CN111588353A - Body temperature measuring method - Google Patents
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- 230000036760 body temperature Effects 0.000 title claims abstract description 134
- 238000000034 method Methods 0.000 title claims abstract description 36
- 210000000056 organ Anatomy 0.000 claims abstract description 43
- 208000031636 Body Temperature Changes Diseases 0.000 claims abstract description 38
- 238000001514 detection method Methods 0.000 claims abstract description 14
- 238000012544 monitoring process Methods 0.000 claims description 60
- 230000011218 segmentation Effects 0.000 claims description 50
- 230000036772 blood pressure Effects 0.000 claims description 23
- 238000009529 body temperature measurement Methods 0.000 claims description 19
- 239000011159 matrix material Substances 0.000 claims description 9
- 230000035487 diastolic blood pressure Effects 0.000 claims description 7
- 230000035488 systolic blood pressure Effects 0.000 claims description 7
- 208000027796 Blood pressure disease Diseases 0.000 claims description 6
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- 210000004204 blood vessel Anatomy 0.000 claims description 4
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- A61B5/01—Measuring temperature of body parts ; Diagnostic temperature sensing, e.g. for malignant or inflamed tissue
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- A—HUMAN NECESSITIES
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- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
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- A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/103—Detecting, measuring or recording devices for testing the shape, pattern, colour, size or movement of the body or parts thereof, for diagnostic purposes
- A61B5/11—Measuring movement of the entire body or parts thereof, e.g. head or hand tremor, mobility of a limb
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Abstract
The invention discloses a body temperature measuring method, which comprises the following steps: acquiring current physical sign data of a user in a current environment, and determining the body temperature change trend of the user by using the current physical sign data and sample physical sign data in the current body temperature environment; acquiring a body temperature compensation value by combining the body temperature change trend with a target organ model; acquiring the human body state of a user every first fixed time within a preset total time; and acquiring a real-time body temperature value of the user by using the human body state and combining the basic data of the user and the body temperature compensation value. The body temperature change trend of the user is obtained by utilizing the physical sign data, the real-time body temperature value is obtained again, the body temperature value of the measured object can be obtained without fully contacting the measured object, the influence of the external temperature on the human body temperature is avoided by obtaining the body temperature compensation value, the final detection result is more accurate, and the problem that the detection result and the actual result have larger deviation due to the fact that the detection result and the actual result are not fully contacted with the measured object and the temperature of the external environment is not interfered is solved.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a body temperature measuring method.
Background
Body temperature is an important body health index, body temperature measurement is one of important indexes for evaluating the health state of a user, the timeliness, the accuracy and the reliability of body temperature measurement directly influence the diagnosis, treatment and nursing effects of diseases, and particularly the perioperative body temperature measurement is of great clinical significance. Many anesthesiologists often ignore body temperature monitoring and hypothermia prevention during perioperative periods, thereby resulting in a higher incidence of "hypothermia". Hypothermia is prone to the adverse consequences of delayed user recovery, reduced resistance, slow wound healing, etc. In general clinical monitoring and treatment, medical care personnel are also often concerned about the changes in body temperature of certain specific users over time.
The current body temperature measuring methods mainly comprise two methods, namely contact temperature measurement and non-contact temperature measurement, wherein the contact temperature measurement is carried out by a thermometer and the like, the non-contact temperature measurement technology mainly represents an infrared thermometer and the like, infrared rays are refracted to the skin of a person, and the temperature of the person is measured by utilizing the temperature relationship between the heat radiation of the person and the surface of the person, and the two methods have the following defects: 1. if not enough contact with the testee can make the result of detection take place very big deviation, lead to appearing the wrong problem of body temperature statistics, 2, the temperature of external environment can disturb the testing result of infrared ray to make testing result and actual result take place great deviation.
Disclosure of Invention
Aiming at the displayed problems, the method obtains the body temperature change trend based on the physical sign data of the human body, and then removes the interference factors of the physical sign data to measure the real-time body temperature value of the user.
A body temperature measurement method is applied to wearable sign detection equipment and comprises the following steps:
acquiring current physical sign data of a user in a current environment, and determining a body temperature change trend of the user by using the current physical sign data and sample physical sign data in the current body temperature environment;
acquiring a body temperature compensation value by combining the body temperature change trend with a target organ model;
acquiring the human body state of a user every first fixed time within a preset total time;
and acquiring a real-time body temperature value of the user by utilizing the human body state in combination with basic data of the user and the body temperature compensation value, wherein the basic data comprises the age and the sex of the user.
Preferably, before obtaining current sign data of a user in a current environment and determining a body temperature change trend of the user by using the current sign data and sample sign data in the current body temperature environment, the method further includes:
acquiring the current temperature of the current environment;
comparing the current temperature with a preset normal temperature, and confirming the difference value between the current temperature and the preset normal temperature;
and determining an error value of the sign data according to the difference value, and eliminating the influence of the ambient temperature on all sign data according to the error value, wherein all sign data comprise the sample sign data and the current sign data.
Preferably, the obtaining of current physical sign data of the user in the current environment, and determining the body temperature change trend of the user by using the current physical sign data and the sample physical sign data in the current body temperature environment includes:
acquiring first characterization data of the user at the current moment under the current environment;
calculating the first body characteristic data and an error value to obtain second body characteristic data;
confirming that the second body sign data is the current body sign data;
acquiring a preset number of sample physical sign data in the current body temperature environment;
establishing a preset line graph;
comparing the current sign data with the preset number of sample sign data to obtain a first comparison result, determining a first body temperature change trend of the user according to the first comparison result, and displaying the first body temperature change trend on the preset line graph.
Preferably, the current physical sign data includes: blood pressure and venous blood vessel temperature.
Preferably, before the body temperature compensation value is obtained by using the body temperature trend in combination with the target organ model, the method further comprises:
acquiring medical projection data of the user;
performing three-dimensional reconstruction on the medical projection data to obtain an original organ model;
acquiring pixel information of each organ in the medical projection data, and inputting the pixel information into the original organ model for training to generate the target organ model.
Preferably, the three-dimensional reconstruction of the medical projection data to obtain an original organ model includes:
performing filtering and smoothing preprocessing on the medical projection data, wherein the medical projection data is used for acquiring an organ image;
acquiring a two-dimensional image of the preprocessed medical projection data;
segmenting the two-dimensional image to obtain n segmentation sequences;
establishing a three-dimensional coordinate system according to the n segmentation sequences;
counting the current segmentation sequence of each organ in the two-dimensional image in the n segmentation sequences;
extracting feature points of two adjacent current segmentation sequences in the current segmentation sequences by using an SIFT feature matching algorithm, and determining a three-dimensional coordinate point of each organ based on the feature points;
and constructing a model in the three-dimensional coordinate system according to the three-dimensional coordinate points to generate the original organ model.
Preferably, extracting the feature points of the current segmentation sequence may further be performed by:
A. calculating the direction gradient of the current segmentation sequence;
wherein, FixFor the gradient of the ith current segmentation sequence in the x direction, FiyFor the gradient of the ith current segmentation sequence in the y direction, FiFor the ith current slicing sequence,
in order to sign the operation of the gradient,(a, b) is a unit vector in the x direction, (c, d) is a unit vector in the y direction;
B. determining a weighting matrix M for an ith current segmentation sequencei；
Wherein A isi、Bi、CiThe mean value of the gradient in the neighborhood of the (u, v) signal point in the ith current segmentation sequence can be expressed as:
wherein σiThe standard deviation of the ith current segmentation sequence is taken as the standard deviation of the ith current segmentation sequence;
C. obtaining a feature point set of a current segmentation sequence;
Ti＝{(u,v)|det(Mi)-α*tra(M)＜Q}
wherein, TiFor the set of feature points of the ith current segmentation sequence, det (M)i) Is a weighting matrix MiA determinant value of tra (M)i) Is a weighting matrix Miα is a parameter and Q is a preset threshold.
Preferably, the acquiring a body temperature compensation value by using the body temperature variation trend and combining with a target organ model includes:
counting third physical characteristics data of the user within a second fixed time;
calculating the second volume feature data and the error value to obtain fourth volume feature data;
comparing the fourth physical sign data with the second sample physical sign data to obtain a second comparison result;
determining a second body temperature change trend of the user through the second comparison result, and displaying the second body temperature change trend through a preset line graph;
determining the influence parameters of the physical sign data on the human body temperature and the relationship between the physical sign data and the human body temperature according to the first body temperature change trend and the second body temperature change trend on the preset line graph;
and calculating the body temperature compensation value according to the influence parameters.
Preferably, the acquiring the human body state of the user every first fixed time within the preset total time includes:
acquiring blood pressure (systolic pressure and diastolic pressure) monitoring results of the user every other first fixed time within the preset total time;
determining the current blood pressure sign state of the user according to the monitoring result of the blood pressure (systolic pressure and diastolic pressure);
when the current blood pressure sign state is within a preset blood pressure sign state range, analyzing and calculating the current blood pressure sign state and the basic data of the user to determine an influence deviation correction value of blood pressure diseases on the body temperature;
acquiring heart rate monitoring results of the users at intervals of the first fixed time within the preset total time;
judging whether the user is in a healthy state or not according to the heart rate monitoring result;
determining the human body state of the user according to the judgment result;
the acquiring the real-time body temperature value of the user by combining the human body state with the basic data of the user and the body temperature compensation value comprises the following steps:
when the human body state is in the healthy state, acquiring fifth physical sign data of the user;
acquiring basic data of the user;
inputting the basic data into a pre-established database to obtain the set temperature of a user;
determining the current temperature of the user according to the fifth characteristic data;
correcting the current temperature using a deviation between the current temperature and the set temperature;
calculating the corrected current temperature and the body temperature compensation value to obtain a first body temperature value of the user;
calculating the first body temperature value and the influence deviation correction value of the blood pressure disease on the body temperature to obtain a second body temperature value;
determining the second body temperature value as a real-time body temperature value of the user.
Preferably, the obtaining of the heart rate monitoring result of the user every other first fixed time period within the preset total time period includes:
acquiring a first heart rate monitoring result of the user every other first fixed time within the preset total time;
calculating a normal heart rate value range of the user according to the following formula;
wherein, the xnIs the heart rate value ynThe number of (a), the x1、x2The number of each heart rate value in the m heart rate values every first fixed time length in the preset total time length; said xn-1Is the heart rate value yn-1(ii) said 80% being a fixed threshold;
acquiring a normal heart rate value of the user, wherein the normal heart rate value is an average value of m heart rate values within a first fixed time interval in the preset total time interval;
determining whether the first heart rate monitoring result is equal to the normal heart rate value or within the range of the normal heart rate value;
if so, acquiring a difference value of two adjacent heart rate monitoring values in the first heart rate monitoring result;
otherwise, acquiring the walking steps of the user in each first fixed time, acquiring a standard heart rate value according to the walking steps, and comparing the first heart rate monitoring result with the standard heart rate value to confirm whether the first heart rate monitoring result is normal or not;
determining whether the difference meets a preset condition, wherein the preset condition is that the difference is smaller than a preset threshold value, the obtained difference is unique within a first fixed time interval, and the time points of the two heart rate monitoring values for obtaining the difference are the initial time point and the final time point of the first fixed time interval;
counting the heart rate monitoring values in the first monitoring result corresponding to the difference values meeting the preset conditions to generate a second heart rate monitoring result;
and confirming the second heart rate monitoring result as the heart rate monitoring result of the user every the first fixed time length in the preset total time length.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and drawings.
The technical solution of the present invention is further described in detail by the accompanying drawings and embodiments.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention without limiting the invention in which:
FIG. 1 is a flowchart illustrating a method for measuring body temperature according to the present invention;
FIG. 2 is another flowchart of a method of body temperature measurement according to the present invention;
fig. 3 is a flowchart illustrating another operation of a method of measuring body temperature according to the present invention.
Detailed Description
Reference will now be made in detail to the exemplary embodiments, examples of which are illustrated in the accompanying drawings. When the following description refers to the accompanying drawings, like numbers in different drawings represent the same or similar elements unless otherwise indicated. The implementations described in the exemplary embodiments below are not intended to represent all implementations consistent with the present disclosure. Rather, they are merely examples of apparatus and methods consistent with certain aspects of the present disclosure, as detailed in the appended claims.
Body temperature is an important body health index, body temperature measurement is one of important indexes for evaluating the health state of a user, the timeliness, the accuracy and the reliability of body temperature measurement directly influence the diagnosis, treatment and nursing effects of diseases, and particularly the perioperative body temperature measurement is of great clinical significance. Many anesthesiologists often ignore body temperature monitoring and hypothermia prevention during perioperative periods, thereby resulting in a higher incidence of "hypothermia". Hypothermia is prone to the adverse consequences of delayed user recovery, reduced resistance, slow wound healing, etc. In general clinical monitoring and treatment, medical care personnel are also often concerned about the changes in body temperature of certain specific users over time.
The current body temperature measuring methods mainly comprise two methods, namely contact temperature measurement and non-contact temperature measurement, wherein the contact temperature measurement is carried out by a thermometer and the like, the non-contact temperature measurement technology mainly represents an infrared thermometer and the like, infrared rays are refracted to the skin of a person, and the temperature of the person is measured by utilizing the temperature relationship between the heat radiation of the person and the surface of the person, and the two methods have the following defects: 1. if not enough contact with the testee can make the result of detection take place very big deviation, lead to appearing the wrong problem of body temperature statistics, 2, the temperature of external environment can disturb the testing result of infrared ray to make testing result and actual result take place great deviation. In order to solve the above problems, the present embodiment discloses a method for measuring a real-time body temperature value of a user by obtaining a body temperature variation trend based on physical sign data of a human body and removing an interference factor of the physical sign data.
A body temperature measurement method is applied to wearable sign detection equipment, and as shown in figure 1, the method comprises the following steps:
s101, obtaining current sign data of a user in a current environment, and determining a body temperature change trend of the user by using the current sign data and sample sign data in the current body temperature environment;
step S102, acquiring a body temperature compensation value by combining a body temperature change trend with a target organ model;
s103, acquiring the human body state of the user every first fixed time within the preset total time;
step S104, acquiring a real-time body temperature value of a user by combining the human body state with basic data and a body temperature compensation value of the user, wherein the basic data comprises the age and the sex of the user;
in this embodiment, the body temperature variation trend of the user is determined according to the current physical sign data of the user, and then the body temperature compensation value is obtained by combining the target organ model, where the body temperature compensation value is obtained by converting the influence of the current physical sign data on the human body temperature into positive and negative value compensation for the current body temperature of the user, so as to determine a more accurate body temperature measurement result.
The working principle of the technical scheme is as follows: acquiring current physical sign data of a user in a current environment, and determining the body temperature change trend of the user by using the current physical sign data and sample physical sign data in the current body temperature environment; acquiring a body temperature compensation value by combining the body temperature change trend with a target organ model; acquiring the human body state of a user every first fixed time within a preset total time; and acquiring a real-time body temperature value of the user by using the human body state and combining the basic data of the user and the body temperature compensation value.
The beneficial effects of the above technical scheme are: the body temperature change trend of the user is obtained by utilizing the physical sign data, then the real-time body temperature value of the user is obtained, the body temperature value of the measured object can be obtained without fully contacting the measured object, the influence of the external temperature on the human body temperature is avoided by obtaining the body temperature compensation value, the final detection result is more accurate and error-free, and the problem that the detection result and the actual result have larger deviation due to the fact that the detection result and the actual result are not interfered by the temperature fully contacting the measured object and the temperature of the external environment in the prior art is solved.
In one embodiment, as shown in fig. 2, before obtaining the current vital sign data of the user in the current environment, and determining the body temperature trend of the user by using the current vital sign data and the sample vital sign data in the current body temperature environment, the method further includes:
step S201, acquiring the current temperature of the current environment;
step S202, comparing the current temperature with a preset normal temperature, and confirming a difference value between the current temperature and the preset normal temperature;
and S203, determining an error value of the sign data according to the difference value, and eliminating the influence of the ambient temperature on all sign data according to the error value, wherein all sign data comprise sample sign data and current sign data.
The beneficial effects of the above technical scheme are: further, the influence of the external temperature is eliminated, so that the final detection result is more accurate.
In one embodiment, obtaining current sign data of a user in a current environment, and determining a body temperature change trend of the user by using the current sign data and sample sign data in the current body temperature environment includes:
acquiring first characterization data of a user at the current moment in the current environment;
calculating the first body characteristic data and the error value to obtain second body characteristic data;
confirming that the second physical sign data is current physical sign data;
acquiring a preset number of sample physical sign data in a current body temperature environment;
establishing a preset line graph;
the current sign data and the sample sign data with the preset number are compared, a first comparison result is obtained, a first body temperature change trend of the user is determined according to the first comparison result, and the first body temperature change trend is displayed on a preset line graph.
The technical scheme has the advantages that the second body characteristic data is more accurately confirmed to be the current body characteristic data, the relationship between the body temperature and the body characteristic data can be roughly known according to the first body temperature change trend, and a good sample is provided for monitoring the body temperature of the user.
In one embodiment, the current vital sign data includes: blood pressure and venous blood vessel temperature.
The beneficial effects of the above technical scheme are: the blood pressure and the venous blood vessel temperature can calculate the temperature of the user more intuitively.
In one embodiment, as shown in fig. 3, before the body temperature compensation value is obtained by using the body temperature trend in combination with the target organ model, the method further includes:
s301, acquiring medical projection data of a user;
s302, three-dimensional reconstruction is carried out on the medical projection data to obtain an original organ model;
step S303, obtaining pixel information of each organ in the medical projection data, inputting the pixel information into an original organ model for training to generate a target organ model.
The beneficial effects of the above technical scheme are: the generated target organ model can be used for acquiring the body temperature compensation finger by using the body temperature compensation finger and the physical sign data, so that the problem that an actual result cannot be obtained due to simple calculation is avoided.
In one embodiment, the medical projection data is three-dimensionally reconstructed to obtain an original organ model, comprising:
acquiring a two-dimensional image of the preprocessed medical projection data;
segmenting the two-dimensional image to obtain n segmentation sequences;
establishing a three-dimensional coordinate system according to the n segmentation sequences;
counting the current segmentation sequence of each organ in the n segmentation sequences in the two-dimensional image;
extracting feature points of two adjacent current segmentation sequences in the current segmentation sequence by using an SIFT feature matching algorithm, and determining a three-dimensional coordinate point of each organ based on the feature points;
and constructing a model in a three-dimensional coordinate system according to the three-dimensional coordinate points to generate an original organ model.
The beneficial effects of the above technical scheme are: and acquiring a three-dimensional coordinate point of each organ according to the characteristic points, and then generating an original organ model in the established three-dimensional coordinate system according to the three-dimensional coordinate points, so that each characteristic point of each organ can be extracted, and the generated original organ model is closer to perfectness and reality.
In one embodiment, extracting the feature points of the current segmentation sequence may further be performed by:
A. calculating the direction gradient of the current segmentation sequence;
wherein, FixFor the gradient of the ith current segmentation sequence in the x direction, FiyFor the gradient of the ith current segmentation sequence in the y direction, FiFor the ith current slicing sequence,
is the sign of the gradient operation, (a, b) is the unit vector in the x direction, (c, d) is the unit vector in the y direction;
B. determining a weighting matrix M for an ith current segmentation sequencei；
Wherein A isi、Bi、CiThe mean value of the gradient in the neighborhood of the (u, v) signal point in the ith current segmentation sequence can be expressed as:
wherein σiThe standard deviation of the ith current segmentation sequence is taken as the standard deviation of the ith current segmentation sequence;
C. obtaining a feature point set of a current segmentation sequence;
Ti＝{(u,v)|det(Mi)-α*tra(M)＜Q}
wherein, TiFor the set of feature points of the ith current segmentation sequence, det (M)i) Is a weighting matrix MiA determinant value of tra (M)i) Is a weighting matrix Miα is a parameter and Q is a preset threshold.
The beneficial effects of the above technical scheme are: extracting point characteristics of signal based on current segmentation sequence, and using Gaussian function to Fix、FiyAnd FixFiyThe gaussian weighting is performed, so that a filtering effect can be achieved, the current segmentation sequence is denoised, the extracted feature points are more representative, and as the parameter α increases, the sensitivity of the technical scheme is reduced, and the extracted feature points are also reduced.
In one embodiment, the body temperature compensation value is obtained by combining the body temperature change trend with a target organ model, and the method comprises the following steps:
counting third physical characteristics data of the user within a second fixed time;
calculating the second volume feature data and the error value to obtain fourth volume feature data;
comparing the fourth physical sign data with the second sample physical sign data to obtain a second comparison result;
determining a second body temperature change trend of the user according to the second comparison result, and displaying the second body temperature change trend through a preset line graph;
determining the influence parameters of the physical sign data on the human body temperature and the relationship between the physical sign data and the human body temperature according to the first body temperature change trend and the second body temperature change trend on the preset line graph;
and calculating a body temperature compensation value according to the influence parameters.
The beneficial effects of the above technical scheme are: the relationship between the physical sign data and the human body temperature can be more accurately determined according to the first body temperature change trend and the second body temperature change trend, the influence parameters of the data on the human body temperature can be adjusted, the human body temperature can be rapidly determined according to the physical sign data of a user under the support of big data, the detection result is faster and more accurate, and meanwhile, the influence of the physical sign data on the human body temperature is further avoided.
In one embodiment, the obtaining of the human body state of the user every first fixed time within the preset total time includes:
acquiring blood pressure (systolic pressure and diastolic pressure) monitoring results of the user every other first fixed time within the preset total time;
determining the current blood pressure sign state of the user according to the monitoring result of the blood pressure (systolic pressure and diastolic pressure);
when the current blood pressure sign state is within a preset blood pressure sign state range, analyzing and calculating the current blood pressure sign state and basic data of a user, and determining an influence deviation correction value of blood pressure diseases on body temperature;
acquiring heart rate monitoring results of users at intervals of a first fixed time length in a preset total time length;
judging whether the user is in a healthy state or not according to the heart rate monitoring result;
determining the human body state of the user according to the judgment result;
utilize human state to combine user's basic data and body temperature compensation value to obtain user's real-time body temperature value, include:
when the human body state is in a healthy state, acquiring fifth physical sign data of the user;
acquiring basic data of a user;
inputting the basic data into a pre-established database to obtain the set temperature of a user;
determining the current temperature of the user according to the fifth characteristic data;
correcting the current temperature using a deviation between the current temperature and the set temperature;
calculating the corrected current temperature and body temperature compensation value to obtain a first body temperature value of the user;
calculating the influence deviation correction value of the first body temperature value and the blood pressure disease on the body temperature to obtain a second body temperature value;
the second body temperature value is determined as a real-time body temperature value of the user.
The beneficial effects of the above technical scheme are: the obtained real-time body temperature value of the user is more accurate and practical, the body temperature value is corrected, the influence of most external factors is eliminated, the influence of the physical sign state of blood pressure (systolic pressure and diastolic pressure) on body temperature deviation is considered, the detection result and the real body temperature of the user are enabled to approach infinitely, and the precision is greatly improved.
In one embodiment, obtaining the heart rate monitoring result of the user every first fixed time duration within the preset total time duration includes:
acquiring a first heart rate monitoring result of a user every other first fixed time within a preset total time;
calculating the normal heart rate value range of the user according to the following formula;
wherein x isnIs the heart rate value ynNumber of (2), x1、x2The number of each heart rate value in the m heart rate values every first fixed time length in the preset total time length; x is the number ofn-1Is the heart rate value yn-180% of the quantity of (c) is a fixed threshold value;
acquiring a normal heart rate value of a user, wherein the normal heart rate value is an average value of m heart rate values within a preset total duration every other first fixed duration;
determining whether the first heart rate monitoring result is equal to the normal heart rate value or within a range of the normal heart rate value;
if so, acquiring a difference value of two adjacent heart rate monitoring values in the first heart rate monitoring result;
otherwise, acquiring the walking steps of the user in each first fixed time length, acquiring a standard heart rate value according to the walking steps, and comparing the first heart rate monitoring result with the standard heart rate value to confirm whether the first heart rate monitoring result is normal or not;
determining whether the difference value meets a preset condition, wherein the preset condition is that the difference value is smaller than a preset threshold value, the obtained difference value is unique every other first fixed time length, and the time points of two heart rate monitoring values of the obtained difference value are the initial time point and the final time point of the first fixed time length;
counting heart rate monitoring values in the first monitoring result corresponding to the difference values meeting the preset conditions to generate a second heart rate monitoring result;
and confirming the second heart rate monitoring result as the heart rate monitoring result of the user every first fixed time length in the preset total time length.
The technical scheme has the advantages that whether the heart rate monitoring result of the user is in a normal range or not is judged, the final heart rate monitoring result is more accurate through the necessary three preset conditions, and meanwhile, whether the heart rate monitoring result of the user is the same as the standard heart rate value after strenuous exercise or not is determined according to the walking steps of the user, so that the condition that the heart rate monitoring result of the user is considered to be abnormal by mistake is avoided.
It will be understood by those skilled in the art that the first and second terms of the present invention refer to different stages of application.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is limited only by the appended claims.
Claims (10)
1. A body temperature measurement method is applied to wearable sign detection equipment and is characterized by comprising the following steps:
acquiring current physical sign data of a user in a current environment, and determining a body temperature change trend of the user by using the current physical sign data and sample physical sign data in the current body temperature environment;
acquiring a body temperature compensation value by combining the body temperature change trend with a target organ model;
acquiring the human body state of a user every first fixed time within a preset total time;
and acquiring a real-time body temperature value of the user by utilizing the human body state in combination with basic data of the user and the body temperature compensation value, wherein the basic data comprises the age and the sex of the user.
2. The method of measuring body temperature according to claim 1, wherein before obtaining the current vital sign data of the user in the current environment, and determining the body temperature trend of the user by using the current vital sign data and the sample vital sign data in the current environment, the method further comprises:
acquiring the current temperature of the current environment;
comparing the current temperature with a preset normal temperature, and confirming the difference value between the current temperature and the preset normal temperature;
and determining an error value of the sign data according to the difference value, and eliminating the influence of the ambient temperature on all sign data according to the error value, wherein all sign data comprise the sample sign data and the current sign data.
3. The method for measuring body temperature according to claim 1, wherein the obtaining current vital sign data of a user in a current environment, and determining a body temperature trend of the user by using the current vital sign data and sample vital sign data in the current body temperature environment comprises:
acquiring first characterization data of the user at the current moment under the current environment;
calculating the first body characteristic data and an error value to obtain second body characteristic data;
confirming that the second body sign data is the current body sign data;
acquiring a preset number of sample physical sign data in the current body temperature environment;
establishing a preset line graph;
comparing the current sign data with the preset number of sample sign data to obtain a first comparison result, determining a first body temperature change trend of the user according to the first comparison result, and displaying the first body temperature change trend on the preset line graph.
4. The method of measuring body temperature according to any one of claims 1-3, wherein the current vital sign data includes: blood pressure and venous blood vessel temperature.
5. The method of measuring body temperature according to claim 1, wherein before using the body temperature trend in combination with a target organ model to obtain a body temperature compensation value, the method further comprises:
medical projection data of the user is acquired,
performing three-dimensional reconstruction on the medical projection data to obtain an original organ model;
acquiring pixel information of each organ in the medical projection data, and inputting the pixel information into the original organ model for training to generate the target organ model.
6. The method for measuring body temperature according to claim 5, wherein the three-dimensional reconstruction of the medical projection data to obtain an original organ model comprises:
performing filtering and smoothing preprocessing on the medical projection data, wherein the medical projection data is used for acquiring an organ image;
acquiring a two-dimensional image of the preprocessed medical projection data;
segmenting the two-dimensional image to obtain n segmentation sequences;
establishing a three-dimensional coordinate system according to the n segmentation sequences;
counting the current segmentation sequence of each organ in the two-dimensional image in the n segmentation sequences;
extracting feature points of two adjacent current segmentation sequences in the current segmentation sequences by using an SIFT feature matching algorithm, and determining a three-dimensional coordinate point of each organ based on the feature points;
and constructing a model in the three-dimensional coordinate system according to the three-dimensional coordinate points to generate the original organ model.
7. The method for measuring body temperature according to claim 6, wherein the extracting of the feature points of the current segmentation sequence is further performed by:
A. calculating the direction gradient of the current segmentation sequence;
wherein, FixFor the gradient of the ith current segmentation sequence in the x direction, FiyFor the gradient of the ith current segmentation sequence in the y direction, FiFor the ith current slicing sequence,
is the sign of the gradient operation, (a, b) is the unit vector in the x direction, (c, d) is the unit vector in the y direction;
B. determining a weighting matrix M for an ith current segmentation sequencei；
Wherein A isi、Bi、CiThe mean value of the gradient in the neighborhood of the (u, v) signal point in the ith current segmentation sequence can be expressed as:
wherein σiThe standard deviation of the ith current segmentation sequence is taken as the standard deviation of the ith current segmentation sequence;
C. obtaining a feature point set of a current segmentation sequence;
Ti＝{(u,v)|det(Mi)-α*tra(M)＜Q}
wherein, TiFor the set of feature points of the ith current segmentation sequence, det (M)i) Is a weighting matrix MiA determinant value of tra (M)i) Is a weighting matrix Miα is a parameter and Q is a preset threshold.
8. The method for measuring body temperature according to claim 1, wherein the using the body temperature trend in combination with a target organ model to obtain a body temperature compensation value comprises:
counting third physical characteristics data of the user within a second fixed time;
calculating the second volume feature data and the error value to obtain fourth volume feature data;
comparing the fourth physical sign data with the second sample physical sign data to obtain a second comparison result;
determining a second body temperature change trend of the user through the second comparison result, and displaying the second body temperature change trend through a preset line graph;
determining the influence parameters of the physical sign data on the human body temperature and the relationship between the physical sign data and the human body temperature according to the first body temperature change trend and the second body temperature change trend on the preset line graph;
and calculating the body temperature compensation value according to the influence parameters.
9. The method for measuring body temperature according to claim 1, wherein the obtaining the human body state of the user every first fixed time within the preset total time comprises:
acquiring blood pressure (systolic pressure and diastolic pressure) monitoring results of the user every other first fixed time within the preset total time;
determining the current blood pressure sign state of the user according to the monitoring result of the blood pressure (systolic pressure and diastolic pressure);
when the current blood pressure sign state is within a preset blood pressure sign state range, analyzing and calculating the current blood pressure sign state and the basic data of the user to determine an influence deviation correction value of blood pressure diseases on the body temperature;
acquiring heart rate monitoring results of the users at intervals of the first fixed time within the preset total time;
judging whether the user is in a healthy state or not according to the heart rate monitoring result;
determining the human body state of the user according to the judgment result;
the acquiring the real-time body temperature value of the user by combining the human body state with the basic data of the user and the body temperature compensation value comprises the following steps:
when the human body state is in the healthy state, acquiring fifth physical sign data of the user;
acquiring basic data of the user;
inputting the basic data into a pre-established database to obtain the set temperature of a user;
determining the current temperature of the user according to the fifth characteristic data;
correcting the current temperature using a deviation between the current temperature and the set temperature;
calculating the corrected current temperature and the body temperature compensation value to obtain a first body temperature value of the user;
calculating the first body temperature value and the influence deviation correction value of the blood pressure disease on the body temperature to obtain a second body temperature value;
determining the second body temperature value as a real-time body temperature value of the user.
10. The method for measuring body temperature according to claim 9, wherein the obtaining heart rate monitoring results of the user every other first fixed time period within the preset total time period comprises:
acquiring a first heart rate monitoring result of the user every other first fixed time within the preset total time;
calculating a normal heart rate value range of the user according to the following formula;
wherein, the xnIs the heart rate value ynThe number of (a), the x1、x2The number of each heart rate value in the m heart rate values every first fixed time length in the preset total time length; said xn-1Is the heart rate value yn-1(ii) said 80% being a fixed threshold;
acquiring a normal heart rate value of the user, wherein the normal heart rate value is an average value of m heart rate values within a first fixed time interval in the preset total time interval;
determining whether the first heart rate monitoring result is equal to the normal heart rate value or within the range of the normal heart rate value;
if so, acquiring a difference value of two adjacent heart rate monitoring values in the first heart rate monitoring result;
otherwise, acquiring the walking steps of the user in each first fixed time, acquiring a standard heart rate value according to the walking steps, and comparing the first heart rate monitoring result with the standard heart rate value to confirm whether the first heart rate monitoring result is normal or not;
determining whether the difference meets a preset condition, wherein the preset condition is that the difference is smaller than a preset threshold value, the obtained difference is unique within a first fixed time interval, and the time points of the two heart rate monitoring values for obtaining the difference are the initial time point and the final time point of the first fixed time interval;
counting the heart rate monitoring values in the first monitoring result corresponding to the difference values meeting the preset conditions to generate a second heart rate monitoring result;
and confirming the second heart rate monitoring result as the heart rate monitoring result of the user every the first fixed time length in the preset total time length.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112233377A (en) * | 2020-12-10 | 2021-01-15 | 江西云本数字科技有限公司 | Internet of things monitoring and early warning equipment |
| CN112315432A (en) * | 2020-09-29 | 2021-02-05 | 北京化工大学 | Information monitoring method, information monitoring device and computer readable storage medium |
| CN112927816A (en) * | 2021-01-27 | 2021-06-08 | 广东顺德鲁棒智能技术有限公司 | Body temperature detection system, body temperature trend prediction method and system |
| CN113288088A (en) * | 2021-06-29 | 2021-08-24 | 北京理工新源信息科技有限公司 | Real-time body temperature monitoring and early warning system based on vital sign detection |
| CN114515140A (en) * | 2020-11-20 | 2022-05-20 | 湖南明珠智能科技有限责任公司 | Accurate individual body temperature measuring and calculating method combining heart rate and body surface temperature |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN112315432A (en) * | 2020-09-29 | 2021-02-05 | 北京化工大学 | Information monitoring method, information monitoring device and computer readable storage medium |
| CN114515140A (en) * | 2020-11-20 | 2022-05-20 | 湖南明珠智能科技有限责任公司 | Accurate individual body temperature measuring and calculating method combining heart rate and body surface temperature |
| CN112233377A (en) * | 2020-12-10 | 2021-01-15 | 江西云本数字科技有限公司 | Internet of things monitoring and early warning equipment |
| CN112927816A (en) * | 2021-01-27 | 2021-06-08 | 广东顺德鲁棒智能技术有限公司 | Body temperature detection system, body temperature trend prediction method and system |
| CN113288088A (en) * | 2021-06-29 | 2021-08-24 | 北京理工新源信息科技有限公司 | Real-time body temperature monitoring and early warning system based on vital sign detection |
| CN113288088B (en) * | 2021-06-29 | 2023-09-15 | 北京理工新源信息科技有限公司 | Real-time body temperature monitoring and early warning system based on vital sign detection |
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