WO2016127540A1 - 基于弹性检测设备的健康状况分析方法及系统 - Google Patents

基于弹性检测设备的健康状况分析方法及系统 Download PDF

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Publication number
WO2016127540A1
WO2016127540A1 PCT/CN2015/081955 CN2015081955W WO2016127540A1 WO 2016127540 A1 WO2016127540 A1 WO 2016127540A1 CN 2015081955 W CN2015081955 W CN 2015081955W WO 2016127540 A1 WO2016127540 A1 WO 2016127540A1
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Prior art keywords
cloud server
health
health condition
data
analysis
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PCT/CN2015/081955
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English (en)
French (fr)
Inventor
王玉娟
贾继东
欧晓娟
尤红
邵金华
孙锦
段后利
Original Assignee
无锡海斯凯尔医学技术有限公司
首都医科大学附属北京友谊医院
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Application filed by 无锡海斯凯尔医学技术有限公司, 首都医科大学附属北京友谊医院 filed Critical 无锡海斯凯尔医学技术有限公司
Priority to ES15881701T priority Critical patent/ES2939839T3/es
Priority to PL15881701.5T priority patent/PL3258404T3/pl
Priority to RU2017131711A priority patent/RU2676025C1/ru
Priority to EP15881701.5A priority patent/EP3258404B1/en
Priority to JP2017542171A priority patent/JP6533586B2/ja
Priority to KR1020177025523A priority patent/KR102007590B1/ko
Priority to BR112017017201A priority patent/BR112017017201A8/pt
Priority to AU2015382817A priority patent/AU2015382817A1/en
Publication of WO2016127540A1 publication Critical patent/WO2016127540A1/zh
Priority to US15/649,528 priority patent/US10599815B2/en
Priority to AU2019204997A priority patent/AU2019204997B2/en

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16Z—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS, NOT OTHERWISE PROVIDED FOR
    • G16Z99/00—Subject matter not provided for in other main groups of this subclass
    • 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
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
    • 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
    • G16H40/67—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 for remote operation
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/48—Diagnostic techniques
    • A61B8/485—Diagnostic techniques involving measuring strain or elastic properties
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B8/00—Diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/52—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves
    • A61B8/5215—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data
    • A61B8/5223—Devices using data or image processing specially adapted for diagnosis using ultrasonic, sonic or infrasonic waves involving processing of medical diagnostic data for extracting a diagnostic or physiological parameter from medical diagnostic data
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
    • G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
    • G06Q50/10—Services
    • G06Q50/22—Social work or social welfare, e.g. community support activities or counselling services
    • 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
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
    • G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
    • 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
    • G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems

Definitions

  • the invention belongs to the technical field of data processing, and in particular relates to a health condition analysis method and system based on an elastic detecting device.
  • the present invention provides a health condition analysis method and system based on an elastic detection device, which is used to achieve an objective for an individual to know their own health condition in a timely and convenient manner through a client.
  • a first aspect of the embodiments of the present invention provides a health condition analysis method based on an elastic detecting device, the elastic detecting device comprising an excitation device for generating an elastic shear wave in a viscoelastic medium, and determining the viscoelastic medium in the a device for capturing displacement data generated by an elastic shear wave; the elastic detecting device sends the obtained displacement data to a cloud server for storage; and the health condition analysis method includes:
  • the client sends a health condition analysis request to the cloud server, where the health condition analysis request includes the individual attribute identification information of the querier, so that the cloud server acquires the data to be analyzed corresponding to the health condition analysis request from the cloud database. And performing data analysis on the data to be analyzed to obtain health status information of the queryer; wherein the data to be analyzed And including the finder by detecting, by the elastic detecting device, the displacement data of the obtained viscoelastic medium;
  • the client receives the health status information of the querier sent by the cloud server.
  • the health condition analysis request further includes community attribute identification information of the querier
  • the health condition analysis request is further configured to: the cloud server obtains a first displacement data set corresponding to the group attribute identification information from a cloud database, and performs data analysis on the first displacement data set to obtain a first And analyzing the result, and causing the cloud server to obtain a second displacement data set corresponding to the individual attribute identification information from the cloud database, performing data analysis on the second displacement data set to obtain a second analysis result, and according to the The first analysis result obtains health status information corresponding to the second analysis result.
  • the method further includes:
  • the client receives the health suggestion information sent by the cloud server, where the health suggestion information is determined by the cloud server according to the health condition information.
  • the group attribute identification information includes at least one of the following identifiers: a condition to be queried Logo, age group ID, gender ID.
  • a second aspect of the embodiments of the present invention provides another method for analyzing a health condition based on an elastic detecting device, the elastic detecting device comprising an exciting device for generating an elastic shear wave in a viscoelastic medium, and determining the viscoelastic medium a device for capturing displacement data generated by the elastic shear wave; the elastic detecting device sends the obtained displacement data to a cloud server for storage; and the health condition analysis method includes:
  • the cloud server receives the health condition analysis request sent by the client, where the health condition analysis request includes the individual attribute identification information of the querier;
  • the cloud server obtains data to be analyzed corresponding to the health condition analysis request from the cloud database, and performs data analysis on the data to be analyzed to obtain health status information of the queryer, where the data to be analyzed And including the finder by detecting, by the elastic detecting device, the displacement data of the obtained viscoelastic medium;
  • the cloud server sends the health status information of the querier to the client.
  • the health condition analysis request further includes community attribute identification information of the querier
  • the cloud server obtains data to be analyzed corresponding to the health condition analysis request from the cloud database, and performs data analysis on the data to be analyzed to obtain the health status information of the queryer, including:
  • the cloud server acquires a second displacement data set corresponding to the individual attribute identification information from the cloud database, and performs data analysis on the second displacement data set to obtain a second analysis result;
  • the cloud server obtains health status information corresponding to the second analysis result according to the first analysis result.
  • the method further includes:
  • the cloud server determines health suggestion information according to the health condition information
  • the cloud server sends the health suggestion information to the client.
  • the group attribute identification information includes at least one of the following identifiers: a condition to be queried Logo, age group ID, gender ID.
  • a third aspect of the embodiments of the present invention provides a health condition analysis system based on an elastic detection device, the elastic detection device comprising an excitation device for generating an elastic shear wave in a viscoelastic medium, and determining the viscoelastic medium in the a device for capturing displacement data generated by an elastic shear wave; the elastic detecting device sends the obtained displacement data to a cloud server for storage; the system includes: a client and a cloud server;
  • the client is configured to send a health condition analysis request to the cloud server, where the health condition analysis request includes individual attribute identification information of the querier;
  • the cloud server is configured to receive a health condition analysis request sent by the client, and obtain data to be analyzed corresponding to the health condition analysis request from the cloud database, and perform data analysis on the data to be analyzed to obtain the queryer.
  • Health status information wherein the to-be-divided
  • the analyzing data includes the displacement data of the viscoelastic medium obtained by the queryer by the elastic detecting device;
  • the cloud server is further configured to send the health status information of the querier to the client.
  • the health condition analysis request further includes community attribute identification information of the querier
  • the cloud server is further configured to obtain a first displacement data set corresponding to the group attribute identification information from a cloud database, and perform data analysis on the first displacement data set to obtain a first analysis result;
  • the cloud server is further configured to obtain a second displacement data set corresponding to the individual attribute identification information from the cloud database, and perform data analysis on the second displacement data set to obtain a second analysis result;
  • the cloud server is further configured to obtain health status information corresponding to the second analysis result according to the first analysis result.
  • the cloud server is further configured to determine health suggestion information according to the health condition information, and Sending the health suggestion information to the client;
  • the client is further configured to receive the health suggestion information.
  • each elastic detecting device performs cloud storage for detecting the displacement data of each person obtained. Therefore, the queryer can send a health condition analysis request to the cloud server through the client set in the terminal device, and the cloud server can obtain the queryer in the health condition analysis request from the cloud database storing the displacement data of each queryer.
  • the individual attribute information corresponds to the data to be analyzed, and the data to be analyzed is analyzed to obtain the health status information of the queryer, such as the trend of the organ's organ elasticity change or the possibility that the queryer has a certain disease. Therefore, with the massive data stored in the cloud server, the queryer can easily and timely understand the physical health of the user through the client.
  • FIG. 1 is a flow chart of Embodiment 1 of a health condition analysis method based on an elastic detecting device according to the present invention.
  • Embodiment 2 is a flowchart of Embodiment 2 of a method for analyzing a health condition based on an elastic detecting device according to the present invention
  • FIG. 3 is a schematic structural diagram of an embodiment of a health condition system based on an elastic detecting device according to the present invention.
  • an elastic detecting device performs elastic detection on a human body to obtain displacement data of a human body, and the displacement data is detected by an elastic detecting device.
  • the elastic viscoelastic medium is obtained by elastic detection, and each elastic detecting device sends the obtained displacement data to the cloud server for storage.
  • the elastic detecting device includes an exciting device that generates an elastic shear wave in a viscoelastic medium of the examiner; and a capturing device that determines displacement data generated by the viscoelastic medium under the action of the elastic shear wave.
  • the working principle of the excitation device and the capture device is simply that, on the surface of the viscoelastic organ medium such as the liver, exciting the shear wave to the viscoelastic medium by the excitation device is equivalent to generating a vibration signal, and the viscoelastic medium is The vibrating signal vibrates, and the capturing device can send an ultrasonic signal to the viscoelastic medium.
  • the viscoelastic medium generates an echo response. Since the elastic stress or the elastic strain of the viscoelastic organ medium is different under different states, such as a normal state or a pathological state, the capturing device calculates the displacement data of the viscoelastic medium according to the echo signals before and after the compression.
  • the displacement data reflects the elastic characteristics of viscoelastic organs and is an important reference for human health.
  • different detectors may use different elastic detection devices to detect at different times.
  • Each elastic detection device is uploaded to the cloud server for cloud storage after obtaining the displacement data of the detector.
  • the method in this implementation includes:
  • Step 101 The client sends a health condition analysis request to the cloud server, where the health condition analysis request includes the individual attribute identification information of the querier, so that the cloud server receives the cloud number from the cloud.
  • Step 102 The client receives the health status information of the querier sent by the cloud server.
  • the client is configured in a user terminal, where the user terminal refers to a terminal device that needs to query an inquirer who obtains its own health status, such as a smart phone, a notebook computer, a tablet computer, etc., and the client terminal, for example. It can be in the form of an app or a web page.
  • the connection mode between the user terminal device and the cloud server to which the client belongs may be a wired connection mode or a wireless network connection mode such as WLAN, 3G, 4G, or GRPS, and is not specifically limited.
  • the cloud server stores displacement data obtained by each inquirer performing elastic detection of a viscoelastic organ medium such as a liver at different times and places.
  • the displacement data includes, for example, identity information such as name, age, ID number, and contact information of the examiner, and the displacement value obtained by the detection, and may further include identification information of the elastic detecting device such as the detection, the elasticity.
  • the querier may send a health condition analysis request to the cloud server through the client when the querier needs to query the health status of the querier, where the health condition analysis request includes the individual attribute identification information of the querier, the individual The attribute identifier is used to uniquely identify the querier, such as the ID number, name, and contact information of the querier.
  • the queryer can input the corresponding individual attribute identifier by prompting in the input prompt box in the page.
  • the cloud server when the cloud server receives the health condition analysis request that is sent by the client and carries the attribute information of the queryer, the cloud server obtains the data to be analyzed corresponding to the individual attribute identification information from the cloud database, where the cloud to be analyzed
  • the data includes displacement data of the viscoelastic medium obtained by the inquirer through the respective elastic detecting devices.
  • the querier's data to be analyzed is a set of displacement data obtained by the querier's multiple elastic detections over a period of time, and the cloud server analyzes the displacement data set to obtain an analysis result.
  • the cloud server analyzes the displacement data set may be a trend graph for analyzing the displacement value of the queryer, that is, a trend graph of each displacement value changing with time; for example, the cloud server performs the displacement data set.
  • the analysis may also be to count the number of times in the displacement data of the finder over a certain time interval and the corresponding displacement value.
  • the analysis result obtained by the cloud server for analyzing the data can be used as a health status information of the queryer, so that the cloud server sends the analysis result to the client, so that the queryer can obtain the result. Its own health status information.
  • the querier can send a health condition analysis request to the cloud server through the client set in the terminal device, and the cloud server can
  • the cloud database storing the displacement data of each queryer obtains the data to be analyzed corresponding to the individual attribute information of the queryer in the health condition analysis request, and performs data analysis on the analyzed data to obtain the health status information of the queryer, such as a query.
  • the tendency of the organ's elasticity to change or the possibility that the inquirer has a certain disease Therefore, with the massive data stored in the cloud server, the queryer can easily and timely understand the physical health of the user through the client.
  • the health information of the querier obtained by the cloud server in order to make the health information of the querier obtained by the cloud server more accurate, it is also necessary to consider the influence of the quotient group attribute information on the health condition analysis result.
  • a chart obtained from the same set of displacement data If the set of displacement data corresponds to a child's test data, the chart reflects that the child's health may be that the child's health is good. And if the displacement data of the group corresponds to the test data of an elderly person, the health condition of the elderly person reflected by the trend chart may be in poor health condition. Therefore, it is necessary to consider the influence of the queryer's group attribute information on the health status analysis results.
  • the health condition analysis request sent by the client to the cloud server includes the attribute attribute identification information of the querier in addition to the individual attribute identification information of the querier.
  • the group attribute identification information includes at least one of the following identifiers: a symptom identifier to be queried, an age group identifier, and a gender identifier.
  • the age group identifier can be, for example, four pre-defined age groups: children, adolescents, young and middle-aged people, and the elderly. The same age range.
  • the condition marker can be, for example, a liver disease marker such as cirrhosis, fatty liver, and the like.
  • the cloud server After the cloud server receives the health condition analysis request that is sent by the client and carries the querier's individual attribute identification information and the group attribute identification information, the cloud server obtains the corresponding attribute information of the group attribute from the cloud database. a first displacement data set, and performing data analysis on the first displacement data set to obtain a first analysis result; on the other hand, the cloud server further acquires a second displacement data set corresponding to the individual attribute identification information from the cloud database, to the second The displacement data set is subjected to data analysis to obtain a second analysis result. According to the description of the foregoing analysis process, the analysis process of the first displacement data set and the second displacement data set by the cloud server is not repeated herein.
  • the first displacement data set is displacement data that meets certain requirements of all persons who have detected the type of disease.
  • the above-mentioned condition refers especially to a condition associated with the result of the elasticity detection, such as the above-mentioned fatty liver, cirrhosis, etc., thereby corresponding to the condition.
  • the displacement data included in the data set needs to meet the requirements corresponding to the disease.
  • the elastic displacement is generally in the range of a1-a2; in the case of B, the elastic displacement is generally in the range of b1-b2.
  • the first analysis result may be an overall trend map of the displacement data corresponding to the disease in the population in the age group;
  • the second analysis result may be a trend graph of displacement data of the condition of the queryer. It can be understood that the age of the querier is within the age range of the group attribute identifier.
  • the cloud server After analyzing the first analysis result and the second analysis result, the cloud server obtains the health status information corresponding to the second analysis result according to the first analysis result, that is, the first analysis result is used as a reference to determine the second analysis result.
  • the first analysis result is an analysis result of a certain type of population and/or a certain type of disease to which the queryer belongs, and the analysis result of the group is used as a reference, and the queryer can be more accurately evaluated.
  • the health of the querier is characterized by the results of the individual analysis.
  • the analysis result of the displacement data of the queryer indicates that all the displacement values of the queryer are located in the interval of A-B, and correspondingly, the corresponding population, such as the displacement data analysis result of the population in a certain age group.
  • the person characterizing the age group has the displacement value in the CD interval, and the AB interval is in the CD interval near the middle region, and the cloud server refers to the analysis result of the group to determine that the health of the query individual is good, thereby the health Status information is fed back to the client.
  • the querier health status information is only indicative of the possibility of the querier suffering from a certain condition.
  • the cloud server may also push the corresponding health suggestion information, such as health management suggestions and other public interest information, according to the health status.
  • the client may receive the health suggestion information sent by the cloud server in addition to receiving the health status information of the querier sent by the cloud server.
  • the health suggestion information pushed by the cloud server may be, for example, a diet or a sports strategy suggestion.
  • the cloud server's push service can be customized. That is, if the client pre-customizes the cloud server's health suggestion push service, the cloud server pushes the corresponding health suggestion to the client after performing the health analysis.
  • Embodiment 2 is a flowchart of Embodiment 2 of a method for analyzing a health condition of an elastic detecting device according to the present invention. As shown in FIG. 2, the method includes:
  • Step 201 The cloud server receives a health condition analysis request sent by the client, where the health condition analysis request includes the individual attribute identification information of the querier;
  • Step 202 The cloud server obtains data to be analyzed corresponding to the health condition analysis request from the cloud database, and performs data analysis on the data to be analyzed to obtain health status information of the queryer, where the to-be-analyzed
  • the data includes displacement data of the viscoelastic medium obtained by the inquirer through the elastic detecting device;
  • Step 203 The cloud server sends the health status information of the querier to the client.
  • the manner of acquiring the displacement data and the composition of the elastic detecting device are the same as those in the embodiment shown in FIG. 1, and details are not described herein again.
  • Displacement data obtained by performing elastic detection of a viscoelastic organ medium such as a liver at different times and places by each inquirer is stored in the cloud server.
  • the displacement data includes, for example, identity information such as name, age, ID number, and contact information of the examiner, and the displacement value obtained by the detection, and may also include, for example, the identifier of the elastic detecting device that performs the detection.
  • the cloud server stores the displacement data, for example, may be classified and stored, for example, different databases are established according to different hospitals or regions, or different storage spaces are defined in the same database; According to the identification of a certain type of disease, the displacement data is stored in the same process, and the displacement data of the same symptom of the same detector is stored in a centralized manner, thereby improving storage efficiency and facilitating subsequent data query convenience. Of course, you can also store them in chronological order.
  • the querier can send a health condition analysis request including the individual attribute identification information of the querier to the cloud server through the client when the querier needs to query the health status of the querier.
  • the cloud server obtains, from the cloud database, the data to be analyzed corresponding to the individual attribute identification information, that is, the set of all the displacement data of the queryer.
  • the cloud server analyzes the displacement data set to obtain an analysis result.
  • the analysis performed by the cloud server on the displacement data set may be, for example, a trend analysis of the displacement value of the queryer, that is, a trend graph of each displacement value as a function of time.
  • the analysis result obtained by the cloud server for analyzing the data for example, can be used as a health status information of the queryer, so that the cloud server sends the analysis result to the client, so that the queryer can obtain the result. Its own health status information.
  • the health condition analysis request sent by the client to the cloud server includes the attribute attribute identification information of the querier in addition to the individual attribute identification information of the querier.
  • the group attribute identification information includes at least one of the following identifiers: a symptom identifier to be queried, an age group identifier, and a gender identifier.
  • the cloud server After the cloud server receives the health condition analysis request that is sent by the client and carries the querier's individual attribute identification information and the group attribute identification information, the cloud server obtains the first displacement data corresponding to the group attribute identification information from the cloud database. Collecting, and performing data analysis on the first displacement data set to obtain a first analysis result; on the other hand, the cloud server further acquires a second displacement data set corresponding to the individual attribute identification information from the cloud database, to the second place The data set is moved for data analysis to obtain a second analysis result. According to the description of the foregoing analysis process, the analysis process of the first displacement data set and the second displacement data set by the cloud server is not repeated herein.
  • the first analysis result may be an overall trend map of the displacement data corresponding to the disease in the population in the age group; correspondingly, The second analysis result may be a trend graph of the displacement data of the condition of the queryer. It can be understood that the age of the querier is within the age range of the group attribute identifier.
  • the cloud server After analyzing the first analysis result and the second analysis result, the cloud server obtains the health status information corresponding to the second analysis result according to the first analysis result, that is, the first analysis result is used as a reference to determine the second analysis result.
  • the first analysis result is an analysis result of a certain type of population and/or a certain type of disease to which the queryer belongs, and the analysis result of the group is used as a reference, and the queryer can be more accurately evaluated.
  • the health of the querier is characterized by the results of the individual analysis.
  • the analysis result of the displacement data of the queryer indicates that all the displacement values of the queryer are located in the interval AB, and correspondingly, the corresponding population, such as the displacement data analysis result of the population in a certain age group, represents the age.
  • the displacement value is in the CD interval
  • the AB interval is in the CD interval near the middle region.
  • the analysis result of the cloud server reference group determines that the health of the queryer is good, so the health information feedback To the client. It should be noted that, in this embodiment, the querier health status information is only indicative of the possibility of the querier suffering from a certain condition.
  • the cloud server may also push the corresponding health suggestion information, such as health management suggestions and other public interest information, according to the health status.
  • the cloud server sends the health suggestion information to the client in addition to sending the health status information of the querier to the client.
  • the querier sends a health condition analysis request to the cloud server through the client set in the terminal device, so that the cloud server can obtain the health condition analysis request from the cloud database storing the displacement data of each querier.
  • the individual attribute information of the inquirer corresponding to the set of displacement data to be analyzed, and the data analysis of the displacement data set to be analyzed to obtain the health status information of the inquirer, such as the organ elasticity change trend of the inquirer or the check The inquirer has the possibility of a certain disease and so on. Therefore, with the massive detection data of the massive finder stored in the cloud server, the querier can conveniently and timely understand the overall physical health condition of the client through the client.
  • FIG. 3 is a schematic structural diagram of an embodiment of a health condition system based on an elastic detection device according to the present invention. As shown in FIG. 3, the system includes: a client 1 and a cloud server 2;
  • the client 1 is configured to send a health condition analysis request to the cloud server, where the health condition analysis request includes individual attribute identification information of the querier;
  • the cloud server 2 is configured to receive a health condition analysis request sent by the client, and obtain data to be analyzed corresponding to the health condition analysis request from the cloud database, and perform data analysis on the data to be analyzed to obtain the query.
  • the health condition information of the person, wherein the data to be analyzed includes displacement data of the viscoelastic medium obtained by the inquirer through the elastic detecting device;
  • the cloud server 2 is further configured to send the health status information of the querier to the client.
  • the elastic detecting device comprises an exciting device for generating an elastic shear wave in the viscoelastic medium, and a capturing device for determining displacement data generated by the viscoelastic medium under the action of the elastic shear wave. And, the elasticity detecting device sends the obtained displacement data to the cloud server for storage.
  • the health condition analysis request further includes group attribute identification information of the querier
  • the cloud server 2 is further configured to obtain a first displacement data set corresponding to the group attribute identification information from a cloud database, and perform data analysis on the first displacement data set to obtain a first analysis result;
  • the cloud server 2 is further configured to obtain a second displacement data set corresponding to the individual attribute identification information from a cloud database, and perform data analysis on the second displacement data set to obtain a second analysis result;
  • the cloud server 2 is further configured to obtain health status information corresponding to the second analysis result according to the first analysis result.
  • the cloud server 2 is further configured to determine health suggestion information according to the health condition information, and send the health suggestion information to the client;
  • the client 1 is further configured to receive the health suggestion information.
  • the system provided in this embodiment may be used to perform the method in the embodiment shown in FIG. 1 or FIG. 2, and the basic principles and technical effects thereof are similar, and details are not described herein again.
  • the foregoing program may be stored in a computer readable storage medium, and the program is executed when executed.
  • the foregoing steps include the steps of the foregoing method embodiments; and the foregoing storage medium includes: a medium that can store program codes, such as a ROM, a RAM, a magnetic disk, or an optical disk.

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Abstract

本发明提供一种基于弹性检测设备的健康状况分析方法及系统，该方法包括：客户端向云服务器发送健康状况分析请求，该健康状况分析请求中包括查询者的个体属性标识信息；云服务器从存储有各查询者的位移数据的云数据库中获取与健康状况分析请求对应的待分析数据，并对待分析数据进行数据分析以得到查询者的健康状况信息；客户端接收云服务器发送的查询者的健康状况信息。因此，借助于云服务器中存储的海量查询者的海量位移数据，查询者可以通过该客户端方便、及时地了解自身的身体健康状况。

Description

基于弹性检测设备的健康状况分析方法及系统 技术领域
本发明属于数据处理技术领域，尤其是涉及一种基于弹性检测设备的健康状况分析方法及系统。
背景技术
随着医学技术的日益进步以及人们生活压力的不断增大，人们的健康意识大为增强。
而现在人们获知自身健康状况的方式仍普遍为到医院进行各种检查，比如进行粘弹性介质的弹性检测，由医生根据某个人的检测数据进行分析以得出该某个人的健康状况。但是，医院中检查的方式往往不能满足人们对自身的健康状况能够实时跟踪，以及时、方便地了解自身的身体状态的需求。
发明内容
针对上述存在的问题，本发明提供一种基于弹性检测设备的健康状况分析方法及系统，用以实现个人能够通过客户端及时、方便地了解自身的健康状况的目的。
本发明实施例第一方面提供了一种基于弹性检测设备的健康状况分析方法，所述弹性检测设备包括在粘弹性介质中产生弹性切变波的激发装置，以及确定所述粘弹性介质在所述弹性切变波作用下产生的位移数据的捕获装置；所述弹性检测设备将获得的位移数据发送至云服务器中存储；所述健康状况分析方法包括：
客户端向云服务器发送健康状况分析请求，所述健康状况分析请求中包括查询者的个体属性标识信息，以使所述云服务器从云数据库中获取与所述健康状况分析请求对应的待分析数据，并对所述待分析数据进行数据分析以得到所述查询者的健康状况信息；其中，所述待分析数据 包括所述查询者通过所述弹性检测设备检测获得的粘弹性介质的所述位移数据；
所述客户端接收所述云服务器发送的所述查询者的健康状况信息。
在第一方面的第一种可能的实现方式中，所述健康状况分析请求中还包括所述查询者的群体属性标识信息；
其中，所述健康状况分析请求还用于使得所述云服务器从云数据库中获取与所述群体属性标识信息对应的第一位移数据集合，对所述第一位移数据集合进行数据分析得到第一分析结果，以及使得所述云服务器从云数据库中获取与所述个体属性标识信息对应的第二位移数据集合，对所述第二位移数据集合进行数据分析得到第二分析结果，并根据所述第一分析结果，得到与所述第二分析结果对应的健康状况信息。
根据第一方面或第一方面的第一种可能的实现方式，在第一方面的第二种可能的实现方式中，所述方法还包括：
所述客户端接收所述云服务器发送的健康建议信息，所述健康建议信息为所述云服务器根据所述健康状况信息确定的。
根据第一方面或第一方面的第一种可能的实现方式，在第一方面的第三种可能的实现方式中，所述群体属性标识信息包括以下标识中的至少一种标识：待查询病症标识、所属年龄段标识、性别标识。
本发明实施例第二方面提供了另一种基于弹性检测设备的健康状况分析方法，所述弹性检测设备包括在粘弹性介质中产生弹性切变波的激发装置，以及确定所述粘弹性介质在所述弹性切变波作用下产生的位移数据的捕获装置；所述弹性检测设备将获得的位移数据发送至云服务器中存储；所述健康状况分析方法包括：
云服务器接收客户端发送的健康状况分析请求，所述健康状况分析请求中包括查询者的个体属性标识信息；
所述云服务器从云数据库中获取与所述健康状况分析请求对应的待分析数据，并对所述待分析数据进行数据分析以得到所述查询者的健康状况信息，其中，所述待分析数据包括所述查询者通过所述弹性检测设备检测获得的粘弹性介质的所述位移数据；
所述云服务器将所述查询者的健康状况信息发送给所述客户端。
在第二方面的第一种可能的实现方式中，所述健康状况分析请求中还包括所述查询者的群体属性标识信息；
所述云服务器从云数据库中获取与所述健康状况分析请求对应的待分析数据，并对所述待分析数据进行数据分析以得到所述查询者的健康状况信息，包括：
所述云服务器从云数据库中获取与所述群体属性标识信息对应的第一位移数据集合，对所述第一位移数据集合进行数据分析得到第一分析结果；
所述云服务器从云数据库中获取与所述个体属性标识信息对应的第二位移数据集合，对所述第二位移数据集合进行数据分析得到第二分析结果；
所述云服务器根据所述第一分析结果，得到与所述第二分析结果对应的健康状况信息。
根据第二方面或第二方面的第一种可能的实现方式，在第二方面的第二种可能的实现方式中，所述方法还包括：
所述云服务器根据所述健康状况信息确定健康建议信息；
所述云服务器将所述健康建议信息发送给所述客户端。
根据第二方面或第二方面的第一种可能的实现方式，在第二方面的第三种可能的实现方式中，所述群体属性标识信息包括以下标识中的至少一种标识：待查询病症标识、所属年龄段标识、性别标识。
本发明实施例第三方面提供了一种基于弹性检测设备的健康状况分析系统，所述弹性检测设备包括在粘弹性介质中产生弹性切变波的激发装置，以及确定所述粘弹性介质在所述弹性切变波作用下产生的位移数据的捕获装置；所述弹性检测设备将获得的位移数据发送至云服务器中存储；所述系统包括：客户端和云服务器；
所述客户端用于向所述云服务器发送健康状况分析请求，所述健康状况分析请求中包括查询者的个体属性标识信息；
所述云服务器用于接收客户端发送的健康状况分析请求，并从云数据库中获取与所述健康状况分析请求对应的待分析数据，对所述待分析数据进行数据分析以得到所述查询者的健康状况信息，其中，所述待分 析数据包括所述查询者通过所述弹性检测设备检测获得的粘弹性介质的所述位移数据；
所述云服务器还用于将所述查询者的健康状况信息发送给所述客户端。
在第三方面的第一种可能的实现方式中，所述健康状况分析请求中还包括所述查询者的群体属性标识信息；
所述云服务器还用于从云数据库中获取与所述群体属性标识信息对应的第一位移数据集合，对所述第一位移数据集合进行数据分析得到第一分析结果；
所述云服务器还用于从云数据库中获取与所述个体属性标识信息对应的第二位移数据集合，对所述第二位移数据集合进行数据分析得到第二分析结果；
所述云服务器还用于根据所述第一分析结果，得到与所述第二分析结果对应的健康状况信息。
根据第三方面或第三方面的第一种可能的实现方式，在第三方面的第二种可能的实现方式中，所述云服务器还用于根据所述健康状况信息确定健康建议信息，并将所述健康建议信息发送给所述客户端；
所述客户端还用于接收所述健康建议信息。
本发明提供的基于弹性检测设备的健康状况分析方法及系统，各个弹性检测设备将检测获得的每个人的位移数据进行云端存储。从而查询者可以通过其终端设备中设置的客户端来向云服务器发送健康状况分析请求，云服务器能够从存储有各查询者的位移数据的云数据库中获取与该健康状况分析请求中查询者的个体属性信息对应的待分析数据，并对待分析数据进行数据分析以得到查询者的健康状况信息，比如查询者的器官弹性变化趋势或者该查询者得某种病的可能性等等。因此，借助于云服务器中存储的海量数据，查询者可以通过该客户端方便、及时地了解自身的身体健康状况。
附图说明
图1为本发明基于弹性检测设备的健康状况分析方法实施例一的流程 图；
图2为本发明基于弹性检测设备的健康状况分析方法实施例二的流程图；
图3为本发明基于弹性检测设备的健康状况系统实施例的结构示意图。
具体实施方式
为使本发明实施例的目的、技术方案和优点更加清楚，下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其它实施例，都属于本发明保护的范围。
图1为本发明基于弹性检测设备的健康状况分析方法实施例一的流程图，本实施例中，弹性检测设备对人体进行弹性检测获得人体的位移数据，该位移数据为弹性检测设备通过对检测者的粘弹性介质进行弹性检测获得的，每个弹性检测设备将获得的位移数据发送至云服务器中存储。该弹性检测设备包括在检测者的粘弹性介质中产生弹性切变波的激发装置；确定所述粘弹性介质在所述弹性切变波作用下产生的位移数据的捕获装置。其中，该激发装置和捕获装置的工作原理简单来说为，在诸如肝脏等粘弹性器官介质的表面，通过激发装置向粘弹性介质激发切变波即相当于产生振动信号，粘弹性介质在该振动信号作用下振动，进而捕获装置可以向该粘弹性介质发送超声波信号，根据弹性力学原理，该粘弹性介质会产生一个回波响应。由于不同状态下比如正常状态或病理状态下，该粘弹性器官介质的弹性应力或弹性应变不同，捕获装置根据受压前后回波信号计算获得该粘弹性介质的位移数据。该位移数据反映了粘弹性器官的弹性特征，是人体健康状况的重要参考。本实施例中，不同检测者可能在不同时间会使用不同的弹性检测设备进行检测，每个弹性检测设备在获得检测者的位移数据之后，都上传至云服务器中进行云端存储。如图1所示，本实施中的所述方法包括：
步骤101、客户端向云服务器发送健康状况分析请求，所述健康状况分析请求中包括查询者的个体属性标识信息，以使所述云服务器从云数 据库中获取与所述健康状况分析请求对应的待分析数据，并对所述待分析数据进行数据分析以得到所述查询者的健康状况信息；其中，所述待分析数据包括所述查询者通过各弹性检测设备检测获得的粘弹性介质的位移数据；
步骤102、客户端接收所述云服务器发送的所述查询者的健康状况信息。
本实施例中所述客户端设置在用户终端中，其中，用户终端是指需要查询获得自身健康状况的查询者的终端设备，比如智能手机、笔记本电脑、平板电脑等，而且，该客户端比如可以是APP形式、Web网页形式。客户端所属的用户终端设备与云服务器间的连接方式比如可以是有线连接方式，也可以是诸如WLAN、3G、4G、GRPS等无线网络连接方式，不做具体限制。
本实施例中，在云服务器中存储有各个查询者在不同时间、地点进行肝脏等粘弹性器官介质的弹性检测而获得的位移数据。而且，这些位移数据中比如包含有检测者的诸如姓名、年龄、身份证号、联系方式等身份信息，以及检测获得的位移值，还可以包括比如进行检测的弹性检测设备的标识信息、该弹性检测设备所在的医院信息、操作该弹性检测设备的医生信息等等。因此，本实施例中，借助于云服务器中的云数据库中存储的海量用户的海量位移数据，来实现查询者自身健康状况的跟踪，以便查询者能够及时、方便地了解自身的身体健康状况。
具体来说，查询者在需要查询获知自身健康状况的时候，可以通过客户端向云服务器发送健康状况分析请求，其中，该健康状况分析请求中包含有该查询者的个体属性标识信息，该个体属性标识用于唯一标识该查询者，比如可以是该查询者的身份证号码、姓名和联系方式等。当客户端为Web网页形式时，查询者比如可以通过在页面中的输入提示框内按照提示输入相应的个体属性标识。从而当云服务器接收到客户端发送的携带有查询者个体属性标识信息的健康状况分析请求时，从自身的云数据库中查询获得与该个体属性标识信息对应的待分析数据，其中，该待分析数据包括该查询者通过各弹性检测设备检测获得的粘弹性介质的位移数据。
该查询者的待分析数据是该查询者在一段时间内进行过的多次弹性检测获得的位移数据的集合，云服务器对该位移数据集合进行分析得到分析结果。其中，云服务器对该位移数据集合进行的分析比如可以是分析该查询者的位移值的走势图，即各次位移值随时间变化的趋势图；再比如，云服务器对该位移数据集合进行的分析还可以是统计该查询者的所有位移数据中在一定时间间隔内超过一定阈值的次数以及对应的位移值。值得说明的是，云服务器对待分析数据进行比如上述分析所得到的分析结果即可以作为该查询者的一种健康状况信息，从而云服务器将该分析结果发送给客户端，以使查询者能够获得其自身的健康状况信息。
本实施例中，由于各个弹性检测设备将检测获得的每个人的位移数据进行云端存储，从而查询者可以通过其终端设备中设置的客户端来向云服务器发送健康状况分析请求，云服务器能够从存储有各查询者的位移数据的云数据库中获取与该健康状况分析请求中查询者的个体属性信息对应的待分析数据，并对待分析数据进行数据分析以得到查询者的健康状况信息，比如查询者的器官弹性变化趋势或者该查询者得某种病的可能性等等。因此，借助于云服务器中存储的海量数据，查询者可以通过该客户端方便、及时地了解自身的身体健康状况。
进一步地，在上述实施例的基础上，为了使得云服务器分析得到的查询者的健康状况信息更为准确，还需考虑查询者的群体属性信息对健康状况分析结果的影响。简单来说，比如由同样的一组位移数据得到的走势图，如果该组位移数据对应的是一个儿童的检测数据，该走势图反映出的该儿童的健康状况可能是该儿童的健康状况良好；而如果该组位移数据对应的是一位老人的检测数据，该走势图反映出的该老人的健康状况可能是健康状况不佳。因此，需考虑查询者的群体属性信息对健康状况分析结果的影响。
具体来说，客户端发送给云服务器的健康状况分析请求中除了查询者的个体属性标识信息外，还包括该查询者的群体属性标识信息。其中，该群体属性标识信息包括以下标识中的至少一种标识：待查询病症标识、所属年龄段标识、性别标识。其中，年龄段标识比如可以是预先划定的四个年龄段：儿童、青少年、中青年、老人，每个年龄段对应不 同的年龄区间。病症标识比如可以是肝脏病症标识，例如肝硬化、脂肪肝等。
具体来说，当云服务器接收到客户端发送的携带有查询者个体属性标识信息和群体属性标识信息的健康状况分析请求后，云服务器一方面从云数据库中获取与该群体属性标识信息对应的第一位移数据集合，并对第一位移数据集合进行数据分析得到第一分析结果；另一方面，云服务器还从云数据库中获取与个体属性标识信息对应的第二位移数据集合，对第二位移数据集合进行数据分析得到第二分析结果。根据前述分析过程的说明，此处不再重复说明云服务器对第一位移数据集合和第二位移数据集合的分析过程。
其中，当群体属性标识信息为某病症标识时，此时，该第一位移数据集合为检测过该类病症的所有人的满足一定要求的位移数据。值得说明的是，在本实施例中以弹性检测为例的情况下，上述病症尤其是指与弹性检测结果有关联的病症，比如上述举例的脂肪肝、肝硬化等，从而，与该病症对应的数据集合中包括的位移数据需要满足与该病症对应的要求，比如A病症时，弹性位移一般在a1-a2的取值区间内；B病症时，弹性位移一般在b1-b2的取值区间内。
值得说明的是，在群体属性标识信息比如为某病症标识和某年龄段标识的情况下，第一分析结果可以是处于该年龄段中的人群中，该病症对应的位移数据的整体走势图；相应的，第二分析结果可以是该查询者的该病症的位移数据的走势图。其中，可以理解的是，该查询者的年龄是位于群体属性标识中的年龄段范围内的。
云服务器在分析得到上述第一分析结果和第二分析结果后，根据第一分析结果，得到与第二分析结果对应的健康状况信息，即以第一分析结果为参照，来确定第二分析结果所反映的健康状况。具体来说，第一分析结果表征的是查询者所归属的某一类人群和/或某一类病症的分析结果，以该群体的分析结果为参照，能够更为准确地评估出该查询者个人的分析结果所表征的该查询者的健康状况。举例来说，比如该查询者个人的位移数据的分析结果表示该查询者的所有位移值位于A-B这个区间内，相应的，对应的群体比如处于某年龄段的人群的位移数据分析结果 表征该年龄段的人，其位移值位于C-D区间，而A-B区间处于C-D区间内靠近中间区域的部分，则云服务器参照群体的分析结果，确定查询者个体的健康状况为良好，从而将该健康状况信息反馈给客户端。值得说明的是，本实施例中，查询者健康状况信息比如只是表征查询者罹患某种病症的可能性高低。
进一步地，云服务器在评估确定出查询者的健康状况信息后，还可以根据该健康状况来为查询者推送相应的健康建议信息，比如健康管理建议以及其他的公益信息等。相应的，上述步骤102中，客户端除了接收云服务器发送的查询者的健康状况信息，还可以接收云服务器发送的健康建议信息。举例来说，比如健康状况信息表征该查询者的肝脏弹性不佳，则云服务器推送的健康建议信息比如可以是饮食、运动策略建议。值得说明的是，云服务器的推送服务是可以定制的，即如果客户端预先定制了云服务器的健康建议推送服务，则云服务器在进行健康状况分析之后，将相应的健康建议推送给客户端。
图2为本发明基于弹性检测设备的健康状况分析方法实施例二的流程图，如图2所示，该方法包括：
步骤201、云服务器接收客户端发送的健康状况分析请求，所述健康状况分析请求中包括查询者的个体属性标识信息；
步骤202、云服务器从云数据库中获取与所述健康状况分析请求对应的待分析数据，并对所述待分析数据进行数据分析以得到所述查询者的健康状况信息，其中，所述待分析数据包括所述查询者通过弹性检测设备检测获得的粘弹性介质的位移数据；
步骤203、云服务器将所述查询者的健康状况信息发送给所述客户端。
本实施例中，位移数据的获取方式以及弹性检测设备的组成与图1所示实施例中一致，不再赘述。
在云服务器中存储有各个查询者在不同时间、地点进行肝脏等粘弹性器官介质的弹性检测而获得的位移数据。而且，这些位移数据中比如包含有检测者的诸如姓名、年龄、身份证号、联系方式等身份信息，以及检测获得的位移值，还可以包括比如进行检测的弹性检测设备的标识 信息、该弹性检测设备所在的医院信息、操作该弹性检测设备的医生信息等等。具体来说，具体来说，云服务器对位移数据的存储，比如可以是进行分类存储的，比如按照医院或地区的不同分别建立不同的数据库或者在同一数据库中划定不同的存储空间；也可以按照某一类病症的标识进行分类存储，并且，在存储的过程中将同一检测者的同一病症的位移数据进行集中存储，从而，能够提高存储效率的同时，便于后续查询数据的方便。当然，也可以按照时间先后顺序集中存储。
查询者在需要查询获知自身健康状况的时候，可以通过客户端向云服务器发送包含有该查询者的个体属性标识信息的健康状况分析请求。云服务器接收到该健康状况分析请求时，从自身的云数据库中查询获得与该个体属性标识信息对应的待分析数据，即该查询者的所有位移数据的集合。
云服务器对该位移数据集合进行分析得到分析结果。其中，云服务器对该位移数据集合进行的分析比如可以是分析该查询者的位移值的走势图，即各次位移值的随时间变化的趋势图。值得说明的是，云服务器对待分析数据进行比如上述分析所得到的分析结果即可以作为该查询者的一种健康状况信息，从而云服务器将该分析结果发送给客户端，以使查询者能够获得其自身的健康状况信息。
进一步地，在上述实施例的基础上，为了使得云服务器分析得到的查询者的健康状况信息更为准确，还需考虑查询者的群体属性信息对健康状况分析结果的影响。具体来说，客户端发送给云服务器的健康状况分析请求中除了查询者的个体属性标识信息外，还包括该查询者的群体属性标识信息。其中，该群体属性标识信息包括以下标识中的至少一种标识：待查询病症标识、所属年龄段标识、性别标识。其中，上述各标识信息的含义在图1所示实施例中有详细举例描述，不再赘述。
当云服务器接收到客户端发送的携带有查询者个体属性标识信息和群体属性标识信息的健康状况分析请求后，云服务器一方面从云数据库中获取与该群体属性标识信息对应的第一位移数据集合，并对第一位移数据集合进行数据分析得到第一分析结果；另一方面，云服务器还从云数据库中获取与个体属性标识信息对应的第二位移数据集合，对第二位 移数据集合进行数据分析得到第二分析结果。根据前述分析过程的说明，此处不再重复说明云服务器对第一位移数据集合和第二位移数据集合的分析过程。其中，在群体属性标识信息比如为某病症标识和某年龄段标识的情况下，第一分析结果可以是处于该年龄段中的人群中，该病症对应的位移数据的整体走势图；相应的，第二分析结果可以是该查询者的该病症的位移数据的走势图。其中，可以理解的是，该查询者的年龄是位于群体属性标识中的年龄段范围内的。
云服务器在分析得到上述第一分析结果和第二分析结果后，根据第一分析结果，得到与第二分析结果对应的健康状况信息，即以第一分析结果为参照，来确定第二分析结果所反映的健康状况。具体来说，第一分析结果表征的是查询者所归属的某一类人群和/或某一类病症的分析结果，以该群体的分析结果为参照，能够更为准确地评估出该查询者个人的分析结果所表征的该查询者的健康状况。举例来说，比如该查询者个人的位移数据的分析结果表示该查询者的所有位移值位于A-B这个区间内，相应的，对应的群体比如处于某年龄段的人群的位移数据分析结果表征该年龄段的人，其位移值位于C-D区间，而A-B区间处于C-D区间内靠近中间区域的部分，则云服务器参照群体的分析结果，确定查询者个体的健康状况为良好，从而将该健康状况信息反馈给客户端。值得说明的是，本实施例中，查询者健康状况信息比如只是表征查询者罹患某种病症的可能性高低。
进一步地，云服务器在评估确定出查询者的健康状况信息后，还可以根据该健康状况来为查询者推送相应的健康建议信息，比如健康管理建议以及其他的公益信息等。相应的，上述步骤203中，云服务器除了将查询者的健康状况信息发送给客户端外，还将健康建议信息发送给所述客户端。
本实施例中，查询者通过其终端设备中设置的客户端来向云服务器发送健康状况分析请求，从而云服务器能够从存储有各查询者的位移数据的云数据库中获取与该健康状况分析请求中的查询者的个体属性信息对应的待分析位移数据集合，并对待分析位移数据集合进行数据分析以得到查询者的健康状况信息，比如查询者的器官弹性变化趋势或者该查 询者得某种病的可能性等等。因此，借助于云服务器中存储的海量查询者的海量检测数据，查询者可以通过该客户端方便、及时地了解自身的全面身体健康状况。
图3为本发明基于弹性检测设备的健康状况系统实施例的结构示意图，如图3所示，该系统包括：客户端1和云服务器2；
所述客户端1用于向所述云服务器发送健康状况分析请求，所述健康状况分析请求中包括查询者的个体属性标识信息；
所述云服务器2用于接收客户端发送的健康状况分析请求，并从云数据库中获取与所述健康状况分析请求对应的待分析数据，对所述待分析数据进行数据分析以得到所述查询者的健康状况信息，其中，所述待分析数据包括所述查询者通过弹性检测设备检测获得的粘弹性介质的位移数据；
所述云服务器2还用于将所述查询者的健康状况信息发送给所述客户端。
其中，弹性检测设备包括在粘弹性介质中产生弹性切变波的激发装置，以及确定所述粘弹性介质在所述弹性切变波作用下产生的位移数据的捕获装置。并且，弹性检测设备将获得的位移数据发送至云服务器中存储。
进一步地，所述健康状况分析请求中还包括所述查询者的群体属性标识信息；
所述云服务器2还用于从云数据库中获取与所述群体属性标识信息对应的第一位移数据集合，对所述第一位移数据集合进行数据分析得到第一分析结果；
所述云服务器2还用于从云数据库中获取与所述个体属性标识信息对应的第二位移数据集合，对所述第二位移数据集合进行数据分析得到第二分析结果；
所述云服务器2还用于根据所述第一分析结果，得到与所述第二分析结果对应的健康状况信息。
进一步地，所述云服务器2还用于根据所述健康状况信息确定健康建议信息，并将所述健康建议信息发送给所述客户端；
所述客户端1还用于接收所述健康建议信息。
本实施例提供的所述系统可以用于执行如图1或图2所示实施例的方法，其基本原理和技术效果与之类似，不再赘述。
本领域普通技术人员可以理解：实现上述方法实施例的全部或部分步骤可以通过程序指令相关的硬件来完成，前述的程序可以存储于一计算机可读取存储介质中，该程序在执行时，执行包括上述方法实施例的步骤；而前述的存储介质包括：ROM、RAM、磁碟或者光盘等各种可以存储程序代码的介质。
最后应说明的是：以上各实施例仅用以说明本发明的技术方案，而非对其限制；尽管参照前述各实施例对本发明进行了详细的说明，本领域的普通技术人员应当理解：其依然可以对前述各实施例所记载的技术方案进行修改，或者对其中部分或者全部技术特征进行等同替换；而这些修改或者替换，并不使相应技术方案的本质脱离本发明各实施例技术方案的范围。

Claims (11)

  1. 一种基于弹性检测设备的健康状况分析方法，所述弹性检测设备包括在粘弹性介质中产生弹性切变波的激发装置，以及确定所述粘弹性介质在所述弹性切变波作用下产生的位移数据的捕获装置；其特征在于，所述弹性检测设备将获得的位移数据发送至云服务器中存储；所述健康状况分析方法包括：
    客户端向云服务器发送健康状况分析请求，所述健康状况分析请求中包括查询者的个体属性标识信息，以使所述云服务器从云数据库中获取与所述健康状况分析请求对应的待分析数据，并对所述待分析数据进行数据分析以得到所述查询者的健康状况信息；其中，所述待分析数据包括所述查询者通过所述弹性检测设备检测获得的粘弹性介质的所述位移数据；
    所述客户端接收所述云服务器发送的所述查询者的健康状况信息。
  2. 根据权利要求1所述的方法，其特征在于，所述健康状况分析请求中还包括所述查询者的群体属性标识信息；
    其中，所述健康状况分析请求还用于使得所述云服务器从云数据库中获取与所述群体属性标识信息对应的第一位移数据集合，对所述第一位移数据集合进行数据分析得到第一分析结果，以及使得所述云服务器从云数据库中获取与所述个体属性标识信息对应的第二位移数据集合，对所述第二位移数据集合进行数据分析得到第二分析结果，并根据所述第一分析结果，得到与所述第二分析结果对应的健康状况信息。
  3. 根据权利要求1或2所述的方法，其特征在于，所述方法还包括：
    所述客户端接收所述云服务器发送的健康建议信息，所述健康建议信息为所述云服务器根据所述健康状况信息确定的。
  4. 根据权利要求1或2所述的方法，其特征在于，所述群体属性标识信息包括以下标识中的至少一种标识：待查询病症标识、所属年龄段标识、性别标识。
  5. 一种基于弹性检测设备的健康状况分析方法，所述弹性检测设备包括在粘弹性介质中产生弹性切变波的激发装置，以及确定所述粘弹性 介质在所述弹性切变波作用下产生的位移数据的捕获装置；其特征在于，所述弹性检测设备将获得的位移数据发送至云服务器中存储；所述健康状况分析方法包括：
    云服务器接收客户端发送的健康状况分析请求，所述健康状况分析请求中包括查询者的个体属性标识信息；
    所述云服务器从云数据库中获取与所述健康状况分析请求对应的待分析数据，并对所述待分析数据进行数据分析以得到所述查询者的健康状况信息，其中，所述待分析数据包括所述查询者通过所述弹性检测设备检测获得的粘弹性介质的所述位移数据；
    所述云服务器将所述查询者的健康状况信息发送给所述客户端。
  6. 根据权利要求5所述的方法，其特征在于，所述健康状况分析请求中还包括所述查询者的群体属性标识信息；
    所述云服务器从云数据库中获取与所述健康状况分析请求对应的待分析数据，并对所述待分析数据进行数据分析以得到所述查询者的健康状况信息，包括：
    所述云服务器从云数据库中获取与所述群体属性标识信息对应的第一位移数据集合，对所述第一位移数据集合进行数据分析得到第一分析结果；
    所述云服务器从云数据库中获取与所述个体属性标识信息对应的第二位移数据集合，对所述第二位移数据集合进行数据分析得到第二分析结果；
    所述云服务器根据所述第一分析结果，得到与所述第二分析结果对应的健康状况信息。
  7. 根据权利要求5或6所述的方法，其特征在于，所述方法还包括：
    所述云服务器根据所述健康状况信息确定健康建议信息；
    所述云服务器将所述健康建议信息发送给所述客户端。
  8. 根据权利要求5或6所述的方法，其特征在于，所述群体属性标识信息包括以下标识中的至少一种标识：待查询病症标识、所属年龄段标识、性别标识。
  9. 一种基于弹性检测设备的健康状况分析系统，所述弹性检测设备包括在粘弹性介质中产生弹性切变波的激发装置，以及确定所述粘弹性介质在所述弹性切变波作用下产生的位移数据的捕获装置；其特征在于，所述弹性检测设备将获得的位移数据发送至云服务器中存储；所述系统包括：客户端和云服务器；
    所述客户端用于向所述云服务器发送健康状况分析请求，所述健康状况分析请求中包括查询者的个体属性标识信息；
    所述云服务器用于接收客户端发送的健康状况分析请求，并从云数据库中获取与所述健康状况分析请求对应的待分析数据，对所述待分析数据进行数据分析以得到所述查询者的健康状况信息，其中，所述待分析数据包括所述查询者通过所述弹性检测设备检测获得的粘弹性介质的所述位移数据；
    所述云服务器还用于将所述查询者的健康状况信息发送给所述客户端。
  10. 根据权利要求9所述的系统，其特征在于，所述健康状况分析请求中还包括所述查询者的群体属性标识信息；
    所述云服务器还用于从云数据库中获取与所述群体属性标识信息对应的第一位移数据集合，对所述第一位移数据集合进行数据分析得到第一分析结果；
    所述云服务器还用于从云数据库中获取与所述个体属性标识信息对应的第二位移数据集合，对所述第二位移数据集合进行数据分析得到第二分析结果；
    所述云服务器还用于根据所述第一分析结果，得到与所述第二分析结果对应的健康状况信息。
  11. 根据权利要求9或10所述的系统，其特征在于，所述云服务器还用于根据所述健康状况信息确定健康建议信息，并将所述健康建议信息发送给所述客户端；
    所述客户端还用于接收所述健康建议信息。
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