WO2018133080A1 - Procédé et dispositif d'analyse de température - Google Patents

Procédé et dispositif d'analyse de température Download PDF

Info

Publication number
WO2018133080A1
WO2018133080A1 PCT/CN2017/072129 CN2017072129W WO2018133080A1 WO 2018133080 A1 WO2018133080 A1 WO 2018133080A1 CN 2017072129 W CN2017072129 W CN 2017072129W WO 2018133080 A1 WO2018133080 A1 WO 2018133080A1
Authority
WO
WIPO (PCT)
Prior art keywords
temperature
measured area
temperature values
surface positions
values corresponding
Prior art date
Application number
PCT/CN2017/072129
Other languages
English (en)
Chinese (zh)
Inventor
康宏
黄建华
段一凡
Original Assignee
上海温尔信息科技有限公司
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by 上海温尔信息科技有限公司 filed Critical 上海温尔信息科技有限公司
Priority to PCT/CN2017/072129 priority Critical patent/WO2018133080A1/fr
Publication of WO2018133080A1 publication Critical patent/WO2018133080A1/fr

Links

Images

Classifications

    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue

Definitions

  • the present application relates to the field of data processing technologies, and in particular, to a temperature analysis method and apparatus.
  • breast tumors have a high incidence in the female population, and early diagnosis has important practical significance in reducing the incidence and mortality of breast tumors.
  • diagnostic methods for breast tumors such as X-ray, ultrasound, magnetic resonance, etc.
  • the characteristic is to give imaging images, and rely on the imager to manually process these images to obtain diagnostic information. Only when the tumor develops to a certain size, it is possible to detect it, and at the same time, they all belong to the loss-assist auxiliary diagnosis; the infrared thermal imaging technology uses the infrared detector to record the temperature distribution of the patient's body surface, and estimates the physiological function information in the body according to the biological heat conduction theory. This is a non-contact, non-radiative, non-destructive auxiliary diagnosis, but currently there is a higher false positive.
  • the inventors found through research that, in general, the body temperature at the tumor is higher than the body temperature under normal conditions. Among them, breast tumors have the most significant effect on the skin above them. Therefore, in principle, the temperature of the epidermis near the tumor or lesion is significantly different from the temperature of other regions. Therefore, the inventors thought that it is possible to assist in the determination of the presence or absence of a lesion based on the method of temperature measurement and analysis. Moreover, the way of measuring the temperature of the body surface does not cause harm to the human body, and is simple and convenient.
  • the inventors have found that due to the activity of the human body, the surface temperature change may be large, so the measurement time generally selected is the sleep time at night. Because at night, people's activities are the smallest in a day, and the body temperature is also relatively low during the day. Taking the scene of testing the surface temperature of the breast as an example, at this time, the influence of the temperature of the breast tumor on the surface of the breast surface is more prominent than the influence of the movement of the human body. Therefore, the measurement of the body surface temperature and the temperature data are performed at this time stage. Analysis often makes the results more accurate.
  • the embodiment of the present application provides a temperature analysis method, including:
  • M*N temperature values corresponding to the measured area of the measured object wherein the M*N temperature values are obtained by continuously collecting the measured area by a contact measurement manner, where M corresponds to the number of acquisitions, and N corresponds to N surface positions of the measured area;
  • the M*N temperature values are analyzed to obtain temperature value distribution characteristics.
  • the method further includes:
  • An abnormal temperature value among the M temperature values corresponding to each of the N surface positions is removed.
  • the analyzing step of the M*N temperature values includes:
  • the analyzing step of the M*N temperature values includes:
  • the analyzing step of the M*N temperature values includes:
  • the method further includes:
  • the N temperature averages and/or the N temperature variance values are output in a Cantor diagram manner.
  • the method further includes:
  • the measured area includes a first measured area and a second measured area, where the first measured area and the second measured area have positional symmetry
  • the analysis steps of M*N temperature values include:
  • Correlation analysis is performed on M temperature values corresponding to the respective M temperature values of the N1 surface positions of the first measured area and the N2 surface positions of the second measured area to obtain N/2 Correlation coefficients.
  • the embodiment of the present application further provides a temperature analysis device, including:
  • a first acquiring module configured to acquire M*N temperature values corresponding to the measured area of the measured object, where the M*N temperature values are obtained by continuously collecting the measured area by a contact measurement manner, where M corresponds to For the number of acquisitions, N corresponds to N surface positions of the measured area;
  • An analysis module is configured to analyze the M*N temperature values to obtain a temperature value distribution characteristic.
  • the first removing module is configured to remove an abnormal temperature value among the M temperature values corresponding to the N surface positions.
  • the analyzing module includes:
  • a temperature difference analyzing unit configured to determine N temperature difference values corresponding to the N surface positions according to the M temperature values corresponding to the N surface positions.
  • the analyzing module includes:
  • the mean value analyzing unit is configured to determine N temperature average values corresponding to the N surface positions according to the M temperature values corresponding to the N surface positions.
  • the analyzing module includes:
  • an variance analysis unit configured to determine N temperature variance values corresponding to the N surface positions according to the M temperature values and the N temperature average values.
  • the device further includes:
  • a second acquiring module configured to acquire a reference temperature value distribution feature corresponding to the measured area obtained in advance
  • a comparison module configured to compare the temperature value distribution feature and the reference temperature value distribution feature to determine whether the temperature value distribution feature is abnormal.
  • the measured area includes a first measured area and a second measured area
  • the first measured area and the second measured area have positional symmetry
  • the analysis module further includes:
  • a correlation analysis unit configured to correlate M temperature values corresponding to each of N1 surface positions of the first measured area and M temperature values corresponding to N2 surface positions of the second measured area Analyze to obtain N/2 correlation coefficients.
  • the embodiment of the present application further provides a computer storage medium, which stores the following program instructions:
  • a first program instruction configured to acquire M*N temperature values corresponding to the measured area of the measured object, where the M*N temperature values are obtained by continuously collecting the measured area by a contact measurement manner, where M corresponds to In the number of acquisitions, N1 corresponds to N surface positions of the measured area;
  • the embodiment of the present application further provides an electronic device, including:
  • a memory configured to store a computer program
  • a communication interface configured to implement communication between the electronic device and other devices
  • a processor coupled to the memory and the communication interface is configured to execute the computer program for:
  • M*N temperature values corresponding to the measured area of the measured object where the M*N temperature values are obtained by continuously collecting the measured area by a contact measurement manner, where M corresponds to Number of acquisitions, N1 corresponding to N surface positions of the measured area;
  • the M*N temperature values are analyzed to obtain temperature value distribution characteristics.
  • the processor before analyzing the M*N temperature values, is further configured to: remove an abnormal temperature value among the M temperature values corresponding to the N surface positions.
  • the method when the processor analyzes the M*N temperature values, the method is specifically configured to: determine the N surface positions according to M temperature values corresponding to the N surface positions. Corresponding N temperature differences.
  • the processor when the processor analyzes the M*N temperature values, the processor is specifically configured to:
  • the processor when the processor analyzes the M*N temperature values, the processor is specifically configured to:
  • the processor when analyzing the M*N temperature values, is specifically configured to: output the N temperature average values and/or the N temperatures in a Cantor pattern manner Variance value.
  • the processor is further configured to:
  • the processor is also used to:
  • Correlation analysis is performed on M temperature values corresponding to the respective M temperature values of the N1 surface positions of the first measured area and the N2 surface positions of the second measured area to obtain N/2 Correlation coefficients.
  • the M*N temperature values corresponding to the measured area of the measured object are measured by a contact type, multi-point continuous measurement manner, where M corresponds to the number of acquisitions, and N corresponds to N of the measured area.
  • the surface position, and then the M*N temperature values obtained by the analysis obtain the temperature value distribution characteristics of the measured area, and provide auxiliary data support for the lesion determination of the measured area of the measured object, which is beneficial to improve the judgment result.
  • Accuracy, and the implementation method is simple and convenient.
  • FIG. 1 is a schematic structural diagram of a data temperature analysis system according to an embodiment of the present application.
  • FIG. 2 is a schematic flow chart of a temperature analysis method according to an embodiment of the present application.
  • FIG. 3 is a schematic flow chart of a temperature analysis method according to another embodiment of the present application.
  • step 202 is a schematic flow chart of an alternative implementation of step 202;
  • FIG. 5 is a schematic flowchart of another alternative implementation manner of step 202;
  • step 202 is a schematic flow chart of still another alternative implementation manner of step 202;
  • FIG. 7 is a schematic flowchart diagram of a temperature analysis method according to another embodiment of the present application.
  • FIG. 8 is a schematic structural diagram of a temperature analysis device according to an embodiment of the present application.
  • FIG. 9 is a schematic structural diagram of an electronic device according to an embodiment of the present application.
  • the temperature analysis method provided by the embodiment of the present application can be implemented based on the temperature analysis system shown in FIG. 1, but is not limited thereto.
  • the temperature analysis system includes a temperature collection device 10 and a temperature analysis device 20, and the temperature collection device 10 and the temperature analysis device 20 are communicatively coupled.
  • the temperature collecting device 10 may be used to measure the temperature of the surface of the measured object to be tested, and based on the temperature measurement result, may be used to determine whether the measured object has a lesion.
  • the temperature collection device 10 can be used to measure the surface of the human breast. The temperature based on the temperature measurement can help determine whether the breast of the human body has a tumor lesion.
  • the measurement of the body surface temperature adopts a multi-point continuous measurement mode, which is simply measured in terms of time and continuous measurement for a long time, from a spatial perspective. Measured in such a way as to measure the temperature of multiple surface locations in one measurement.
  • the temperature collecting device 10 in the embodiment of the present application may have the following structural features: a plurality of temperature sensors may be distributed on the side of the material close to the skin, such as a mesh shape, on the side of the material close to the skin. Multiple temperature sensors are distributed. In combination with different application scenarios, the plurality of temperature sensors may be distributed in various forms, for example, in a scene for measuring the surface temperature of the breast, and may be distributed in a grid pattern of left and right symmetry.
  • the temperature collecting device 10 can be controlled based on the control elements in the temperature collecting device 10 to continuously collect the surface of the breast at a certain acquisition frequency. The temperature, so that at each acquisition time, the temperature values at multiple locations on the surface of the mammary gland can be obtained.
  • the temperature collecting device 10 may transmit the obtained plurality of temperature values to the temperature analyzing device 20 after obtaining a plurality of temperature values each time, for the temperature analyzing device 20 to pass through a plurality of temperatures obtained for each acquisition thereof.
  • the value, or all the temperature values obtained by multiple acquisitions, are analyzed to obtain a temperature value distribution characteristic to assist in the determination of the lesion.
  • the temperature analysis device 20 in this embodiment may be any device having a data storage and data processing function such as a server, a computer, a tablet, an intelligent terminal, or the like.
  • the temperature collecting device 10 and the temperature analyzing device 20 may be connected by wireless or wired network.
  • the network standard of the mobile network may be 2G (GSM), 2.5G (GPRS), 3G (WCDMA, TD-SCDMA, CDMA2000). UTMS), 4G (LTE), 4G+ (LTE+), WiMax, and the like.
  • the temperature collecting device 10 can also be communicably connected to the temperature analyzing device 20 by wireless communication methods such as Bluetooth, Wi-Fi, infrared, and the like.
  • FIG. 2 is a schematic flow chart of a temperature analysis method according to an embodiment of the present application. As shown in FIG. 2, the method includes:
  • Step 201 Obtain M*N temperature values corresponding to the measured area of the measured object, and M*N temperature values are obtained by continuously collecting the measured area by a contact measurement method, where M corresponds to the number of times of acquisition, and N corresponds to N surface positions of the area to be tested.
  • the object to be measured in step 201 is the human body to be measured, and the measured area is a certain area of the surface of the breast.
  • the temperature collection device 10 can be set in advance, such as the acquisition frequency, the measurement time, and the like, that is, for example, during what period of time the temperature collection device 10 is configured to continuously collect the surface temperature of the breast, and thus the set acquisition frequency.
  • the measurement time determines the value of M in the above step 201.
  • the temperature of the surface of the mammary gland may change due to the activity of the object to be measured, so the measurement time generally selected is the sleep time at night. Because at night, people's activities are the smallest in a day, and people's body temperature is also relatively low in a day. At this time, the influence of the temperature of the breast tumor on the surface of the breast surface is more prominent than the influence of the motion of the measured object.
  • a separate temperature collecting device 10 can be used for each breast, also The temperature collecting device 10 can be used: in a temperature collecting device 10, including a control component and two temperature collecting portions, the two temperature collecting portions share the control component and are electrically connected to the control component respectively, and the two temperature collecting portions can be It is achieved as mentioned above: based on the material adhering to the surface of the breast, a plurality of temperature sensors are distributed thereon, such as in a symmetrical grid shape.
  • the scene in which the bilateral breasts are simultaneously measured is only an optional scene, and is not limited thereto.
  • the above N temperature values refer to the total number of surface positions of the bilateral breast surface, one Generally speaking, the number of temperature sensors corresponding to the surface of the breast on both sides is the same, and the position corresponds. Therefore, the position of the surface of each breast can be regarded as N/2.
  • the above N temperature values refer to the number of measured positions on the surface of the breast on the side to be tested.
  • the M corresponds to the number of acquisitions
  • N corresponds to the N surface positions of the measured area. Therefore, the M*N temperature values are continuously measured by the contact measurement method. The temperature values obtained from the N surface positions of the measured area are acquired.
  • the contact measurement is relative to a non-contact measurement method such as infrared, and it can be understood that the temperature sensor measures the temperature in such a manner as to be attached to the surface.
  • the temperature collecting device 10 can transmit the collected N temperature values to the temperature analyzing device 20 at each acquisition time, so that the temperature analyzing device 20 can finally obtain the N temperature values transmitted by the temperature collecting device 10 each time. M*N temperature values corresponding to the measured area of the measured object.
  • Step 202 Analyze M*N temperature values to obtain temperature value distribution characteristics.
  • the temperature analysis device 20 can perform a certain data analysis process on the acquired M*N temperature values to obtain a temperature value distribution characteristic of the measured region such as the breast, and provide basic data support for determining the breast tumor lesion.
  • step 201 may further include the following steps:
  • Step 301 Remove an abnormal temperature value among M temperature values corresponding to each of the N surface positions.
  • the temperature collection device 10 can send the temperature value and the temperature value when transmitting the collected temperature value to the temperature analysis device 20.
  • the acquisition time and the correspondence of the sensor identification are sent to the temperature analysis device 20, so that the temperature analysis device 20 can analyze the data to determine the information content: which sensor is the temperature value collected at what time.
  • the temperature analysis device may store the M temperature information corresponding to each sensor identifier based on the sensor identifier, wherein the temperature information may include a temperature value and an acquisition time. For example, it is stored in the form of a table.
  • the columns in the table represent the sensor identification, and the rows represent the corresponding temperature information. Since the number of positions to be measured is N, each position is measured M times, so that the number of columns in the table is N, the number of rows For M. It can be understood that since the sensor identifiers corresponding to different positions are different, the sensor identifiers are equivalent to characterizing different positions.
  • the temperature analysis device 20 can obtain M temperature values corresponding to each position, and can sort the M temperature values based on the acquisition time, so that the temperature analysis device 20 obtains one for any of the measured positions. A sequence of temperature values containing M temperature values. Further, the temperature analyzing device 20 may remove the abnormal data in the temperature value sequence based on the time domain characteristic of the temperature value sequence. Further, the temperature analyzing device 20 may further uniformly process the temperature value sequence after the abnormal data is removed in time. Continuous data segment.
  • the abnormal temperature value is removed based on the time domain characteristic of the sequence of temperature values, taking into account that under normal circumstances, the body temperature of the human body is continuous and does not suddenly jump, and thus, for the M temperature values corresponding to one measured position, The temperature value of a sudden jump should belong to the abnormal situation during the acquisition process, and the body temperature of the measured object does not really jump.
  • the body temperature change is relatively flat. Generally, the body temperature change will not exceed 0.05 degrees per second. If the actual temperature value changes exceed this range, it should belong to the abnormal situation during the collection process, not measured. The body temperature of the object really changes at this rate. Therefore, the abnormal temperature value of the M temperature values corresponding to each position can be removed based on the above rule.
  • the data analysis device 20 performs a uniform processing over time on successive data segments in the sequence of temperature values after removal of the abnormal temperature value to provide a reliable, temporally continuous and uniform continuous data segment for subsequent use.
  • the continuous data segment refers to a data segment in which the time interval corresponding to all adjacent temperature values is less than a preset time interval threshold in the temperature value sequence after the abnormal temperature value is removed.
  • removing the abnormal temperature value therein can also be achieved as follows:
  • a time window is set, which reflects the time domain characteristic of the temperature, and simply is the characteristic that the temperature changes with time.
  • the body temperature in order to continuously collect human body temperature, in general, the body temperature does not change more than 0.5 degrees within 3 minutes, and according to this characteristic, the time window can be set to 3 minutes. This means that in the body temperature data within 3 minutes, the body temperature temperature value exceeding 0.5 degrees is an abnormal temperature value.
  • removing the abnormal temperature value in any of the data segments may be:
  • the temperature value in the data segment where the volatility is greater than the fluctuation threshold is removed.
  • analyzing M*N temperature values to obtain a temperature value distribution feature may include the following steps:
  • Step 401 Determine N temperature difference values corresponding to the N surface positions according to the M temperature values corresponding to the N surface positions.
  • Step 402 Output N temperature difference values.
  • the highest temperature value and the lowest temperature value can be determined therefrom, and the difference between the two is the temperature difference corresponding to the sensor identifier, thereby finally obtaining N surface positions.
  • the corresponding temperature difference is the temperature difference corresponding to the sensor identifier.
  • the output mode of the N temperature difference values may be simply outputted in a column of values, or may be output in a curved manner, outputted in a Cantor mode, etc., and the output mode is not specifically limited.
  • the degree of temperature change at different positions during the measurement time can be visually found, thereby providing an auxiliary basis for the determination of the lesion.
  • analyzing M*N temperature values to obtain a temperature value distribution feature may include the following steps:
  • Step 501 Determine N temperature average values corresponding to the N surface positions according to the M temperature values corresponding to the N surface positions.
  • an average value of the M temperature values can be obtained, so that a temperature average value corresponding to each of the N positions can be finally obtained, which reflects each time during the measurement time.
  • the combination of the average temperature value can aid in the determination of the lesion.
  • Step 502 Determine N temperature variance values corresponding to the N surface positions according to the M temperature values corresponding to the N surface positions and the N temperature average values.
  • This embodiment provides another parameter that characterizes the degree of temperature change, that is, the temperature variance value.
  • the calculation method of the temperature variance value can be determined based on the general variance calculation method, that is, according to the M temperature values corresponding to the N surface positions and the N temperature average values that have been obtained, the N surface positions are respectively determined. Temperature variance value.
  • Step 503 Output N temperature average values and/or N temperature variance values in a Cantor diagram manner.
  • N temperature average values and/or N temperature variance values are outputted in a Cantor diagram manner, and the temperature conditions and temperature changes at different positions can be visually seen.
  • step 502 is an optional step, and the simultaneous existence of step 501 and step 502 is not strictly defined.
  • the measured area may include a first measured area and a second measured area, where the first measured area and the second measured area have positional symmetry
  • the measured area refers to the bilateral mammary gland region
  • the first measured region and the second measured region are respectively the left breast region and the right breast region
  • Analyzing the M*N temperature values to obtain a temperature value distribution feature may also include the following steps:
  • Step 601 Perform correlation analysis on M temperature values corresponding to respective M temperature values of N1 surface positions of the first measured area and N2 surface positions of the second measured area to obtain N/2
  • the correlation coefficient may include a first measured area and a second measured area.
  • a is one of N1 surface positions in the first measured area
  • b is located in one of N2 surface positions in the second measured area, and both have positional symmetry. Since M temperature measurements are taken at each position during the measurement time, the a and b positions respectively correspond to M temperature values. Based on the preset correlation coefficient calculation method, by performing correlation calculation on the M temperature values corresponding to the positions a and b respectively, the corresponding correlation coefficient can be obtained, and based on this, N/2 correlation coefficients can be finally obtained, and the correlation is combined.
  • the coefficient can assist in the determination of the lesion in the measured area. For example, for the correlation coefficient of the two positions a and b above, if there is no lesion on one side of the lesion, the correlation coefficient of the two is often low.
  • the M*N temperature values corresponding to the measured area of the measured object are measured by the contact type and multi-point continuous measurement, where M corresponds to the number of acquisitions, and N corresponds to the measured area.
  • M corresponds to the number of acquisitions
  • N corresponds to the measured area.
  • the N surface positions, and then the M*N temperature values obtained by the analysis, to obtain the temperature value distribution characteristics of the measured area, provide auxiliary data support for the lesion determination of the measured area of the measured object, and are beneficial to improve The accuracy of the determination result is simple and convenient.
  • the plurality of different metrics provided above for measuring the temperature value distribution characteristics of the measured area may be assisted by a combination of one or more of the parameters. Determine the determination of the lesion in the area.
  • the determination assistance can be provided by comparing with the reference value, as shown in FIG.
  • FIG. 7 is a schematic flowchart of a temperature analysis method according to another embodiment of the present application. As shown in FIG. 7 , after step 202, the following steps may be further included:
  • Step 701 Acquire a reference temperature value distribution feature corresponding to the measured area obtained in advance.
  • Step 702 Compare the temperature value distribution characteristic with the reference temperature value distribution characteristic to determine whether the temperature value distribution characteristic is abnormal.
  • the reference temperature value distribution feature corresponding to the measured area refers to a temperature value distribution characteristic corresponding to the case where the measured area of the measured object does not have a lesion.
  • the reference temperature value distribution feature can be obtained by monitoring and analyzing the temperature of the measured area for a long time.
  • the reference temperature value distribution feature may also be a statistical feature obtained by performing long-term temperature monitoring and analysis on a plurality of different measured objects in different measured objects, and reflecting a temperature value distribution corresponding to a certain population. feature.
  • FIG. 8 is a schematic structural diagram of a temperature analysis apparatus according to an embodiment of the present invention. As shown in FIG. 8 , the apparatus includes: a first acquisition module 81 and an analysis module 82.
  • the first obtaining module 81 is configured to acquire M*N temperature values corresponding to the measured area of the measured object, where the M*N temperature values are obtained by continuously collecting the measured area by a contact measurement method.
  • M corresponds to the number of acquisitions
  • N corresponds to N surface positions of the measured area.
  • the analysis module 82 is configured to analyze the M*N temperature values to obtain a temperature value distribution feature.
  • the apparatus further includes: a first removal module 83.
  • the first removing module 83 is configured to remove an abnormal temperature value of the abnormal temperature values among the M temperature values corresponding to the N surface positions.
  • the analyzing module 82 includes:
  • the temperature difference analyzing unit 821 is configured to determine N temperature difference values corresponding to the N surface positions according to the M temperature values corresponding to the N surface positions.
  • the analyzing module 82 includes:
  • the mean value analyzing unit 822 is configured to determine N temperature average values corresponding to the N surface positions according to the M temperature values corresponding to the N surface positions.
  • the analyzing module 82 includes:
  • the variance analysis unit 823 is configured to determine N temperature variance values corresponding to the N surface positions according to the M temperature values and the N temperature average values.
  • the analysis module 82 includes:
  • the correlation analysis unit 824 is configured to correlate M temperature values corresponding to the N1 surface positions of the first measured area and the M temperature values corresponding to the N2 surface positions of the second measured area. Sex analysis to obtain N/2 correlation coefficients.
  • the apparatus further includes:
  • the second obtaining module 84 is configured to obtain a reference temperature value distribution feature corresponding to the measured area that is obtained in advance;
  • the comparison module 85 is configured to compare the temperature value distribution feature with the reference temperature value distribution feature to determine whether the temperature value distribution feature is abnormal.
  • the temperature analysis device provided in this embodiment may be used to perform the process provided by the foregoing method embodiments, and details are not described herein again.
  • the temperature analysis device measures the M*N temperature values corresponding to the measured area of the measured object by means of contact type and multi-point continuous measurement, where M corresponds to the number of acquisitions, and N corresponds to the measured area. N surface positions, and then the M*N temperature values obtained by the analysis, to obtain the temperature value distribution characteristics of the measured area, and provide auxiliary data support for the lesion determination of the measured area of the measured object, which is beneficial to improve the determination.
  • M corresponds to the number of acquisitions
  • N corresponds to the measured area.
  • N corresponds to the measured area.
  • N corresponds to the measured area.
  • N corresponds to the measured area.
  • N corresponds to the measured area.
  • N corresponds to the measured area.
  • N corresponds to the measured area.
  • N corresponds to the measured area.
  • N corresponds to the measured area.
  • N corresponds to the measured area.
  • N corresponds to the measured area.
  • N corresponds to the measured area.
  • the temperature analysis device can be implemented as an electronic device including: a memory 91, a processor 92, and a communication interface 93.
  • the memory 91 is configured to store a computer program.
  • the memory 91 can also be configured to store other various data to support operation on the electronic device. Examples of such data include instructions for any application or method operating on an electronic device, contact data, phone book data, messages, pictures, videos, and the like.
  • the memory 91 can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (SRAM), electrically erasable programmable read only memory (EEPROM), erasable.
  • SRAM static random access memory
  • EEPROM electrically erasable programmable read only memory
  • EPROM Programmable Read Only Memory
  • PROM Programmable Read Only Memory
  • ROM Read Only Memory
  • Magnetic Memory Flash Memory
  • Disk Disk or Optical Disk.
  • the communication interface 93 is configured to implement communication between the electronic device and other devices, such as wired or wireless communication.
  • the electronic device can access a wireless network based on a communication standard such as WiFi, 2G or 3G, or a combination thereof.
  • the communication interface 93 receives broadcast signals or broadcast associated information from an external broadcast management system via a broadcast channel.
  • communication interface 93 also includes a near field communication (NFC) module to facilitate short range communication.
  • NFC near field communication
  • the NFC module can be implemented based on radio frequency identification (RFID) technology, infrared data association (IrDA) technology, ultra-wideband (UWB) technology, Bluetooth (BT) technology, and other technologies.
  • RFID radio frequency identification
  • IrDA infrared data association
  • UWB ultra-wideband
  • Bluetooth Bluetooth
  • a processor 92 coupled to the memory 91 and the communication interface 93, is configured to execute a computer program in the memory 91 for:
  • the M*N temperature values corresponding to the measured area of the measured object are obtained through the communication interface 93, and the M*N temperature values are obtained by continuously collecting the measured area by the contact measurement method, and M corresponds to the number of times of collection. , N corresponds to N surface positions of the measured area;
  • the M*N temperature values are analyzed to obtain temperature value distribution characteristics.
  • the processor 92 described above is also configured to execute by calling a computer program in the memory 91. All or part of the steps in the foregoing method embodiments are not repeated herein.
  • the electronic device further includes: a display 94, a power supply component 95, an audio component 96, and the like. Only some of the components are schematically illustrated in FIG. 9, and it is not meant that the electronic device includes only the components shown in FIG.
  • Display 94 includes a screen whose screen may include a liquid crystal display (LCD) and a touch panel (TP). If the screen includes a touch panel, the screen can be implemented as a touch screen to receive input signals from the user.
  • the touch panel includes one or more touch sensors to sense touches, slides, and gestures on the touch panel. The touch sensor may sense not only the boundary of the touch or sliding action, but also the duration and pressure associated with the touch or slide operation.
  • a power supply assembly 95 provides power to various components of the electronic device.
  • Power component 95 can include a power management system, one or more power sources, and other components associated with generating, managing, and distributing power for client devices.
  • the audio component 96 is configured to output and/or input an audio signal.
  • the audio component 96 includes a microphone (MIC) that is configured to receive an external audio signal when the electronic device is in an operational mode, such as a call mode, a recording mode, and a voice recognition mode.
  • the received audio signal may be further stored in the memory 91 or transmitted via the communication interface 93.
  • audio component 96 also includes a speaker for outputting an audio signal.
  • the embodiment of the present application further provides a computer storage medium suitable for a computer program, where the computer storage medium stores the following program instructions:
  • a first program instruction configured to acquire M*N temperature values corresponding to the measured area of the measured object, where the M*N temperature values are obtained by continuously collecting the measured area by a contact measurement manner, where M corresponds to In the number of acquisitions, N1 corresponds to N surface positions of the measured area;
  • the method flow provided by the foregoing method embodiment can be implemented, and the temperature value distribution feature of the measured area can be obtained simply and conveniently, and the lesion determination of the measured area of the measured object can be assisted. data support.
  • embodiments of the present invention can be provided as a method, system, or computer program product. Accordingly, the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment, or a combination of software and hardware. Moreover, the invention can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.
  • computer-usable storage media including but not limited to disk storage, CD-ROM, optical storage, etc.
  • the computer program instructions can also be stored in a computer readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture comprising the instruction device.
  • the apparatus implements the functions specified in one or more blocks of a flow or a flow and/or block diagram of the flowchart.
  • These computer program instructions can also be loaded onto a computer or other programmable data processing device such that a series of operational steps are performed on a computer or other programmable device to produce computer-implemented processing for execution on a computer or other programmable device.
  • the instructions provide steps for implementing the functions specified in one or more of the flow or in a block or blocks of a flow diagram.
  • a computing device includes one or more processors (CPUs), input/output interfaces, network interfaces, and memory.
  • processors CPUs
  • input/output interfaces network interfaces
  • memory volatile and non-volatile memory
  • the memory may include non-persistent memory, random access memory (RAM), and/or non-volatile memory in a computer readable medium, such as read only memory (ROM) or flash memory.
  • RAM random access memory
  • ROM read only memory
  • Memory is an example of a computer readable medium.
  • Computer readable media includes both permanent and non-persistent, removable and non-removable media.
  • Information storage can be implemented by any method or technology.
  • the information can be computer readable instructions, data structures, modules of programs, or other data.
  • Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read only memory. (ROM), electrically erasable programmable read only memory (EEPROM), flash memory or other memory technology, compact disk read only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, Magnetic tape cartridges, magnetic tape storage or other magnetic storage devices or any other non-transportable media can be used to store information that can be accessed by a computing device.
  • computer readable media does not include temporary storage of computer readable media, such as modulated data signals and carrier waves.
  • embodiments of the present application can be provided as a method, system, or computer program product.
  • the present application can take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment in combination of software and hardware.
  • the application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) including computer usable program code.

Landscapes

  • Life Sciences & Earth Sciences (AREA)
  • Health & Medical Sciences (AREA)
  • Medical Informatics (AREA)
  • Biophysics (AREA)
  • Pathology (AREA)
  • Engineering & Computer Science (AREA)
  • Biomedical Technology (AREA)
  • Heart & Thoracic Surgery (AREA)
  • Physics & Mathematics (AREA)
  • Molecular Biology (AREA)
  • Surgery (AREA)
  • Animal Behavior & Ethology (AREA)
  • General Health & Medical Sciences (AREA)
  • Public Health (AREA)
  • Veterinary Medicine (AREA)
  • Measuring And Recording Apparatus For Diagnosis (AREA)

Abstract

La présente invention concerne un procédé et un dispositif d'analyse de température. Le procédé d'analyse de température comprend les étapes consistant à : acquérir M x N valeurs de température correspondant à une zone soumise à l'essai d'un objet d'essai, les M x N valeurs de température étant acquises au moyen de la réalisation de mesures consécutives basées sur un contact sur la zone soumise à l'essai, M correspond au nombre des mesures, et N correspond à N positions de surface de la zone soumise à l'essai (201); et analyser les M x N valeurs de température pour acquérir une caractéristique de distribution de valeur de température (202). Par la mesure de M x N valeurs de température correspondant à une zone soumise à l'essai d'un objet d'essai au moyen de la réalisation de mesures multipoints à base de contact consécutives, et analyser en outre les M x N valeurs de température pour acquérir une caractéristique de distribution de valeur de température de la zone soumise à l'essai, la présente invention fournit un support de données auxiliaires pour la détermination d'une région de la zone soumise à l'essai de l'objet à l'essai, améliore la précision du résultat de la détermination, et est facile et pratique à mettre en œuvre.
PCT/CN2017/072129 2017-01-22 2017-01-22 Procédé et dispositif d'analyse de température WO2018133080A1 (fr)

Priority Applications (1)

Application Number Priority Date Filing Date Title
PCT/CN2017/072129 WO2018133080A1 (fr) 2017-01-22 2017-01-22 Procédé et dispositif d'analyse de température

Applications Claiming Priority (1)

Application Number Priority Date Filing Date Title
PCT/CN2017/072129 WO2018133080A1 (fr) 2017-01-22 2017-01-22 Procédé et dispositif d'analyse de température

Publications (1)

Publication Number Publication Date
WO2018133080A1 true WO2018133080A1 (fr) 2018-07-26

Family

ID=62907541

Family Applications (1)

Application Number Title Priority Date Filing Date
PCT/CN2017/072129 WO2018133080A1 (fr) 2017-01-22 2017-01-22 Procédé et dispositif d'analyse de température

Country Status (1)

Country Link
WO (1) WO2018133080A1 (fr)

Cited By (1)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111337138A (zh) * 2020-03-17 2020-06-26 北京领邦智能装备股份公司 红外体温测量方法、装置、设备、系统及可读存储介质

Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6086247A (en) * 1998-02-05 2000-07-11 Von Hollen; Dirk Differential temperature sensor device for use in the detection of breast cancer and breast disease
CN105260620A (zh) * 2015-11-09 2016-01-20 上海温尔信息科技有限公司 基于人体体温建模的健康评估方法及专家系统
CN105520721A (zh) * 2015-12-18 2016-04-27 上海温尔信息科技有限公司 基于体表温度场的癌变区域的精准测量及识别装置
CN105662361A (zh) * 2015-12-18 2016-06-15 上海温尔信息科技有限公司 体温持续监测仪
CN105686810A (zh) * 2015-07-31 2016-06-22 上海温尔信息科技有限公司 一种温度测量方法及装置
CN105996981A (zh) * 2015-03-25 2016-10-12 施乐公司 用于乳癌筛查的软件界面工具
CN106096608A (zh) * 2016-06-14 2016-11-09 上海温尔信息科技有限公司 胸部温度异常区定位方法及装置

Patent Citations (7)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
US6086247A (en) * 1998-02-05 2000-07-11 Von Hollen; Dirk Differential temperature sensor device for use in the detection of breast cancer and breast disease
CN105996981A (zh) * 2015-03-25 2016-10-12 施乐公司 用于乳癌筛查的软件界面工具
CN105686810A (zh) * 2015-07-31 2016-06-22 上海温尔信息科技有限公司 一种温度测量方法及装置
CN105260620A (zh) * 2015-11-09 2016-01-20 上海温尔信息科技有限公司 基于人体体温建模的健康评估方法及专家系统
CN105520721A (zh) * 2015-12-18 2016-04-27 上海温尔信息科技有限公司 基于体表温度场的癌变区域的精准测量及识别装置
CN105662361A (zh) * 2015-12-18 2016-06-15 上海温尔信息科技有限公司 体温持续监测仪
CN106096608A (zh) * 2016-06-14 2016-11-09 上海温尔信息科技有限公司 胸部温度异常区定位方法及装置

Cited By (2)

* Cited by examiner, † Cited by third party
Publication number Priority date Publication date Assignee Title
CN111337138A (zh) * 2020-03-17 2020-06-26 北京领邦智能装备股份公司 红外体温测量方法、装置、设备、系统及可读存储介质
CN111337138B (zh) * 2020-03-17 2022-02-18 北京领邦智能装备股份公司 红外体温测量方法、装置、设备、系统及可读存储介质

Similar Documents

Publication Publication Date Title
US20170000392A1 (en) Micro-Camera Based Health Monitor
Francis et al. Automatic detection of abnormal breast thermograms using asymmetry analysis of texture features
CN109890274A (zh) 用于确定对象的核心体温的设备、系统和方法
Tran et al. A robust real time system for remote heart rate measurement via camera
US10278649B2 (en) Methods and systems for detecting cancer
US20120323085A1 (en) Information processing device, information processing method, and information processing program
JP2009279076A (ja) 監視システム
WO2018202065A1 (fr) Système à reconnaissance artificielle pour la recommandation d'un produit et d'un service cosmétiques
US9928586B2 (en) Devices and methods for determining menstrual blood loss
CA2882080A1 (fr) Detection de caracteristique physiologique en temps reel sur la base de composantes de lumiere reflechies
KR102539144B1 (ko) 개인화된 단위 스펙트럼 획득 장치 및 방법과, 생체 성분 추정 장치 및 방법
Zaunseder et al. Spatio-temporal analysis of blood perfusion by imaging photoplethysmography
US10750959B2 (en) Heart rate estimation from face videos using quality based fusion
WO2018133080A1 (fr) Procédé et dispositif d'analyse de température
EP3318179B1 (fr) Procédé pour mesurer la fréquence respiratoire et la fréquence cardiaque à l'aide des deux caméras d'un téléphone intelligent
CN108652621B (zh) 一种吞咽实时监测方法及其系统
Pal et al. Improved heart rate detection using smart phone
Cui et al. Non-contact time varying heart rate monitoring in exercise by video camera
Wang et al. Camera-based respiration monitoring: Motion and PPG-based measurement
WO2018126366A1 (fr) Procédé et appareil de mesure de température
WO2018032610A1 (fr) Dispositif et procédé de mesure de fréquence cardiaque
Singh et al. A new approach for identification of heartbeats in multimodal physiological signals
US20190209082A1 (en) Determining an intimate activity by a detection device
KR102132925B1 (ko) 피부 영상 기반 혈량 측정 방법 및 이를 지원하는 장치
CN115426947A (zh) Sp02小程序：ai辅助sp02测量app

Legal Events

Date Code Title Description
121 Ep: the epo has been informed by wipo that ep was designated in this application

Ref document number: 17892102

Country of ref document: EP

Kind code of ref document: A1

NENP Non-entry into the national phase

Ref country code: DE

32PN Ep: public notification in the ep bulletin as address of the adressee cannot be established

Free format text: NOTING OF LOSS OF RIGHTS PURSUANT TO RULE 112(1) EPC (EPO FORM 1205A DATED 31.12.2019)

122 Ep: pct application non-entry in european phase

Ref document number: 17892102

Country of ref document: EP

Kind code of ref document: A1