WO2015129533A1 - Dispositif de support de mesure, système de support de santé, procédé pour support de mesure, et programme de support de mesure - Google Patents

Dispositif de support de mesure, système de support de santé, procédé pour support de mesure, et programme de support de mesure Download PDF

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Publication number
WO2015129533A1
WO2015129533A1 PCT/JP2015/054538 JP2015054538W WO2015129533A1 WO 2015129533 A1 WO2015129533 A1 WO 2015129533A1 JP 2015054538 W JP2015054538 W JP 2015054538W WO 2015129533 A1 WO2015129533 A1 WO 2015129533A1
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WIPO (PCT)
Prior art keywords
measurement
measurement pattern
time series
information
subject
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PCT/JP2015/054538
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English (en)
Japanese (ja)
Inventor
アズハールタズビル
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オムロン株式会社
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Publication of WO2015129533A1 publication Critical patent/WO2015129533A1/fr

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/60—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to nutrition control, e.g. diets
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
    • G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0002—Remote monitoring of patients using telemetry, e.g. transmission of vital signals via a communication network
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
    • A61B5/021—Measuring pressure in heart or blood vessels
    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01G—WEIGHING
    • G01G19/00—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups
    • G01G19/44—Weighing apparatus or methods adapted for special purposes not provided for in the preceding groups for weighing persons
    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
    • G16H20/30—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to physical therapies or activities, e.g. physiotherapy, acupressure or exercising

Definitions

  • the present invention relates to a technique for presenting a time-series measurement pattern related to repeated measurement of the body with a measuring machine such as a scale to the subject.
  • the inventor of the present application is a subject who is making efforts to increase or decrease an item related to the body such as weight (hereinafter referred to as a body item). It was confirmed that there are some things that are likely to be successful, others are low, depending on the time-series measurement pattern of repeated measurement behavior. In other words, by presenting the subject with a time-series measurement pattern (recommended time-series measurement pattern) of measurement behavior that is likely to achieve the purpose of increasing or decreasing physical items. Support of the target person can be performed from the viewpoint that was not done.
  • the object of the present invention is to provide a subject with a time-series measurement pattern of measurement behavior that is likely to achieve the purpose of increasing or decreasing an item related to the body such as weight and supporting the subject. It is to provide technology to do.
  • the measurement support device of the present invention is configured as follows in order to achieve the object.
  • the wellness information storage unit stores the wellness information received by the receiving unit.
  • the wellness information includes a subject ID for identifying the subject, body information obtained by measuring the subject's body, and a measurement time when the body information is measured.
  • the physical information is, for example, weight and blood pressure.
  • the time series measurement pattern detector uses the wellness information stored in the wellness information storage unit to calculate and recommend the fitness of changes in the measured body information for each time series measurement pattern in which the body information is measured. Detect time series measurement patterns of physical information.
  • the fitness is a degree indicating the strength of the relationship between the time-series measurement pattern and the measured change in physical information.
  • the presenting unit presents the time series measurement pattern recommended by the body information detected by the time series measurement pattern detection unit to the subject.
  • time-series measurement pattern of measurement behavior (recommended time-series measurement pattern of physical information) that is likely to achieve the purpose of increasing or decreasing items related to the body such as weight and blood pressure. ) Can be presented. Therefore, it is possible to support a target person who is working on a diet or the like from a point of view that has not been assumed so far.
  • the time series measurement pattern detecting unit detects a recommended time series measurement pattern of physical information for each attribute such as age and sex.
  • the time series measurement pattern detection unit for each time series measurement pattern in which the body information is measured, the fitness of the change in which the measurement value related to the physical information decreases and the fitness of the change in which the measurement value related to the physical information increases. It is preferable that the time series measurement pattern of the recommended body information is detected and calculated. For example, as a time-series measurement pattern recommended for one of the decrease or increase of the measurement value related to physical information, the fitness for one change is greater than a predetermined first threshold, and the other A time-series measurement pattern in which the degree of fitness associated with the change in is smaller than a predetermined second threshold is detected.
  • the time series measurement pattern detection unit detects a time series measurement pattern in a predetermined period, for example, one week.
  • a time series measurement pattern of measurement behavior that is highly likely to achieve the purpose of increasing or decreasing an item related to the body such as weight is presented to the subject, and has been assumed so far. Can support the target person from the point of view that did not exist.
  • FIG. 1 is a block diagram showing a configuration of a health support system according to this example.
  • the health support system according to this example supports a subject who is working on a weight loss diet.
  • This health support system includes a measurement support device 1, a portable terminal 2, and a weight scale 3.
  • the portable terminal 2 and the weight scale 3 are owned by the subject who is working on the diet.
  • the portable terminal 2 and the weight scale 3 are paired.
  • FIG. 1 only a pair of portable terminals 2 and a scale 3 owned by a subject are shown as representatives, and the portable terminal 2 connected to the measurement support device 1 via a network is shown. It does not mean that it is only this target person. A large number of subject mobile terminals 2 are connected to the measurement support apparatus 1 via a network.
  • the scale 3 has a short-range wireless communication function that can measure the weight and transmits the measurement result to the portable terminal 2 by short-range wireless communication.
  • Some scales of this type have already been commercialized (for example, see http://www.healthcare.omron.co.jp/sp/hbf252f/).
  • the portable terminal 2 has a short-range wireless communication function capable of performing short-range wireless communication with the scale 3, and a network communication function capable of communicating with the measurement support apparatus 1 via a network such as the Internet.
  • This type of mobile terminal 2 includes a smartphone that has already been commercialized.
  • the portable terminal 2 can be replaced with a personal computer or the like.
  • FIG. 2 is a block diagram showing the configuration of the main part of the measurement support apparatus according to this example.
  • the measurement support device 1 includes an arithmetic processing unit 11, a subject database 12 (hereinafter referred to as a subject DB 12), a measurement history database 13 (hereinafter referred to as a measurement history DB 13), and a communication unit 14. I have.
  • the arithmetic processing unit 11 controls the operation of the main body of the measurement support device 1 and performs a process of detecting a time-series measurement pattern of measurement actions for repeatedly measuring body weight according to the attributes of the subject. Details of the processing performed by the arithmetic processing unit 11 will be described later.
  • the arithmetic processing unit 11 has a computer on which the measurement support program according to the present invention is installed, and this computer executes the measurement support method according to the present invention. Further, the arithmetic processing unit 11 has a configuration corresponding to the time series measurement pattern detection unit referred to in the present invention.
  • the target person DB 12 is a database for managing the target person.
  • FIG. 3 is a diagram showing the subject database.
  • the target person mentioned here is a member registered in this health support system, and is working on a diet to lose weight.
  • the target person DB 12 is a target in which an ID (identification code) for identifying the target person, a registered e-mail address of the target person, the name of the target person, the sex of the target person, the date of birth of the target person, etc. are associated with each target person. It is a database that registered person records. The age of the subject is obtained from the registered date of birth.
  • This target person DB 12 has a configuration corresponding to the attribute storage unit referred to in the present invention.
  • the measurement history DB 13 accumulatively stores measurement data (corresponding to wellness information, referred to in the present invention) in which the measurement date / time of the body weight and the measured body weight are associated with each other.
  • FIG. 4 is a diagram showing a measurement history database.
  • the measurement history DB 13 has an area for storing measurement data for twice in the morning and afternoon every day for each subject.
  • the measurement data are measurement time and measurement weight.
  • the area in which the measurement data is not stored means that the subject has not measured the weight and no measurement data exists.
  • the measurement history DB 13 has a configuration corresponding to the wellness information storage unit referred to in the present invention.
  • the time series measurement pattern for measuring the weight is different for each subject due to differences in living environment and lifestyle.
  • the communication unit 14 communicates with the mobile terminal 2 via a network.
  • This communication part 14 is the structure corresponded to the receiving part and presentation part said by this invention.
  • the health support system according to this example is intended for a subject who repeats weight measurement with a scale 3 to confirm the effect of the activity while performing an activity effective for a weight loss diet. Present a time series measurement pattern of body weight measurement (measurement behavior) that is likely to achieve (diet). The operation of the health support system according to this example will be described below.
  • a person who wishes to become a target person can register his / her name, gender, date of birth, purpose (weight loss or increase, etc.), e-mail address on the registration page published on the Internet by the measurement support device 1 Enter the required items.
  • a person who wishes to become a target person is given an ID based on the contents entered on this registration page, and is registered in the target person DB 12.
  • the measurement support apparatus 1 notifies the target person registered this time of the ID assigned at this time.
  • the weight scale 3 temporarily stores measurement data in which the measurement date and time are associated with the measured weight in a memory or the like provided in the body of the weight scale 3.
  • the weight scale 3 transmits the measurement data temporarily stored in the memory by the short-range wireless communication to the portable terminal 2.
  • the weight scale 3 and the portable terminal 2 may be configured to communicate with each other by wire. Further, the subject may input the measurement date / time when the weight is measured by the scale 3 or the measured weight to the portable terminal 2.
  • the portable terminal 2 attaches an ID to the measurement data transmitted from the scale 3 and transmits it to the measurement support device 1.
  • the measurement data transmitted from the portable terminal 2 to the measurement support device 1 corresponds to wellness information referred to in the present invention.
  • the measurement support device 1 receives the measurement data with the ID (measurement data transmitted from the mobile terminal 2) by the communication unit 14, the measurement support device 1 stores the measurement data in the measurement history DB 13. Thereby, the measurement support device 1 stores the measurement data in the measurement history DB 13 in an accumulative manner for each subject.
  • FIG. 5 is a flowchart showing this detection process.
  • the measurement support device 1 detects a time series measurement pattern of weight measurement that is highly likely to achieve a diet for each group in which subjects are classified by attributes. Groups are categorized by gender and age. There are five age groups, for example, less than 20's, 20's, 30's, 40's and 50's or more. In this case, the measurement support apparatus 1 detects a time series measurement pattern of weight measurement with high possibility of achieving a diet for 10 groups classified by attribute.
  • the measurement support apparatus 1 determines the attribute of the subject related to the group for detecting the time series measurement pattern of the weight measurement that is likely to achieve the diet by the arithmetic processing unit 11 (s1).
  • s1 for example, attributes such as women in their 30s, women in their 40s, men in their 40s are determined.
  • the arithmetic processing unit 11 searches the subject DB 12, and extracts all IDs of subjects belonging to the group classified by the attribute determined in s1 (s2). In s2, for example, all the IDs of subjects who are female in their 30s are extracted.
  • the arithmetic processing unit 11 extracts measurement data stored in the measurement history DB 13 for each ID extracted in s2 (s3).
  • s3 for example, measurement data is extracted for each subject who is a woman in her 30s.
  • the arithmetic processing unit 11 divides the measurement data extracted in s3 into blocks divided by a predetermined period (in this example, one week) for each subject (s4).
  • a predetermined period in this example, one week
  • the measurement data of the subject is classified into one block of measurement data for one week from Monday to the next Sunday. Therefore, the number of blocks created for one target person is not limited to one.
  • the arithmetic processing unit 11 extracts a block whose weight is reduced by a predetermined amount or more (in this example, 1% or more) during the divided block period as a block that has been successfully reduced (s5). In addition, the arithmetic processing unit 11 extracts a block whose weight has increased by a predetermined amount or more (in this example, 1% or more) during the divided block period as a block that has failed to be reduced (s6). Either of the processing orders of s5 and s6 may be performed first.
  • the arithmetic processing unit 11 adds up the number of blocks extracted in s5 for each time series measurement pattern of weight measurement (s7).
  • fitness DOA Degree of Azhar
  • FIG. 6 is a diagram illustrating a result of summing up blocks according to time series measurement patterns of weight measurement in s7 and calculating fitness DOA in s8.
  • the day of the week (Monday, Tuesday, Wednesday, Thursday, Saturday, and Sunday) is included in the time series measurement pattern, indicating that the weight has been measured (measurement data exists). "" Indicates that the weight was not measured (there is no measurement data).
  • the total number of blocks is the number of blocks extracted in s5.
  • the arithmetic processing unit 11 adds up the number of blocks extracted in s6 for each time series measurement pattern of weight measurement (s9).
  • fitness DOA is calculated for each time series measurement pattern of weight measurement in which the number of blocks is totaled (s10).
  • FIG. 7 is a diagram showing a result of totalizing blocks according to time series measurement patterns of weight measurement in s9 and calculating fitness DOA in s10.
  • FIG. 7 includes the day of the week (Monday, Tue, Wed, Thu, Fri, Sat and Sun) in the time series measurement pattern because the weight was measured (measurement data exists).
  • “_” instead of the day of the week indicates that the weight was not measured (there is no measurement data).
  • the total number of blocks is the number of blocks extracted in s6.
  • the order of the processes related to s7 to s10 does not have to be the order described above, but the process related to s8 is performed after the process related to s7 is performed, and the process related to s10 is the process related to s9. Is done after.
  • the arithmetic processing unit 11 detects a time series measurement pattern recommended in weight measurement performed by the subject having the attribute determined in s1 in order to achieve a diet (s11).
  • the time series measurement pattern of the weight measurement of the subject who succeeded in the diet (here, the subject who lost 1% or more) and the fitness DOA thereof, and the subject who failed in the diet
  • Time series measurement of weight measurement recommended for a subject having the attribute determined in s1 using a time series measurement pattern of body weight measurement of a person (here, a subject increased by 1% or more) and its fitness DOA Detect patterns.
  • the higher the fitness DOA the higher the possibility of succeeding in the diet.
  • the higher the fitness DOA the higher the possibility of diet failure.
  • the lower the fitness DOA the lower the possibility of diet failure.
  • the fitness DOA is larger than the predetermined first threshold value
  • the time series of the weight measurement of the subject who failed in the diet In the measurement pattern, a weight measurement time series measurement pattern having a fitness DOA smaller than a predetermined second threshold is detected as a recommended weight measurement time series measurement pattern.
  • the first threshold value and the second threshold value may be the same value or different values.
  • the first threshold value 2 [%]
  • the second threshold value 1 [%].
  • the time series measurement pattern for weight measurement that satisfies the above conditions is a pattern “Monday Tuesday Wednesday Thursday Saturday Saturday Tuesday Tuesday Wednesday Friday _day” in which the body weight is not measured only in the afternoon on Saturday.
  • the first threshold value and the second threshold value described above are It ’s not that big.
  • the arithmetic processing unit 11 determines the recommended time series measurement pattern for weight measurement to be presented to the subject having the attribute determined in s1 (s12, s13). On the other hand, if the time series measurement pattern for weight measurement recommended in s11 cannot be detected, the arithmetic processing unit 11 assumes that there is no recommended time series measurement pattern for weight measurement to be presented to the subject having the attribute determined in s1. (S12, s14).
  • the arithmetic processing unit 11 can detect a time series measurement pattern of weight measurement recommended for subjects belonging to each group by performing the processing shown in FIG. 5 for each group classified by attribute.
  • the measurement support apparatus 1 transmits to the subject a time series measurement pattern of recommended weight measurement detected by the process shown in FIG. Further, this e-mail may be transmitted only to a subject who has not succeeded in losing weight. Furthermore, if the subject has succeeded in dieting at that time, the recommended weight measurement time series measurement pattern is different from the detected weight measurement time series measurement pattern. You may be made not to send the electronic mail which presents.
  • the detection of the time series measurement pattern of weight measurement recommended in s11 may be replaced with the following processing.
  • a time series measurement pattern of weight measurement indicating the timing for recommending measurement of weight and the timing at which weight measurement may or may not be detected is detected. That is, a weight measurement time series measurement pattern that defines at least the timing of measuring weight is detected.
  • a time series measurement pattern of weight measurement that defines at least the timing of measuring the weight is shown in the morning , And the timing specified for weighing on Friday afternoon, we measured weight at least on Monday, Wednesday, Thursday and Friday for 5 days and Friday afternoon and succeeded in losing weight (> 1% weight loss)
  • a time series measurement pattern (at least a weight measurement time series measurement pattern that defines the timing of measuring body weight) is detected.
  • the time series measurement pattern (19%) of the body weight measurement which is defined as the above example and which defines at least the timing of measuring body weight on the morning of Monday, Tuesday, Wednesday, Thursday, Friday and Friday afternoon, is more daily. It becomes larger than the time series measurement pattern (10%) of body weight measurement which stipulates that body weight is measured in the morning and afternoon.
  • time series measurement pattern of the weight measurement in which the morning of Monday, Tuesday, Wednesday, Thursday, and Friday afternoon are defined as the timing of measuring the weight is shown as an example.
  • the fitness DOA of women in their 30s who have failed to lose weight from the fitness DOA of women in their 30s who have succeeded in losing weight for at least a plurality of time series measurement patterns of weight measurement that define the timing for measuring body weight.
  • a value (difference value) obtained by subtracting is calculated, and the time series measurement pattern of weight measurement in which the difference value is maximum is detected as a recommended time series measurement pattern of weight measurement.
  • the time series measurement pattern for measuring the body weight which specifies that the body weight is measured, is provided with a condition that the timing for measuring the body weight is, for example, 6 times or more.
  • the arithmetic processing unit 11 has the maximum difference value. If it is less than a predetermined value (for example, 10%), it may be determined that there is no recommended time series measurement pattern for weight measurement.
  • a predetermined value for example, 10%
  • the email sent to the subject is, for example, “Don't forget to measure your weight on Mondays, Wednesdays, Thursdays, and Fridays for a total of 6 mornings and Friday afternoons. You ’re more likely to succeed on a diet.” Send a message.
  • the present invention is not limited to an example of presenting a recommended time series measurement pattern for weight measurement to a subject who wants to lose weight as described above, but to a subject who wants to gain weight.
  • a recommended time series measurement pattern of weight measurement can be presented.
  • a recommended time-series measurement pattern can be presented for the body fat percentage, BMI (obesity level), blood pressure, and the like.

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  • Health & Medical Sciences (AREA)
  • Engineering & Computer Science (AREA)
  • Public Health (AREA)
  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Primary Health Care (AREA)
  • Biomedical Technology (AREA)
  • Business, Economics & Management (AREA)
  • General Business, Economics & Management (AREA)
  • Nutrition Science (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)
  • Medical Treatment And Welfare Office Work (AREA)

Abstract

　Selon l'invention, lorsque des informations de bien-être comprenant un identifiant de sujet pour identifier un sujet, des informations de corps dans lesquelles le corps du sujet est mesuré, et le temps de mesure auquel les informations de corps ont été mesurées, sont reçus dans une unité de communication (14), un dispositif de support de mesure (1) stocke les informations de bien-être dans une base de données d'historique de mesure (13). Une unité de traitement par calcul (11) calcule la santé physique d'un changement des informations de corps mesurées pour chaque type de mesure en série temporelle des informations de corps mesurées à l'aide des informations de bien-être de la base de données d'historique de mesure (13), et détecte un type de mesure en série temporelle recommandé des informations de corps. Le type de mesure en série temporelle recommandé détecté des informations de corps est ensuite présenté au sujet.
PCT/JP2015/054538 2014-02-25 2015-02-19 Dispositif de support de mesure, système de support de santé, procédé pour support de mesure, et programme de support de mesure WO2015129533A1 (fr)

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JP2014-033558 2014-02-25
JP2014033558A JP2015158434A (ja) 2014-02-25 2014-02-25 測定サポート装置、健康サポートシステム、測定サポート方法、および測定サポートプログラム

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Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009093307A (ja) * 2007-10-05 2009-04-30 Hitachi Ltd 保健指導支援システム
JP2010057552A (ja) * 2008-09-01 2010-03-18 Omron Healthcare Co Ltd 生体指標管理装置
JP2011209871A (ja) * 2010-03-29 2011-10-20 Omron Healthcare Co Ltd 健康管理支援装置、健康管理支援システムおよび健康管理支援プログラム
JP2011258137A (ja) * 2010-06-11 2011-12-22 Sharp Corp 健康管理装置、健康管理制御プログラム、および記録媒体
WO2014006862A1 (fr) * 2012-07-05 2014-01-09 パナソニック株式会社 Système d'assistance à l'amélioration des maladies liées au mode de vie, procédé d'assistance à l'amélioration des maladies liées au mode de vie, programme d'ordinateur d'assistance à l'amélioration des maladies liées au mode de vie, et support d'enregistrement pouvant être lu par un ordinateur sur lequel est mémorisé un programme d'ordinateur d'assistance à l'amélioration des maladies liées au mode de vie

Patent Citations (5)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
JP2009093307A (ja) * 2007-10-05 2009-04-30 Hitachi Ltd 保健指導支援システム
JP2010057552A (ja) * 2008-09-01 2010-03-18 Omron Healthcare Co Ltd 生体指標管理装置
JP2011209871A (ja) * 2010-03-29 2011-10-20 Omron Healthcare Co Ltd 健康管理支援装置、健康管理支援システムおよび健康管理支援プログラム
JP2011258137A (ja) * 2010-06-11 2011-12-22 Sharp Corp 健康管理装置、健康管理制御プログラム、および記録媒体
WO2014006862A1 (fr) * 2012-07-05 2014-01-09 パナソニック株式会社 Système d'assistance à l'amélioration des maladies liées au mode de vie, procédé d'assistance à l'amélioration des maladies liées au mode de vie, programme d'ordinateur d'assistance à l'amélioration des maladies liées au mode de vie, et support d'enregistrement pouvant être lu par un ordinateur sur lequel est mémorisé un programme d'ordinateur d'assistance à l'amélioration des maladies liées au mode de vie

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