WO2021040373A1

WO2021040373A1 - Complex stress index-based stress management method

Info

Publication number: WO2021040373A1
Application number: PCT/KR2020/011306
Authority: WO
Inventors: 황원주
Original assignee: 경희대학교 산학협력단
Priority date: 2019-08-26
Filing date: 2020-08-25
Publication date: 2021-03-04
Also published as: KR102097246B1

Abstract

A complex stress index-based stress management method comprises the steps in which: a computer device calculates an initial body index using initial biometric data of a subject; the computer device calculates an initial psychological index using initial medical inquiry data of the subject; the computer device calculates an initial stress index of the subject using the initial psychological index and the initial body index; and the computer device provides content information on the subject on the basis of the initial stress index. The computer device calculates an anxiety index, a depression index, and a perceived stress scale (PSS) index by using different types of medical inquiry data, and calculates the initial psychological index by reflecting weights for each of the anxiety index, the depression index, and the PSS index.

Description

Stress management method based on complex stress index

The technology described below is a technology that calculates a subject's stress level and provides content for stress management.

In the current society, stress is becoming a socially important issue. Stress is highly associated with mental/physical disorders. There are various devices or therapies for stress relief, but not all subjects achieve the same effect. It is necessary to provide a service that quantifies the level and type of stress of the subject and provides customized content.

The technique described below is intended to quantify the subject's stress using various types of data, and to provide customized content according to the measured stress level. Further, the technology described below is intended to provide more effective stress relief content by accumulating collected subject information, stress level, and validity information of the content.

The stress management method based on the complex stress index includes the steps of: a computer device calculating an initial body index using the subject's initial biometric data, the computer device calculating an initial psychological index using the subject's initial questionnaire data, the Computing, by a computer device, an initial stress index of the subject using the initial psychological index and the initial body index, and providing, by the computer device, content information on the subject based on the initial stress index. . The computer device calculates an anxiety index, a depression index, and a PSS (Perceived Stress Scale) index using different types of paperweight data, and for each of the anxiety index, the depression index, and the PSS index. The initial psychological index is calculated by reflecting the weight.

The stress management device based on the complex stress index calculates an initial body index using a storage device that stores a program for calculating a stress index, an input device that receives initial biometric data and initial interview data of a subject, and the initial biometric data, An initial psychological index is calculated using the initial questionnaire data, an initial stress index of the subject is calculated using the initial psychological index and the initial physical index, and content information on the subject is provided based on the initial stress index. It includes a computing device to provide. The initial questionnaire data includes different types of questionnaire data, and the computing device calculates an anxiety index, a depression index, and a PSS index using the interview data, and calculates the anxiety index, the depression index, and the PSS index, respectively. The initial psychological index is calculated by reflecting the weight for.

The type and degree of stress can be specifically quantified by using the complex stress index described below. Through this, the technology described below can provide optimized stress relief content to the subject.

1 is an example showing a stress management system.

2 is another example showing a stress management system.

3 is another example showing a stress management system.

4 is an example of a process of calculating a stress index.

5 is another example of a process of calculating a stress index.

6 is an example of a configuration of a stress management device.

The technology to be described below may be modified in various ways and may have various embodiments, and specific embodiments will be illustrated in the drawings and described in detail. However, this is not intended to limit the technology to be described below with respect to a specific embodiment, and it should be understood to include all changes, equivalents, or substitutes included in the spirit and scope of the technology to be described below.

Terms such as 1st, 2nd, A, B, etc. may be used to describe various components, but the components are not limited by the above terms, and only for the purpose of distinguishing one component from other components. Is only used. For example, a first component may be referred to as a second component, and similarly, a second component may be referred to as a first component without departing from the scope of the rights of the technology described below. The term and/or includes a combination of a plurality of related listed items or any of a plurality of related listed items.

In terms of the terms used in the present specification, expressions in the singular should be understood as including plural expressions unless clearly interpreted differently in context, and terms such as "includes" are specified features, numbers, steps, actions, and components. It is to be understood that the presence or addition of one or more other features or numbers, step-acting components, parts or combinations thereof is not meant to imply the presence of, parts, or combinations thereof.

Prior to the detailed description of the drawings, it is intended to clarify that the division of the constituent parts in the present specification is merely divided by the main function that each constituent part is responsible for. That is, two or more constituent parts to be described below may be combined into one constituent part, or one constituent part may be divided into two or more for each more subdivided function. In addition, each of the constituent units to be described below may additionally perform some or all of the functions of other constituent units in addition to its own main function, and some of the main functions of each constituent unit are different. It goes without saying that it can also be performed exclusively by.

In addition, in performing the method or operation method, each of the processes constituting the method may occur differently from the specified order unless a specific order is clearly stated in the context. That is, each of the processes may occur in the same order as the specified order, may be performed substantially simultaneously, or may be performed in the reverse order.

Hereinafter, terms used in the description will be defined.

The subject is a user who is subject to stress measurement.

Biometric data refers to the subject's biometric or body information. The biometric data may include clinical information and lifestyle information.

Clinical information refers to data extracted as a result of medical examination. Clinical information can be managed by medical institutions. Alternatively, the clinical information may be obtained by the user/subject using professional measurement equipment, personal portable terminal, or the like. Clinical information may include (i) phenotype information, (ii) results of analysis of samples (blood, etc.) extracted from humans or humans with medical equipment, and (iii) results of diagnosis by medical staff. For example, the phenotypic information may include information such as age, height, weight, sex, race, and the like. For example, equipment measurement results include blood pressure, obesity, body mass index (BMI), cholesterol level, glycated hemoglobin level, blood sugar level, hormone level, photoplethysmogram (PPG), heart rate, heart rate variability (HRV), etc. It can contain the same information. Further, the equipment measurement result may include medical images such as X-ray, CT, PET, MRI, and the like. The medical staff's diagnosis result refers to diagnosis information that is determined based on phenotypic information, equipment measurement results, and interviews. For example, the diagnosis result of the medical staff may include a diagnosis of a disease, a degree of the disease, a predicted lifespan, a treatment method, drug information, and the like.

Lifestyle information refers to information related to lifelog. For example, the lifestyle information may include (i) physical activity information, (ii) food intake information, (iii) exercise information, and the like. The physical activity information may include sleep time, wake up time, working time, break time, and the like. Food intake information may include calories consumed per day, amount of nutrients consumed, and the like. The exercise information may include information such as an exercise amount and exercise intensity. Lifestyle information can be measured by monitoring with measuring equipment. Furthermore, lifestyle information may be obtained through a questionnaire on personal life.

The questionnaire data is data obtained through a questionnaire on the subject. The questionnaire data is the result of the subject's questionnaire offline, but the questionnaire data in the following description assumes digital data. That is, the paperweight data may be stored in a storage medium such as a database. Further, the questionnaire data may be collected in a way that a user inputs a response to a questionnaire through a device such as a computer or a smartphone.

The paperweight data may be data for determining various types of scales. For example, the questionnaire data may be data for measuring a Perceived Stress Scale (PSS) related to psychological stress. In addition, the questionnaire data may be data for anxiety evaluation. Furthermore, the questionnaire data may be data for evaluating depression. PSS, anxiety and depression assessments can be performed using different types of questionnaire data. In the following description, the questionnaire data basically means complex data for evaluating various scales or groups of different types of paperweight data.

Job data means job-related information of the subject. Job data can be information that judges job stress. Job data may include information such as time and attendance information (such as tardy/absence), workload, job satisfaction, presentationism, salary, sales volume, and sales contribution of the target person. Meanwhile, factors such as job satisfaction may be obtained as a result of a survey. Job data can be held by the user, and in this case, it can be obtained by accessing the user DB. Alternatively, it may be collected in a manner that the subject inputs during the stress measurement process.

The stress index is an index indicating the subject's stress scale. In some cases, the stress index may indicate a type of stress or a stress characteristic. The stress index may be determined by combining multiple factors or different types of stress scales.

The body index represents a stress scale measured based on the subject's biometric data.

The psychological index represents a stress scale measured based on the subject's questionnaire data. Meanwhile, the psychological index may be determined using different types of paperweight data.

The anxiety index is a scale measured based on the questionnaire data to measure the degree of anxiety.

The depression index is a scale measured based on the questionnaire data to measure the degree of depression.

The PSS index is a measure that is measured based on paperweight data to measure the level of traditional stress.

The psychological index may be calculated using at least one of an anxiety index, a depression index, and a PSS index.

The job index represents a stress scale measured based on the subject's job data.

The complex stress index may be a stress scale measured using a physical index and a psychological index. In addition, the composite stress index may be a stress scale measured using a combination of a body index, a psychological index, and a job index.

The technique described below calculates a stress index in consideration of complex factors. The technique described below can calculate a stress index using three types of data. The three types of data are the aforementioned biometric data, interview data, and job data.

1 is an example illustrating a stress management system 100. The stress management system 100 is a system that provides a stress management service through a server. The subject may check content information for relieving stress by inputting certain information through his or her computer device 50.

The stress management system 100 may include a living body DB 110, a paperweight DB 120, a job DB 130, a service server 150, and a content DB 160. In addition, the stress management system 100 may further include a big data DB 170.

The biometric DB 110 holds biometric data. The living body DB 110 may be a device configuration managed by a medical institution. For example, the living body DB 110 may hold at least one data of a data group including blood pressure, obesity, sleep amount, exercise amount, stress hormone level, PPG (pulse wave), and heart rate. A representative stress hormone is cortisol.

The paperweight DB 120 holds paperweight data. The questionnaire DB 120 may hold individual questionnaire data for measuring an anxiety index, a depression index, and a PSS index, respectively. The questionnaire DB 120 also holds information on the subject's response to the questionnaire data.

Job DB 130 holds job data. For example, the job DB 130 may hold at least one of data groups including workload, job satisfaction, presentation, time and attendance information, salary, and sales.

The service server 150 receives biometric data, interview data, and job data from the biometric DB 110, the interview DB 120, and the job DB 130, respectively. In some cases, the service server 150 may directly receive at least one of biometric data, interview data, and job data through the computer device 50.

The service server 150 calculates a body index using biometric data. The body index may be calculated from a plurality of biometric data. The service server 150 may calculate a body index from a plurality of biometric data using a program or function for calculating a body index.

The service server 150 calculates a psychological index using the questionnaire data. As described above, the psychological index may be calculated from a plurality of paperweight data. The service server 150 may calculate a body index from a plurality of biometric data using a program or function for calculating a psychological index. The service server 150 may calculate a psychological index by allocating a score per questionnaire item based on the response content of the questionnaire data. The service server 150 may calculate an anxiety index using the first questionnaire data. The service server 150 may calculate a depression index using the second questionnaire data. The service server 150 may calculate the PSS index using the third questionnaire data. The service server 150 may calculate a final psychological index by inputting an anxiety index, a depression index, and a PSS index into a certain function. For example, the service server 150 may calculate the psychological index by adding a certain weight to the anxiety index, the depression index, and the PSS index, respectively, or by adding the average.

The service server 150 calculates a job index using job data. The service server 150 may calculate a job index from job data using a program or function for calculating the job index.

The service server 150 may calculate a complex stress index using a body index, a psychological index, and a job index. The service server 150 may calculate a complex stress index by inputting a body index, a psychological index, and a job index into a function. For example, the service server 150 may calculate a composite stress index by adding weights (which may be different values) to the body index, psychological index, and job index, respectively, or by adding the average.

The content DB 160 holds content or information on content that can alleviate the subject's stress. The content DB 160 may hold various types of content or information capable of relieving stress according to a stress type or a stress index. The types of content may vary, such as moving pictures, still images, music, e-books, meditation, sayings, and yoga. The content of the content may also vary depending on the type of stress or characteristics of the stress. The contents DB 160 may hold various contents known to contribute to stress relief in the related art.

Furthermore, the content DB 160 may hold information on content suitability according to a stress type, a stress index, or a stress characteristic. Content suitability refers to the degree of contribution to stress relief of a specified subject. Content suitability may be prepared in advance according to the type of stress, stress index, or stress characteristics with reference to the previously studied results. On the other hand, content suitability may be determined according to big data analysis.

The service server 150 may select one or more contents having high content suitability from the contents DB 160 based on the complex stress index for the target person. The service server 150 delivers content information to a target person. Alternatively, the service server 150 may stream content itself, such as an image, to a target person. Content with high content suitability can be said to be customized content. The customized content may be one or a plurality of contents.

The subject performs customized content. The service server 150 may analyze new data of the subject in order to evaluate customized content. The stress management system 100 may evaluate the customized content by receiving feedback from the subject who performed the customized content.

When data previously used by the service server 150 is referred to as initial data, new data may be referred to as post data. The service server 150 may calculate the complex stress index again by using the post-biometric data, post-interview data, and post-job data.

Among the post-biometric data, there are data that take time to measure. In addition, it may take time to collect job data again afterwards. Accordingly, the service server 150 can calculate a new complex stress index using only data that can be fed back in a relatively short time. For example, the service server 150 may calculate a new complex stress index (post-stress index) by updating only the blood pressure, PPG, etc., which can be measured in real time, among the interview data and biometric data.

The service server 150 may accumulate customized content information according to a stress index or stress characteristic. The service server 150 may store information such as data used in the process of calculating a stress index, a stress index, customized contents, and effects of customized contents in the big data DB 170.

The big data DB 170 may hold information such as initial biometric data, initial interview data, post biometric data, post interview data, initial stress index, post stress index, customized content information, and customized content contribution. The degree of contribution to customized content indicates the degree to which the subject's stress is relieved. For example, the customized content contribution may be a difference between a post-stress index and an initial stress index. When the service server 150 repeatedly calculates the stress index for multiple targets and selects customized content, the information held by the big data DB 170 also increases.

Thereafter, the service server 150 may search for content with high content suitability from the big data DB 170 based on part or all of data belonging to at least one of the subject's biometric data, interview data, and job data. That is, the service server 150 may perform a customized content search by additionally using information accumulated as big data in addition to the content search based on the conventional complex stress index.

2 is another example illustrating the stress management system 200. The stress management system 200 is a system that provides a stress management service through a user terminal. The subject may input certain information through his/her user terminal 250 to check content information for relieving stress. The user terminal 250 may be a device such as a PC, a notebook computer, or a smart phone.

The stress management system 200 may include a biological DB 210, a job DB 230, a user terminal 250, and a content DB 260. In addition, the stress management system 200 may further include a big data DB 270.

The biometric DB 210 holds biometric data. The living body DB 210 may be a device configuration managed by a medical institution. For example, the living body DB 110 may hold at least one data of a data group including blood pressure, obesity, sleep amount, exercise amount, stress hormone level, PPG (pulse wave), and heart rate. A representative stress hormone is cortisol.

Although not shown in FIG. 2, there may be a paperweight DB as shown in FIG. 1. In this case, the user terminal 250 may receive the paperweight data from the paperweight DB. However, in FIG. 2, it is assumed that the user terminal 250 provides the questionnaire data and the target person inputs a response to the questionnaire data into the user terminal 250.

The user terminal 250 calculates a body index using the biometric data. The body index may be calculated from a plurality of biometric data. The user terminal 250 may calculate a body index from a plurality of biometric data using a program or function for calculating the body index.

The user terminal 250 calculates a psychological index using the questionnaire data. As described above, the psychological index may be calculated from a plurality of paperweight data. The user terminal 250 may calculate a body index from a plurality of biometric data using a program or function for calculating a psychological index. The user terminal 250 may calculate a psychological index by allocating a score per questionnaire item based on the response content of the questionnaire data. The user terminal 250 may calculate an anxiety index using the first questionnaire data. The user terminal 250 may calculate a depression index using the second questionnaire data. The user terminal 250 may calculate the PSS index using the third questionnaire data. The user terminal 250 may calculate a final psychological index by inputting an anxiety index, a depression index, and a PSS index into a certain function. For example, the user terminal 250 may calculate a psychological index by adding a certain weight to the anxiety index, the depression index, and the PSS index, respectively, or by adding the average.

The user terminal 250 calculates a job index using job data. The user terminal 250 may calculate a job index from job data using a program or function for calculating the job index.

The user terminal 250 may calculate a complex stress index using a body index, a psychological index, and a job index. The user terminal 250 may calculate a complex stress index by inputting a body index, a psychological index, and a job index into a function. For example, the user terminal 250 may calculate a composite stress index by adding weights (which may be different values) to the body index, psychological index, and job index, respectively, or by adding the average.

The content DB 260 holds content or information on content that can alleviate the subject's stress. The content DB 260 may hold various types of content or information capable of relieving stress according to a stress type or a stress index. The content DB 260 may hold information on a content suitability according to a stress type, a stress index, or a stress characteristic. Content suitability may be prepared in advance according to the type of stress, stress index, or stress characteristics with reference to the previously studied results. On the other hand, content suitability may be determined according to big data analysis.

The user terminal 250 may select one or more contents having a high content suitability from the contents DB 260 based on the complex stress index for the subject. The user terminal 250 delivers the content information to the target person. Alternatively, the user terminal 250 may stream content itself, such as an image, to a target person. Content with high content suitability can be said to be customized content. The customized content may be one or a plurality of contents.

The subject performs customized content. The user terminal 250 may analyze new data of the subject in order to evaluate the customized content. The stress management system 200 may evaluate the customized content by receiving feedback from the subject who performed the customized content.

The user terminal 250 may refer to previously used data as initial data, and new data may be referred to as post data. The user terminal 250 may calculate the complex stress index again by using the post-biometric data, post-interview data, and post-job data.

Among the post-biometric data, there are data that take time to measure. In addition, it may take time to collect job data again afterwards. Accordingly, the user terminal 250 can calculate a new complex stress index using only data that can be fed back in a relatively short time. For example, the user terminal 250 may calculate a new complex stress index (post-stress index) by updating only the blood pressure, PPG, etc., which can be measured in real time, among the interview data and biometric data.

The user terminal 250 may accumulate customized content information according to a stress index or stress characteristic. The user terminal 250 may store information such as data used in the stress index calculation process, stress index, customized contents, and effects of customized contents in the big data DB 270.

The big data DB 270 may hold information such as initial biometric data, initial interview data, post biometric data, post interview data, initial stress index, post stress index, customized content information, and customized content contribution. The degree of contribution to customized content indicates the degree to which the subject's stress is relieved. For example, the customized content contribution may be a difference between a post-stress index and an initial stress index. When the user terminal 250 repeatedly calculates the stress index for multiple targets and selects customized content, the information held by the big data DB 270 also increases.

FIG. 2 shows the content DB 260 and the big data DB 270 as separate objects different from the user terminal 250. In some cases, the content DB 260 and the big data DB 270 may be objects existing in the user terminal 250. In this case, there may be a content DB 260 and a big data DB 270 in a storage medium of the user terminal 250.

Thereafter, the user terminal 250 may search for content with high content suitability from the big data DB 270 based on some or all of data belonging to at least one category among the subject's biometric data, interview data, and job data. That is, the user terminal 250 may perform a customized content search by additionally using information accumulated as big data in addition to the content search based on the conventional complex stress index.

3 is another example illustrating the stress management system 300. The stress management system 300 is a system that provides a stress management service through a user terminal. The subject may input certain information through his/her user terminal 350 to check content information for relieving stress. The user terminal 250 may be a device such as a PC, a notebook computer, or a smart phone.

The stress management system 300 may include a user terminal 350 and a content DB 360. In addition, the stress management system 300 may further include a big data DB 370.

The user terminal 350 may hold biometric data, interview data, and job data in advance. Alternatively, the user terminal 250 may obtain data that can be measured using a sensing device among biometric data in real time.

For example, the subject may photograph a skin image using the user terminal 350 and may calculate a pulse wave (PPG) by analyzing the blood flow in the skin image using the user terminal 350. Briefly, the user terminal 350 may extract a color value for a skin area and detect a pulse wave signal based on a color value change over time. The user terminal 250 may generate a tachogram for the heartbeat interval from the pulse wave signal, analyze the tachogram, and calculate PPG to HRV.

The user terminal 350 calculates a body index using the biometric data. The body index may be calculated from a plurality of biometric data. The user terminal 350 may calculate a body index from a plurality of biometric data using a program or function for calculating the body index.

The user terminal 350 calculates a psychological index using the questionnaire data. As described above, the psychological index may be calculated from a plurality of paperweight data. The user terminal 350 may calculate a body index from a plurality of biometric data using a program or function for calculating a psychological index. The user terminal 350 may calculate a psychological index by allocating a score per questionnaire item based on the response content of the questionnaire data. The user terminal 350 may calculate an anxiety index using the first questionnaire data. The user terminal 350 may calculate a depression index using the second questionnaire data. The user terminal 350 may calculate the PSS index using the third questionnaire data. The user terminal 350 may calculate a final psychological index by inputting an anxiety index, a depression index, and a PSS index into a certain function. For example, the user terminal 350 may calculate a psychological index by adding a certain weight to the anxiety index, the depression index, and the PSS index, respectively, or by adding the average.

The user terminal 350 calculates a job index using job data. The user terminal 350 may calculate a job index from job data using a program or function for calculating the job index.

The user terminal 350 may calculate a complex stress index using a body index, a psychological index, and a job index. The user terminal 350 may calculate a complex stress index by inputting a body index, a psychological index, and a job index into a function. For example, the user terminal 350 may calculate a composite stress index by adding weights (which may be different values) to the body index, psychological index, and job index, respectively, or by adding the average.

The content DB 360 holds content or information on content that can alleviate the subject's stress. The content DB 360 may hold various types of content or information capable of relieving stress according to a stress type or a stress index. The content DB 360 may hold information on a content suitability according to a stress type, a stress index, or a stress characteristic. Content suitability may be prepared in advance according to the type of stress, stress index, or stress characteristics with reference to the previously studied results. On the other hand, content suitability may be determined according to big data analysis.

The user terminal 350 may select one or more contents having a high content suitability from the contents DB 360 based on the complex stress index for the subject. The user terminal 350 delivers the content information to the target person. Alternatively, the user terminal 350 may stream content itself, such as an image, to a target audience. Content with high content suitability can be said to be customized content. The customized content may be one or a plurality of contents.

The subject performs customized content. The user terminal 350 may analyze new data of the subject in order to evaluate the customized content. The stress management system 300 may evaluate the customized content by receiving feedback from the subject who performed the customized content.

When the user terminal 350 refers to previously used data as initial data, new data may be referred to as post data. The user terminal 350 may calculate the complex stress index again by using the post-biometric data, post-interview data, and post-job data.

Among the post-biometric data, there are data that take time to measure. In addition, it may take time to collect job data again afterwards. Accordingly, the user terminal 350 can calculate a new complex stress index using only data that can be fed back in a relatively short time. For example, the user terminal 350 may calculate a new complex stress index (post-stress index) by updating only the blood pressure, PPG, etc., which can be measured in real time among the interview data and biometric data.

The user terminal 350 may accumulate customized content information according to a stress index or stress characteristic. The user terminal 350 may store information such as data used in the process of calculating the stress index, the stress index, customized contents, and effects of customized contents in the big data DB 370.

The big data DB 370 may hold information such as initial biometric data, initial interview data, post biometric data, post interview data, initial stress index, post stress index, customized content information, and customized content contribution. The degree of contribution to customized content indicates the degree to which the subject's stress is relieved. For example, the customized content contribution may be a difference between a post-stress index and an initial stress index. When the user terminal 350 repeatedly calculates the stress index for multiple targets and selects customized content, the information held by the big data DB 370 also increases.

3 shows the content DB 360 and the big data DB 370 as separate objects different from the user terminal 350. In some cases, the content DB 360 and the big data DB 370 may be objects existing inside the user terminal 350. In this case, there may be a content DB 360 and a big data DB 370 in a storage medium of the user terminal 350.

Thereafter, the user terminal 350 may search for content with high content suitability from the big data DB 370 based on some or all of the data belonging to at least one of the subject's biometric data, interview data, and job data. That is, the user terminal 350 may perform a customized content search by additionally using information accumulated as big data in addition to the content search based on the conventional complex stress index.

4 is an example of a process 400 for calculating a stress index. 4 corresponds to a process in which the service server 150 or the

user terminals

250 and 350 calculates a stress index. For convenience of explanation, it will be described that the computer device performs a process of calculating a stress index. The server or user terminal corresponds to a kind of computer device.

The computer device receives biometric data (411). As described above, the biometric data may include blood pressure, obesity, sleep, exercise, stress hormone levels, pulse wave (PPG), heart rate, heart rate variability (HVR), and the like. The computer device may receive biometric data from a medical institution DB or measurement equipment.

The computer device calculates a body index using the biometric data (412). The correlation between the biometric data and the body index indicating stress can use the previously studied results. The computer device may assign a weight to each of a plurality of biometric data or calculate a body index using a plurality of biometric data using a specific function. In some cases, the computer device may calculate a body index based on one piece of biometric data.

The computer device receives the paperweight data (421). As described above, the paperweight data may include a plurality of data measuring different scales. The interview data may include anxiety stress data, depression stress data, PSS data, and the like. Anxiety stress data is a questionnaire data that measures the degree of anxiety. The depression stress data is a questionnaire data that measures the degree of depression. PSS data is a paperweight data that measures perceived stress. The computer device may receive a paperweight DB or paperweight data from a subject.

The computer device may calculate an anxiety index by using the anxiety stress data. The computer device may calculate a depression index using the depression stress data. The computer device may calculate the PSS index using the PSS data (422). The computer device may calculate the final psychological index using the anxiety index, the depression index, and the PSS index (423). The computer device may calculate the psychological index by assigning individual weights to the anxiety index, the depression index, and the PSS index.

The computer device receives job data (431). Job data may include workload, job satisfaction, presentation, time and attendance information, salary, sales and sales contribution. The computer device may receive job data from a company DB or a target person.

The computer device calculates a job index using job data (432). The previously studied results can be used for the correlation between job data and job index indicating stress. The computer device may assign a weight to each of a plurality of job data or calculate a body index using a plurality of job data using a specific function. In some cases, the computer device may calculate a job index based on one job data.

The computer device may calculate a final composite stress index using the body index, the psychological index, and the job index (441). For example, the computer device may calculate a complex stress index by assigning individual weights to a body index, a psychological index, and a job index.

5 is another example of a process 500 of calculating a stress index. 5 corresponds to a process in which the service server 150 or the

user terminals

250 and 350 calculates a stress index. For convenience of explanation, it will be described that the computer device performs a process of calculating a stress index.

The computer device receives biometric data (511). As described above, the biometric data may include blood pressure, obesity, sleep, exercise, stress hormone levels, pulse wave (PPG), heart rate, heart rate variability (HVR), and the like. The computer device may receive biometric data from a medical institution DB or measurement equipment.

The computer device calculates a body index using the biometric data (512). The correlation between the biometric data and the body index indicating stress can use the previously studied results. The computer device may assign a weight to each of a plurality of biometric data or calculate a body index using a plurality of biometric data using a specific function. In some cases, the computer device may calculate a body index based on one piece of biometric data.

The computer device receives the paperweight data (521). As described above, the paperweight data may include a plurality of data measuring different scales. The interview data may include anxiety stress data, depression stress data, PSS data, and the like. Anxiety stress data is a questionnaire data that measures the degree of anxiety. The depression stress data is a questionnaire data that measures the degree of depression. PSS data is a paperweight data that measures perceived stress. The computer device may receive a paperweight DB or paperweight data from a subject.

The computer device may calculate an anxiety index by using the anxiety stress data. The computer device may calculate a depression index using the depression stress data. The computer device may calculate the PSS index using the PSS data (522). The computer device may calculate a final psychological index using the anxiety index, the depression index, and the PSS index (523).

The computer device may calculate the psychological index by assigning individual weights to the anxiety index, the depression index, and the PSS index. In this case, the computer device may separately use a parameter for determining the weight. The computer device may determine the weight parameter based on the body index or at least one biometric data used to calculate the body index. In other words, it considers the relationship that body-related information affects the psychological index. The correlation between the physical index (or the value of the biometric data) and the psychological index (anxiety index, depression index, PSS index, or overall psychological index) can be applied to the previously studied results. Alternatively, a weight parameter may be determined by performing a study proving the relationship between a specific body index and a psychological index.

The computer device receives job data (531). Job data may include workload, job satisfaction, presentation, time and attendance information, salary, sales and sales contribution. The computer device may receive job data from a company DB or a target person.

The computer device calculates a job index using job data (532). The previously studied results can be used for the correlation between job data and job index indicating stress. The computer device may assign a weight to each of a plurality of job data or calculate a body index using a plurality of job data using a specific function. In some cases, the computer device may calculate a job index based on one job data.

The computer device may calculate a final composite stress index using the body index, the psychological index, and the job index (541). For example, the computer device may calculate a complex stress index by assigning individual weights to a body index, a psychological index, and a job index.

6 is an example showing the configuration of the stress management device 600. The stress management device 600 is a component corresponding to the service server 150 to the

user terminals

250 and 350 described above. The stress management device 600 may be physically implemented in various forms. For example, the stress management device 600 may have a form such as a PC, a smart device, a computer device, a server of a network, a chipset dedicated to data processing, and the like.

The stress management device 600 includes a storage device 610, a memory 620, a computing device 630, an interface device 640, and a communication device 650.

The storage device 610 may store a program for calculating a stress index. The storage device 610 may store various types of data used to calculate the stress index. For example, the storage device 610 may store biometric data, interview data, job data, and the like. The storage device 610 may store data (interview data, etc.) input by a user. The storage device 610 may store initial data. Furthermore, the storage device 610 may store new post data on a subject who has been provided with customized content.

The memory 620 may store data required for a data processing process by the stress management device 600 and temporary data generated.

The interface device 640 is a device that receives certain commands and data from the outside. The interface device 640 may receive the subject's biometric data, interview data, and job data from an input device physically connected or an external storage device. The interface device 640 may receive a program for processing data.

The communication device 650 refers to a component that receives and transmits certain information through a wired or wireless network. The communication device 650 may receive the subject's biometric data, interview data, and job data from an external object. The communication device 650 may receive a program and data for data processing.

The communication device 650 may receive necessary data from a biometric DB, a paperweight DB, and a job DB existing on the network. In addition, the communication device 650 may receive necessary content or content information from the content DB. In addition, the communication device 650 may transmit information about the effect of the data calculated during the stress index analysis process and the customized content to the big data DB. The communication device 650 may transmit the stress index and customized content information for the target person to the outside.

The communication device 650 to the interface device 640 are devices that receive certain data or commands from the outside. The communication device 650 to the interface device 640 may be referred to as an input device.

The computing device 630 may calculate an initial body index using initial biometric data, calculate an initial psychological index using initial interview data, and calculate an initial job index using the initial job data. The computing device 630 may calculate an initial psychological index using an anxiety index, a depression index, and a PSS index. The computing device 630 may calculate an initial complex stress index using an initial body index, an initial psychological index, and an initial job index.

The computing device 630 may search for customized content from the content DB based on the initial complex stress index. The computing device 630 may transmit customized content information to the outside through the communication device 650. The computing device 630 may output customized content information to its own display device and a speaker (not shown).

The computing device 630 may re-evaluate the level of stress on the user who is provided with the customized content. The computing device 630 may calculate the complex stress index again by using the post-biometric data, post-interview data, and post-job data.

Among the post-biometric data, there are data that take time to measure. In addition, it may take time to collect job data again afterwards. Accordingly, the computing device 630 may calculate a new complex stress index using only data that can be fed back in a relatively short time. For example, the computing device 630 may calculate a new complex stress index (post-stress index) by updating only the blood pressure, PPG, etc. that can be measured in real time among the medical examination data and biometric data.

The communication device 650 may deliver customized content information according to a stress index or stress characteristic to the big data DB. The big data DB accumulates information such as data used in the stress index calculation process, stress index, customized contents, and effects of customized contents.

The big data DB may hold information such as initial biometric data, initial interview data, post biometric data, post interview data, initial stress index, post stress index, customized content information and customized content contribution. The degree of contribution to customized content indicates the degree to which the subject's stress is relieved. For example, the customized content contribution may be a difference between a post-stress index and an initial stress index.

Thereafter, the computing device 630 may search for content with high content suitability from the big data DB based on some or all of the data belonging to at least one category among the subject's biometric data, interview data, and job data. Alternatively, the communication device 650 may query a big data DB for some or all of data belonging to at least one category among the subject's biometric data, interview data, and job data to receive a response (receive) with content with high suitability. In this case, the computing device 630 may perform a customized content search by additionally using information accumulated as big data in addition to the content search based on the conventional complex stress index.

The computing device 630 may be a device such as a processor, an AP, or a chip in which a program is embedded that processes data and processes certain operations.

In addition, the stress index calculation method or the method of providing customized content for stress relief as described above may be implemented as a program (or application) including an executable algorithm that can be executed on a computer. The program may be provided by being stored in a non-transitory computer readable medium.

The non-transitory readable medium refers to a medium that stores data semi-permanently and can be read by a device, rather than a medium that stores data for a short moment, such as a register, cache, and memory. Specifically, the above-described various applications or programs may be provided by being stored in a non-transitory readable medium such as a CD, DVD, hard disk, Blu-ray disk, USB, memory card, ROM, or the like.

The present embodiment and the accompanying drawings are merely illustrative of some of the technical ideas included in the above-described technology, and those skilled in the art can easily be used within the scope of the technical idea included in the specification and drawings of the above-described technology. It will be apparent that all of the modified examples and specific embodiments that can be inferred are included in the scope of the rights of the above-described technology.

Claims

Calculating, by the computer device, an initial body index using the subject's initial biometric data;

Calculating, by the computer device, an initial psychological index using the subject's initial questionnaire data;

Calculating, by the computer device, an initial stress index of the subject using the initial psychological index and the initial physical index; And

Including the step of providing, by the computer device, content information on the subject based on the initial stress index,

The computer device calculates an anxiety index, a depression index, and a PSS (Perceived Stress Scale) index using different types of paperweight data, and for each of the anxiety index, the depression index, and the PSS index. A stress management method based on a complex stress index that calculates the initial psychological index by reflecting a weight.
The method of claim 1,

The biometric data is a stress management method based on a complex stress index including blood pressure, obesity, sleep, exercise, stress hormone levels, PPG (pulse wave), and heart rate.
The method of claim 2,

The computer device is a stress management method based on a complex stress index for calculating a PPG (Photoplethysmogram) by using the skin image of the subject.
The method of claim 1,

The computer device determines a weight for each of the anxiety index, the depression index, and the PSS index based on the initial body index.
The method of claim 1,

A stress management method based on a complex stress index in which the computer device calculates a job index using job data and further calculates the stress index using the job index.
The method of claim 5,

The job data is a stress management method based on a complex stress index including workload, job satisfaction, presentation, time and attendance information, salary and sales.
The method of claim 1,

The computer device further comprises evaluating, by the computer device, a level of stress for the subject provided with stress relief content according to the content information,

The step of evaluating the level of stress

Calculating a post-mortem body index using the new biometric data of the subject;

Calculating a post-mortem index using the subject's new questionnaire data; And

A stress management method based on a complex stress index comprising the step of calculating a post stress index of the subject using the post psychological index and the post body index.
The method of claim 7,

The computer device further comprises storing the initial biometric data, the initial medical examination data, the post biometric data, the post medical examination data, the initial stress index, the post stress index, and the content information in a database for the subject. A stress management method based on a complex stress index.
The method of claim 8,

The content information includes information on a plurality of content,

The computer device compares the initial stress index and the post stress index, maps information on the degree of stress relaxation for each of the plurality of contents, and stores it in the database,

When the computer device calculates a stress index for a new subject, content information for the new user is provided based on a psychological index and a body index for the new subject, but prioritizes content with a high degree of stress relief. Stress management method based on a complex stress index that provides a.
A storage device that stores a program for calculating a stress index;

An input device for receiving initial biometric data and initial interview data of a subject; And

An initial physical index is calculated using the initial biometric data, an initial psychological index is calculated using the initial medical examination data, and an initial stress index of the subject is calculated using the initial psychological index and the initial physical index, Including a computing device for providing content information on the subject based on the initial stress index,

The initial questionnaire data includes different types of questionnaire data, and the computing device calculates an anxiety index, a depression index, and a PSS (Perceived Stress Scale) index using the interview data, and the anxiety A stress management device based on a complex stress index that calculates the initial psychological index by reflecting a weight for each of the index, the depression index, and the PSS index.
The method of claim 10,

The computing device is a stress management device based on a complex stress index for determining weights for each of the anxiety index, the depression index, and the PSS index based on the initial body index.
The method of claim 10,

The input device further receives job data,

The computing device is a stress management device based on a complex stress index that calculates a job index using the job data and further calculates the stress index by using the job index.
The method of claim 12,

The job data is a stress management device based on a complex stress index including workload, job satisfaction, presentation, time and attendance information, salary, and sales.
The method of claim 10,

The computing device evaluates a level of stress for the subject provided with stress relief content according to the content information,

The subject's post-mortem body index is calculated by using the subject's new biometric data, the subject’s post-mortem index is calculated using the subject’s new questionnaire data, and the subject’s post-stress index using the post-psychological index and the post-body index And, by comparing the initial stress index and the post-stress index to evaluate the degree of stress, a stress management device based on a complex stress index.
The method of claim 14,

The storage device further stores initial biometric data, initial interview data, post biometric data, post interview data, the initial stress index, the post stress index, and the content information for the subject.
The method of claim 15,

The content information includes information on a plurality of content,

The computing device compares the initial stress index and the post stress index, and maps and stores information on the degree of stress relaxation for each of the plurality of contents in the storage device,

When calculating a stress index for a new target, the computing device provides content information for the new user based on a psychological index and a body index for the new target, but prioritizes content with a high degree of stress relief. A stress management device based on a complex stress index that provides a.
A computer-readable recording medium in which a program for executing the stress management method based on the complex stress index according to any one of claims 1 to 9 is recorded on a computer.