CN106777937A - A kind of intelligent medical comprehensive detection system - Google Patents

A kind of intelligent medical comprehensive detection system Download PDF

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Publication number
CN106777937A
CN106777937A CN201611105547.3A CN201611105547A CN106777937A CN 106777937 A CN106777937 A CN 106777937A CN 201611105547 A CN201611105547 A CN 201611105547A CN 106777937 A CN106777937 A CN 106777937A
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detection module
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不公告发明人
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Large Shenzhen Kechuang Technology Development Co Ltd
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    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/50—Information retrieval; Database structures therefor; File system structures therefor of still image data
    • G06F16/58—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually
    • G06F16/583—Retrieval characterised by using metadata, e.g. metadata not derived from the content or metadata generated manually using metadata automatically derived from the content
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/33—Querying
    • G06F16/335—Filtering based on additional data, e.g. user or group profiles
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
    • G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
    • G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
    • G06F16/35—Clustering; Classification
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06F—ELECTRIC DIGITAL DATA PROCESSING
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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
    • 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
    • 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
    • G16H40/63—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 local operation

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Abstract

The invention provides a kind of intelligent medical comprehensive detection system, including：PC terminals and intelligent comprehensive detector are constituted, and Fingerprint Identification Unit and face recognizer are integrated with the PC terminals；The intelligent comprehensive detector is made up of temperature check module, heart rate detection module, blood pressure detecting module, blood sugar test module, body weight detection module, height detection module and blood oxygen detection module, and the data that detect of temperature check module, heart rate detection module, blood pressure detecting module, blood sugar test module, body weight detection module, height detection module and blood oxygen detection module are transferred in PC terminals via bluetooth communication module and process.Beneficial effects of the present invention are：Solve product function Single-issue.

Description

A kind of intelligent medical comprehensive detection system
Technical field
The present invention relates to medical field, and in particular to a kind of intelligent medical comprehensive detection system.
Background technology
Have temperature check module on the market now, can remote monitoring, numerical monitor, wireless transmission function also has similar Intelligent blood sugar test module, electronic boby weight claims, electrocardiograph, heart rate detection module etc., but they can only all realize it is single Function, can only measure when using and obtain instant data.
The content of the invention
Regarding to the issue above, the present invention is intended to provide a kind of intelligent medical comprehensive detection system.
The purpose of the present invention is realized using following technical scheme：
There is provided a kind of intelligent medical comprehensive detection system, including：PC terminals and intelligent comprehensive detector are constituted, the PC Fingerprint Identification Unit and face recognizer are integrated with terminal；The intelligent comprehensive detector is by temperature check module, heart rate detection Module, blood pressure detecting module, blood sugar test module, body weight detection module, height detection module and blood oxygen detection module composition, and Temperature check module, heart rate detection module, blood pressure detecting module, blood sugar test module, body weight detection module, height detection module The data detected with blood oxygen detection module are transferred in PC terminals via bluetooth communication module and process.
Beneficial effects of the present invention are：Solve product function Single-issue.
Brief description of the drawings
Using accompanying drawing, the invention will be further described, but embodiment in accompanying drawing is not constituted to any limit of the invention System, for one of ordinary skill in the art, on the premise of not paying creative work, can also obtain according to the following drawings Other accompanying drawings.
Fig. 1 is structure connection diagram of the invention.
Reference：
PC terminals 1, intelligent comprehensive detector 2.
Specific embodiment
The invention will be further described with the following Examples.
Referring to Fig. 1, a kind of intelligent medical comprehensive detection system of the present embodiment, including：PC terminals 1 and intelligent comprehensive are detected Instrument 2 is constituted, and Fingerprint Identification Unit and face recognizer are integrated with the PC terminals 1；The intelligent comprehensive detector 2 is examined by body temperature Survey module, heart rate detection module, blood pressure detecting module, blood sugar test module, body weight detection module, height detection module and blood oxygen Detection module is constituted, and temperature check module, heart rate detection module, blood pressure detecting module, blood sugar test module, body weight detection mould The data that block, height detection module and blood oxygen detection module are detected are transferred in PC terminals 1 via bluetooth communication module and process.
Preferably, the query system of the PC terminals 1, the inquiry system includes that data acquisition module, data are classified Module, classification and Detection module and detection fusion module；The data acquisition module is used to gather the data for needing to be detected；Institute Data categorization module is stated for the data exported by data acquisition module to be divided into view data and text data, and to classification Data afterwards carry out filtration treatment；The classification and Detection module is used to be analyzed detection to sorted data；The detection View data and text data that Fusion Module is used for according to needed for detection demand screening.
This preferred embodiment is easy to client to realize data query.
Preferably, the PC terminals 1 are panel computer or notebook computer, and integrated bluetooth communication module, PC terminals 1 are led to Cross Ethernet and be connected to internet high in the clouds, integrated bluetooth communication module on the intelligent comprehensive detector 2.
This preferred embodiment realizes bluetooth communication between PC terminals 1 and intelligent comprehensive detector 2.
Preferably, the collection needs the data for being detected, including：
The data for being detected are needed in a, collection certain period of time, the data are carried out tentatively by the filtering rule of setting Filtration treatment, the filtering rule of the setting includes deleting comprising spcial character, promotes related special Chinese character and web page interlinkage Content data；If the time range of the certain period of time is [YB,YE], by [YB,YE] be equally divided into sequentially in time N sub- time period, the data in each sub- time period are carried out with importance degree assessment, assessment formula is defined as：
In formula, ViIt is i-th significance level of sub- time period, VTiIt is i-th significance level of sub- time period of setting Value, CiIt is i-th quantity of the data of sub- time period, C is in [YB,YE] in data quantity；B, by each importance degree according to by It is small to being ranked up greatly, according to putting in order for importance degree, data are sent to data categorization module successively.
This preferred embodiment is deleted the data that need not be detected by setting filtering rule, reduces inspection Survey the data volume of subsequent treatment；Importance degree assessment is carried out by the data to each sub- time period, and it is suitable according to the arrangement of importance degree Sequence, data are sent to data categorization module successively, follow-up module is anticipated significance level data high, are improved The speed of detection.
Preferably, it is described that sorted data are carried out with filtration treatment, including：
A, extraction text data, clustering processing is carried out to this article notebook data, forms the text data set of multiple classifications；B, meter The quantity of the data of the text data concentration of each classification is calculated, according to quantity by entering to multiple text data sets to big order less Row sequence；C, the text data set for deleting preceding 19%, remaining text data set and view data are sent to classification and Detection Module.
This preferred embodiment further carries out clustering processing to text data, filters out the text data set of negligible amounts, The data volume of subsequent detection is reduced, so as to further increase the speed of detection.
Preferably, it is described to carry out clustering processing to this article notebook data, including：
The number K that a, determination cluster, including：To this article notebook data using the first of method of equal intervals setting k-means clustering algorithms Beginning center, obtain cluster centre；Using the midpoint of adjacent cluster centre as the division points classified after cluster centre is obtained, will Each object is added in closest class, so that it is determined that the number K for clustering；This article notebook data is divided into n sample, it is right N sample carries out vectorization, and all samples similarity between any two is calculated by included angle cosine function, obtains similarity matrix SIM：SIM=[sim (ui,uj)]n×n, i, j=1 ..., n；The similarity sum of each sample and other all samples is calculated, Sum formula is：In formula,It is sample uiWith the similarity of other all samples it With sim (ui,uj) represent sample ui,ujBetween similarity, i, j=1 ..., n；B, arrange in descending orderI=1 ..., n, ifIt is u by the corresponding sample of preceding 4 values for arranging from big to smallmax,umax-1,umax-2,umax-3, it is determined according to the following equation First initial center med that clusters：
In formula, ωmax-μRepresent umax-μImportance degree weights；c、In the corresponding matrix of maximum in row vector Element carry out ascending order arrangement, it is assumed that first k-1 minimum element is SIMpq, q=1 ..., k-1, the preceding k-1 minimum of selection Element S IMpqCorresponding sample is used as the remaining k-1 initial center that clusters；D, the remaining sample of calculating gather with each initial Similarity between cluster center, remaining sample is distributed to during similarity highest clusters, and is formed the k after change and is clustered；e、 Calculate change after cluster in each sample average, as renewal after cluster center replace update before the center that clusters； If the center that clusters before f, renewal is identical with the center that clusters after updating, or object function has reached minimum value, stops updating, The object function is：Wherein, CzCluster for z-th during expression k clusters, uxIt is Z cluster in sample,It is the center for clustering for z-th.
This preferred embodiment is prevented effectively from the single contingency for taking arbitrary sampling method to be brought, and solves to text number According to the problems of when choosing k values and initializing cluster centre, cluster stability is improve when carrying out clustering processing, enter One step improves the precision that filtration treatment is carried out to text data.
Preferably, the classification and Detection module includes view data detection unit and text data detection unit；The figure As data detecting unit is detected based on semantic feature to view data, specially：Using the method for wavelet transformation to image Split, region low-level feature is extracted, structural feature matrix is reapplied Non-negative Matrix Factorization training algorithm construction language Adopted space, projects image onto the space to obtain image, semantic feature；The text data detection unit includes text data Modeling subelement, text data classification subelement, detection sub-unit, specially：
(1) text data modeling subelement, the semanteme for expressing document using the lexical item for constituting document, it is by n Document t1,t2,…,tnEvery document representation into m dimensional feature vectors v1,v2,…,vm, constitute the document-eigenmatrix of n × m：
In formula, m is the quantity of the lexical item for constituting document；
In formula, l (ti,vj) represent lexical item vjIn document tiIn shared weight, f (ti,vj) represent lexical item vjIn document tiIn The number of times of appearance, f (vj) represent lexical item vjThe number of times summation occurred in all documents；
(2) text data classification subelement, for classifying to the text document after modeling, specifically includes：
A, by the document Random Maps in text set to a two dimensional surface mesh space, one can only be projected in each grid Piece document, meanwhile, a number of ant is placed on two dimensional surface；B, every ant are random in the movement of two-dimensional grid space, One document of selection is picked up, and carries it in two-dimensional grid space random movement, and once, ant calculates its entrained text for often movement The swarm similarity of shelves or institute's document within a grid and surrounding environment, decides whether to pick up or put down the document, will be every Individual grid is used as two-dimensional grid spatial spreading value, if ant position is p, the swarm similarity of environment is defined as where it：
In formula, ti∈ p (a × a) represent document tiThe neighborhood of the length of side a × a of p, r (t in positioni,tj) represent two texts Text distance between shelves, σ represents the similarity factor, and the span of σ is [1,2],
In formula, m represents lexical item quantity in document；C, pick up and put down, if ant does not carry any document movement, So it will pick up the document relatively low with surrounding environment swarm similarity；If ant is carrying a document movement, then When ant is higher with the swarm similarity of surrounding environment in abortive haul lattice, and this document, it will put down this document, pick up Play probability Pj(ti) and put down probability Pf(ti) be defined as：
In formula, T1And T2It is constant threshold, T1=0.14, T2=0.16；D, repeatedly b and c, it is similar through after a while Property document high will be collected at the same area.
This preferred embodiment carries out classification and Detection to data, can make full use of different types of data feature, using correspondence Method detected, improve the specific aim of detection；Document is modeled, non-structured text data is converted into can The structural data of calculating, while being easy to subsequently classify document；Text data classification subelement improves detection efficiency, Detection time is saved.
Medical data testing result of the present invention is as shown in the table：
Detection mesh number Data Detection speed Data examine side accuracy rate
3 0.22s 96%
4 0.26s 94%
5 0.28s 93%
Finally it should be noted that the above embodiments are merely illustrative of the technical solutions of the present invention, rather than the present invention is protected The limitation of scope is protected, although being explained to the present invention with reference to preferred embodiment, one of ordinary skill in the art should Work as understanding, technical scheme can be modified or equivalent, without deviating from the reality of technical solution of the present invention Matter and scope.

Claims (4)

1. a kind of intelligent medical comprehensive detection system, it is characterized in that, including：PC terminals and intelligent comprehensive detector are constituted, described Fingerprint Identification Unit and face recognizer are integrated with PC terminals；The intelligent comprehensive detector is examined by temperature check module, heart rate Module, blood pressure detecting module, blood sugar test module, body weight detection module, height detection module and blood oxygen detection module composition are surveyed, And temperature check module, heart rate detection module, blood pressure detecting module, blood sugar test module, body weight detection module, height detection mould The data that block and blood oxygen detection module are detected are transferred in PC terminals via bluetooth communication module and process.
2. a kind of intelligent medical comprehensive detection system according to claim 1, it is characterized in that, the PC terminal built-ins inquiry System, the inquiry system includes data acquisition module, data categorization module, classification and Detection module and detection fusion module.
3. a kind of intelligent medical comprehensive detection system according to claim 2, it is characterized in that, the PC terminals are flat board electricity Brain or notebook computer, and integrated bluetooth communication module, PC terminals are connected to internet high in the clouds by Ethernet, and the intelligence is comprehensive Close integrated bluetooth communication module on detector.
4. a kind of intelligent medical comprehensive detection system according to claim 3, it is characterized in that, the collection needs are examined The data of survey, including：
The data for being detected are needed in a, collection certain period of time, the data are tentatively filtered by the filtering rule of setting Process, the filtering rule of the setting includes deleting comprising the interior of spcial character, the special Chinese character of popularization correlation and web page interlinkage The data of appearance；If the time range of the certain period of time is [YB,YE], by [YB,YE] n is equally divided into sequentially in time The sub- time period, the data in each sub- time period are carried out with importance degree assessment, assessment formula is defined as：
V i = V T i + C i C × 100 % , 1 ≤ i ≤ n
In formula, ViIt is i-th significance level of sub- time period, VTiIt is i-th importance value of sub- time period of setting, Ci It is i-th quantity of the data of sub- time period, C is in [YB,YE] in data quantity；B, by each importance degree according to by it is small to It is ranked up greatly, according to putting in order for importance degree, data is sent to data categorization module successively.
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