KR101555541B1 - Method for producing wellbeing life care index model in Ubiquitous environment - Google Patents

Abstract

A method of manufacturing a well-being life-care index model in a ubiquitous environment is disclosed. The method of manufacturing a well-being life-care index model in a ubiquitous environment according to an embodiment of the present invention is characterized in that sub-factors constituting factors for determining a well-being index index have a reference value indicating a weight occupied in a corresponding factor, Determining the well-being index index by adding the sub-factor values calculated by multiplying the sub-factor values by a predetermined characteristic weight to obtain respective factor values, and adding weight factor values determined by multiplying the factor values by a factor weight.

Description

[0001] The present invention relates to a method for producing a well-being life-care index model in a ubiquitous environment,

The present invention relates to a method for producing a well-being life-care index model in a ubiquitous environment. In particular, by collecting and analyzing personal lifestyle data, personal life patterns for a well-being life care of each member constituting a ubiquitous society are quantified And how to build an index model that provides refined criteria for self-monitoring of well-being.

Currently, the program for supporting individual health information includes a method of obtaining personal health information by visiting a medical institution directly at a high cost and a variety of online health support programs (hereinafter referred to as "health portal site" ) Can be divided into a method of providing limited contents to the health condition of the person by inputting and replicating some information directly into the check list.

In the former case, since health information is provided on the basis of the biometric data as a result of the test, not only limited information but also various tests are added, thereby increasing the burden of medical expenses on the general health checkup subjects.

In the case of a health portal site, due to the limitation of the provision of uniformized information (the body mass index, the temporary blood pressure value, etc.) of the portal service, the health index service is provided only in response to the checklist provided by a specific portal site. Service can not be expected. In addition, both kinds of programs provide only contents about health status, and they do not provide an index service expressing the condition of the whole life such as sensitivity, personal preference.

I would like to receive personalized personalized health information and wellness services that include personalized health information and personalized measures that would interest an increase in income and overall quality of life. Lack.

In addition, medical institutions use supplementary application software for analyzing data after health checkup, but these software only visualize the data of clinical data at the time of measurement, against general standards.

In addition, since most of the support contents use physical information and clinical measurement information, important lifestyle information on individual daily patterns of nutrition, overall eating habits, exercise behavior, preference (smoking, snacks, drinking etc.) .

Therefore, in order to support personal well-being lifecare service, the index model generation method for calculating personalized measurement index considering personal life pattern and environmental information is gradually becoming important as a source index necessary for smart home service system in the future ubiquitous society It is becoming.

Through collecting and analyzing personal lifestyle data, it is possible to quantify and present individual life patterns for the well-being lifecare of individual members constituting the ubiquitous society, and provide ubiquitous standards that provide refined criteria for individual self- And a method for manufacturing a well-being life-care index model in an environment.

According to another aspect of the present invention, there is provided a method for producing a well-being life-care index model in a ubiquitous environment, the method comprising: calculating a proportion of a sub- Determining a well factor index value by adding the sub factor values calculated by multiplying the reference value by a predetermined characteristic weight for each sub-factor to obtain respective factor values, and adding weight factor values determined by multiplying the factor value by a factor weight, .

These factors are health, emotion, exercise, body and preference.

The subfactors that make up the health are nutrition, family history and BMI (Body Mass Index). The reference values of the subfactors are 30 for nutrition, 20 for family history, and 50 for BMI.

The sub-factors constituting the emotion are stress, depression and sleep satisfaction. The reference values of the subfactors are 30 for stress, 40 for depression, and 30 for sleep.

The subfactors constituting the motion are momentum and activity. The reference values of the subfactors have an exercise amount of 60 and an activity amount of 40, respectively.

The subfactors constituting the living body are blood pressure, blood sugar, triglyceride (TG), high-density lipoprotein (HDL), and total cholesterol (TC). The reference values of the subfactors are 40 for blood pressure, 10 for blood sugar, 10 for triglyceride, 20 for HDL and 20 for total cholesterol.

The sub-factors constituting the preference are smoking, drinking and eating out. The reference values of the subfactors are 40 for smoking, 40 for drinking, and 20 for drinking.

로 표시되며, 여기서 F는 팩터이고, SF는 서브팩터이며 BV는 기준값이다. The step of obtaining each of the factor values includes:

Where F is a factor, SF is a subfactor, and BV is a reference value.

로 표시되며, WI는 웰빙인덱스지수이고, Wi는 팩터가중치이며 Fi는 각각의 팩터를 나타낸다. Wherein the step of determining the well-

WI is a well-being index index, Wi is a factor weight, and Fi is a factor.

As described above, the present invention determines the factors of the factors for calculating a well-being index index and the sub-factors that make up the factors to provide a personalized wellness care service for the individual, and the mutual influence between the sub- The user is able to monitor the overall wellness level of the individual by quantifying the degree of well-being in consideration of the individual's specific life patterns and habits And can be used as an index for inducing a change of an individual's wrong lifestyle.

In addition, since it is constructed based on the clinical background reflecting actual data such as personal life pattern and health information, it is possible to provide differentiated and accurate data from other index models.

In addition, there is an advantage that it is accurate data that is not dependent on a specific company or product because it is not an index developed and calculated in relation to a product in a specific company.

In order to fully understand the present invention, operational advantages of the present invention, and objects achieved by the practice of the present invention, reference should be made to the accompanying drawings and the accompanying drawings which illustrate preferred embodiments of the present invention.

Hereinafter, the present invention will be described in detail with reference to the preferred embodiments of the present invention with reference to the accompanying drawings. In each drawing, the same reference numerals denote the same members.

1 is a diagram illustrating an initial model of a well-being index index using a measurement item through a clinical test and extracted sub-factors.

The method of manufacturing a well-being life-care index model in a ubiquitous environment according to an embodiment of the present invention is characterized in that sub-factors constituting factors for determining a well- And adding the sub-factor values calculated by multiplying the sub-factors calculated by multiplying the sub-factor values by predetermined weighting factors, and determining the well-being index index by adding the weighting factor values determined by multiplying the factor values by the factor weights.

Referring to FIG. 1, the principle of calculating the respective factor values and determining the well-being index index by adding weight factor values are sequentially shown.

The step of obtaining each factor value is determined by the following equation.

Where F is a factor, SF is a subfactor, and BV is a reference value.

Further, the step of determining the well-being index index is determined by the following equation.

Here, WI is a well-being index index, Wi is a factor weight, and Fi is a factor.

As can be seen from the above Equations 1 and 2, several factors are required to calculate the well-being index index WI. In particular, in the present invention, five factors F, i.e., health, emotion, exercise, .

Each of the five factors F has a factor weight Wi in accordance with the degree of influence on the well being index index WI and has a weight factor Wi obtained by multiplying the factor weight of the factor F by the factor weight Wi, The well-being index index (WI) is then determined. The Well-being Index Index (WI) is expressed in numbers and the higher the number, the better the well-being for individual life-care.

And the factor weight Wi is set by determining the degree of influence on the well-being index index (WI) by statistically analyzing the opinions of the medical experts. Particularly, the well-being index index (WI) according to the embodiment of the present invention is obtained by taking a clinical day as a sample of a male between 30 and 49 years old. If the subject is female or has a different age, the factor weight Wi It can be different.

Each factor F is also made up of subfactors SF constituting the factor F and a reference value BV indicating the proportion (importance) occupied in the factor F to which the subfactors SF correspond is present do.

Each of the sub-factors SF is divided into several elements according to their contents, and has a characteristic weight representing the degree to which the factor affects the sub-factors SF.

As can be seen from Equation (1), the sub-factor values of the sub-factors SF are determined by multiplying the respective reference values BV by the characteristic weights determined by the respective elements, and by adding all the determined sub-factor values, Is determined. The well-being index index WI is determined by adding weight factor values determined by multiplying the factor value thus determined by the factor weight Wi.

Figure 2 is a diagram illustrating the correlation of subfactors to health factors;

Referring to FIG. 2, the subfactors SF constituting health, which is one of the factors F, are nutrition, family history, and BMI (Body Mass Index). The reference value BV of the subfactors SF is 30 for nutrition, 20 for family history, and 50 for BMI. When each reference value BV is added, it becomes 100.

When the subfactor (SF) is nutrition, if the total calories consumed per day is 2000 to 2500 calories, the characteristic weight is 1, otherwise the characteristic weight is 0.3. In other words, if the total calories consumed by an individual exceeds 2,000 to 2,500 calories, or if the calories are exceeded, the characteristic weight is applied so that the subfactor value of the nutrient consumes 1 day. The calorie intake is 2000 to 2500 kg, do.

Similarly, when the subfactor (SF) is family history, if the symptom of metabolic syndrome is present in all parents, the characteristic weight is only one of 0.2 parents, and the characteristic weight is 0.4. The subfactor values of family members are determined according to these classification factors.

In the case of BMI, if the value is less than 23, the characteristic weight is 0.6, when the characteristic weight is 23 to 25, and when the characteristic weight is more than 1, the characteristic weight is 0.2.

The case in which the characteristic weight for the elements of the subfactor SF is 1 is all good and represents a normal state.

Each subfactor value is determined in this manner and the factor values for nutrition are determined by adding all of the subfactor values according to Equation (1).

3 is a diagram for explaining the correlation of sub-factors for the emotion factor.

Referring to FIG. 3, the sub-factors SF constituting emotions are stress, depression, and sleep satisfaction. The reference value BV of the sub-factors SF is 30 for stress, 40 for depression, and 30 for sleep.

Referring to FIG. 3, when the stress index is 149 or less, the characteristic weight is 1, which means that the characteristic weight is normal. When the stress index is 150 to 299, the characteristic weight is 0.7. The same explanation can be applied for depression and sleep satisfaction. Here, stress index uses Holmes stress scale. In the case of depression, the Beck depression index is used.

Each subfactor value is determined in this way, and a factor value for the emotion is determined by adding all the subfactor values according to Equation (1).

Figure 4 is a diagram illustrating the correlation of subfactors to motion factors;

Referring to FIG. 4, the subfactors (SF) constituting the motion are momentum and activity. The reference values of the sub-factors SF are 60 for the momentum and 40 for the activity.

In the exercise group, the non-exercise group does not exercise, and the regular exercise group means three times a week, the exercise is performed more than 20 minutes once, and the irregular exercise group means the other cases.

The amount of activity is divided into elements based on pedometer. The characteristic weight is 0.7 when walking between 4000 ~ 8000 baud per day, and the characteristic weight is 1 when the characteristic weight is 0.3 or more. The sub-factor value is determined by multiplying the characteristic weight by the reference value (BV), and the sub-factor values of the momentum and the activity are added to the factor of the motion factor.

5 is a diagram for explaining the correlation of subfactors with respect to a biomodulator factor.

The sub-factors SF constituting the living body are blood pressure, blood sugar, triglyceride (TG), high-density lipoprotein (HDL), and total cholesterol (TC). The reference values of the subfactors are 40 for blood pressure, 10 for blood sugar, 10 for triglyceride, 20 for HDL and 20 for total cholesterol.

The blood pressure is divided into systolic blood pressure and diastolic blood pressure, each having a reference value (BV) of 20. If the systolic blood pressure is between 100 and 127, the characteristic weight is 1, 128 to 139, and the characteristic weight is 0.7.

As shown in FIG. 5, if the systolic blood pressure minus the diastolic blood pressure is 40 or more, the individual is warned of the risk, and if the blood pressure is 140/90 for 6 months or longer, a warning is issued.

In addition to blood pressure, characteristic weights and factors are also divided for blood glucose, triglyceride (TG), high-density lipoprotein (HDL), and total cholesterol (TC) as shown in FIG. When the sub-factor value of the factor SF is determined and the sub-factor value is added, the factor value of the bi-factor is determined.

6 is a diagram for explaining the correlation of sub-factors for the preference factor.

Referring to FIG. 6, the subfactors constituting the preference degree are smoking, drinking and eating out. The reference values of the sub-factors SF are 40 for smoking, 40 for drinking, and 20 for drinking.

For non-smokers, the characteristic weight is 1, 0.7 for past abscesses, and 0.3 for current smokers. In the case of drinking, the person who drank one cup of shochu per day has a characteristic weight of 1, which is the standard.

Subfactor values are calculated in the same manner as described above, and the factor value of the preference factor is determined by adding the calculated subfactor values.

When the motion factor value, the emotion factor value, the health factor value, the biometric factor value, and the preference factor value are determined by the above process, the respective factor values are multiplied by the factor weights to obtain the weight factor values, When the factor values are added, a well-being index index (WI) is determined.

The factors F and the respective subfactors SF constituting the factor F are determined by the results of various clinical tests over a long period of time and are based on quantification of wellness care according to an individual's life pattern and habit Can be a reference.

That is, the method of producing a well-being index index model according to an embodiment of the present invention exposes and quantifies individual life patterns quantitatively, thereby enabling to monitor the individual's well-being level as a whole and to monitor the individual's life pattern and health information It is a differentiated and sophisticated index technology because it is constructed by reflecting actual data.

In addition, by subdividing the detailed indexes of emotional, exercise, health, vital, and preference indexes of the personal life patterns, the specific areas can be monitored for the partial factors affecting specific diseases, Monitoring service by individual life pattern may be possible in the field (health examination center and health care center) and service using the Internet.

In addition, through the present invention, quantitative service technology for personal lifestyle can be developed, and such technology can be used in the field of U-health service and health promotion service.

While the present invention has been particularly shown and described with reference to exemplary embodiments thereof, it will be understood by those of ordinary skill in the art that various changes in form and details may be made therein without departing from the spirit and scope of the invention as defined by the appended claims. It will be understood that the invention may be embodied in other forms without departing from the spirit or scope of the invention. Accordingly, modifications of the embodiments of the present invention will not depart from the scope of the present invention.

1 is a diagram illustrating an initial model of a well-being index index using a measurement item through a clinical test and extracted sub-factors.

Figure 2 is a diagram illustrating the correlation of subfactors to health factors;

3 is a diagram for explaining the correlation of sub-factors for the emotion factor.

Figure 4 is a diagram illustrating the correlation of subfactors to motion factors;

5 is a diagram for explaining the correlation of subfactors with respect to a biomodulator factor.

6 is a diagram for explaining the correlation of sub-factors for the preference factor.

Claims (13)

A method for producing a well-being life-care index model in a ubiquitous environment, The sub-factors calculated by multiplying the sub-factors each constituting the factors for determining the well-being index index by a predetermined characteristic weight for each of the sub-factors is added to the reference value indicating the proportion occupied by the corresponding factors, Obtaining; Determining the well-being index index by adding the weight factor values determined by multiplying the factor value by a factor weight, The step of obtaining each of the factor values includes:

Lt; / RTI > Where F is a factor, SF is a subfactor, BV is a reference value, Wherein the step of determining the well-

Lt; / RTI > Wherein WI is a well-being index index, Wi is a factor weight, and Fi is a factor of each well. The method according to claim 1, Wherein the factors are health, emotion, exercise, living body and preference. 3. The method of claim 2, wherein the sub- Nutrition, family history, and body mass index (BMI) of a well-being life-care index model in a ubiquitous environment. 4. The method according to claim 3, wherein the reference values of the subfactors are 30 for nutrition, 20 for family history, and 50 for BMI. 3. The method of claim 2, wherein the sub- Stress, depression, and sleep satisfaction in a ubiquitous environment. 6. The method according to claim 5, wherein the reference values of the subfactors are respectively a stress of 30, a depression of 40, and a sleep satisfaction of 30. 3. The method of claim 2, wherein the sub- And the amount of exercise and the amount of activity. 8. The method of claim 7, wherein the reference values of the subfactors are respectively an exercise amount of 60 and an activity amount of 40. The method of claim 1, 3. The method according to claim 2, wherein the sub- Wherein the blood pressure is blood pressure, blood glucose, triglyceride (TG), high-density lipoprotein (HDL), and total cholesterol (TC). 10. The method according to claim 9, wherein the reference values of the subfactors are respectively 40 blood pressure, 10 glucose, 10 neutral fat, 20 HDL, and 20 total cholesterol. . 3. The method according to claim 2, Smoking, drinking and eating out in a ubiquitous environment. 12. The method of claim 11, wherein the reference values of the subfactors are 40 for smoking, 40 for alcohol, and 20 for alcohol. delete

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