner surface of the storage unit 340. Although three sensors 310, 320, and 330 are illustrated in FIG. 3, one or more arbitrary numbers of sensors may be disposed on an inner surface of the storage unit 340 of the smart menstrual cup 110.
  • the plurality of sensors may be disposed at any position from the top to the bottom of the inner surface of the smart menstrual cup 110.
  • the sensors 310-330 may be intermittently disposed from the top to the bottom of the inner surface of the smart menstrual cup 110.
  • the plurality of sensors 350 may be continuously disposed.
  • the sensors disposed on the inner surface of the storage unit 340 may include, for example, at least one of the sensors included in the second group of sensor modules 220 configured to measure second data indicating characteristics of menstrual blood. It may include.
  • the sensor 360 may be disposed on an outer surface of the storage unit 340 of the smart menstrual cup 110. Although only one sensor 360 is illustrated in FIG. 4, a plurality of sensors may be disposed on an outer surface of the storage unit 340. According to an embodiment, the sensors disposed on the outer surface of the storage unit 340 may include at least one of the sensors included in the first group of sensor modules 210 configured to measure first data representing the environment of the smart menstrual cup. It may include one. For example, a pH sensor capable of measuring pH in the vagina in which the smart menstrual cup is worn may be disposed on the outer surface of the storage unit 340, and does not require a separate component in the smart menstrual cup 110. Intravaginal pH data can be obtained by measuring the pH of the site where the pH sensor is contacted.
  • the sensor 370 may be disposed to be included in the storage 340. According to an embodiment, as shown in FIG. 5, the sensor 370 may be continuously disposed in the storage 340.
  • the sensor 370 may include a sensor capable of measuring the characteristics of the menstrual blood without directly contacting the menstrual blood.
  • the sensor 370 may include a sensor capable of measuring characteristics of the surrounding environment without directly contacting the surrounding environment of the smart menstrual cup 110.
  • the sensor 390 may be configured to be disposed at the bottom of the storage unit 340 of the smart menstrual cup 110. According to an embodiment, as shown in FIG. 6, the sensor 390 may be included in the smart menstrual cup 110 and disposed at the bottom of the storage unit 340. In FIG. 6, only one sensor is illustrated at the bottom of the smart menstrual cup 110, but a plurality of sensors may be disposed in the smart menstrual cup 110.
  • Each of the sensors of FIGS. 3-6 or any combination thereof may be disposed in the smart menstrual cup 110.
  • Each of the sensors of FIGS. 3 to 6 may include at least one sensor of the sensors of the first group of sensor modules 210.
  • each of the sensors of FIGS. 3 to 6 may include at least one sensor of the sensors of the second group of sensor modules 220.
  • FIG. 7 is a block diagram illustrating a detailed configuration of a computing device 130 according to an embodiment of the present disclosure.
  • the computing device 130 may include a communication unit 410, a storage device 420, a controller 430, and an output unit 440.
  • the computing device 130 may further include a learning module 450.
  • the computing device 130 may include a communication unit 410 configured to receive first data and second data from the smart menstrual cup 110.
  • the communication unit 410 may include a component for performing communication with the smart menstrual cup 110 and / or an external device by using a wired or wireless communication means such as Bluetooth, infrared, Zigbee, Wi-Fi.
  • the storage device 420 may be configured to store the first data and the second data received from the smart menstrual cup 110.
  • the storage device 420 may store verification items of the first set of first data and predetermined verification range data for each verification item.
  • the verification item of the first set of first data includes the constant temperature of the outer surface of the smart menstrual cup 110, the rotational angular velocity of the smart menstrual cup 110, the air pressure in the smart menstrual cup 110, the smart menstrual cup.
  • the verification may include at least one of illumination in the vagina worn by 110 and pH in the vagina in which the smart menstrual cup 110 is worn.
  • the storage device 420 may store a verification item of the second set of second data and predetermined verification range data for each verification item.
  • the second set of validation items of the second data may include at least one validation item of permittivity of menstrual blood, dissolved oxygen of menstrual blood, dissolved carbon dioxide of menstrual blood, pH of menstrual blood and oxygen saturation of menstrual blood. Can be.
  • the controller 430 may be configured to determine whether data received from the smart menstrual cup 110 and / or data stored in the storage device 420 is actually obtained from the body of the user. According to one embodiment, the first verification result indicating whether the measured first data corresponds to a predetermined verification range for the verification item of the first set of first data and the measured second data is the second set of second data The authenticity of menstrual blood may be determined based on at least one verification result of the second verification result indicating whether the verification item corresponds to the verification range of the verification item.
  • the controller 430 is a device that can communicate with other devices through a wired or wireless network, and operates using any one of a central processing unit (CPU), a graphic processing unit (GPU), a digital signal processor (DSP), and the like. It may be an element capable of performing, but is not limited thereto.
  • the output unit 440 may be configured to output information indicating whether the menstrual blood is authentic. According to an embodiment of the present disclosure, the output unit 440 may output information about the authenticity of menstrual blood through the output device of the computing device 130.
  • the output device of the computing device 130 may be any device (eg, a display device) capable of outputting information about the authenticity of menstrual blood, and the information about the authenticity of menstrual blood is displayed on the display device. It can be displayed and provided to the user.
  • the output unit 440 may provide information on whether the menstrual blood is authentic to the output device of the external device through the communication unit 410.
  • the computing device 130 may further include a learning module 450.
  • the learning module 450 may input at least one of the first data and the second data measured by the sensor of the smart menstrual cup 110 to the input layer of the artificial neural network to extract information about the authenticity of menstrual blood. It is configured to train the artificial neural network.
  • the first and second data may be input to an input layer of the artificial neural network to be configured to train the artificial neural network to extract respective verification results for the first group verification item and the second group verification item.
  • the artificial neural network receives a quantified value of the constant temperature and rotational angular velocity of the smart menstrual cup 110 as first data into the input layer of the artificial neural network, and succeeds the verification result for the first group verification item. Or to extract as a failure.
  • the learning module 450 may include at least one of data representing a surrounding environment of a corresponding smart menstrual cup received from each of the plurality of smart menstrual cups and data representing characteristics of menstrual blood of a user wearing the corresponding smart menstrual cup.
  • One is input to the input layer of the artificial neural network can be configured to learn the artificial neural network to extract information about the authenticity of menstrual blood of the user wearing the corresponding smart menstrual cup. The learning and reasoning process of the artificial neural network will be described in more detail with reference to FIG. 13 below.
  • the smart menstrual cup 510 may include the sensor module 210 of the first group, the sensor module 220 of the second group, the communication unit 230, and the storage device 240 of the smart menstrual cup 110 shown in FIG. 2. It may include the same or similar components. As shown in FIG. 8, the smart menstrual cup 510 may further include a controller 515 configured to determine whether the menstrual blood received in the smart menstrual cup 510 is authentic. The controller 515 may provide a function or configuration that is the same as or similar to that of the controller 430 of the computing device 130 described with reference to FIG. 7.
  • the controller 515 may include a first verification result and a second verification result indicating whether the first data measured from the first group sensor module corresponds to a predetermined verification range for a verification item of the first set of first data. And determine the authenticity of menstrual blood based on at least one of the second verification results indicating whether the second data measured from the group sensor module conforms to a predetermined verification range for the verification item of the second set of second data. Can be.
  • the controller 515 may be disposed at any position of the smart menstrual cup 510 connected to communicate with the first group sensor module and the second group sensor module of the smart menstrual cup 510. According to an embodiment, as shown in FIG. 8, the controller 515 may be disposed at the lower end of the storage unit in which the menstrual blood is accommodated in the smart menstrual cup 510. In addition, the controller 515 may be disposed to be included in the smart menstrual cup 510.
  • Information about the authenticity of menstrual blood determined by the control unit 515 of the smart menstrual cup 510 may be provided to the control unit 430 via a network 520 through a communication unit (not shown) of the smart menstrual cup 510. have.
  • the communication unit may be formed at various positions in the smart menstrual cup 510.
  • the communication unit may be included in the control unit 515 or located at the top or bottom of the control unit 515. can do.
  • the information on the authenticity of menstrual blood determined by the control unit 515 of the smart menstrual cup 510 is displayed on the output device (for example, the display device) of the user's smartphone so that the user can check Can be.
  • information about the authenticity of the first data and / or the second data and the determined menstrual blood is provided from the smart menstrual cup 510 to the server device so that the server device can statistically analyze the data and information or This data and information can be used to train artificial neural networks.
  • FIG. 9 is a flowchart illustrating a method of determining whether menstrual blood is true or not according to an embodiment of the present disclosure.
  • a step 610 of measuring first data representing the surrounding environment of the smart menstrual cup 110 and the smart menstrual cup 110 may be worn. And measuring 615 second data indicating characteristics of menstrual blood.
  • the measured first data and the second data may be stored in the storage device 240 (620).
  • the storage device 240 may accumulate and store the first data and the second data measured at different time points. Alternatively, only the first data and the second data measured at the last time may be stored in the storage device 240.
  • the stored data may be transmitted to the computing device 130 through the communication unit 230, and when the smart menstrual cup 510 includes the controller 515, the data may be analyzed by the controller 515.
  • the controller 430 of the computing device 130 or the controller 515 of the smart menstrual cup 510 determines whether the first data corresponds to a predetermined verification range for the verification item of the first group of the first data.
  • the second verification result indicating whether the second data corresponds to a predetermined verification range for the verification item of the second group of the second data may be generated (635). ).
  • the authenticity of menstrual blood may be determined based on at least one of the first verification result and the second verification result generated in the previous step.
  • the authenticity of the determined menstrual blood may be output by the output of the computing device 130 (650).
  • the verification range of the verification item may be corrected using the first data and the second data stored in the storage device 420 of the computing device 130 (660). However, when the first data and the second data deviate from a predetermined verification range for the verification item of the first group and the verification item of the second group, they may not be used as data for correction.
  • FIG. 10 is a flowchart illustrating a process of verifying the authenticity of menstrual blood by a computing device according to an exemplary embodiment of the present disclosure.
  • the first data indicating the surrounding environment of the smart menstrual cup 110 is measured through the first group sensor module 210 (710), and the smart menstruation through the second group sensor module 220.
  • Second data representing characteristics of the menstrual blood received in the cup 110 may be measured (715).
  • verification of the first data and the second data may be performed.
  • the controller 430 of the computing device 130 determines whether the first data and the second data to be verified are within a normal range in the items requiring verification by the accumulated quantitative values of the first data and the second data. It may be determined (730). According to an embodiment of the present disclosure, it may be determined whether at least one of the first data and the second data falls within a normal range in the items requiring verification.
  • the output unit 440 may output information that the verification was successful (750). If all items in the normal range in the items that need to be verified (745), it is determined that the data is obtained from a material other than menstrual blood or a material other than the data obtained in the human vagina, and the output unit 440 is determined. In operation 755, information indicating that verification has failed may be output.
  • the authenticity of menstrual blood may be determined according to the degree of deviation from the normal range and / or the degree of the data out of the normal range for some of the verification items, rather than the normal range.
  • the authenticity determination criteria according to the case where some verification items deviate from the normal range and / or the degree to which the data deviate from the normal range will be described with reference to exemplary tables 1 to 3. .
  • Second data Vaginal roughness (lux) Vaginal pH Permittivity of menstrual blood (3 GHz, 25 ° C) PH of menstrual blood Normal range 0 4.5-6.5 60-70 6.0-8.0 Actual value 0 6.7 62 7.1 Verification result success
  • the vaginal roughness in which the smart menstrual cup 110 is worn is included in the normal range among the first data, and the permittivity of menstrual blood and pH of the menstrual blood contained in the menstrual cup are included in the normal range.
  • the intravaginal pH of the first data is 6.7, which is 0.2 from the normal range of 4.5-6.5.
  • the vaginal pH may be higher or lower than the normal range when a disease such as vaginitis occurs depending on the user's physical condition.
  • the verification result may be represented as success rather than failure according to the verification item and the degree of deviation.
  • Second data Vaginal roughness (lux) Vaginal pH Permittivity of menstrual blood PH of menstrual blood Normal range 0 4.5-6.5 60-70 6.0-8.0 Actual value 5 5.5 62 7.1 Verification result failure
  • the pH in the vagina in which the smart menstrual cup 110 is worn in the first data is determined to be within a normal range, and the permittivity of menstrual blood and the pH of menstrual blood in the menstrual cup of the second data are normal. It is included in the scope. However, it can be seen that the vaginal illuminance is 5 lux, which deviates from the normal range of 0 lux. Even if the outside of the normal range is small, when the menstrual cup is worn, there should be no light in the vagina, so if the light is detected, it can be determined that the menstrual blood is not a verification result.
  • First data Second data Vaginal roughness (lux) Constant temperature outside the menstrual cup Permittivity of menstrual blood PH of menstrual blood Primary Normal Range 0 36.3-37.0, ⁇ 1 62-67 6.5-7.5 2nd normal range 0 35.5-39.5, ⁇ 2 60-70 6.0-8.0 Actual value 0 35.0 63 6.2 Verification result success
  • the normal range for determining the authenticity of menstrual blood may be divided into a first normal range and a second normal range.
  • the first normal range is the range of data that can be obtained when the menstrual blood is collected using the smart menstrual cup in everyday life
  • the second normal range is the smart menstrual cup when the extreme conditions or the user has a disease
  • the range of data that can be generated outside of the primary normal range when some menstrual blood is collected by using the blood including a wider range than the primary normal range. Therefore, when all items are included in the second normal range and at least one of the verification items is included in the first normal range, the verification result may be indicated as success.
  • FIG. 11 is a schematic diagram illustrating a process in which the computing device 810 collects and analyzes menstrual blood data from each of the plurality of smart menstrual cups 820_1 to 820_n.
  • the computing device 810 may be the computing device 130 shown in FIG. 1, the computing device 530 shown in FIG. 8, or another computing device.
  • the computing device 810 may include a module including a configuration that is the same as or similar to that of the controller 430 or the learning module 450 of FIG. 7.
  • the computing device 810 may include a user who wears the corresponding smart menstrual cup and first data representing the surrounding environment of the corresponding smart menstrual cup measured by each of the smart menstrual cups 820_1 to 820_n. And second data indicative of the characteristic of menstrual blood. According to one embodiment, such data may be sent to learning module 450 periodically (eg, at five minute intervals). According to another embodiment, such data may be transmitted to the learning module 450 in real time. According to an embodiment, when the control unit 515 is in the smart menstrual cup 510 as shown in FIG. 8, after generating the first data and the second data for the menstrual blood, the control unit 515 is derived from the control unit 515. The verification results may be stored in storage and one or more verification results may be sent to the computing device 810 via the network 520 periodically or aperiodically (eg, in real time).
  • the computing device 810 may input at least one of first and second data received from each of the plurality of smart menstrual cups to an input layer of an artificial neural network and wear a corresponding smart menstrual cup. It can be configured to train the artificial neural network to extract information about the authenticity of the menstrual blood of a user.
  • Computing device 130 inputs the first data and the second data for the smart menstrual cup 110 to the learned artificial neural network, information about the authenticity of menstrual blood received in the smart menstrual cup 110 through the artificial neural network Can be extracted.
  • the computing device 810 may include a predetermined verification range for the verification item of the first group based on at least one of the first data and the second data received from each of the plurality of smart menstrual cups; At least one of predetermined verification ranges for verification items of the second group may be generated.
  • the first data may be classified by item for each verification item of the first group, and each of the predetermined verification ranges for the verification item may be generated based on the classified data.
  • the second data may be classified by item for each verification item of the second group, and each of the predetermined verification ranges for the verification item may be generated based on the classified data.
  • the computing device 810 may add new first data and second data to existing first data and second data accumulated in the predetermined range, and the verification range of the second group. It is possible to correct the predetermined verification range for.
  • the computing device 810 may receive the first data and the second data received from each of the plurality of smart menstrual cups together with a result indicating whether the menstrual blood is true or not with respect to the data, and thus the predetermined verification range and the first data may be obtained. It may be used to generate or correct at least one of predetermined verification ranges for two groups of verification items.
  • the verification range for at least some of the first group verification item and the second group verification item may be probabilistically distributed.
  • the predetermined verification range is determined by adding new data received from each of the plurality of smart menstrual cups (that is, data about the surrounding environment of the corresponding smart menstrual cup and data about menstrual blood contained in the corresponding smart menstrual cup) to the control unit. Can be corrected by For example, although the verification range was initially determined as the verification range, the interval corresponding to ⁇ standard deviation from the mean value of the normal distribution curve derived from the data at that time, but the new value is added to the mean value of the newly derived normal distribution curve. If changed, the interval corresponding to ⁇ standard deviation from the mean value of the curve may be corrected to the verification range.
  • the predetermined verification range may be increased for the verification item.
  • the determined verification range may be comprehensively analyzed by the control unit for the first group verification item and the second group verification item, and a predetermined verification range for the specific verification item may be corrected based on the result.
  • the artificial neural network 1000 is a machine learning technique and a cognitive science, which is a structure for executing a statistical learning algorithm or an algorithm implemented based on the structure of a biological neural network. That is, the artificial neural network 1000 is a node, artificial neurons that form a network by synaptic coupling as in a biological neural network iteratively adjust the weight of the synapse, the correct output corresponding to a specific input and inferred output By learning so that the error between them is reduced, we present a machine learning model with problem solving ability.
  • an artificial neural network is implemented with a multilayer perceptron (MLP) composed of multiple nodes and a connection between them.
  • the artificial neural network 1000 may be implemented using one of various artificial neural network structures including an MLP.
  • the artificial neural network 1000 includes an input layer 1020 that receives input signals or data 1010 and 1012 from an external source, and output signals or data 1050 and 1052 corresponding to the input data.
  • the input layer 1020 and the output layer 1040 Located between the output layer 1040, the input layer 1020 and the output layer 1040 to output and receives the signal from the input layer 1020 to n hidden layers (1030_1 to 1030_n) to extract the characteristic and deliver it to the output layer 1040 It is composed.
  • the output layer 1040 receives a signal from the hidden layers 1030_1 to 1030_n and outputs it to the outside.
  • the learning method of the artificial neural network 1000 includes a supervised learning method for learning to be optimized for solving a problem by inputting a teacher signal (correct answer), and an unsupervised learning method that does not require the teacher signal ( There is an Unsupervised Learning method and a Semi-supervised Learning method that combines these two lessons together.
  • the input of the artificial neural network 1000 to the first data and / or the second data received from the smart menstrual cup 110 using semi-supervised learning is performed. It is input to the layer 1020 and whether the authenticity of menstrual blood for this data is output to the output layer 1040.
  • the result of the authenticity of menstrual blood is received from each of the plurality of smart menstrual cups can be used for learning.
  • the authenticity of menstrual blood for the first data and / or the second data received through the learning module 450 may be determined.
  • the learned artificial neural network 1000 allows the authenticity of menstrual blood to be more accurately determined.
  • the input variable of the artificial neural network 1000 which can infer the verification range of the verification item, the first data and the second group sensor measured from the first group sensor module It can be the second data measured from the module.
  • the input variable input to the input layer 1020 of the artificial neural network 1000 includes categories of the first data measured from the first group sensor module and the second data measured from the second group sensor module, respectively. It may be a first vector 1010 and a second vector 1012 composed of one vector data element.
  • the second data of 99% is generated, among the verification items of the first group sensor module, the value of 1 in the element corresponding to 5.5 atm in the verification item of air pressure of the menstrual cup and 5.5 in the verification item of intravaginal pH Is assigned, and the remaining elements may be assigned a value of zero.
  • a value of 1 is assigned to a factor corresponding to 7.1% in a verification item called pH of menstrual blood, and a verification item called oxygen saturation degree of menstrual blood, and 0 to other elements. You can assign a value.
  • the output variable output from the output layer 1040 of the artificial neural network 1000 may be a vector indicating whether the menstrual blood corresponding to the first data and the second data is authentic.
  • the output variable may include a first verification range vector 1050 and a second verification range vector 1052.
  • the first verification range vector 1050 may include, as a data element, verification ranges of verification items as to whether the first data obtained from the peripheral environment data of menstrual blood is actually data obtained by wearing a menstrual cup. have.
  • the output variable of the artificial neural network 1000 is not limited to the two types described above, and may be composed of three or more vectors according to the input and output variables.
  • the input layer 1020 and the output layer 1040 of the neural network 1000 are matched with a plurality of output variables corresponding to the plurality of input variables, respectively, so that the input layer 1020, the hidden layers 1030_1 to 1030_n, and the output layer (
  • the synaptic value between the nodes included in 1040 it can be learned to infer the correct output corresponding to a specific input.
  • the learned artificial neural network 1000 in response to the input of the first data and the second data of the smart menstrual cup, the result value of the authenticity of the menstrual blood contained in the smart menstrual cup may be extracted.
  • the method for verifying authenticity of menstrual blood as described above may be implemented as computer readable codes on a computer readable recording medium (eg, storage devices 240 and 420).
  • Computer-readable recording media include all kinds of recording devices that store data that can be read by a computer system. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disks, optical data storage devices, and the like.
  • the computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion.
  • functional programs, codes, and code segments for implementing the above embodiments can be easily inferred by programmers in the art to which the present invention pertains.
  • the processing units used to perform the techniques may include one or more ASICs, DSPs, digital signal processing devices (DSPDs), programmable logic devices (PLDs). Field programmable gate arrays (FPGAs), processors, controllers, microcontrollers, microprocessors, electronic devices, other electronic units designed to perform the functions described herein, It may be implemented within a computer, or a combination thereof.
  • ASICs application-specific integrated circuits
  • DSPs digital signal processing devices
  • DSPDs digital signal processing devices
  • PLDs programmable logic devices
  • FPGAs Field programmable gate arrays
  • processors controllers, microcontrollers, microprocessors, electronic devices, other electronic units designed to perform the functions described herein, It may be implemented within a computer, or a combination thereof.
  • the various exemplary logic blocks, modules, and circuits described in connection with the disclosure herein may be general purpose processors, DSPs, ASICs, FPGAs or other programmable logic devices, discrete gate or transistor logic, discrete hardware components, or It may be implemented or performed in any combination of those designed to perform the functions described herein.
  • a general purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine.
  • a processor may also be implemented as a combination of computing devices, eg, a combination of a DSP and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a DSP core, or any other such configuration.
  • the techniques may include random access memory (RAM), read-only memory (ROM), non-volatile random access memory (NVRAM), PROM (on computer readable media such as programmable read-only memory (EPROM), electrically programmable read-only memory (EPROM), electrically erasable PROM (EEPROM), flash memory, compact disc (CD), magnetic or optical data storage devices, and the like. It may be implemented as stored instructions. The instructions may be executable by one or more processors and may cause the processor (s) to perform certain aspects of the functionality described herein.
  • Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another.
  • Storage media may be any available media that can be accessed by a computer.
  • such computer-readable media may be in the form of RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or desired program code in the form of instructions or data structures.
  • any connection is properly termed a computer readable medium.
  • the software is transmitted from a website, server, or other remote source using coaxial cable, fiber optic cable, twisted pair, digital subscriber line (DSL), or wireless technologies such as infrared, wireless, and microwave
  • coaxial cable , Fiber optic cable, twisted pair, digital subscriber line, or wireless technologies such as infrared, wireless, and microwave
  • disks and disks include CDs, laser disks, optical disks, digital versatile discs, floppy disks, and Blu-ray disks, where the disks are usually magnetic Data is reproduced optically, while discs are optically reproduced using a laser. Combinations of the above should also be included within the scope of computer-readable media.
  • the software module may reside in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, removable disk, CD-ROM, or any other type of storage medium known in the art.
  • An example storage medium can be coupled to the processor such that the processor can read information from or write information to the storage medium.
  • the storage medium may be integral to the processor.
  • the processor and the storage medium may reside in an ASIC.
  • the ASIC may be present in the user terminal.
  • the processor and the storage medium may reside as discrete components in a user terminal.
  • example implementations may refer to utilizing aspects of the presently disclosed subject matter in the context of one or more standalone computer systems, the subject matter is not so limited, but rather in connection with any computing environment, such as a network or a distributed computing environment. It may be implemented. Moreover, aspects of the presently disclosed subject matter may be implemented in or across a plurality of processing chips or devices, and storage may be similarly affected across a plurality of devices. Such devices may include PCs, network servers, and handheld devices.
  • Computer-readable recording media include all kinds of recording devices that store data that can be read by a computer system. Examples of computer-readable recording media include ROM, RAM, CD-ROM, magnetic tape, floppy disks, optical data storage devices, and the like.
  • the computer readable recording medium can also be distributed over network coupled computer systems so that the computer readable code is stored and executed in a distributed fashion. And, the functional program, code and code segments for implementing the embodiments can be easily inferred by programmers in the art to which the present invention belongs.

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Abstract

La présente invention concerne un dispositif informatique pour vérifier l'authenticité du sang menstruel. Le dispositif comprend : une unité de communication configurée pour recevoir des premières données représentant un environnement ambiant d'une coupelle menstruelle intelligente et des secondes données représentant une caractéristique du sang menstruel, mesurée à partir de la coupelle menstruelle intelligente; un dispositif de stockage configuré pour stocker les premières données et les secondes données; une unité de commande configurée pour déterminer l'authenticité du sang menstruel sur la base d'au moins l'un parmi un premier résultat de vérification indiquant si les premières données mesurées satisfont ou non une plage de vérification prédéterminée correspondant à un élément de vérification du premier ensemble de premières données et un second résultat de vérification indiquant si les secondes données mesurées satisfont ou non une plage de vérification prédéterminée correspondant à un élément de vérification du second ensemble de secondes données; et une unité de sortie configurée pour délivrer des informations indiquant l'authenticité du sang menstruel.
PCT/KR2018/013940 2018-08-30 2018-11-14 Dispositif informatique pour vérifier l'authenticité du sang menstruel, et coupelle menstruelle intelligente WO2020045745A1 (fr)

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KR10-2018-0103050 2018-08-30

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012105839A (ja) * 2010-11-18 2012-06-07 Hitachi Ltd オムツ、オムツ濡れ検知装置、健康管理装置、及び健康管理システム
WO2012118494A1 (fr) * 2011-03-01 2012-09-07 Empire Technology Development Llc Analyse du liquide menstruel
WO2017015767A1 (fr) * 2015-07-29 2017-02-02 Standard Innovation Corporation Dispositif et procédé de surveillance de l'hygiène féminine
KR101768812B1 (ko) * 2016-07-05 2017-08-17 고려대학교 산학협력단 흉부 단층영상에서 검색된 폐결절의 암 진단 보조 시스템 및 프로그램
KR101877495B1 (ko) * 2017-06-29 2018-08-07 주식회사 룬랩 스마트 생리컵 및 스마트 생리컵을 이용한 생리혈 측정 방법

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2012105839A (ja) * 2010-11-18 2012-06-07 Hitachi Ltd オムツ、オムツ濡れ検知装置、健康管理装置、及び健康管理システム
WO2012118494A1 (fr) * 2011-03-01 2012-09-07 Empire Technology Development Llc Analyse du liquide menstruel
WO2017015767A1 (fr) * 2015-07-29 2017-02-02 Standard Innovation Corporation Dispositif et procédé de surveillance de l'hygiène féminine
KR101768812B1 (ko) * 2016-07-05 2017-08-17 고려대학교 산학협력단 흉부 단층영상에서 검색된 폐결절의 암 진단 보조 시스템 및 프로그램
KR101877495B1 (ko) * 2017-06-29 2018-08-07 주식회사 룬랩 스마트 생리컵 및 스마트 생리컵을 이용한 생리혈 측정 방법

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