CN105740614A - Comparison assessment method and device for humiture field model based on cancer cell abnormality - Google Patents

Comparison assessment method and device for humiture field model based on cancer cell abnormality Download PDF

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CN105740614A
CN105740614A CN201610059511.XA CN201610059511A CN105740614A CN 105740614 A CN105740614 A CN 105740614A CN 201610059511 A CN201610059511 A CN 201610059511A CN 105740614 A CN105740614 A CN 105740614A
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humidity
temperature
model
sampling
similarity
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康宏
蔡皓
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SHANGHAI WEN'ER INFORMATION TECHNOLOGY Co Ltd
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SHANGHAI WEN'ER INFORMATION TECHNOLOGY Co Ltd
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Publication of CN105740614A publication Critical patent/CN105740614A/en
Priority to PCT/CN2016/107688 priority patent/WO2017128848A1/en
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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
    • 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
    • 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
    • G16H50/50—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for simulation or modelling of medical disorders

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  • Engineering & Computer Science (AREA)
  • Medical Informatics (AREA)
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  • Databases & Information Systems (AREA)
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  • Epidemiology (AREA)
  • General Health & Medical Sciences (AREA)
  • Primary Health Care (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

The invention discloses a comparison assessment method and device for a humiture field model based on cancer cell abnormality and provides a humidity state monitoring method and device, a humiture state monitoring method and device. The humidity state monitoring method comprises the steps of: determining a humidity rhythm similarity between a humidity sampling model of a monitoring object and a humidity reference model; identifying a humidity state of the monitoring object based on the humidity rhythm similarity. According to the comparison assessment method and device for the humiture field model based on cancer cell abnormality, the humidity state and/or the humiture state of any part such as female breasts and the like can be identified, thus the physical health of people can be identified.

Description

Evaluation method and device based on the abnormal humiture field model of tumor cell
Technical field
The present invention relates to physiological status monitoring field, relate more specifically to a kind of moisture condition monitoring method and device and humiture state monitoring method and device.
Background technology
Breast carcinoma examination is the one anti-cancer measure for asymptomatic women, with early discovery breast carcinoma, reaches early diagnosis and early treatment, the final purpose reducing crowd's Death Rate of Breast Cancer.The universal key factor being breast carcinoma and declining at American-European countries's mortality rate of breast carcinoma examination.In American-European countries, molybdenum target X ray (MG) inspection is main breast carcinoma screening method.But, MG checks the examination being more suited to for lard type breast lesion, and the imaging results of dense form breast lesion is poor.Additionally, be difficult to avoid that in the process that checks of MG and cause that some women produces pain, will also result in simultaneously and be screened women and accept certain radiation, excessively frequent MG checks will necessarily increase its potential side effect.
Ultrasonic (BUS) checks have easy and simple to handle, noinvasive, economic dispatch advantage.At present, BUS checks a kind of important means, the particularly women for dense form mammary gland that have become breast carcinoma examination.But, the applied research that BUS checks is still immature.
Magnetic resonance (MRI) checks and as the compensation process of breast carcinoma examination, can check the women being all negative especially for MG and BUS.Owing to soft tissue is had higher spatial resolution and temporal resolution by MRI, and not by the impact of corpus mamma compactness extent, so breast lesion can more clearly be shown.It addition, MRI checks multicenter and multifocal pathological changes sensitivity is also higher.But, the somewhat expensive that MRI checks, normally only it is proposed to be used in the examination of breast carcinoma High risk group.
Summary of the invention
After deliberation, the normal cell of human body is being converted into glucose and oxygen in the process of water and carbon dioxide and is obtaining energy, and these energy can ensure that normal cell has the temperature of a relative constancy.The tumor cell of human body is also being converted into glucose and oxygen in the process of water and carbon dioxide and is obtaining energy, and therefore tumour cell division is vigorous simultaneously can consume substantial amounts of glucose and oxygen.Additionally, tumor cell has aberrant nascent vessels more, the blood flow of these blood vessels is abundant and is not subject to autogenous control, therefore usually can lose normal daily rhythmicity.
The energy that the metabolic activity of tumor cell produces makes the temperature of tumor tissues slightly above normal structure.According to the principle of tumor cell molecule thermokinetics, necessarily have heat and spread from the tumor tissues that temperature is slightly higher until body surface towards periphery.Therefore, the position at tumor tissues place, surrounding are until body surface can form a Temperature Distribution, i.e. " temperature field ".Meanwhile, " temperature field ", in conjunction with the humidity (perspiration) near body surface, can form unique " micro climate ".
In conjunction with the studies above of inventor and for the drawbacks described above in background technology, the present invention proposes a kind of moisture condition monitoring method and device and humiture state monitoring method and device, in order to the moisture condition of the human body any part of breast identifying such as women etc and/or humiture state；And, the abnormal humiture field model that can present at body surface based on the tumor cell of the human bodies such as such as mammary gland, with reference model for reference, assessment that its intensity of anomaly is compared.
According to one embodiment of present invention, it is provided that a kind of moisture condition monitoring method, the humidity rhythm and pace of moving things similarity between humidity sampling model and the humidity reference model of monitoring object is comprised determining that；And based on humidity rhythm and pace of moving things similarity, identify the moisture condition of monitoring object.
According to another embodiment of the present invention, it is provided that a kind of moisture condition monitoring device, including: humidity similarity determining unit, it is configured to determine that the humidity rhythm and pace of moving things similarity between humidity sampling model and the humidity reference model of monitoring object；And moisture condition recognition unit, it is configured to, based on humidity rhythm and pace of moving things similarity, identify the moisture condition of monitoring object.
By the moisture condition monitoring method in above-described embodiment or device, it may be determined that the diversity factor between humidity sampling model and the humidity reference model of monitoring object, so that it is determined that the normal degree of the moisture condition of monitoring object.
According to still another embodiment of the invention, it is provided that a kind of humiture state monitoring method, the rhythm and pace of moving things similarity between temperature-humidity sampling model and the temperature-humidity reference model of monitoring object is comprised determining that；And based on rhythm and pace of moving things similarity, identify the humiture state of monitoring object.
According to one more embodiment of the present invention, it is provided that a kind of humiture state monitoring apparatus, including: rhythm and pace of moving things similarity determining unit, it is configured to determine that the rhythm and pace of moving things similarity between temperature-humidity sampling model and the temperature-humidity reference model of monitoring object；And humiture state recognition unit, it is configured to, based on rhythm and pace of moving things similarity, identify the humiture state of monitoring object.
By the humiture state monitoring method in above-described embodiment or device, may determine that the rhythm and pace of moving things diversity factor between temperature-humidity sampling model and the temperature-humidity reference model of monitoring object, so that it is determined that the normal degree of the state of the physical signs such as the humiture of monitoring object.
Accompanying drawing explanation
By reading detailed description non-limiting example made referring to accompanying drawing, the other features, objects and advantages of the present invention will become more apparent upon, and wherein, same or analogous accompanying drawing labelling represents same or analogous feature.
Fig. 1 is the structural representation of moisture condition according to an embodiment of the invention monitoring device；
Fig. 2 is the flow chart of moisture condition monitoring method according to an embodiment of the invention；
Fig. 3 is the structural representation of moisture condition monitoring device according to another embodiment of the present invention；
Fig. 4 is the structural representation of moisture condition monitoring device according to still another embodiment of the invention；
Fig. 5 is the structural representation of humiture state monitoring apparatus according to an embodiment of the invention；
Fig. 6 is the flow chart of humiture state monitoring method according to an embodiment of the invention；
Fig. 7 is temperature-humidity sampling model according to an embodiment of the invention and temperature-humidity reference model distribution schematic diagram in temperature-humidity coordinate system；
Fig. 8 is temperature-humidity sampling model according to an embodiment of the invention and temperature-humidity reference model distribution schematic diagram in temperature-humidity-time coordinate system.
Detailed description of the invention
It is described more fully with example embodiment referring now to accompanying drawing.But, example embodiment can be implemented in a variety of forms, and is not understood as limited to embodiment set forth herein；On the contrary, it is provided that these embodiments make the present invention more comprehensively and completely, and the design of example embodiment is conveyed to those skilled in the art all sidedly.In the drawings, in order to clearly, it is not necessary to be the assembly being drawn to scale in figure.Accompanying drawing labelling identical in the drawings represents same or similar structure, thus will omit their detailed description.
Additionally, described feature, structure or characteristic can be combined in one or more embodiment in any suitable manner.In the following description, it is provided that many details are thus providing fully understanding embodiments of the invention.It will be appreciated, however, by one skilled in the art that one or more without in described specific detail of technical scheme can be put into practice, or other method, constituent element, material etc. can be adopted.In other cases, known features, material or operation are not shown in detail or describe to avoid the major technique intention of the fuzzy present invention.
Compared to temperature and/or the humidity information of single time point, monitoring object more can reflect that the temperature of monitoring object and/or the physiological health degree of the humidity change rhythm and pace of moving things (rhythm) and behind thereof maybe can cause the course of disease of the disease of Temperature changing in temperature and/or the humidity information of a continuous time comprehensively, such as phase morning, noon and afternoon, etc. information.
Therefore, the method or apparatus of some embodiments of the present invention, by the humidity rhythm and pace of moving things similarity between humidity sampling model and the humidity reference model based on monitoring object, identifies the moisture condition of monitoring object.Below, in conjunction with Fig. 1 and Fig. 2, moisture condition according to an embodiment of the invention monitoring apparatus and method are described.
Fig. 1 is the structural representation of moisture condition according to an embodiment of the invention monitoring device.Fig. 2 is the flow chart of moisture condition monitoring method according to an embodiment of the invention.As it is shown in figure 1, moisture condition monitoring device 100 includes humidity similarity determining unit 102 and moisture condition recognition unit 104.Here, humidity similarity determining unit 102 is configured to determine that the humidity rhythm and pace of moving things similarity between humidity sampling model and the humidity reference model of monitoring object, i.e. perform step S102；Moisture condition recognition unit 104 is configured to the humidity rhythm and pace of moving things similarity between humidity sampling model and humidity reference model based on monitoring object, identifies the moisture condition of monitoring object, i.e. perform step S104.
Determining monitoring object, such as, appointed part in the left breast of specific women at the appointed time section, such as, before moisture condition during morning 00:00 to 03:00, moisture condition monitoring device 100 can obtain this appointed part humidity sampling model during the above-mentioned time period from Humidity Model construction unit (not shown).In certain embodiments, Humidity Model construction unit can be configured to, with humidity sensor and arbitrary appointment in the time period, the humidity of above-mentioned appointed part be sampled, to build this appointed part humidity sampling model within this appointment time period.Such as, Humidity Model construction unit can be configured to, at the appointed time in section, receive the humidity sampled value for appointed part every specific interval from humidity sensor, to build the humidity sampling model in this appointed part at the appointed time section.Those skilled in the art are it is to be understood that Humidity Model construction unit can monitor a part for device 100 as moisture condition, it is also possible to be positioned at the outside of moisture condition monitoring device 100.
In certain embodiments, humidity sampling model can be the sample sequence only including humidity sampled value, for instance { H1, H2, H3..., HN}；Humidity reference model can be the reference sequences only including humidity reference value, for instance { S1, S2, S3..., SM, wherein, M and N is positive integer.In these embodiments, owing to not accounting for time factor, such as, in two sequences element corresponding relation in time, humidity similarity determining unit 102 can determine the difference between humidity sampling model and humidity reference model roughly, thus moisture condition recognition unit 104 may recognize that the substantially moisture condition of monitoring object.
For the difference more accurately determined between humidity sampling model and humidity reference model and then the more accurate moisture condition identifying monitoring object, in certain embodiments, humidity sampling model can be that each sampled point therein is respectively provided with humidity sampled value and the sample sequence of corresponding two attributes of sampling time, for instance { (H1, t1), (H2, t2), (H3, t3) ..., (HN, tN)}；Accordingly, humidity reference model can be that each reference point therein is respectively provided with humidity reference value and the reference sequences of corresponding two attributes of reference time, for instance { (S1, T1), (S2, T2)(S3, T3) ..., (SM, TM), wherein, M and N is positive integer.It is to say, humidity sampling model can include the one or more sampled points being associated with humidity sampled value and corresponding sampling time, humidity reference model can also include the one or more reference points being associated with humidity reference value and corresponding reference time.In these embodiments, humidity similarity determining unit 102 first can find out reference time and sampling time each reference point immediate in humidity sampling model from humidity reference model, each reference point that correspondence in sequential is the strongest in other words, it is then determined that humidity sampling model and the humidity of each reference point composition found out are with reference to the humidity rhythm and pace of moving things similarity between submodel.
In certain embodiments, humidity similarity determining unit 102 may determine that the humidity sampling model dispersion relative to humidity reference model, thus the humidity rhythm and pace of moving things similarity reflected between humidity sampling model and humidity reference model.Such as, humidity similarity determining unit 102 can pass through to calculate humidity sampling model relative to the distance of humidity reference model, standard deviation, mean deviation or variance, determines the humidity sampling model dispersion relative to humidity reference model.
Wherein, standard deviation is also referred to as standard deviation or experimental standard deviation, and it can reflect the dispersion degree of a data acquisition system.When the average of two data acquisition systems is identical, their standard deviation is not necessarily the same.Assume that a data acquisition system includes numerical value X1, X2, X3..., XN, N is positive integer, and its arithmetic mean of instantaneous value is μ, and its standard deviation can be calculated by below equation:
σ = 1 N Σ i = 1 N ( x i - μ ) 2
Differ greatly between most of numerical value and its arithmetic mean of instantaneous value or expected value in one bigger standard deviation representative data set；Most of numerical value in one less standard deviation representative data set is closer to its arithmetic mean of instantaneous value or expected value.In certain embodiments, it is possible to by the i-th humidity sampled value X in certain detected part humidity sampling modeli(i=1 ..., N) it is considered as the x in above formulai, by the humidity reference model of corresponding position on the sampling time with XiCorresponding element numerical value as expected value μ, or by humidity reference model on the sampling time with XiThe element numerical value being close or the arithmetic mean of instantaneous value of several element numerical value, as the expected value μ in above-mentioned formula, calculate the humidity sampling model standard deviation relative to humidity reference model.It is to say, the humidity sampled value Xi at different sampling stages point place can corresponding different expected value μ.Thus, the moisture condition monitoring method of some embodiments of the present invention, if being applied to the dispersion degree of humidity information by breast part and assessing the health condition of breast or suffer from the risk of certain disease, is then considered as a kind of disease, such as breast carcinoma, diagnosis or the method for examination.
Mean deviation and variance also are able to the dispersion degree of one data acquisition system of reflection.In certain embodiments, it is possible to calculate humidity sampling model relative to the mean deviation of humidity reference model or variance by calculating humidity sampling model similar as above relative to the process of the standard deviation of humidity reference model, therefore repeat no more here.
Humidity sampling model is relative to the Euclidean distance (euclidean metric, Euclideanmetric) that the distance of humidity reference model can be between them.Euclidean distance is a conventional distance definition, refers to the actual distance between two points in m-dimensional space or the natural length of vector.Euclidean distance in two and three dimensions space is exactly the actual range between 2.
In certain embodiments, humidity similarity determining unit 102 may determine that the humidity sampling model cross correlation measure relative to humidity reference model, cross correlation measure between humidity sampling model and humidity reference model in other words, as the humidity rhythm and pace of moving things similarity between humidity sampling model and humidity reference model.Such as, humidity similarity determining unit 102 can pass through to calculate the cosine similarity between humidity sampling model and humidity reference model or cross-correlation function value, determines the cross correlation measure between humidity sampling model and humidity reference model.
Cosine similarity is also called cosine similarity, assesses their similarity by calculating two vectorial included angle cosine values.Cross-correlation function represents the degree of correlation between two time serieses.Those skilled in the art should understand that the calculation of cross correlation measure between two functions or sequence, repeat no more here.
As it has been described above, the moisture condition of monitoring object can reflect the physiological health state of monitoring object to a certain extent.Such as, the humidity sampling model of monitoring object is more big relative to the dispersion of humidity reference model, illustrate that the moisture condition monitoring object is more big with the diversity factor of normal moisture condition or similarity is more little, then monitoring object suffers from the disease that can cause body surface humidity/temperature anomaly, such as breast carcinoma, probability more high；Otherwise, the humidity sampling model of monitoring object is more big relative to the similarity of humidity reference model, and illustrating to monitor object, to suffer from the probability of the disease that can cause body surface humidity/temperature anomaly more low.So, in certain embodiments, as it is shown on figure 3, moisture condition monitoring device 300 is except including above-described humidity similarity determining unit 102 and moisture condition recognition unit 104, it is also possible to include health status and determine unit 106 and health status reporting unit 108.Here, health status determines that unit 106 is configured to the moisture condition according to monitoring object, it is determined that the physiological health degree of monitoring object；Health status reporting unit 108 is configured to the physiological health degree of monitoring object is supplied to user.Here, physiological health degree can be such as, the risk of monitoring object.Utilize the moisture condition monitoring device 300 shown in Fig. 3, it is possible to provide the user the information more intuitively of the physiological health state of relevant monitoring object.
In some cases, when the temperature monitoring object is relatively low, the humidity of monitoring object is correspondingly relatively low；When the temperature monitoring object is higher, the humidity of monitoring object is correspondingly higher.But, consider people's individual variation in perspiration, namely some people is easier to perspire, and some people is less susceptible to perspire, although the humidity of monitoring object is likely to the temperature representing monitoring object higher than threshold temperature more than threshold value humidity, but is also not excluded for the temperature possibility not higher than threshold temperature of monitoring object.In like manner, although the temperature of monitoring object is likely to the humidity representing monitoring object higher than threshold value humidity more than threshold temperature, but is also not excluded for the humidity possibility not higher than threshold value humidity of monitoring object.
As it has been described above, when temperature corresponding to a part of submodel in the temperature model monitoring object is higher than threshold temperature, the probability that monitoring object suffers from certain disease causing shell temperature to raise is higher；Correspondingly, when humidity corresponding to a part of submodel in the Humidity Model monitoring object is more than threshold value humidity, the temperature of monitoring object higher than threshold temperature thus to suffer from the probability of certain disease causing shell temperature to raise higher.Additionally, in some cases, monitor the temperature humidity that a part of submodel in Humidity Model is corresponding not higher than threshold temperature corresponding to a part of submodel in the temperature model of the object temperature humidity that higher than threshold temperature a part of submodel in Humidity Model corresponding corresponding higher than a part of submodel in the temperature model of threshold value humidity or monitoring object not higher than threshold value humidity, these situations belong to abnormality to a certain extent, and now to suffer from the probability of certain disease causing body surface humidity/temperature anomaly higher for monitoring object.
That is, in a way, temperature sampling value in temperature model is above/below the submodel above/below threshold value humidity of the humidity sampled value in threshold temperature and Humidity Model, more can embodying health physical signs higher or lower than homergy when, the physiological health state for judging, monitor object is more valuable.In certain embodiments, it is possible to come prespecified threshold value humidity and threshold temperature according to the difference of monitoring object.Such as, for the breast of human body, threshold value humidity may be located at [60,100], it is preferred to the relative humidity of 70%, 80% or 90%；Temperature threshold may be located at [34,39.5], it is preferred to 35,36,37 or 38 DEG C.
Therefore, in order to more accurately determine the physiological health state of monitoring object, in certain embodiments, when Humidity Model construction unit can be configured as the temperature of monitoring object higher or lower than threshold temperature, sample to build the humidity sampling model monitoring object to the humidity of monitoring object.
In certain embodiments, as shown in Figure 4, moisture condition monitoring device 400 is except including above-described humidity similarity determining unit 102, except moisture condition recognition unit 104, health status determine unit 106 and health status reporting unit 108, it is also possible to include temperature model construction unit 110, temperature similarity determining unit 112 and state of temperature recognition unit 114.Here, when temperature model construction unit 110 is configured as the humidity of monitoring object higher or lower than threshold value humidity, sample to build the temperature sampling model monitoring object to the temperature of monitoring object；Temperature similarity determining unit 112 is configured to determine that the thermorhythm similarity between temperature sampling model and the temperature reference model of monitoring object；State of temperature recognition unit 114 is configured to the thermorhythm similarity between temperature sampling model and temperature reference model based on monitoring object, identifies the state of temperature of monitoring object.
In certain embodiments, temperature sampling model can be the sample sequence only including temperature sampling value, for instance { W1, W2, W3..., WN}；Temperature reference model can be the reference sequences only including temperature reference value, for instance { R1, R2, R3..., RM, wherein, M and N is all positive integer.In these embodiments, owing to not accounting for time factor, the such as two respective elements of sequence corresponding relation in time, temperature similarity determining unit 112 can determine the difference between temperature sampling model and temperature reference model roughly, thus, the normal degree of the substantially state of temperature of monitoring object is may recognize that by state of temperature recognition unit 114.
For the difference more accurately determined between temperature sampling model and temperature reference model and then the more accurate state of temperature identifying monitoring object, in certain embodiments, temperature sampling model can be that each sampled point therein is respectively provided with temperature sampling value and the sample sequence of corresponding two attributes of sampling time, for instance { (W1, t1), (W2, t2), (W3, t3) ..., (WN, tN)}；Accordingly, temperature reference model can be that each reference point therein is respectively provided with temperature reference value and the reference sequences of corresponding two attributes of reference time, for instance { (R1, T1), (R2, T2)(R3, T3) ..., (RM, TM), wherein, M and N is positive integer.It is to say, temperature sampling model can include the one or more sampled points being associated with temperature sampling value and corresponding sampling time, temperature reference model can also include the one or more reference points being associated with temperature reference value and corresponding reference time.In these embodiments, temperature similarity determining unit 112 first can find out reference time and sampling time each reference point immediate in temperature sampling model from temperature reference model, each reference point that correspondence in sequential is the strongest in other words, then, it is determined that temperature sampling model and find out each reference point composition temperature reference submodel between thermorhythm similarity.
Temperature similarity determining unit 112 may determine that the temperature sampling model of monitoring object is relative to the dispersion between temperature reference model or cross correlation measure, and such index can reflect the thermorhythm similarity between temperature sampling model and temperature reference model as monitoring object.Such as, temperature similarity determining unit 112 can pass through the temperature sampling model calculating monitoring object relative to the Euclidean distance of temperature reference model, standard deviation, mean deviation or variance, it is determined that the temperature sampling model of monitoring object is relative to the dispersion of temperature reference model；Temperature similarity determining unit 112 can by the temperature sampling model of the calculating monitoring object cosine similarity relative to temperature reference model or cross-correlation function value, it is determined that the cross correlation measure between temperature sampling model and the temperature reference model of monitoring object.The determination process determination for humidity rhythm and pace of moving things similarity similar as above for thermorhythm similarity processes, and therefore here repeats no more.
In certain embodiments, health status determines that unit 106 can be additionally configured to the state of temperature according to monitoring object, it is determined that the physiological health degree of monitoring object.It is to say, health status determines one or both that unit 106 can be configured in the moisture condition according to monitoring object and state of temperature, it is determined that the physiological health degree of monitoring object.As such, it is possible to the moisture condition of comprehensive monitoring object and state of temperature, it is considered to people, in the individual variation perspired and in body temperature, more accurately determines the physiological health state of monitoring object.Again such as, in the example that the appointed part of the breast of human body is monitored, physiological health degree can include the risk of the local of breast.
Can use in above-described embodiment moisture condition monitoring device monitor such as, the appointed part of the left breast of specific women at the appointed time section, for instance, morning 00:00 to 03:00 deep sleep during moisture condition and/or state of temperature.
In more above-mentioned embodiments, humidity reference model and temperature reference model can be large sample with side same time/with the humidity statistical model of period and temperature statistics model, namely by the appointed part of the left breast of greater number of healthy women humidity sampled value during the above-mentioned appointment time period and temperature sampling value are added up the humidity statistical model and temperature statistics model that obtain.
Consider people's individual variation in body temperature and perspiration, in certain embodiments, humidity reference model and temperature reference model can be the appointed part with measurand have certain symmetric offside (or claiming healthy side, strong side) position same time/with the temperature sampling model of period.Such as, moisture condition monitoring device in using above-described embodiment is monitored, the such as appointed part of the left breast of specific women at the appointed time section, such as, during 00:00 to 03:00 in morning, moisture condition and/or when state of temperature, the corresponding position that can pass through the right breast to this specific women carries out humidity and temperature sampling during the above-mentioned appointment time period, sampling period can at [5s, 60s] between, build humidity reference model and the temperature reference model of the appointed part of the left breast for this women.
Further, it is contemplated that the body temperature of the same area of the symmetrical both sides of same person and the difference of perspiration aspect, in certain embodiments, humidity reference model and temperature reference model may refer to the temperature sampling model of history same period of position, bonding part.Such as, moisture condition monitoring device in using above-described embodiment is monitored, the such as appointed part of the left breast of specific women at the appointed time section, such as, during 00:00 to 03:00 in morning, moisture condition and/or when state of temperature, can utilize such as, previous decade, the first five years, the first two years, the previous year, the first half, first trimesters etc. are for the above-mentioned appointed part of the left breast of this specific women, the annulus of 2-2.3 centimetre or the neighborhood at the 4.5cm place along nipple sensing oxter such as it is about around nipple radius, humidity sampled value during the above-mentioned appointment time period and temperature sampling value, build humidity reference model and the temperature reference model of the appointed part of left breast for this specific women.
Further, other embodiments of the present invention are by the rhythm and pace of moving things similarity between temperature-humidity sampling model and the temperature-humidity reference model combined of the associating based on monitoring object, thus fusion temperature jointly identifies the humiture state of monitoring object with Humidity Model.Below, in conjunction with Fig. 5 and Fig. 6, humiture state monitoring apparatus according to an embodiment of the invention and method are described.
Fig. 5 is the structured flowchart illustrating humiture state monitoring apparatus according to another embodiment of the present invention.Fig. 6 is the flow chart illustrating humiture state monitoring method according to another embodiment of the present invention.As it is shown in figure 5, humiture state monitoring apparatus 500 includes rhythm and pace of moving things similarity determining unit 502 and humiture state recognition unit 504.Here, rhythm and pace of moving things similarity determining unit 502 is configured to determine that the rhythm and pace of moving things similarity between temperature-humidity sampling model and the temperature-humidity reference model of monitoring object, i.e. perform step S502；Humiture state recognition unit 504 is configured to the rhythm and pace of moving things similarity between temperature-humidity sampling model and temperature-humidity reference model based on monitoring object, identifies the humiture state of monitoring object, i.e. perform step S504.
Determining monitoring object, such as, somewhere appointed part at the appointed time section in the left breast of specific women, such as, during 00:00 to 03:00 in morning, humiture state before, humiture state monitoring apparatus 500 can obtain this appointed part temperature-humidity sampling model during the above-mentioned time period from humiture model construction unit (not shown).In certain embodiments, humiture model construction unit can be configured to, with temperature sensor and humidity sensor and arbitrary appointment in the time period, the temperature and humidity of arbitrary appointed part be sampled, to build the temperature-humidity sampling model in this appointed part at the appointed time section.Such as, humiture model construction unit can be configured at the appointed time in section, the temperature sampling value for appointed part and humidity sampled value is received from temperature sensor and humidity sensor, to build the temperature-humidity sampling model in this appointed part at the appointed time section every specific interval.Those skilled in the art are it is to be understood that humiture model construction unit can as a part for humiture state monitoring apparatus 500, it is also possible to be provided independently from the outside of humiture state monitoring apparatus 500.
In certain embodiments, temperature-humidity sampling model can be that each sampled point therein only includes temperature sampling value and the sample sequence of two attributes of humidity sampled value, for instance { (Wi, H1), (W2, H2), (W3, H3) ..., (WN, HN}；Temperature-humidity reference model can be that each reference point therein includes temperature reference value and the reference sequences of humidity reference value, for instance { (R1, S1), (R2, S2), (R3, S3) ..., (RM, SM), wherein, M and N is positive integer.It is to say, temperature-humidity sampling model can include the one or more sampled points being associated with temperature sampling value and humidity sampled value；Temperature-humidity reference model can include the one or more reference points being associated with temperature reference value and humidity reference value.In these embodiments, owing to not accounting for time factor, such as, in two sequences element corresponding relation in time, rhythm and pace of moving things similarity determining unit 502 can determine the difference between temperature-humidity sampling model and temperature-humidity reference model roughly, may identify which out the substantially humiture state of monitoring object thereby through humiture state recognition unit 504.
For the difference more accurately determined between temperature-humidity sampling model and temperature-humidity reference model and then the more accurate humiture state identifying monitoring object, in certain embodiments, temperature-humidity sampling model can be the sample sequence that each sampled point therein is respectively provided with temperature sampling value, humidity sampled value and corresponding three attributes of sampling time, for instance { (W1, H1, t1), (W2, H2, t2), (W3, H3, t3) ..., (WN, HN, tN)}；Temperature-humidity reference model can be the reference sequences that each reference point therein is respectively provided with three attributes of reference time of temperature reference value, humidity reference value and correspondence, for instance { (R1, S1, T1), (R2, S2, T2)(R3, S3, T3) ..., (RM, SM, TM), wherein, M and N is positive integer.It is to say, temperature-humidity sampling model can include the one or more sampled points being associated with temperature sampling value, humidity sampled value and corresponding sampling time；Temperature-humidity reference model can include the one or more reference points being associated with temperature reference value, humidity reference value and corresponding reference time.In these embodiments, rhythm and pace of moving things similarity determining unit 502 first can find out sampling time each reference point immediate in reference time and temperature-humidity sampling model from temperature-humidity reference model, it is then determined that temperature-humidity sampling model and the temperature-humidity of each reference point composition found out are with reference to the rhythm and pace of moving things similarity between submodel.
In certain embodiments, rhythm and pace of moving things similarity determining unit 502 may determine that the temperature-humidity sampling model dispersion relative to temperature-humidity reference model, as the rhythm and pace of moving things similarity between temperature-humidity sampling model and temperature-humidity reference model.Such as, rhythm and pace of moving things similarity determining unit 502 can pass through the distance calculating temperature-humidity sampling model relative to temperature-humidity reference model, such as Euclidean distance, standard deviation, mean deviation or variance, determine the temperature-humidity sampling model dispersion relative to temperature-humidity reference model.
Such as, rhythm and pace of moving things similarity determining unit 502 can by (the W of the ith sample point in the temperature-humidity sampling model of certain detected parti, Hi) as Xi, by the temperature reference value of upper for the time in the temperature-humidity reference model of corresponding position identical or corresponding reference point and humidity reference value (Ri, Si) as expected value μ.Or, by temperature-humidity reference model on the sampling time with temperature-humidity sampled point (Wi, Hi) the temperature-humidity reference value (R of a close elementi, Si) or the meansigma methods (R of temperature-humidity reference value of several elementAi, SAi), as expected value μ, utilize 1 N Σ i = 1 N ( ( W i - R i ) 2 + ( H i - S i ) 2 ) , Or 1 N Σ i = 1 N ( ( W i - R A i ) 2 + ( H i - S A i ) 2 ) , ( i = 1 , ... , N ) Calculate the temperature-humidity sampling model standard deviation relative to temperature-humidity reference model.It is to say, different sampled points in temperature-humidity sampling model can be corresponding different expected value μ.Additionally, rhythm and pace of moving things similarity determining unit 502 can calculate temperature-humidity sampling model relative to the mean deviation of temperature-humidity reference model or variance by the similar as above temperature-humidity sampling model that calculates relative to the process of the standard deviation of temperature-humidity reference model, therefore repeats no more here.
In certain embodiments, rhythm and pace of moving things similarity determining unit 502 may determine that the temperature-humidity sampling model cross correlation measure relative to temperature-humidity reference model, as the rhythm and pace of moving things similarity between temperature-humidity sampling model and temperature-humidity reference model.Such as, rhythm and pace of moving things similarity determining unit 502 can pass through to calculate the cosine similarity between temperature-humidity sampling model and temperature-humidity reference model or cross-correlation function value, determines the cross correlation measure between temperature-humidity sampling model and temperature-humidity reference model.Those skilled in the art should understand that the calculation of cross correlation measure between two functions or sequence, repeat no more here.
Fig. 7 be the temperature-humidity sampling model in some embodiments of the present invention and temperature-humidity reference model at temperature-humidity schematic diagram, for ease of understanding, schematically the distribution of above-mentioned model is placed in coordinate system visually herein and presents.As it is shown in fig. 7, the sampled point in temperature-humidity sampling model falls in the elliptical region indicated by 701, the reference point in temperature-humidity reference model falls in the border circular areas indicated by 702.In certain embodiments, rhythm and pace of moving things similarity determining unit 502 can by the line distance of the center of gravity in the beeline (if the two region is separated from each other) between the elliptical region corresponding to temperature-humidity sampling model and the border circular areas corresponding to temperature-humidity reference model or the two region or geometric center, thus the rhythm and pace of moving things similarity reflected between temperature-humidity sampling model and temperature-humidity reference model.In certain embodiments, each sampled point in region 701 can have respective weight, and each reference point in region 702 can also have respective weight, and these weights can be identical, it is also possible to different；Accordingly, the spacing in above-mentioned two regions, it is possible to for the Weighted distance of each included sampled point or reference point.
In certain embodiments, when region 701 represents such as, the distributed areas of the temperature-humidity sampled point of the appointed part of the left breast of specific women, region 702 represents such as, during the distributed areas of the temperature-humidity reference point of the appointed part of the left breast of a lot of healthy womens, distance between region 701 and 702 actually represent the same area of the appointed part of the left breast of this specific women and the left breast of healthy population gap in humiture state, the appointed part of the left breast of gap this specific women of more big explanation is more abnormal, that is the left breast of this specific women more has and suffers from the disease that can cause body surface temperature anomaly, such as breast carcinoma, probability.
Only the appointed part of the left breast of this specific women being compared not enough with healthy population, because individual variation is likely to very big, somebody easily perspires, fever, and somebody does not then perspire throughout the year, body temperature is low.So, it is symmetrical in view of Human Physiology to a certain extent, in certain embodiments, it is possible to the same area of the appointed part of the left breast of this specific women Yu its right breast compared, the humiture state of the appointed part of the almost symmetry of arranged on left and right sides breast is namely measured respectively.
But, still inadequate just with Human Physiology symmetry to a certain extent, because human body symmetrical is relative, rather than absolute.So, in certain embodiments, it is possible to using the historical data of the appointed part of the left breast of this specific women as temperature-humidity reference model.Such as, some period in March, 2008 measures the humiture state of this appointed part, and within the roughly the same period in March, 2009, again measure the humiture state of this appointed part, can using the measurement result in March, 2008 as temperature-humidity reference model, the measurement result in March, 2009 is as temperature-humidity sampling model.
Whether there is the disease still can be defective based on the appointed part of the left breast of the specific women of the region decision shown in Fig. 7, because such as to the multiple sampled points in region 701, " if the sampling optimization on daytime is in oval upper right side; the sampling optimization at night is in oval lower left ", with " sampling optimization on daytime is in oval lower left; the sampling optimization at night is in oval upper right side ", both of these case is different in fact.But, this situation is not reflected in the humiture state monitoring method described in conjunction with Fig. 6, and the humiture sample area that the situation that both difference are very big in other words is formed is the same.
In order to overcome this problem, Fig. 7 can be stretched along time shaft in certain embodiments, each temperature-humidity sample sequence is launched in time, can schematically be visually presented with out in three dimensions by correlation model/sequence.In fig. 8, A, B sequence represents temperature-humidity reference model and temperature-humidity sampling model respectively.Can directly calculate the distance between the corresponding point on two space curves of A, B, it is weighted summation or arithmetic is sued for peace the average distance obtaining between these two curves, or the measure such as available above-mentioned inequality, standard deviation embodies spacing or the dispersion degree of two curves.Alternatively, available interpolation method processes two temperature-humidity sample sequences and generates the matched curve of correspondence respectively, then seeks the spatial area between two matched curves by integration method, as the distance corresponding to certain period between these two curves.Distance between two space curves of A, B, can reflect the rhythm and pace of moving things similarity between temperature-humidity reference model and temperature-humidity sampling model.
The humiture state of monitoring object can reflect the physiological health state of monitoring object more accurately.Such as, the temperature-humidity sampling model of monitoring object is more big relative to the dispersion of temperature-humidity reference model, illustrates that monitoring object suffers from the disease that can cause body surface humidity/temperature anomaly, such as breast carcinoma, probability more high；The temperature-humidity sampling model of monitoring object is more big relative to the similarity of temperature-humidity reference model, and illustrating to monitor object, to suffer from the probability of the disease that can cause body surface humidity/temperature anomaly more low.So, in certain embodiments, moisture condition monitoring device 500 shown in Fig. 5 is except including above-described rhythm and pace of moving things similarity determining unit 502 and humiture state recognition unit 504, it is also possible to include determining unit and health status reporting unit above in association with the health status described in Fig. 3-4.In these embodiments, health status determines that unit is configured to the humiture state according to monitoring object, it is determined that the physiological health degree of monitoring object；Health status reporting unit is configured to the physiological health degree of monitoring object is supplied to user.Utilize above-mentioned humiture state monitoring apparatus can provide the user the information more intuitively of the physiological health state about monitoring object, such as, prompting some body temperature relevant disease of user, such as breast carcinoma, the percentage ratio that the risk in detected breast local increases within a certain period or reduces.
Additionally, as mentioned above, usually above/temperature sampling the value lower than threshold temperature and the humidity sampled value above/below threshold value humidity, more can embody health physical signs higher or lower than homergy when, physiological health state for judging monitoring object is more valuable, so in certain embodiments, humiture model construction unit can only obtain the monitoring temperature sampling value higher or lower than threshold temperature of object and the humidity sampled value higher or lower than threshold value humidity, and utilize these temperature sampling values and humidity sampled value to build temperature-humidity sampling model and temperature-humidity reference model.
Need clearly, to the invention is not limited in customized configuration that is described above and that illustrate in the drawings and process.For brevity, the detailed description to known method technology is omitted here.In the above-described embodiments, describe and illustrate some concrete steps exemplarily.But, the procedure of the present invention is not limited to concrete steps that are described and that illustrate, and those skilled in the art after the spirit understanding the present invention, can be variously modified, revise and add, or changes the order between step.
What those skilled in the art should understand that is, although moisture condition monitoring method according to embodiments of the present invention and device and humiture state monitoring method and device are described by the example above in association with the breast of women, but these method and apparatus according to embodiments of the present invention can also be used to such as, the leg of human body, arm, face, foot, brain etc. have certain symmetric position and are monitored, thus helping in the various disease likely causing temperature anomaly state of above-mentioned part Identification, for instance the tumor of early metaphase, cancer etc..
Functional device shown in structures described above block diagram can be implemented as hardware, software, firmware or their combination.When realizing in hardware, it can be such as electronic circuit, special IC (ASIC), suitable firmware, plug-in unit, function card etc..When realizing with software mode, the element of the present invention is the program or the code segment that are used for performing required task that will be run by processor.Program or code segment can be stored in machine readable media, or sent at transmission medium or communication links by the data signal carried in carrier wave." machine readable media " may be configured to storage or any medium of transmission information.The example of machine readable media includes electronic circuit, semiconductor memory devices, ROM, flash memory, erasable ROM (EROM), floppy disk, CD-ROM, CD, hard disk, fiber medium, radio frequency (RF) link, etc..Code segment can be downloaded via the computer network of such as the Internet, Intranet etc..
In other words, above-described moisture condition monitoring device or humiture state monitoring apparatus can be embodied in the device including following assembly: processor；Memorizer, is used for storing the executable instruction of processor, wherein these instructions be when executed by operable to perform above-described moisture condition monitoring method or humiture state monitoring method.
The present invention can realize in other specific forms, without deviating from its spirit and substitutive characteristics.Such as, the algorithm described in specific embodiment can be modified, and system architecture is without departing from the essence spirit of the present invention.Therefore, current embodiment is all counted as being exemplary rather than determinate in all respects, the scope of the invention but not foregoing description definition, further, the whole changes in the implication of claim and the scope of equivalent are fallen into thus being all included within the scope of the invention.

Claims (53)

1. a moisture condition monitoring method, including:
Determine the humidity rhythm and pace of moving things similarity between humidity sampling model and the humidity reference model of monitoring object；And
Based on described humidity rhythm and pace of moving things similarity, identify the moisture condition of described monitoring object.
2. moisture condition monitoring method according to claim 1, wherein, described humidity sampling model includes at least one sampled point being associated with humidity sampled value and corresponding sampling time, and described humidity reference model includes at least one reference point being associated with humidity reference value and corresponding reference time.
3. moisture condition monitoring method according to claim 1 and 2, wherein, described humidity rhythm and pace of moving things similarity is described humidity sampling model relative to the dispersion of described humidity reference model or cross correlation measure.
4. moisture condition monitoring method according to claim 3, wherein, described dispersion is that described humidity sampling model is relative to the distance of described humidity reference model, standard deviation, mean deviation or variance.
5. moisture condition monitoring method according to claim 3, wherein, described cross correlation measure is the cosine similarity between described humidity sampling model and described humidity reference model or cross-correlation function value.
6. the moisture condition monitoring method according to any one of claim 1-5, wherein, described monitoring to as if the appointed part of human body, described humidity reference model is the humidity sampling model of the same period at the offside position of the humidity sampling model of history same period of described appointed part, described appointed part or the large sample humidity statistical model of the same period with side.
7. moisture condition monitoring method according to claim 6, before determining described humidity rhythm and pace of moving things similarity, also includes:
When the temperature of described monitoring object is higher or lower than threshold temperature, sample to build described humidity sampling model to the humidity of described monitoring object.
8. moisture condition monitoring method according to claim 6, also includes:
When the humidity of described monitoring object is higher or lower than threshold value humidity, the temperature of described monitoring object is sampled to build the temperature sampling model of described monitoring object；
Determine the thermorhythm similarity between described temperature sampling model and temperature reference model；And
Based on described thermorhythm similarity, identify the state of temperature of described monitoring object.
9. moisture condition monitoring method according to claim 8, wherein, described temperature sampling model includes at least one sampled point being associated with temperature sampling value and corresponding sampling time, and described temperature reference model includes at least one reference point being associated with temperature reference value and corresponding reference time.
10. moisture condition monitoring method according to claim 8 or claim 9, wherein, described thermorhythm similarity is described temperature sampling model relative to the dispersion of described temperature reference model or cross correlation measure.
11. moisture condition monitoring method according to claim 10, wherein, described dispersion is that described temperature sampling model is relative to the distance of described temperature reference model, standard deviation, mean deviation or variance.
12. moisture condition monitoring method according to claim 10, wherein, described cross correlation measure is the cosine similarity between described temperature sampling model and described temperature reference model or cross-correlation function value.
13. the moisture condition monitoring method according to any one of-12 according to Claim 8, wherein, described monitoring to as if the appointed part of human body, described temperature reference model is the temperature sampling model of the same period at the offside position of the temperature sampling model of history same period of described appointed part, described appointed part or the large sample temperature statistics model of the same period with side.
14. moisture condition monitoring method according to claim 13, also include:
According to described moisture condition and/or described state of temperature, it is determined that the physiological health degree of described monitoring object；
Described physiological health degree is supplied to user.
15. a moisture condition monitoring device, including:
Humidity similarity determining unit, is configured to determine that the humidity rhythm and pace of moving things similarity between humidity sampling model and the humidity reference model of monitoring object；And
Moisture condition recognition unit, is configured to, based on described humidity rhythm and pace of moving things similarity, identify the moisture condition of described monitoring object.
16. moisture condition according to claim 15 monitoring device, wherein, described humidity sampling model includes at least one sampled point being associated with humidity sampled value and corresponding sampling time, and described humidity reference model includes at least one reference point being associated with humidity reference value and corresponding reference time.
17. the moisture condition monitoring device according to claim 15 or 16, wherein, described humidity rhythm and pace of moving things similarity is described humidity sampling model relative to the dispersion of described humidity reference model or cross correlation measure.
18. moisture condition according to claim 17 monitoring device, wherein, described dispersion is that described humidity sampling model is relative to the distance of described humidity reference model, standard deviation, mean deviation or variance.
19. moisture condition according to claim 17 monitoring device, wherein, described cross correlation measure is the cosine similarity between described humidity sampling model and described humidity reference model or cross-correlation function value.
20. the moisture condition monitoring device according to any one of claim 15-19, wherein, described monitoring to as if the appointed part of human body, described humidity reference model is the humidity sampling model of the same period at the offside position of the humidity sampling model of history same period of described appointed part, described appointed part or the large sample humidity statistical model of the same period with side.
21. moisture condition according to claim 20 monitoring device, also include:
Humidity Model construction unit, when being configured as the temperature of described monitoring object higher or lower than threshold temperature, samples to build described humidity sampling model to the humidity of described monitoring object.
22. moisture condition according to claim 20 monitoring device, also include:
Temperature model construction unit, when being configured as the humidity of described monitoring object higher or lower than threshold value humidity, samples to build the temperature sampling model of described monitoring object to the temperature of described monitoring object；
Temperature similarity determining unit, is configured to determine that the thermorhythm similarity between described temperature sampling model and temperature reference model；And
State of temperature recognition unit, is configured to, based on described thermorhythm similarity, identify the state of temperature of described monitoring object.
23. moisture condition according to claim 22 monitoring device, wherein, described temperature sampling model includes at least one sampled point being associated with temperature sampling value and corresponding sampling time, and described temperature reference model includes at least one reference point being associated with temperature reference value and corresponding reference time.
24. the moisture condition monitoring device according to claim 22 or 23, wherein, described thermorhythm similarity is described temperature sampling model relative to the dispersion of described temperature reference model or cross correlation measure.
25. moisture condition according to claim 24 monitoring device, wherein, described dispersion is that described temperature sampling model is relative to the distance of described temperature reference model, standard deviation, mean deviation or variance.
26. moisture condition according to claim 24 monitoring device, wherein, described cross correlation measure is the cosine similarity between described temperature sampling model and described temperature reference model or cross-correlation function value.
27. the moisture condition monitoring device according to any one of claim 22-26, wherein, described monitoring to as if the appointed part of human body, described temperature reference model is the temperature sampling model of the same period at the offside position of the temperature sampling model of history same period of described appointed part, described appointed part or the large sample temperature statistics model of the same period with side.
28. moisture condition according to claim 27 monitoring device, also include:
Health status determines unit, is configured to according to described moisture condition and/or described state of temperature, it is determined that the physiological health degree of described monitoring object；
Health status reporting unit, is configured to described physiological health degree is supplied to user.
29. a humiture state monitoring method, including:
Determine the rhythm and pace of moving things similarity between temperature-humidity sampling model and the temperature-humidity reference model of monitoring object；And
Based on described rhythm and pace of moving things similarity, identify the humiture state of described monitoring object.
30. humiture state monitoring method according to claim 29, wherein, described rhythm and pace of moving things similarity is the distance between center of gravity or the geometric center of the first area corresponding to described temperature-humidity sampling model and the second area corresponding to described temperature-humidity reference model.
31. humiture state monitoring method according to claim 29, wherein, described temperature-humidity sampling model includes at least one sampled point being associated with temperature sampling value, humidity sampled value and corresponding sampling time, and described temperature-humidity reference model includes at least one reference point being associated with temperature reference value, humidity reference value and corresponding reference time.
32. humiture state monitoring method according to claim 31, wherein, described rhythm and pace of moving things similarity is the first space curve corresponding to described temperature-humidity sampling model and the distance between the second space curve corresponding to described temperature-humidity reference model.
33. humiture state monitoring method according to claim 32, wherein, the distance between described first space curve and described second space curve be the mean deviation between described first space curve and described second space curve, area between poor or described first space curve of weighted average and described second space curve.
34. the humiture state monitoring method according to claim 29 or 31, wherein, described rhythm and pace of moving things similarity is described temperature-humidity sampling model relative to the dispersion of described temperature-humidity reference model or cross correlation measure.
35. humiture state monitoring method according to claim 34, wherein, described dispersion is that described temperature-humidity sampling model is relative to the distance of described temperature-humidity reference model, standard deviation, mean deviation or variance.
36. humiture state monitoring method according to claim 34, wherein, described cross correlation measure is the cosine similarity between described temperature-humidity sampling model and described temperature-humidity reference model or cross-correlation function value.
37. the humiture state monitoring method according to any one of claim 29-36, wherein, described monitoring to as if the appointed part of human body, described temperature-humidity reference model is the temperature-humidity sampling model of the same period at the offside position of the temperature-humidity sampling model of history same period of described appointed part, described appointed part or the large sample temperature-humidity statistical model of the same period with side.
38. the humiture state monitoring method according to claim 37, wherein, described appointed part is the local of breast.
39. the humiture state monitoring method according to claim 38, also include:
According to described humiture state, it is determined that the physiological health degree of the local of described breast；
Described physiological health degree is supplied to user.
40. the humiture state monitoring method according to any one of claim 29-39, wherein, described temperature-humidity reference model and described temperature-humidity sampling model are based on higher than the temperature sampling value of threshold temperature and corresponding humidity sampled value and/or build higher than humidity sampled value and the corresponding temperature sampling value of threshold value humidity.
41. a humiture state monitoring apparatus, including:
Rhythm and pace of moving things similarity determining unit, is configured to determine that the rhythm and pace of moving things similarity between temperature-humidity sampling model and the temperature-humidity reference model of monitoring object；And
Humiture state recognition unit, is configured to, based on described rhythm and pace of moving things similarity, identify the humiture state of described monitoring object.
42. humiture state monitoring apparatus according to claim 41, wherein, described rhythm and pace of moving things similarity is the distance between center of gravity or the geometric center of the first area corresponding to described temperature-humidity sampling model and the second area corresponding to described temperature-humidity reference model.
43. humiture state monitoring apparatus according to claim 41, wherein, described temperature-humidity sampling model includes at least one sampled point being associated with temperature sampling value, humidity sampled value and corresponding sampling time, and described temperature-humidity reference model includes at least one reference point being associated with temperature reference value, humidity reference value and corresponding reference time.
44. humiture state monitoring apparatus according to claim 43, wherein, described rhythm and pace of moving things similarity is the first space curve corresponding to described temperature-humidity sampling model and the distance between the second space curve corresponding to described temperature-humidity reference model.
45. humiture state monitoring apparatus according to claim 44, wherein, the distance between described first space curve and described second space curve be the mean deviation between described first space curve and described second space curve, area between poor or described first space curve of weighted average and described second space curve.
46. the humiture state monitoring apparatus according to claim 41 or 43, wherein, described rhythm and pace of moving things similarity is described temperature-humidity sampling model relative to the dispersion of described temperature-humidity reference model or cross correlation measure.
47. humiture state monitoring apparatus according to claim 46, wherein, described dispersion is that described temperature-humidity sampling model is relative to the distance of described temperature-humidity reference model, standard deviation, mean deviation or variance.
48. humiture state monitoring apparatus according to claim 46, wherein, described cross correlation measure is the cosine similarity between described temperature-humidity sampling model and described temperature-humidity reference model or cross-correlation function value.
49. the humiture state monitoring apparatus according to any one of claim 41-48, wherein, described monitoring to as if the appointed part of human body, described temperature-humidity reference model is the temperature-humidity sampling model of the same period at the offside position of the temperature-humidity sampling model of history same period of described appointed part, described appointed part or the large sample temperature-humidity statistical model of the same period with side.
50. humiture state monitoring apparatus according to claim 49, wherein, described appointed part is the local of breast.
51. humiture state monitoring apparatus according to claim 50, also include:
Health status determines unit, is configured to according to described temperature-humidity state, it is determined that the physiological health degree of the local of described breast；
Health status reporting unit, is configured to described physiological health degree is supplied to user.
52. the humiture state monitoring apparatus according to any one of claim 41-51, wherein, described temperature-humidity reference model and described temperature-humidity sampling model are based on higher than the temperature sampling value of threshold temperature and corresponding humidity sampled value and/or build higher than humidity sampled value and the corresponding temperature sampling value of threshold value humidity.
53. humiture state monitoring apparatus according to claim 51, wherein, described physiological health degree includes the risk of the local of described breast.
CN201610059511.XA 2016-01-28 2016-01-28 Comparison assessment method and device for humiture field model based on cancer cell abnormality Pending CN105740614A (en)

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CN114468996A (en) * 2021-12-20 2022-05-13 香港生物节律研究院有限公司 Method for analyzing breast signs based on orderliness, multimodality and symmetry deficiency
CN114468996B (en) * 2021-12-20 2024-01-23 香港生物节律研究院有限公司 Method for analyzing breast signs based on order, multi-mode and symmetry deficiency

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