Method and system for determining prognosis of disease using toothbrush

Abstract

The present invention relates to a method for determining prognosis of disease, using a toothbrush, the method comprising the steps of: receiving indicator data containing various biometric information of a user through the toothbrush; analyzing a health condition of the user on the basis of the indicator data to calculate health data; and generating control data for controlling the function of the toothbrush on the basis of the health data.

Description

Method and system for determining disease prognosis using a toothbrush

[0001] The present invention relates to a method and system for determining the prognosis of a disease using a toothbrush, and more particularly, to a technical idea for utilizing various bio-information that can be obtained from a user's body using a toothbrush as indicator information for determining the prognosis of a disease, thereby enabling the user's health condition or the prognosis of a specific disease to be determined in advance while the user brushes his or her teeth daily or through the time before and after brushing his or her teeth.

[0002] People's interest in their health is growing significantly, and they are using various health-related devices. Through these health-related devices (smartwatches, etc.), people are increasingly demanding information about their health status or the prognosis of certain diseases.

[0003] However, while interest in health has always been high, there have been insufficient devices and services that bring this closer to real life and minimize the hassle and inconvenience of separate measurement steps, which has hindered the growth of the digital healthcare industry as a whole, making it difficult to effectively manage health.

[0004] Smartwatches also target consumers above a certain age, and the inconvenience of having to wear them continuously is a concern. To address this, devices and services that allow users to manage data periodically and chronologically, from early to late in life, and are user-friendly are needed.

[0005] In particular, since it is difficult for people to monitor their dental or oral health in real time, there is an increasing demand to know the status of their dental or oral health or the prognosis of certain diseases.

[0006] However, in order to determine the disease prognosis with relative accuracy, a complex examination and analysis process is required, making it difficult for users to find out at any time they want.

[0007] Accordingly, a technical idea is required that enables users to easily determine their health status or disease prognosis by obtaining various biometric information from users using a toothbrush and utilizing the obtained biometric information as indicator information for determining disease prognosis.

[0008] The present invention aims to provide a method and system for determining disease prognosis using a toothbrush, which enables the user to obtain various biometric information using a toothbrush with which the user brushes his / her teeth at least once a day, and to utilize the obtained biometric information as indicator information for determining disease prognosis.

[0009] In order to achieve the above-described purpose, a method for determining a disease prognosis using a toothbrush according to an embodiment of the present invention may include a step of receiving indicator data including various biometric information of a user through the toothbrush, a step of analyzing the health status of the user based on the indicator data to produce health data, and a step of generating control data for controlling the function of the toothbrush based on the health data.

[0010] Additionally, the above indicator data may include the user's body temperature, pulse, oxygen saturation, blood pressure, grip strength, bioelectrical current, expiratory information, ultrasound information, mental health, genetic material, and biomarkers.

[0011] In addition, the step of producing the health data may include inputting the indicator data into a neural network model to produce the health data, and the neural network model may be trained to produce the health data by analyzing the health status of the user based on the correlation between biometric information in the indicator data.

[0012] In addition, the step of calculating the health data reflects a weight value to each biometric information in the indicator data, and calculates the health data using the indicator data to which the weight value is reflected, and the weight value can be variably determined depending on the disease to be determined.

[0013] In addition, the step of receiving the user's communication data may be further included, and the step of calculating the health data may analyze the health status by further considering the communication data.

[0014] Meanwhile, a disease prognosis judgment system using a toothbrush may include a communication unit that receives indicator data containing various bio-information of the user through the toothbrush, a health data generation unit that analyzes the health status of the user based on the indicator data and generates health data, and a control unit that generates control data for controlling the function of the toothbrush based on the health data.

[0015] Additionally, the above indicator data may include the user's body temperature, pulse, oxygen saturation, blood pressure, grip strength, bioelectrical current, expiratory information, ultrasound information, mental health, genetic material, and biomarkers.

[0016] In addition, the step of producing the health data may include inputting the indicator data into a neural network model to produce the health data, and the neural network model may be trained to produce the health data by analyzing the health status of the user based on the correlation between biometric information in the indicator data.

[0017] In addition, the health data generation unit reflects a weight value to each biometric information in the indicator data, and generates health data using the indicator data to which the weight value is reflected, and the weight value can be variably determined depending on the disease to be judged. In addition, the communication unit further receives the user's communication data, and the health data generation unit can analyze the health status by further considering the communication data.

[0018] Meanwhile, a computer-readable recording medium according to an embodiment of the present invention for achieving the above-described purpose may store a program for performing the above-described method. Furthermore, a computer program according to an embodiment of the present invention for achieving the above-described purpose may record program code for executing the above-described method.

[0019] According to the present invention, the prognosis of a disease can be detected early by using the user's biometric information in real time, which enables personalized health management and preventive measures to be taken.

[0020] Additionally, the collected biometric information of the present invention can be shared with medical professionals, which can improve accessibility to medical services by enabling remote diagnosis and consultation.

[0021] FIG. 1 is a conceptual diagram illustrating a system for determining disease prognosis using a toothbrush according to one embodiment of the present invention.

[0022] Figure 2 is a flowchart illustrating a disease prognosis determination method according to one embodiment of the present invention.

[0023] Figure 3 is an exemplary diagram showing an ensemble neural network model according to one embodiment of the present invention.

[0024] Figure 4 is a flowchart illustrating a disease prognosis determination method according to one embodiment of the present invention.

[0025] Figure 5 is a timing diagram showing a disease prognosis determination method according to one embodiment of the present invention.

[0026] am.

[0027] Figure 6 is a block diagram showing the configuration of a disease prognosis judgment system according to one embodiment of the present invention.

[0028] The following merely exemplifies the principles of the invention. Therefore, those skilled in the art will be able to implement the principles of the invention and invent various devices within the scope and spirit of the invention, even if not explicitly described or illustrated herein. Furthermore, all conditional terms and embodiments listed herein are expressly intended, in principle, to facilitate understanding of the invention, and should be understood as being in no way limiting to the specifically enumerated embodiments and conditions.

[0029] The above-described purposes, features and advantages will become clearer through the following detailed description with reference to the attached drawings, so that a person having ordinary skill in the art to which the invention pertains can easily practice the technical idea of ​​the invention.

[0030] Furthermore, when describing the invention, detailed descriptions of known technologies related to the invention will be omitted if they are deemed to unnecessarily obscure the gist of the invention. Below, preferred embodiments of the present invention will be described in detail with reference to the attached drawings.

[0031] FIG. 1 is a conceptual diagram illustrating a system for determining disease prognosis using a toothbrush according to one embodiment of the present invention.

[0032] Referring to FIG. 1, a disease prognosis judgment system (100) using a toothbrush can receive indicator data containing various biometric information of a user from a toothbrush (200). At this time, the toothbrush (200) may have replaceable bristles. Here, the toothbrush (200) refers to an electronic device capable of acquiring a user's biometric information, and the indicator data may include various biometric information that can be acquired through the sensor of the toothbrush (200).

[0033] For example, the indicator data may include various biometric information that can be obtained from the user's body, such as the user's body temperature information, pulse, oral images, breathing strength or breath components / odor (bad breath), grip strength, accumulated usage methods (changes in brushing strength / method, angle of use, function use mode, etc.), ultrasound results, time of use, usage duration, blood pressure, OCT (optical coherence tomography), pH measurement unit, etc.

[0034] In addition, according to an implementation example, the disease prognosis judgment system (100) can receive indicator data or communication data corresponding to the user from an external system (300) (e.g., a hospital medical system, a data analysis system, a user terminal, etc.).

[0035] For example, the disease prognosis judgment system (100) may receive indicator data including mental health information, medical history, etc., medical feedback, etc. from a hospital medical system (300), or may receive indicator data including genetic material and biomarker information, etc. from a data analysis system (300).

[0036] At this time, genetic material and biomarker information may be user indicator data physically acquired through the toothbrush bristles.

[0037] That is, the side operating the external system (300) or the disease prognosis judgment system (100) needs to collect and analyze the toothbrush bristles used by the user.

[0038] In addition, the disease prognosis judgment system (100) can generate health data for disease prognosis by judging the health status of the user based on the received indicator data and communication data.

[0039] Next, the disease prognosis judgment system (100) generates control data that can control the function of the toothbrush (200) using the user's health data and transmits it to the toothbrush (200).

[0040] Can be.

[0041] That is, the disease prognosis judgment system (100) can use the user's indicator data to judge the disease prognosis and control the function of the toothbrush (200) according to the disease prognosis.

[0042] Below, the disease prognosis judgment method of the disease prognosis judgment system (100) is specifically described in Fig. 2.

[0043] Figure 2 illustrates a disease prognosis determination method according to one embodiment of the present invention.

[0044] It's a flow chart.

[0045] Referring to FIG. 2, the disease prognosis judgment system (100) can receive indicator data containing various bio-information of the user from a toothbrush (200) or an external system (300) (S1000).

[0046] Specifically, the disease prognosis judgment system (100) can receive indicator data including the user's body temperature information, pulse, oral cavity image, breathing strength or breath components / odor (bad breath), grip strength, accumulated usage method (degree of change in brushing strength / method, usage angle, function usage mode, etc.), ultrasonic results, usage time, usage duration, etc. from the toothbrush (200). At this time, the toothbrush (200) can also obtain the necessary indicator information through various sensors for obtaining biometric information (for example, an odor sensor capable of sensing bad breath, a temperature sensor for measuring body temperature, an image sensor for obtaining an image of the user's oral cavity, a piezoelectric sensor for measuring grip strength, a geomagnetic sensor for measuring brushing, an ultrasonic sensor, etc.). In addition, the disease prognosis judgment system (100) can receive or directly obtain indicator data including genetic material and biomarker information physically obtained from an external system (300).

[0047] In addition, it is also possible to output certain notification information through the toothbrush (200) and / or the disease prognosis judgment system (100) so that the user can perform the corresponding action, thereby obtaining the necessary indicator information at the necessary time.

[0048] That is, the indicator data may include the user's body temperature, pulse, oxygen saturation, grip strength, bioelectrical current, expiratory information, ultrasound information, mental health, genetic material, and biomarkers.

[0049] Next, the disease prognosis judgment system (100) can analyze the user's health status based on the user's indicator data and produce health data (S2000).

[0050] Specifically, in the health data production step (S2000), the disease prognosis judgment system (100) can compare whether the numerical value or the degree of change in the user's indicator data matches the disease reference data, and then produce health data including the user's disease prognosis. At this time, the disease reference data may be data in which the numerical values ​​of various bio-information are tabulated according to the type of disease (e.g., caries, gingivitis, periodontal disease, halitosis, oral cancer, gastrointestinal disease (GI tract related), obesity, sinusitis, rhinitis, extraoral disease causing bad breath, etc.) and the prognosis of the disease.

[0051] In addition, in the health data production step (S2000), the disease prognosis judgment system (100) can produce health data by inputting indicator data into a pre-trained neural network model. At this time, the neural network model is trained to produce the user's health data by analyzing the user's health status based on the correlation between bio-information in the indicator data, and a convolutional neural network (CNN), a recurrent neural network (RNN), etc. can be used. Here, the health data includes information related to the prognosis of the disease, and may include the type of the user's disease, accuracy, and degree of disease progression.

[0052] Additionally, the neural network model learns the degree of disease progression based on the numerical value or degree of change in the disease indicator group, and can also determine the prognosis of a disease by learning the degree of change in the accumulated user indicator information and the correlation with the disease.

[0053] For example, a neural network model for learning the correlation between disease and changes in disease indicators or indicator information can be trained by receiving a large number of labeled, standardized data as input data, and can be trained to determine characteristic patterns between changes in specific indicator information and specific diseases to produce health data.

[0054] In addition, the disease prognosis judgment system (100) reflects a weight value for each biometric information within the indicator data, and can calculate health data using the indicator data with the weight value reflected. At this time, the disease prognosis judgment system (100) can variably reflect the weight value by considering the user's brushing strength, brushing method (pattern), and grip strength.

[0055] In addition, the disease prognosis judgment system (100) can variably determine weight values ​​in the time series for bio-information acquired in a time series and reflect them in the corresponding bio-information.

[0056] Through this, the disease prognosis judgment system (100) can correct the measurement error of the indicator data to judge a more accurate disease prognosis.

[0057] In addition, the disease prognosis judgment system (100) can select at least one biometric information among the user's indicator data according to the selection criteria, and generate health data by judging the user's health status using only the selected biometric information.

[0058] At this time, the selection criteria for indicator data can be variably determined based on the type of disease, user personal information (age, gender, past medical history, etc.), and reliability of biometric information.

[0059] For example, the disease prognosis judgment system (100) can judge the reliability of the current biometric information received using past biometric information, and if the reliability of the biometric information is judged to be low, the disease prognosis can be judged using indicator data from which the biometric information is excluded.

[0060] In addition, the disease prognosis judgment system (100) can classify indicator data into several partial indicator data according to selection criteria and input the partial indicator data into an ensemble neural network model to generate health data. Here, partial indicator data refers to indicator data in which only a portion of the bioinformation is selected.

[0061] In this regard, an explanation is provided with reference to Fig. 3.

[0062] Figure 3 is an exemplary diagram showing an ensemble neural network model according to one embodiment of the present invention.

[0063] Referring to FIG. 3, the disease prognosis judgment system (100) can classify indicator data into first partial indicator data, second partial indicator data, …, and Nth partial indicator data according to selection criteria, and input each classified partial indicator data into an ensemble neural network model (30).

[0064] And, the partial indicator data are each inputted into a partial neural network model (31) within the ensemble neural network model (30), and each prediction data outputted from the partial neural network model (31) is inputted again into the meta model (32), and the meta model (32) can make a final prediction based on the prediction data outputted from the partial neural network model and output the health data of the corresponding user.

[0065] Meanwhile, the disease prognosis judgment system (100) can additionally consider the user's communication data to produce health data.

[0066] In this regard, further explanation is provided with reference to Fig. 4.

[0067] Referring to FIG. 4, the disease prognosis judgment system (100) can receive the user's communication data through the user terminal (hereinafter, external system) (S1100). Here, the communication data can include information such as email, chat, text, call history, etc.

[0068] And, in the health data production step (S2000), the disease prognosis judgment system (100) can analyze the user's health status by additionally considering communication data.

[0069] Specifically, the disease prognosis judgment system (100) can analyze and learn the degree of change in the words used in communication data (the words themselves and the length of sentences), call time, and voice tone (excluding changes in tone) depending on when the user is in normal condition and when the user is sick, thereby judging the user's disease prognosis.

[0070] For example, a disease prognosis judgment system (100) collects and learns the user's communication information in normal times and the communication information when the user is ill, and if it detects that the user's communication data changes from normal times to communication data when the user is ill, it can be determined that there is a disease prognosis.

[0071] Again, referring to FIG. 2, the disease prognosis judgment system (100) can generate control data for controlling the function of the toothbrush (200) based on health data (S3000).

[0072] Specifically, the disease prognosis judgment system (100) can generate control data for controlling the function of the toothbrush (100) by considering the type of disease, disease progression, etc. in the health data. Here, the control data relates to the control of the function of the toothbrush (100) that can help the user's health, and can include information about the near-infrared intensity, vibration degree, vibration pattern, etc. of the toothbrush (100).

[0073] Additionally, the disease prognosis judgment system (100) can generate control data for controlling the function of the toothbrush (200) based on health feedback data received from an external system (300). Here, the health feedback data is health-related information presented by a doctor (attending physician) after analyzing the user's health data, and may refer to data on measures to improve disease prognosis.

[0074] Next, with reference to FIG. 5, the data transmission relationship between the disease prognosis judgment system (100), the toothbrush (200), and the external system (300) will be described.

[0075] Figure 5 is a timing diagram showing a disease prognosis determination method according to one embodiment of the present invention.

[0076] Referring to FIG. 5, the toothbrush (200) can obtain biometric information and generate index data each time the user brushes his / her teeth (S1001).

[0077] In addition, the disease prognosis judgment system (100) can request and receive indicator data from the toothbrush (200) (S1002), and can request and receive indicator data and communication data from an external system (300) (S1003). At this time, the disease prognosis judgment system (100) can request indicator data and communication data at each reference interval, and the reference interval can be variably determined depending on the user's health status, communication environment, etc.

[0078] Next, the disease prognosis judgment system (100) analyzes the user's health status using indicator data and communication data to produce health data (S1004), and can transmit the produced health data upon request from an external system (300) (S1005). At this time, the disease prognosis judgment system (100) can transmit the health data to the external system (300) even if there is no request from the external system (300) if the health data is generated.

[0079] And, the disease prognosis judgment system (100) can receive health feedback data corresponding to health data (S1006). At this time, the health feedback data can be generated by a doctor.

[0080] Next, the disease prognosis judgment system (100) can generate control data for controlling the function of the toothbrush (200) (S1007) and transmit the generated control data to the toothbrush (200) (S1008).

[0081] After that, the toothbrush (200) can operate a function based on the control data (S1009). For example, the toothbrush (200) can control the near-infrared intensity, vibration degree, and vibration pattern based on the control data.

[0082] Additionally, the toothbrush (200) is based on the user's brushing pattern (direction) control data.

[0083] In cases other than the above, it may provide warning notifications, warning messages, etc.

[0084] Hereinafter, the configuration of the disease prognosis judgment system (100) will be described with reference to FIG. 6.

[0085] Figure 6 is a block diagram showing the configuration of a disease prognosis judgment system (100) according to one embodiment of the present invention.

[0086] Referring to FIG. 6, the disease prognosis judgment system (100) may include some or all of a communication unit (110), a health data generation unit (120), a database (130), and a control unit (140).

[0087] The communication unit (110) can communicate with multiple devices and transmit and receive multiple data.

[0088] Specifically, the communication unit (110) can receive indicator data including various biometric information of the user from the toothbrush (200) or can receive indicator data, health feedback data, communication data, etc. from an external system (300).

[0089] Additionally, the communication unit (110) can transmit health data to an external system (300). The health data generation unit (120) can analyze the user's health status based on indicator data and generate health data.

[0090] Specifically, the data generation unit (120) can compare whether the numerical value or degree of change in the user's indicator data matches the disease reference data, and then generate health data including the user's disease prognosis.

[0091] Additionally, the data generation unit (120) can input indicator data into a pre-trained neural network model to generate health data.

[0092] The database (130) may store various data generated or received from various components of the disease prognosis judgment system (100).

[0093] Specifically, the database (130) is classified by user into indicator data, health feedback data, communication data, health feedback data, and control data.

[0094] Can be saved.

[0095] Additionally, a neural network model, an ensemble neural network model, etc. may be stored in the database (130), and a program for performing a disease prognosis judgment method may be stored. The control unit (140) may control the overall operation of the disease prognosis judgment system (100).

[0096] Specifically, the control unit (140) can control the communication unit (110) to receive indicator data, health feedback data, and communication data or transmit health data.

[0097] Additionally, the control unit (140) can generate control data for controlling the function of the toothbrush based on health data.

[0098] Meanwhile, each component of the disease prognosis judgment system (100) can perform the operation of the disease prognosis judgment system (100) of FIGS. 2 to 5 described above.

[0099] According to the present invention, the prognosis of a disease can be detected early by using the user's biometric information in real time, which enables personalized health management and preventive measures to be taken.

[0100] Furthermore, the collected biometric information can be shared with medical professionals, enabling remote diagnosis and consultation, thereby improving accessibility to medical services. Furthermore, by accumulating data from numerous users, the present invention can create a large-scale health database. This database can be utilized in health-related research to understand the correlations between disease patterns, behavior, and biometric information.

[0101] Additionally, since the present invention can identify a user's health status in real time through biometric information, it can be utilized by insurance companies to offer personalized insurance rates or reward healthy behavior.

[0102] Meanwhile, a method for determining disease prognosis using a toothbrush according to an embodiment of the present invention may be implemented in the form of a computer-readable program command and stored in a computer-readable recording medium, and a control program and a target program according to an embodiment of the present invention may also be stored in a computer-readable recording medium.

[0103] Computer-readable recording media include all types of recording devices that store data that can be read by a computer system.

[0104] Meanwhile, the various embodiments described herein may be implemented in a recording medium readable by a computer or similar device, for example, using software, hardware, or a combination thereof.

[0105] In terms of hardware implementation, the embodiments described herein can be implemented using at least one of ASICs (application specific integrated circuits), DSPs (digital signal processors), DSPDs (digital signal processing devices), PLDs (programmable logic devices), FPGAs (field programmable gate arrays), processors, controllers, micro-controllers, microprocessors, and other electrical units for performing functions. In some cases, the embodiments described herein can be implemented as a control module itself.

[0106] In a software implementation, the procedures and functions described herein, as well as other embodiments, may be implemented as separate software modules. Each of these software modules may perform one or more of the functions and operations described herein. The software code may be implemented as a software application written in a suitable programming language. The software code may be stored in a memory module and executed by a control module.

[0107] The above description is merely an example of the technical idea of ​​the present invention, and those skilled in the art will appreciate that various modifications, changes, and substitutions can be made without departing from the essential characteristics of the present invention.

[0108] Accordingly, the embodiments disclosed in the present invention and the accompanying drawings are intended to illustrate, rather than limit, the technical concept of the present invention, and the scope of the technical concept of the present invention is not limited by these embodiments and the accompanying drawings. The scope of protection of the present invention should be interpreted by the following claims, and all technical concepts within the scope equivalent thereto should be interpreted as being included within the scope of the rights of the present invention.

[0109] According to the present invention, a user's biometric information can be used in real time to detect disease prognosis early, enabling personalized health management and preventive measures. Furthermore, the collected biometric information can be shared with medical professionals, enabling remote diagnosis and consultation, thereby improving accessibility to medical services.

Claims

1. In the method of determining disease prognosis using a toothbrush, Receive index data containing various biometric information of the user through the toothbrush above. is the step; Based on the above indicator data, the health status of the user is analyzed to provide health data. Step of producing a ter; and Control data for controlling the function of the toothbrush based on the above health data A method for determining disease prognosis, comprising the steps of:

2. In paragraph 1, The above indicator data includes the user's body temperature, pulse, oxygen saturation, grip strength, and vital signs. Including current, expiratory information, ultrasound information, mental health, genetic material and biomarkers. A method for determining disease prognosis, characterized by:

3. In paragraph 1, The step of producing the above health data is to input the above indicator data into a neural network model. and produce health data, The above neural network model is characterized by being trained to analyze the health status of the user based on the correlation between biometric information in the index data and to produce the health data. A method for judging disease prognosis.

4. In paragraph 1, The step of producing the above health data is to calculate each biometric information within the above indicator data. It reflects the weight value and uses the indicator data that reflects the weight value to display health data. Produce, A disease prognosis judgment method characterized in that the above weights are variably determined depending on the disease being judged.

5. In paragraph 1, Further comprising a step of receiving the user's communication data; A method for determining a disease prognosis, characterized in that the step of producing the above health data analyzes the health status by additionally considering the above communication data.

6. In a disease prognosis judgment system using a toothbrush, Receive index data containing various biometric information of the user through the toothbrush above. is the communications department; A health data generation unit that analyzes the health status of the user based on the above indicator data and generates health data; and Control data for controlling the function of the toothbrush based on the above health data A disease prognosis judgment system comprising a control unit that generates; 7. In paragraph 6, The above indicator data includes the user's body temperature, pulse, oxygen saturation, grip strength, and vital signs. Including current, expiratory information, ultrasound information, mental health, genetic material and biomarkers. A disease prognosis judgment system characterized by:

8. In paragraph 6, The step of producing the above health data is to input the above indicator data into a neural network model. and produce health data, The above neural network model is based on the correlation between biometric information in the index data. It is characterized by being trained to analyze the user's health status and produce the above health data. A disease prognosis judgment system.

9. In paragraph 6, The above health data generation unit applies a weight to each biometric information in the above indicator data. It reflects the value and calculates health data using indicator data that reflects the weighted value. A disease prognosis judgment system characterized in that the above weights are variably determined depending on the disease being judged.

10. In paragraph 6, The above communication unit further receives the user's communication data, A disease prognosis judgment system characterized in that the health data output unit analyzes the health status by additionally considering the communication data.

11. A computer-readable recording medium storing a program for performing a disease prognosis determination method described in any one of claims 1 to 5.

12. Stored in a computer-readable recording medium and referred to in one of the clauses 1 to 5. A computer program comprising program code for executing a method for determining disease prognosis.

Images