WO2016200244A1 - Système informatique et procédé d'aide à la classification du mibyeong sur la base de l'analyse du gaz respiratoire - Google Patents

Système informatique et procédé d'aide à la classification du mibyeong sur la base de l'analyse du gaz respiratoire Download PDF

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WO2016200244A1
WO2016200244A1 PCT/KR2016/006276 KR2016006276W WO2016200244A1 WO 2016200244 A1 WO2016200244 A1 WO 2016200244A1 KR 2016006276 W KR2016006276 W KR 2016006276W WO 2016200244 A1 WO2016200244 A1 WO 2016200244A1
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subject
computer
model
information
respiratory gas
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PCT/KR2016/006276
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English (en)
Korean (ko)
Inventor
이시우
이영섭
진희정
박만영
박기현
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Korea Institute of Oriental Medicine KIOM
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Korea Institute of Oriental Medicine KIOM
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Priority claimed from KR1020150125544A external-priority patent/KR101785788B1/ko
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    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material
    • G01N33/497—Physical analysis of biological material of gaseous biological material, e.g. breath
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass

Definitions

  • a computing system and a method of operating the same are provided to process the data obtained through the respiratory gas analysis required for the activity to assist in the classification of the disease.
  • the World Health Organization defines 'health' as a physical, mental and social well-being and not simply a state without illness or weakness.
  • the 'illness' state is an intermediate step between health and illness, and can be interpreted as a kind of deterioration state that can lead to disease if left unattended.
  • respiratory gas analysis according to activity is an important indicator in determining the individual's exercise ability, muscle mitochondria efficiency, circulatory function.
  • Maximum oxygen intake which is commonly used in respiratory gas analysis, is one of the important determinants of endurance exercise ability and is used to compare aerobic exercise capacity. This information is determined by genetic factors, gender, age and body type, but can also be increased through exercise, especially when assessing athletes' athletic performance.
  • the ability to inhale oxygen in the air and deliver it to each part of the body through breathing, and at the same time, the ability to release carbon dioxide means the activity of the overall function of the body, which is not yet a medical condition, but the quality of health is deteriorated. There is something in common with the disease that means.
  • a system for classifying diseases of oriental medicine using reference data including control information between a healthy group and a US group for respiratory gas parameters and constitution information is provided.
  • a system for objectively quantifying a disease in a subject by using quantitative indicators associated with respiratory gas, which indicates the overall physiological activity of the human body is provided.
  • a computer-implemented system is provided that is at least temporarily implemented by a computer to assist in disease classification.
  • the computer-implemented system includes an interface unit for interfacing with a database storing reference data including reference information of health and US soldiers for respiratory gas parameters and constitution information, and at least one measured and input for the subject. And a processor for determining whether the subject corresponds to the health group or the US disease group based on the first respiratory gas parameter and first constitution information corresponding to the subject.
  • the respiratory gas parameter may include at least one of a maximum oxygen amount, a maximum carbon dioxide amount, a ratio of a maximum oxygen amount to a heart rate, and a ratio of a ventilation amount to a maximum carbon dioxide amount.
  • the processor makes the determination using at least one of a CART model, a RandomForest model, an MNL model, an SVM model, and an NN model.
  • the processor determines a model to be used for the determination of the subject among the CART model, the RandomForest model, the MNL model, the SVM model, and the NN model according to the first constitution information.
  • the reference data is a classification of the health group and the U.S. armed group according to demographic information including age and gender, and physique information including weight and height
  • the processor may divide the population of the subject. The determination is further performed using the academic information and the physique information of the subject.
  • the determination result according to one embodiment is provided to the database through the interface unit and optionally reflected in the reference data, thereby contributing to data training.
  • a computer-implemented method includes maintaining an interface for interfacing with a database storing reference data including reference data of health and US soldiers for respiratory gas parameters and constitution information, and measuring and inputting a subject. And determining whether the subject corresponds to the health group or the US disease group by comparing the at least one first respiratory gas parameter and the first constitution information corresponding to the subject with the reference data, wherein the breathing is performed.
  • the gas parameter includes at least one of the maximum oxygen amount, the maximum carbon dioxide amount, the ratio of the maximum oxygen amount to the heart rate, and the ratio of the ventilation amount to the maximum carbon dioxide amount.
  • the determining may include determining a model to be used for the determination of the subject among the CART model, the RandomForest model, the MNL model, the SVM model, and the NN model according to the first constitution information. It includes a step.
  • the reference data is divided into the health group and the US disease group according to demographic information including age and gender, and physique information including weight and height, and the determining includes: And performing the determination by further using demographic information of the subject and the physique information of the subject.
  • the determination result according to one embodiment is provided to the database through the interface unit and optionally reflected in the reference data, thereby contributing to data training.
  • a computer-implemented program is measured for a subject and a set of instructions for maintaining an interface for interfacing with a database storing reference data including reference data of health and US soldiers for respiratory gas parameters and constitution information. And a set of instructions for determining whether the subject corresponds to the health group or the US disease group based on the input data including at least one first respiratory gas parameter and first constitution information corresponding to the subject,
  • the respiratory gas parameter includes at least one of the maximum oxygen amount, the maximum carbon dioxide amount, the ratio of the maximum oxygen amount to the heart rate, and the ratio of the ventilation amount to the maximum carbon dioxide amount.
  • the disease of oriental medicine may be classified using reference data including control information between the health group and the US disease group for the respiratory gas parameter and the constitution information.
  • the disease of the subject may be objectively quantified by using quantitative indicators associated with respiratory gas, which indicates the overall physiological activity of the human body.
  • FIG. 1 is a diagram illustrating an entire system utilizing a computer implemented system according to an embodiment.
  • FIG. 2 is a diagram illustrating a computer-implemented system according to one embodiment.
  • FIG. 3 is a diagram illustrating the disease evaluation and respiratory gas data collected for non-ill patients.
  • FIG. 4 illustrates a computer-implemented method according to an embodiment.
  • FIG. 1 is a diagram illustrating an entire system 100 utilizing a computer implemented system 140 according to one embodiment.
  • the entire system 100 may monitor a disease state for a user by utilizing the computer implemented system 140 according to an embodiment.
  • the computer implemented system 140 may collect various types of respiratory gases from the respiratory gas analyzer 110.
  • the respiratory gas analyzer 110 may measure oxygen per minute, ventilation per minute, carbon dioxide emissions per minute, heart rate per minute, and provide the measured information to the computer implemented system 140.
  • the heart rate per minute may be measured in the wearable band, and the respiratory gas analyzer 110 may collect the heart rate per minute measured by the wearable band and provide it to the computer implemented system 140.
  • the computer implemented system 140 may use information provided from the respiratory gas analyzer 110 as an important indicator for determining an individual's athletic ability, the efficiency of muscle mitochondria, the circulation function, and the like.
  • Computer-implemented system 140 may calculate the maximum oxygen intake from the information provided from the breathing gas analyzer 110, which is one of the important factors that determine the endurance athletic performance, It can also be used for evaluation.
  • the computer-implemented system 140 may determine whether the disease is not a medical condition but a disease that indicates a deteriorated quality of health through the ability to emit carbon dioxide.
  • the computer-implemented system 140 may collect body information such as a gender, height, and weight of the subject.
  • the computer-implemented system 140 may collect body type information such as the height and weight of the subject from the body type / gender measuring unit 120.
  • the body type / gender measuring unit 120 may transmit body shape information, such as height and weight, collected from the subject to the computer-implemented system 140 through a wired / wireless communication network.
  • the body shape / gender measurer 120 may transmit body shape information, such as height and weight, collected from the subject to the computer-implemented system 140 using a short range communication method.
  • the body type / gender measuring unit 120 may be in the form of a measuring device that can measure the body shape of the subject rather than a terminal such as a smart phone.
  • the measuring device may be connected to a wired or wireless communication network or may include a communication module for short-range wireless communication.
  • the computer-implemented system 140 may further consider the subject's frail constitution in classifying diseases.
  • the subject may request to transmit the filamentous constitution through the body / gender 120 to the computer implemented system 140.
  • the computer-implemented system 140 may finally classify the disease by applying the filamentous constitution of the subject in order to increase the accuracy of the filamentous constitution after classifying the disease.
  • computer-implemented system 140 may finally classify the disease based on the subject's frail constitution among already classified disease.
  • computer-implemented system 140 may train the reference data by using the disease of the classified subject.
  • the subject A may register on a web page related to the computer-implemented system 200, and register height, weight, and gender information when registering. If you know the constitution, you can enter the constitution value, if you do not know can perform the constitution diagnosis tool. That is, the subject does not have to input the constitution value. That is, the subject may input constitution information at a specific time while using the web page related to the computer-implemented system 200.
  • the body shape / gender measurer 120 may provide the inputted constitution information to the computer implemented system 200.
  • the computer-implemented system 140 classifies the diseased stages of the subject by applying the disease evaluation variable of the subject to the disease classification apparatus.
  • the data used for classification target the currently collected clinical data, and the classification algorithm is updated with the addition of clinical data with established disease stages.
  • Computer-implemented system 140 may generate a variable for the evaluation of disease using the collected information, and may use it to classify disease for a subject from a database recorded as clinical data.
  • the computer-implemented system 140 may generate a variable for disease classification using the collected information. To this end, the computer-implemented system 140 finds the maximum values of oxygen and carbon dioxide per minute, corrects the subject's height, weight, gender, and frail constitution, and generates a disease evaluation parameter of the subject. In addition, a new variable may be generated by dividing the maximum amount of oxygen and the amount of carbon dioxide by heart rate.
  • FIG. 2 is a diagram illustrating a computer implemented system 200 according to an embodiment.
  • the computer implemented system 200 includes an interface unit 210 and a processor 220.
  • the interface unit 210 interfaces with a database 230 that stores reference data including control information of a health group and a US soldier against a respiratory gas parameter and constitution information.
  • the database 230 may record the respiratory gas data per minute with the disease evaluation for non-diseases for a certain period, which will be described in more detail with reference to FIG. 3.
  • the processor 220 includes the at least one first respiratory gas parameter measured and input to the subject and first constitution information corresponding to the subject in relation to the reference data. Determine if it corresponds.
  • the processor 220 may classify the disease from the respiratory gas parameters using various classification algorithms. For example, the processor 220 generates a disease classification algorithm using the disease diagnosis result and the respiratory gas variable in the data and tests the accuracy. At this time, the disease classification algorithm may be classified into a classification and regression trees (CART) model, a randomForest model, an MNL model, a support vector machine (SVM) model, a neural network (NN) model, and the like. The disease can be classified by data mining methods.
  • CART classification and regression trees
  • SVM support vector machine
  • NN neural network
  • the processor 220 using at least one of the classification and regression trees (CART) model, the randomForest model, the MNL model, the support vector machine (SVM) model, the neural network (NN) model, any of the health and US soldiers It can be determined whether the correspondence.
  • the processor 220 may determine a model to be used for the determination without directly performing the determination.
  • oriental medical disease reflects all of the subject's general physical condition, it is meaningful to classify the disease based on respiratory gas in terms of checking the individual's physical condition every day before consulting a specialist.
  • the processor 220 may classify an illness from a database by using variables calculated from respiratory gas and eventual constitution information of the subject. To this end, the processor 220 may determine the subject's thought constitution information based on the identification information for each of the thought constitutions input from the user terminal, and classify the illness using the determined thought constitution information. In other words, the processor 220 may receive the physiological constitution from the user and use it for classifying disease.
  • the processor 220 may diagnose a sacrificial constitution of the subject by using a diagnostic tool, determine the sacrificial constitution information, and classify the disease by using the determined sacrificial constitution information.
  • the processor 220 may classify the final disease by applying the subject's filamentous constitution to classified frailties in order to increase accuracy with filamentous constitution after classifying the disease. That is, the processor 220 may finally classify the disease based on the physiological constitution of the subject among the already classified disease.
  • the processor 220 may train the reference data by using the disease of the classified subject.
  • the target person A may register on a web page related to the computer-implemented system 200 and register height, weight, and gender information when registering. If you know the constitution, you can enter the constitution value, if you do not know can perform the constitution diagnosis tool. That is, the subject does not have to input the constitution value. That is, the subject may input the constitution information at a specific point in time while using the web page associated with the computer-implemented system.
  • Subject A uses a respiratory analyzer to measure the volume of respiratory gas per minute and transmits it to the disease classification system via Bluetooth or direct connection. If necessary, self-entry can be performed on the disease classification system.
  • Subject A's heart rate can be measured together with a respiratory analyzer or can be measured separately using a wearable band.
  • data may be transmitted to the computer-implemented system 200 using Bluetooth or directly connected to a computer.
  • the computer-implemented system 200 may use the currently input height and weight, or input new height and weight according to the user's judgment.
  • the computer implemented system 200 may classify the disease by using a disease classification algorithm.
  • the computer-implemented system 200 may display the unclassified result of the subject in a result window or a result sheet, and display a corresponding management method.
  • FIG. 3 is a diagram illustrating data 300 related to cardiovascular evaluation and cardiovascular circulatory function collected for non- diseased persons.
  • the reference data is a segmentation of the health group and the U.S. soldier according to the demographic information including age and gender, and the physique information including weight and height, and the processor may divide the demographic information of the subject and the physique information of the subject. Determination may be performed using more.
  • the data 300 is based on the disease evaluation and respiratory gas data for non-ill patients, and measures the minute volume of breath per minute for 232 healthy and 99 US soldiers, and sets the maximum value among these data. Values were generated by correcting each maximum value in consideration of the height, weight, and gender. These variables were used to test the difference between the healthy group and the US group, and the classification of the healthy group and the US group was collected using the Disease Classification Questionnaire of the Korea Institute of Oriental Medicine.
  • the data 300 shows that the U.S. military has reduced the maximum amount of oxygen and the maximum amount of carbon dioxide compared to the health group, and can improve the accuracy of classification by using correction variables such as heart rate and ventilation amount when there is gender or specific constitution information.
  • the disease classification result and the respiratory gas parameters may be used to generate the disease classification algorithm and test the accuracy.
  • disease classification algorithms include classification and regression trees (CART) models, randomForest models, MNL models, support vector machine (SVM) models, neural network (NN) models, and the like. The disease can be classified by applying.
  • the data is classified according to gender or constitution, and then randomly assigned 70% to the training set and 30% to the test set to verify the accuracy of the algorithm generated in the training set in the test set 100 times. Can be done.
  • Table 1 shows the total data of the quartile and the mean of the distribution of the accuracy tested in the test set.
  • [Table 2] is a result of analyzing male data among the total data, it is analyzed to show a value that is generally higher than the values of the total data.
  • Table 3 is a result of analyzing the female data of the total data, it is analyzed that the value is generally lower than the values of the entire data as well as the male data of [Table 2].
  • Table 4 shows the results of classification by the disease-free classification algorithm for the Taeumin among all the data.
  • variables used to determine disease classification for subjects based on respiratory gases are oxygen per minute, carbon dioxide, ventilation, and heart rate, and computer-implemented systems use this to maximize oxygen, maximum carbon dioxide, heart rate, and ventilation rate. Variables can be used to classify diseases.
  • a computer-implemented system can add variables such as respiratory (RC) correction, oxygen, carbon dioxide, body mass index (BMI) correction, and metabolism (MET) for each variable for analysis. have.
  • RC respiratory
  • BMI body mass index
  • MET metabolism
  • the maximum oxygen intake (VO2 peak) is a major index for assessing cardiopulmonary function, which can be used in computer-implemented systems as a criterion for evaluating cardiopulmonary endurance or aerobic capacity
  • the lactate threshold (VO2 LT) is also known as endurance performance. It can be used as a useful indicator for predicting cardiovascular disease.
  • the maximum exercise capacity (METs) is determined according to the respiration and circulation function, it can be used as an indicator for evaluating the maximum oxygen uptake (VO2 peak) and lactate threshold (VO2 LT).
  • VO2 peak maximum oxygen uptake
  • VO2 LT lactate threshold
  • the disease is judged by reflecting the overall physical condition of the subject, and the criterion is mostly composed of subjective factors. Therefore, in the present invention, by using the quantitative indicators associated with the respiratory gas, which means the overall physiological activity of the human body can objectively quantify the disease of the subject.
  • FIG. 4 is a diagram illustrating a computer-implemented method for classifying a disease according to an embodiment.
  • the computer-implemented method maintains an interface for interfacing with a database storing reference data including reference information of health and US soldiers for respiratory gas parameters and constitution information, and at least measured and input to the subject.
  • reference data including reference information of health and US soldiers for respiratory gas parameters and constitution information, and at least measured and input to the subject.
  • One of the first respiratory gas parameters and the first constitution information corresponding to the subject may be compared with the reference data to determine whether the subject corresponds to the health group or the US soldier.
  • the computer-implemented method may collect respiratory gas related information (step 401).
  • the respiratory gas related information includes at least one of oxygen absorption amount per minute, ventilation amount per minute, carbon dioxide emission per minute, and heart rate per minute.
  • the heart rate per minute may be measured in the wearable band, and the wearable band may collect the measured heart rate per minute and provide it to a computer-implemented system.
  • the maximum oxygen intake which is one of the important factors that determine the endurance athletic performance, may be used in the evaluation of aerobic exercise capacity.
  • the computer-implemented method collects the respiratory gas-related information, it is possible to determine whether or not the filamentous constitution information on the subject is recorded (step 402). If the Sasang constitution information is not recorded, the computer-implemented method determines whether to measure the constitution (step 403), and receives the input from the subject directly from the subject according to the determination result, or judges the Sasang constitution using a diagnostic tool. May be step 404.
  • the computer-implemented method may determine whether there is gender information for the target person (step 405).
  • the computer-implemented method may measure metabolic amount in consideration of the collected information and the gender of the subject (step 406).
  • the computer-implemented method may determine whether to receive a gender from the subject (step 407), and may receive a gender from the subject according to the determination result (step 407). 408). If no gender is input, the computer-implemented method may branch to step 406.
  • the collected amount of information related to the collected respiratory gas may be used to measure metabolic rate for the subject.
  • the computer-implemented method may determine whether there is no disease, which means a state in which the quality of health is deteriorated, although it is not yet a medical condition based on the measured metabolic amount.
  • the computer-implemented method according to an embodiment may transmit the classified illness-related results to the terminal of the subject (step 409).
  • the disease of oriental medicine may be classified using reference data including control information of a healthy group and a US group with respect to respiratory gas parameters and constitution information.
  • Method according to an embodiment of the present invention can be implemented in the form of program instructions that can be executed by various computer means may be recorded on a computer readable medium.
  • the computer readable medium may include program instructions, data files, data structures, etc. alone or in combination.
  • Program instructions recorded on the media may be those specially designed and constructed for the purposes of the present invention, or they may be of the kind well-known and available to those having skill in the computer software arts.
  • Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tape, optical media such as CD-ROMs, DVDs, and magnetic disks, such as floppy disks.
  • Examples of program instructions include not only machine code generated by a compiler, but also high-level language code that can be executed by a computer using an interpreter or the like.
  • the hardware device described above may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

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Abstract

La présente invention a trait à un système informatisé destiné à faciliter un processus de classification du mibyeong, et à un procédé de fonctionnement de ce système, un système informatisé selon un mode de réalisation comprenant : une unité de calcul conçue pour compenser les paramètres cardiovasculaires collectés sur une personne examinée en fonction de sa biométrie ; et une unité de traitement permettant la classification du mibyeong, conformément aux paramètres cardiovasculaires compensés, au moyen d'une base de données qui contient des données de référence incluant des informations comparatives relatives à un groupe sain et un groupe en état de mibyeong pour chaque paramètre cardiovasculaire.
PCT/KR2016/006276 2015-06-12 2016-06-13 Système informatique et procédé d'aide à la classification du mibyeong sur la base de l'analyse du gaz respiratoire Ceased WO2016200244A1 (fr)

Applications Claiming Priority (4)

Application Number Priority Date Filing Date Title
KR10-2015-0083728 2015-06-12
KR20150083728 2015-06-12
KR10-2015-0125544 2015-09-04
KR1020150125544A KR101785788B1 (ko) 2015-06-12 2015-09-04 호흡가스 분석에 기반하여 미병 분류를 보조하는 컴퓨팅 시스템 및 방법

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Cited By (1)

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Publication number Priority date Publication date Assignee Title
CN112885476A (zh) * 2019-11-29 2021-06-01 深圳市大雅医疗技术有限公司 一种数据关联方法、装置、服务器及存储介质

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KR20070083810A (ko) * 2004-10-28 2007-08-24 가부시키가이샤 심스 질병 진단 시스템
JP2013523242A (ja) * 2010-03-31 2013-06-17 コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ 患者により排せつされる総二酸化炭素の要素の測定
JP2014502894A (ja) * 2010-12-21 2014-02-06 コーニンクレッカ フィリップス エヌ ヴェ 非侵襲的換気中に排出される二酸化炭素を決定するシステム及び方法
JP5443376B2 (ja) * 2007-11-13 2014-03-19 オリディオン・メディカル・１９８７・リミテッド 医療装置

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Publication number Priority date Publication date Assignee Title
US20040100376A1 (en) * 2002-11-26 2004-05-27 Kimberly-Clark Worldwide, Inc. Healthcare monitoring system
KR20070083810A (ko) * 2004-10-28 2007-08-24 가부시키가이샤 심스 질병 진단 시스템
JP5443376B2 (ja) * 2007-11-13 2014-03-19 オリディオン・メディカル・１９８７・リミテッド 医療装置
JP2013523242A (ja) * 2010-03-31 2013-06-17 コーニンクレッカ フィリップス エレクトロニクス エヌ ヴィ 患者により排せつされる総二酸化炭素の要素の測定
JP2014502894A (ja) * 2010-12-21 2014-02-06 コーニンクレッカ フィリップス エヌ ヴェ 非侵襲的換気中に排出される二酸化炭素を決定するシステム及び方法

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN112885476A (zh) * 2019-11-29 2021-06-01 深圳市大雅医疗技术有限公司 一种数据关联方法、装置、服务器及存储介质

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