CN106296780A - A kind of body temperature early warning 3D model and using method thereof - Google Patents
A kind of body temperature early warning 3D model and using method thereof Download PDFInfo
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- CN106296780A CN106296780A CN201510260995.XA CN201510260995A CN106296780A CN 106296780 A CN106296780 A CN 106296780A CN 201510260995 A CN201510260995 A CN 201510260995A CN 106296780 A CN106296780 A CN 106296780A
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Abstract
The present invention provides a kind of body temperature early warning 3D model using method, including: obtain a two dimension temperature curve；Described two dimension temperature curve is carried out denoising, it is thus achieved that the two-dimentional temperature curve after denoising；It is fitted the two-dimentional temperature curve after described denoising obtaining three-dimensional body temperature curved surface；Described three-dimensional body temperature curved surface is compared with background data base standard three-dimensional body temperature curved surface；Judge that according to described comparison result the variation tendency of body temperature is the most normal.By setting up body temperature early warning 3D model, the present invention may determine that the variation tendency of body temperature is the most normal.
Description
Technical field
The present invention relates to technical field of medical instruments, particularly to body temperature early warning 3D model using method.
Background technology
Two dimension (2D) is content in one plane.Two dimension i.e. left and right, former and later two directions, do not exist
Up and down.Content on a sheet of paper just can regard two dimension, the most only area as, does not has volume.Two dimension is empty
Between refer to only empty by two planes that key element is formed of length and width (by X-axis and Y-axis in geometry)
Between, only extend extension to place plane.
Three-dimensional (3D) refers to add again the space system that a direction vector is constituted in planar system.Three
Dimension is made up of a peacekeeping two dimension, and two dimension only exists the staggered, by two peacekeeping one of both direction
Dimension is superimposed together and has just obtained three-dimensional.Three-dimensional is i.e. three axles of coordinate axes, i.e. X-axis, Y-axis and Z axis,
Wherein X represents space, left and right, and Y represents that upper and lower space, Z represent space, left and right, material is thus formed people's
Visual stereoscopic sense.The solid space that three dimensions is made up of length, width and three key elements of height.
In prior art, measurement body temperature instrument, after recording body temperature, is usually formed a two-dimension temperature curve,
It is analyzed according to this temperature curve subsequently, but owing to being two-dimension temperature curve, is a planar graph,
Therefore the Temperature changing trend of the synchronization of a period of time cannot be judged.
Summary of the invention
It is an object of the invention to provide a kind of body temperature early warning 3D model and using method thereof, to solve existing skill
Art cannot judge the most normal problem of Temperature changing trend.
For solving above-mentioned technical problem, the present invention provides a kind of body temperature early warning 3D model, including:
Acquisition module, for obtaining a two dimension temperature curve；
Denoising module, for carrying out denoising to described two dimension temperature curve, it is thus achieved that the two-dimentional body temperature after denoising is bent
Line；
Fitting module, is used for being fitted the two-dimentional temperature curve after described denoising obtaining three-dimensional body temperature curved surface；
Comparing module, for carrying out described three-dimensional body temperature curved surface with background data base standard three-dimensional body temperature curved surface
Comparison
According to described comparison result, judge module, for judging that the variation tendency of body temperature is the most normal.
Further, in described body temperature early warning 3D model, by bent for described two dimension body temperature in denoising module
Line carries out denoising as entirety to this two dimension temperature curve.
Further, in described body temperature early warning 3D model, described denoising module includes:
Denoising segmentation module, for by the temperature curve segmentation of described two dimension；
Sub-denoising module, for carrying out denoising to the two-dimentional temperature curve after segmentation；
Module is integrated in denoising, for the two-dimentional temperature curve after denoising is integrated into complete two-dimentional temperature curve.
Further, in described body temperature early warning 3D model, described fitting module includes:
Matching segmentation module, for carrying out segmentation by date by the complete two-dimentional temperature curve after denoising；
Matching order module, for being arranged by date by the two-dimensional curve after segmentation, is built into the three-dimensional of disconnection
Temperature curve；
Matching builds module, is fitted for the three-dimensional temperature curve that will be switched off, and is built into continuous print three-dimensional
Body temperature curved surface.
Further, in described body temperature early warning 3D model, described background data base standard three-dimensional body temperature is bent
Face includes the normal class of Temperature changing trend and the abnormal class of Temperature changing trend, and described Temperature changing trend is normal
Class and the abnormal class of Temperature changing trend include multiple three-dimensional body temperature curved surface respectively.
Accordingly, the present invention also provides for a kind of body temperature early warning 3D model using method, including:
Obtain a two dimension temperature curve；
Described two dimension temperature curve is carried out denoising, it is thus achieved that the two-dimentional temperature curve after denoising；
It is fitted the two-dimentional temperature curve after described denoising obtaining three-dimensional body temperature curved surface；
Described three-dimensional body temperature curved surface is compared with background data base standard three-dimensional body temperature curved surface；
Judge that according to described comparison result the variation tendency of body temperature is the most normal.
Further, in described body temperature early warning 3D model using method, to described two dimension temperature curve
Carry out in the step of denoising, described two dimension temperature curve is carried out denoising as entirety to this two dimension temperature curve.
Further, in described body temperature early warning 3D model using method, described two dimension temperature curve is entered
Row denoising, it is thus achieved that the step of the two-dimentional temperature curve after denoising includes:
By the temperature curve segmentation of described two dimension；
Two-dimentional temperature curve after segmentation is carried out denoising；
Two-dimentional temperature curve after denoising is integrated into complete two-dimentional temperature curve.
Further, in described body temperature early warning 3D model using method, to the two-dimentional body after described denoising
Temperature curve is fitted obtaining the step of three-dimensional body temperature curved surface and includes:
Complete two-dimentional temperature curve after denoising is carried out segmentation by date；
Two-dimensional curve after segmentation is arranged by date, is built into the three-dimensional temperature curve of disconnection；
The three-dimensional temperature curve that will be switched off is fitted, and is built into continuous print three-dimensional body temperature curved surface.
Further, in described body temperature early warning 3D model using method, described back-end data library standard three
Dimension body temperature curved surface includes the normal class of Temperature changing trend and the abnormal class of Temperature changing trend, described Temperature changing
The normal class of trend and the abnormal class of Temperature changing trend include multiple three-dimensional body temperature curved surface respectively.
The body temperature early warning 3D model of present invention offer and using method thereof, have the advantages that the present invention
The Temperature changing trend of synchronization that may determine that a period of time by setting up body temperature early warning 3D model is
No normally.
Accompanying drawing explanation
Fig. 1 is the body temperature early warning 3D model structure figure of the embodiment of the present invention；
Fig. 2 is the body temperature early warning 3D model using method flow chart of the embodiment of the present invention；
Fig. 3 is the two-dimentional temperature curve schematic diagram of the embodiment of the present invention；
Fig. 4 is the three-dimensional body temperature curved surface schematic diagram of the embodiment of the present invention.
Detailed description of the invention
The body temperature early warning 3D model present invention proposed below in conjunction with the drawings and specific embodiments and user thereof
Method is described in further detail.According to following explanation and claims, advantages and features of the invention will more
Clear.It should be noted that, accompanying drawing all uses the form simplified very much and all uses non-ratio accurately, only uses
To facilitate, to aid in illustrating lucidly the purpose of the embodiment of the present invention.
Refer to the body temperature early warning 3D model structure figure that Fig. 1, Fig. 1 are the embodiment of the present invention.As it is shown in figure 1,
The present invention provides a kind of body temperature early warning 3D model, including: acquisition module 11, denoising module 12, matching mould
Block 13, comparing module 14 and judge module 15；Wherein said denoising module 12 also include denoising segmentation module,
Module is integrated in sub-denoising module and denoising；Described fitting module 13 also includes matching segmentation module, matching sequence
Module and matching build module.
Refer to the body temperature early warning 3D model using method flow chart that Fig. 2, Fig. 2 are the embodiment of the present invention.As
Shown in Fig. 2, the present invention provides a kind of body temperature early warning 3D model using method, specifically includes following steps:
S21: acquisition module obtains a two dimension temperature curve, as it is shown on figure 3, Fig. 3 shows a calendar month
Two-dimentional temperature curve；
S22: denoising module carries out denoising to described two dimension temperature curve, it is thus achieved that the two-dimentional temperature curve after denoising；
In this step, the present embodiment have employed two kinds of methods and two dimension temperature curve carried out denoising, but not
It is confined to both approaches.First method be using described two dimension temperature curve as entirety to this two dimension body temperature
Curve carries out denoising.Second method is to carry out denoising after the temperature curve segmentation of described two dimension, and the method is first
First denoising segmentation module is by the temperature curve segmentation of described two dimension, and the most sub-denoising module is to the two-dimentional body after segmentation
Temperature curve carries out denoising, and last denoising is integrated module and the two-dimentional temperature curve after denoising is integrated into complete two
Dimension temperature curve.
Two-dimentional temperature curve after described denoising is fitted obtaining three-dimensional body temperature curved surface by S23: fitting module；
In this step, the two-dimentional temperature curve after denoising has first been integrated into by the present embodiment matching segmentation module
Whole two-dimentional temperature curve, the two-dimensional curve after segmentation is arranged by then matching order module by date, builds
The three-dimensional temperature curve disconnected, the three-dimensional temperature curve that last matching structure module will be switched off is become to be fitted,
It is built into continuous print three-dimensional body temperature curved surface (as shown in Figure 4).
Described three-dimensional body temperature curved surface is entered by S24: comparing module 14 with background data base standard three-dimensional body temperature curved surface
Row comparison；
According to described comparison result, S25: judge module judges that the variation tendency of body temperature is the most normal.
Specifically, described background data base standard three-dimensional body temperature curved surface include the normal class of Temperature changing trend and
The abnormal class of Temperature changing trend, the described normal class of Temperature changing trend and the abnormal class of Temperature changing trend are divided
Do not include multiple three-dimensional body temperature curved surface.
Such as, described background data base standard three-dimensional body temperature curved surface includes the normal class of Temperature changing trend and body temperature
The abnormal class of variation tendency.The described normal class of Temperature changing trend includes A three-dimensional body temperature curved surface, B said three-dimensional body
Temperature curved surface and C three-dimensional body temperature curved surface；The described abnormal class of Temperature changing trend include D three-dimensional body temperature curved surface,
E three-dimensional body temperature curved surface, F three-dimensional body temperature curved surface and G three-dimensional body temperature curved surface.By described three-dimensional body temperature curved surface with after
Platform database standard three-dimensional body temperature curved surface is compared, if described three-dimensional body temperature curved surface and B three-dimensional body temperature curved surface
Similarity is the highest, then assert that the variation tendency of body temperature is normal；If described three-dimensional body temperature curved surface is three-dimensional with F
Body temperature curved surface similarity is the highest, then assert that the variation tendency of body temperature is abnormal.
In sum, prior art can only be by two dimension temperature curve observation one month or the body of a day 24 hours
Temperature change, and the present invention may determine that the synchronization of a period of time by setting up body temperature early warning 3D model
Temperature changing trend.
Foregoing description is only the description to present pre-ferred embodiments, not any limit to the scope of the invention
Fixed, any change that the those of ordinary skill in field of the present invention does according to the disclosure above content, modification, all belong to
Protection domain in claims.
Claims (10)
1. a body temperature early warning 3D model, it is characterised in that including:
Acquisition module, for obtaining a two dimension temperature curve；
Denoising module, for carrying out denoising to described two dimension temperature curve, it is thus achieved that the two-dimentional body temperature after denoising is bent
Line；
Fitting module, is used for being fitted the two-dimentional temperature curve after described denoising obtaining three-dimensional body temperature curved surface；
Comparing module, for carrying out described three-dimensional body temperature curved surface with background data base standard three-dimensional body temperature curved surface
Comparison
According to described comparison result, judge module, for judging that the variation tendency of body temperature is the most normal.
2. body temperature early warning 3D model as claimed in claim 1, it is characterised in that will in denoising module
Described two dimension temperature curve carries out denoising as entirety to this two dimension temperature curve.
3. body temperature early warning 3D model as claimed in claim 1, it is characterised in that described denoising module bag
Include:
Denoising segmentation module, for by the temperature curve segmentation of described two dimension；
Sub-denoising module, for carrying out denoising to the two-dimentional temperature curve after segmentation；
Module is integrated in denoising, for the two-dimentional temperature curve after denoising is integrated into complete two-dimentional temperature curve.
4. body temperature early warning 3D model as claimed in claim 1, it is characterised in that described fitting module bag
Include:
Matching segmentation module, for carrying out segmentation by date by the complete two-dimentional temperature curve after denoising；
Matching order module, for being arranged by date by the two-dimensional curve after segmentation, is built into the three-dimensional of disconnection
Temperature curve；
Matching builds module, is fitted for the three-dimensional temperature curve that will be switched off, and is built into continuous print three-dimensional
Body temperature curved surface.
5. body temperature early warning 3D model as claimed in claim 1, it is characterised in that described background data base
Standard three-dimensional body temperature curved surface includes the normal class of Temperature changing trend and the abnormal class of Temperature changing trend, described body
The temperature normal class of variation tendency and the abnormal class of Temperature changing trend include multiple three-dimensional body temperature curved surface respectively.
6. a body temperature early warning 3D model using method, it is characterised in that including:
Obtain a two dimension temperature curve；
Described two dimension temperature curve is carried out denoising, it is thus achieved that the two-dimentional temperature curve after denoising；
It is fitted the two-dimentional temperature curve after described denoising obtaining three-dimensional body temperature curved surface；
Described three-dimensional body temperature curved surface is compared with background data base standard three-dimensional body temperature curved surface；
Judge that according to described comparison result the variation tendency of body temperature is the most normal.
7. body temperature early warning 3D model using method as claimed in claim 6, it is characterised in that to institute
State two dimension temperature curve and carry out in the step of denoising, using described two dimension temperature curve as entirety to this two dimension body
Temperature curve carries out denoising.
8. body temperature early warning 3D model using method as claimed in claim 7, it is characterised in that to described
Two dimension temperature curve carries out denoising, it is thus achieved that the step of the two-dimentional temperature curve after denoising includes:
By the temperature curve segmentation of described two dimension；
Two-dimentional temperature curve after segmentation is carried out denoising；
Two-dimentional temperature curve after denoising is integrated into complete two-dimentional temperature curve.
9. body temperature early warning 3D model using method as claimed in claim 7, it is characterised in that to described
Two-dimentional temperature curve after denoising is fitted obtaining the step of three-dimensional body temperature curved surface and includes:
Complete two-dimentional temperature curve after denoising is carried out segmentation by date；
Two-dimensional curve after segmentation is arranged by date, is built into the three-dimensional temperature curve of disconnection；
The three-dimensional temperature curve that will be switched off is fitted, and is built into continuous print three-dimensional body temperature curved surface.
10. body temperature early warning 3D model using method as claimed in claim 7, it is characterised in that after described
Platform database standard three-dimensional body temperature curved surface includes that the normal class of Temperature changing trend and Temperature changing trend are abnormal
Class, the described normal class of Temperature changing trend and the abnormal class of Temperature changing trend include multiple three-dimensional body temperature respectively
Curved surface.
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| CN201510260995.XA CN106296780A (en) | 2015-05-20 | 2015-05-20 | A kind of body temperature early warning 3D model and using method thereof |
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| CN201510260995.XA CN106296780A (en) | 2015-05-20 | 2015-05-20 | A kind of body temperature early warning 3D model and using method thereof |
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111486990A (en) * | 2020-04-29 | 2020-08-04 | 广州柏颐信息科技有限公司 | Human body state monitoring method, system, device and storage medium |
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| WO2007132379A2 (en) * | 2006-05-11 | 2007-11-22 | Koninklijke Philips Electronics N.V. | A device for drug administration and/or monitoring the status of a patient |
| CN104305968A (en) * | 2014-11-14 | 2015-01-28 | 上海温尔信息科技有限公司 | Continuous body temperature monitoring corresponding-period comparing algorithm |
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Patent Citations (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| WO2007132379A2 (en) * | 2006-05-11 | 2007-11-22 | Koninklijke Philips Electronics N.V. | A device for drug administration and/or monitoring the status of a patient |
| CN104305968A (en) * | 2014-11-14 | 2015-01-28 | 上海温尔信息科技有限公司 | Continuous body temperature monitoring corresponding-period comparing algorithm |
Non-Patent Citations (1)
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN111486990A (en) * | 2020-04-29 | 2020-08-04 | 广州柏颐信息科技有限公司 | Human body state monitoring method, system, device and storage medium |
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Application publication date: 20170104 |