Body temperature monitoring remote monitoring system based on real-time data

Abstract

The invention relates to the technical field of medical monitoring, and particularly discloses a body temperature monitoring remote monitoring system based on real-time data. Comprising a body temperature measurement state monitoring module, a use state monitoring analysis module, a body temperature data monitoring module, an influence data monitoring module, a body temperature state analysis module, a health state analysis module, an abnormal grade analysis module, a remote monitoring early warning terminal and a remote monitoring display terminal. The body temperature and the influence data of the target old person corresponding to the current monitoring time period are monitored in real time, and the body temperature state of the target old person corresponding to the current monitoring time period is analyzed, so that the analysis result is more targeted, and the influence of the physiological sign data, the activity data and the environment data on the body temperature of the target old person is comprehensively considered; the analysis result has scientific representativeness and comprehensiveness, the risk of body temperature misjudgment caused by a single factor is reduced, and the accuracy of body temperature health analysis corresponding to the target old person is achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical monitoring, and in particular to a temperature monitoring remote monitoring system based on real-time data. Background Art

[0002] With the development of society and the accelerated pace of life, the aging of the population is becoming increasingly serious, and the number of elderly people living alone is also rising. In this context, the issue of health monitoring for elderly people living alone has received more and more attention. As one of the important indicators of human physiological state, abnormal body temperature is often an early signal of the occurrence or aggravation of disease, which highlights the importance of remote monitoring of body temperature for elderly people living alone.

[0003] At present, traditional body temperature monitoring methods often have many limitations. For example, commonly used thermometers require the elderly to operate them personally, which may be difficult for the elderly with limited mobility or decreased cognitive ability. Moreover, this method cannot achieve real-time monitoring and remote monitoring, and it is difficult for children or medical staff to obtain the changes in the elderly's body temperature in a timely manner. In addition, although some existing body temperature monitoring devices can perform real-time monitoring to a certain extent, most of them simply record body temperature data and lack in-depth analysis and comprehensive use of these data. They cannot combine body temperature data with other physiological indicators or environmental factors to conduct a comprehensive health assessment. Summary of the invention

[0004] The purpose of the present invention is to provide a temperature monitoring remote monitoring system based on real-time data to solve the problems raised in the above background.

[0005] The purpose of the present invention can be achieved through the following technical solutions: A temperature monitoring remote monitoring system based on real-time data, comprising:

[0006] The temperature measurement status monitoring module is used to monitor and analyze the measurement status of the temperature monitor corresponding to the target elderly. If the measurement status of the temperature monitor corresponding to the target elderly is not measured, the remote monitoring early warning terminal is started. On the contrary, if the measurement status of the temperature monitor corresponding to the target elderly is measured, the use status monitoring and analysis module is executed;

[0007] The usage status monitoring and analysis module is used to monitor and analyze the usage status of the target elderly person corresponding to the current monitoring period. If the usage status of the target elderly person corresponding to the current monitoring period is a sleeping state, the smart camera is started to monitor the sleeping posture of the target elderly person corresponding to the current monitoring period and send it to the remote monitoring display terminal. Otherwise, the body temperature data monitoring module is started;

[0008] The body temperature data monitoring module is used to monitor the body temperature data of the target elderly person in real time during the current monitoring period and send it to the remote monitoring display terminal;

[0009] The impact data monitoring module is used to monitor the impact data of the target elderly person corresponding to the current monitoring period in real time and send it to the remote monitoring display terminal;

[0010] The body temperature status analysis module is used to analyze the body temperature health assessment index of the target elderly person corresponding to the current monitoring period, and obtain the body temperature health assessment index of the target elderly person corresponding to the current monitoring period;

[0011] The health status analysis module is used to analyze the temperature health status of the target elderly person corresponding to the current monitoring period. If the temperature health status of the target elderly person corresponding to the current monitoring period is abnormal, the abnormal level analysis module is executed. Otherwise, the temperature health status of the target elderly person corresponding to the current monitoring period is sent to the remote monitoring display terminal;

[0012] The abnormal level analysis module is used to analyze the abnormal level of the target elderly person corresponding to the current monitoring period and send it to the remote monitoring early warning terminal;

[0013] Remote monitoring and early warning terminal, used to send remote early warning information to the designated device of the guardian of the target elderly person, and perform corresponding early warning operations at the same time;

[0014] Remote monitoring display terminal, used to send remote display information to the designated device of the guardian of the target elderly person, and display it accordingly;

[0015] The system storage library is used to store the motion amplitude waveform corresponding to each usage state, store the actual time periods corresponding to the sleep state of the target elderly in the historical cycle, and store the physiological characteristic data corresponding to the target elderly.

[0016] As a further solution of the present invention, the measurement status of the temperature monitor corresponding to the target elderly is monitored and analyzed, and the specific execution steps are as follows:

[0017] The contact pressure between the temperature monitor and the target elderly person is detected by a pressure sensor in the temperature monitor, and a contact pressure value of the temperature monitor corresponding to the target elderly person is obtained, which is recorded as a marking pressure;

[0018] The marked pressure of the temperature monitor corresponding to the target elderly person is compared with the set reference marked pressure. If the marked pressure of the temperature monitor corresponding to the target elderly person is less than the set reference marked pressure, the measurement state of the temperature monitor corresponding to the target elderly person is determined to be an unmeasured state. Otherwise, the measurement state of the temperature monitor corresponding to the target elderly person is determined to be a measured state.

[0019] As a further solution of the present invention, the usage status of the target elderly corresponding to the current monitoring period is monitored and analyzed, and the specific execution steps are as follows:

[0020] The motion sensor is used to monitor the motion amplitude of the target elderly person at each monitoring time point in the current monitoring period, and the motion amplitude of the target elderly person at each monitoring time point in the current monitoring period is obtained;

[0021] With each monitoring time point as the horizontal coordinate and the movement amplitude at each monitoring time point as the vertical coordinate, a two-dimensional dynamic coordinate system is constructed, and the movement amplitude of the target elderly corresponding to each monitoring time point in the current monitoring period is plotted in the two-dimensional dynamic coordinate system and connected by lines to obtain a waveform diagram of the movement amplitude of the target elderly corresponding to the current monitoring period;

[0022] The motion amplitude waveform diagram of the target elderly corresponding to the current monitoring period is matched with the motion amplitude waveform diagrams corresponding to each usage status stored in the system storage library to obtain the usage status of the target elderly corresponding to the current monitoring period.

[0023] As a further solution of the present invention, the temperature health assessment index of the target elderly person corresponding to the current monitoring period is analyzed, and the specific analysis method is as follows:

[0024] Extract the body temperature of the target elderly person at each monitoring time point in the current monitoring period from the body temperature data of the target elderly person in the current monitoring period, and construct a body temperature change curve graph of the target elderly person in the current monitoring period;

[0025] Extract each abnormal temperature period from the temperature change curve diagram of the target elderly corresponding to the current monitoring period, obtain the duration of each abnormal temperature period in the current monitoring period of the target elderly, and obtain the previous period of each abnormal temperature period, and at the same time make the duration of the previous period equal to the duration of the corresponding abnormal temperature period, and then form each abnormal temperature period and its corresponding previous period into an overall period, recorded as a temperature marking period, thereby obtaining each temperature marking period of the target elderly corresponding to the current monitoring period;

[0026] Extracting the waist circumference, height, weight, age and gender of the target elderly from the physiological characteristic data of the target elderly stored in the system repository, matching the gender of the target elderly with the first body fat influence value corresponding to each gender stored, and obtaining the first body fat influence value X1 of the target elderly;

[0027] The first body fat assessment index κ1 corresponding to the target elderly is calculated by the formula;

[0028] Match the gender corresponding to the target elderly person with the stored second body fat influence value corresponding to each gender to obtain the second body fat influence value X2 corresponding to the target elderly person;

[0029] The second body fat assessment index κ2 corresponding to the target elderly is calculated by the formula;

[0030] According to the formula Calculate the body fat assessment coefficient κ of the target person, a1 and a2 are

[0031] It is expressed as the coefficient factors corresponding to the set first body fat assessment index and second body fat assessment index.

[0032] Matching the gender corresponding to the target elderly with the stored first metabolic impact values ​​corresponding to each gender to obtain the first metabolic impact value Y1 corresponding to the target elderly;

[0033] The first basic metabolic assessment index λ1 corresponding to the target elderly is calculated by the formula;

[0034] Matching the gender corresponding to the target elderly with the stored second metabolic impact values ​​corresponding to each gender to obtain the second metabolic impact value Y2 corresponding to the target elderly;

[0035] The second basic metabolic assessment index λ2 corresponding to the target elderly is calculated by the formula;

[0036] According to the formula Calculate the basal metabolic assessment coefficient λ corresponding to the target elderly, where a3 and a4 represent the coefficient factors corresponding to the set first basal metabolic assessment index and second basal metabolic assessment index, respectively;

[0037] The physiological sign impact index γ corresponding to the target elderly is calculated according to the formula γ = κ × a5 + λ × a6, where a5 and a6 represent the weight factors corresponding to the set body fat assessment coefficient and basal metabolic assessment coefficient respectively;

[0038] From the activity data of the target elderly corresponding to the current monitoring period, the activity intensity, the number of body posture changes, and the emotional state feedback values ​​of the target elderly corresponding to each temperature marking period in the current monitoring period are extracted and marked as ZD i 、N i , QX i , i represents the number of each temperature marking period, i=1,2,....,m, m represents the total number of temperature marking period numbers;

[0039] According to the formula Calculate the activity data impact index of the target elderly corresponding to each temperature marking period ZD', N', QX' represent the set reference activity intensity, number of body posture changes, and emotional state feedback value, respectively; b1, b2, and b3 represent the weight factors corresponding to the set activity intensity, number of body posture changes, and emotional state feedback value, respectively;

[0040] The atmospheric temperature and humidity at each marked time point in each temperature marked period of the target elderly person corresponding to the current monitoring period are extracted from the environmental data of the target elderly person corresponding to the current monitoring period, and the averages are calculated respectively to obtain the average atmospheric temperature and average atmospheric humidity of each temperature marked period of the target elderly person corresponding to the current monitoring period, which are recorded as WD i , SD i ;

[0041] According to the formula Calculate the environmental data impact index σ for each temperature mark period of the target elderly i , WD', SD' represent the set reference atmospheric temperature and reference atmospheric humidity respectively, b4, b5 represent the weight factors corresponding to the set atmospheric temperature and atmospheric humidity respectively;

[0042] According to the formula Calculate the comprehensive data impact index ω of the target elderly corresponding to each abnormal temperature period i , c1, c2, and c3 represent the weight factors corresponding to the set physiological characteristics impact index, activity data impact index, and environmental data impact index, respectively;

[0043] The comprehensive data impact index of the target elderly corresponding to each abnormal temperature period is matched with the temperature impact value corresponding to each set comprehensive data impact index to obtain the temperature impact value ΔTW of the target elderly corresponding to each abnormal temperature period i ;

[0044] The body temperature of the target elderly at each time point in each temperature mark period is extracted from the temperature change curve of the target elderly corresponding to the current monitoring period, and recorded as TW j i , j represents the number of each time point, j = 1, 2, ...., n, n represents the total number of time point numbers;

[0045] According to the formula The temperature health assessment index μ of the target elderly person corresponding to the current monitoring period is calculated, and TW' is represented as the set reference temperature.

[0046] As a further solution of the present invention, the temperature health status of the target elderly person corresponding to the current monitoring period is analyzed, and the specific analysis method is as follows:

[0047] The body temperature health assessment index of the target elderly person corresponding to the current monitoring period is compared with the set body temperature health assessment index threshold. If the body temperature health assessment index of the target elderly person corresponding to the current monitoring period is less than the set body temperature health assessment index threshold, the body temperature health status of the target elderly person corresponding to the current monitoring period is judged to be abnormal; otherwise, the body temperature status of the target elderly person corresponding to the current monitoring period is judged to be normal.

[0048] As a further solution of the present invention, the abnormal level of the target elderly person corresponding to the current monitoring period is analyzed, and the specific analysis method is as follows:

[0049] If the temperature health status of the target elderly person corresponding to the current monitoring period is abnormal, the temperature health status assessment index of the target elderly person corresponding to the current monitoring period is subtracted from the set temperature health status assessment index threshold to obtain the temperature health status assessment index difference of the target elderly person corresponding to the current monitoring period;

[0050] The temperature health status assessment index difference of the target elderly person corresponding to the current monitoring period is matched with the temperature health status assessment index difference corresponding to each set abnormal level to obtain the abnormal level of the target elderly person corresponding to the current monitoring period.

[0051] Beneficial effects of the present invention:

[0052] The present invention monitors and analyzes the measurement status of the temperature monitor corresponding to the target elderly person, and initiates corresponding operations according to the measurement status, thereby improving the standardization of the temperature measurement of the target elderly person to a certain extent, avoiding the omission of the patient's abnormal temperature due to the temperature monitor not working properly, avoiding the misjudgment of the patient's temperature condition due to data missing, and at the same time providing reliable protection for the health status monitoring and analysis of the target elderly person.

[0053] The present invention analyzes the usage status of the target elderly person corresponding to the current monitoring period, thereby determining the usage status of the target elderly person corresponding to the current monitoring period, and initiates corresponding operations based on the usage status, thereby avoiding misjudgment in the monitoring process to a certain extent, achieving accurate monitoring, and providing strong data support for subsequent body temperature status analysis.

[0054] The present invention performs real-time monitoring of the body temperature and influencing data of the target elderly person corresponding to the current monitoring period, and thereby analyzes the body temperature status of the target elderly person corresponding to the current monitoring period. The analysis result is more targeted, and the influence of physiological sign data, activity data and environmental data on the body temperature of the target elderly person is comprehensively considered, so that the analysis result is more scientifically representative and comprehensive, and the risk of misjudgment of body temperature due to a single factor is reduced, thereby achieving the accuracy of the corresponding body temperature health analysis of the target elderly person.

[0055] The present invention helps to timely discover potential health problems by analyzing the corresponding body temperature health status of the target elderly and performing corresponding display and early warning processing. Through abnormal level analysis, the severity of the abnormality can be understood more accurately, providing a basis for taking corresponding treatment measures, and helping to achieve more targeted medical intervention and care, avoiding excessive investment in mild abnormalities or insufficient investment in severe abnormalities, and to a certain extent improving the timeliness of response to health risks of the target elderly and the safety of living alone, and reducing the risk of living alone for the target elderly. BRIEF DESCRIPTION OF THE DRAWINGS

[0056] The present invention will be further described below in conjunction with the accompanying drawings.

[0057] Figure 1 It is a system block diagram of the present invention. DETAILED DESCRIPTION

[0058] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0059] See also Figure 1 As shown, the present invention is a temperature monitoring remote monitoring system based on real-time data, including: a temperature measurement status monitoring module, a usage status monitoring and analysis module, a temperature data monitoring module, an impact data monitoring module, a temperature status analysis module, a health status analysis module, an abnormal level analysis module, a remote monitoring early warning terminal, a remote monitoring display terminal and a system repository.

[0060] The body temperature measurement status monitoring module is respectively connected to the usage status monitoring and analysis module and the remote monitoring early warning terminal, the usage status monitoring and analysis module is respectively connected to the body temperature data monitoring module, the impact data monitoring module and the system repository, the body temperature data monitoring module and the impact data monitoring module are both connected to the body temperature status analysis module and the remote monitoring display terminal, the body temperature status analysis module is connected to the health status analysis module, the health status analysis module is connected to the abnormal level analysis module and the remote monitoring display terminal, and the abnormal level analysis module is connected to the remote monitoring early warning terminal.

[0061] Sensors in a temperature monitor include but are not limited to: pressure sensors, temperature sensors, and motion sensors.

[0062] The temperature measurement status monitoring module is used to monitor and analyze the measurement status of the temperature monitor corresponding to the target elderly. The specific execution steps are as follows:

[0063] The contact pressure between the temperature monitor and the target elderly person is detected by a pressure sensor in the temperature monitor, and a contact pressure value of the temperature monitor corresponding to the target elderly person is obtained, which is recorded as a marking pressure;

[0064] The marked pressure of the temperature monitor corresponding to the target elderly person is compared with the set reference marked pressure. If the marked pressure of the temperature monitor corresponding to the target elderly person is less than the set reference marked pressure, the measurement state of the temperature monitor corresponding to the target elderly person is determined to be an unmeasured state. Otherwise, the measurement state of the temperature monitor corresponding to the target elderly person is determined to be a measured state.

[0065] If the measurement status of the temperature monitor corresponding to the target elderly person is the unmeasured state, the remote monitoring warning terminal is started. Conversely, if the measurement status of the temperature monitor corresponding to the target elderly person is the measured state, the usage status monitoring and analysis module is executed.

[0066] In a specific embodiment, the present invention monitors and analyzes the measurement status of the temperature monitor corresponding to the target elderly person, and initiates corresponding operations based on the measurement status, thereby improving the standardization of the temperature measurement of the target elderly person to a certain extent, avoiding missing the abnormal temperature of the patient due to the abnormal operation of the temperature monitor, and avoiding misjudgment of the patient's temperature condition due to missing data, and at the same time providing reliable protection for the health status monitoring and analysis of the target elderly person.

[0067] The usage status monitoring and analysis module is used to monitor and analyze the usage status of the target elderly corresponding to the current monitoring period. The specific execution steps are as follows:

[0068] The motion sensor is used to monitor the motion amplitude of the target elderly person at each monitoring time point in the current monitoring period, and the motion amplitude of the target elderly person at each monitoring time point in the current monitoring period is obtained;

[0069] With each monitoring time point as the horizontal coordinate and the movement amplitude at each monitoring time point as the vertical coordinate, a two-dimensional dynamic coordinate system is constructed, and the movement amplitude of the target elderly corresponding to each monitoring time point in the current monitoring period is plotted in the two-dimensional dynamic coordinate system and connected by lines to obtain a waveform diagram of the movement amplitude of the target elderly corresponding to the current monitoring period;

[0070] Extract the target elderly's motion amplitude sign vector X=(x1,x2,....,x g ), x g It is expressed as the action amplitude at the g-th monitoring time point;

[0071] Extracting a motion amplitude waveform corresponding to each use state from a system repository, wherein the use state includes an awake activity state and a sleeping state;

[0072] Extract the motion amplitude feature vector Y=(y1,y2,....,y g ), y g It is represented as the amplitude of the awake activity state at the g-th monitoring time point. The amplitude feature vector Z=(z1,z2,....,z g ), z g It is expressed as the movement amplitude of the sleep state at the g-th monitoring time point;

[0073] By formula Calculate the similarity d of the action amplitude waveform characteristics of the target elderly person corresponding to the awake activity state in the current monitoring period XY ;

[0074] By formula Calculate the characteristic similarity d of the target elderly person's motion amplitude waveform corresponding to the sleep state in the current monitoring period XZ ;

[0075] The characteristic similarities of the action amplitude waveforms of the target elderly corresponding to each usage state in the current monitoring period are compared with each other, and the specific analysis steps are as follows:

[0076] If the characteristic similarity of the motion amplitude waveform graph of the target elderly person corresponding to the awake activity state in the current monitoring period is greater than the characteristic similarity of the motion amplitude waveform graph of the target elderly person corresponding to the sleeping state in the current monitoring period, it is determined that the use state of the target elderly person corresponding to the current monitoring period is the awake activity state;

[0077] If the characteristic similarity of the motion amplitude waveform graph of the target elderly person corresponding to the awake activity state in the current monitoring period is less than the characteristic similarity of the motion amplitude waveform graph of the target elderly person corresponding to the sleep state in the current monitoring period, it is determined that the use state of the target elderly person corresponding to the current monitoring period is the sleep state;

[0078] If the characteristic similarity of the motion amplitude waveform graph of the target elderly person corresponding to the awake activity state in the current monitoring period is equal to the characteristic similarity of the motion amplitude waveform graph of the target elderly person corresponding to the sleeping state in the current monitoring period, the actual time period corresponding to the current monitoring period is extracted, and the actual time periods corresponding to the sleeping state in the historical period corresponding to the target elderly person are extracted from the system repository, and the actual time period corresponding to the current monitoring period is matched with the actual time periods corresponding to the sleeping state in the historical period corresponding to the target elderly person. If the match is successful, it is determined that the usage state of the target elderly person corresponding to the current monitoring period is the sleeping state. Otherwise, it is determined that the usage state of the target elderly person corresponding to the current monitoring period is the awake activity state.

[0079] Thus, the usage status of the target elderly corresponding to the current monitoring period is obtained;

[0080] If the target elderly person is in a sleeping state during the current monitoring period, the smart camera is started to monitor the sleeping posture of the target elderly person during the current monitoring period and send the data to the remote monitoring display terminal. Otherwise, the body temperature data monitoring module is started.

[0081] In a specific embodiment, the present invention analyzes the usage status of the target elderly person corresponding to the current monitoring period, thereby determining the usage status of the target elderly person corresponding to the current monitoring period, and initiates corresponding operations based on the usage status, thereby avoiding misjudgment during the monitoring process to a certain extent, achieving accurate monitoring, and providing strong data support for subsequent body temperature status analysis.

[0082] The body temperature data monitoring module is used to monitor the body temperature data of the target elderly person in real time during the current monitoring period and send it to the remote monitoring display terminal;

[0083] The impact data monitoring module is used to monitor the impact data of the target elderly in the current monitoring period in real time, where the impact data includes physiological sign data, activity data and environmental data. The physiological sign data specifically includes waist circumference, height, weight, age and gender. The activity data specifically includes the activity intensity, number of body posture changes and emotional state feedback value of the target elderly in the current monitoring period. The environmental data specifically includes atmospheric temperature and atmospheric humidity. The atmospheric humidity is monitored by a humidity sensor and sent to the remote monitoring display terminal;

[0084] The body temperature status analysis module is used to analyze the body temperature health assessment index of the target elderly person corresponding to the current monitoring period. The specific analysis method is as follows:

[0085] Extract the body temperature of the target elderly person at each monitoring time point in the current monitoring period from the body temperature data of the target elderly person in the current monitoring period, and construct a body temperature change curve graph of the target elderly person in the current monitoring period;

[0086] Match the body temperature of the target elderly at each monitoring time point in the body temperature change curve diagram corresponding to the current monitoring period with the set abnormal body temperature threshold. If the body temperature of the target elderly at a certain monitoring time point in the current monitoring period successfully matches the set abnormal body temperature threshold, then the monitoring time point is recorded as the abnormal body temperature time point, and the adjacent abnormal body temperature time points are integrated to form an abnormal body temperature period, thereby obtaining each abnormal body temperature period corresponding to the current monitoring period of the target elderly, obtaining the duration of each abnormal body temperature period in the current monitoring period corresponding to the target elderly, and obtaining the previous period of each abnormal body temperature period, and at the same time making the duration of the previous period equal to the duration of the corresponding abnormal body temperature period, and then each abnormal body temperature period and its corresponding previous period constitute an overall period, recorded as a body temperature marking period, thereby obtaining each body temperature marking period corresponding to the current monitoring period of the target elderly;

[0087] Extract the waist circumference YW, height SG, weight TZ, age NL and gender of the target elderly from the physiological characteristic data of the target elderly stored in the system repository, match the gender of the target elderly with the first body fat influence value corresponding to each gender stored, and obtain the first body fat influence value X1 of the target elderly;

[0088] According to the formula Calculate the first body fat assessment index κ1 corresponding to the target elderly;

[0089] Match the gender corresponding to the target elderly person with the stored second body fat influence value corresponding to each gender to obtain the second body fat influence value X2 corresponding to the target elderly person;

[0090] According to the formula Calculate the second body fat assessment index κ2 corresponding to the target elderly;

[0091] According to the formula Calculate the body fat assessment coefficient κ corresponding to the target person, where a1 and a2 represent the coefficient factors corresponding to the set first body fat assessment index and second body fat assessment index, respectively.

[0092] Matching the gender corresponding to the target elderly with the stored first metabolic impact values ​​corresponding to each gender to obtain the first metabolic impact value Y1 corresponding to the target elderly;

[0093] The first basic metabolic assessment index λ1 corresponding to the target elderly is calculated according to the formula λ1=Y1+13.7×TZ+50×SG-6.8×NL;

[0094] Matching the gender corresponding to the target elderly with the stored second metabolic impact values ​​corresponding to each gender to obtain the second metabolic impact value Y2 corresponding to the target elderly;

[0095] The second basic metabolic assessment index λ2 corresponding to the target elderly is calculated according to the formula λ2=Y2+9.6×TZ+1.8×SG-4.7×NL;

[0096] According to the formula Calculate the basal metabolic assessment coefficient λ corresponding to the target elderly, where a3 and a4 represent the coefficient factors corresponding to the set first basal metabolic assessment index and second basal metabolic assessment index, respectively;

[0097] The physiological sign impact index γ corresponding to the target elderly is calculated according to the formula γ = κ × a5 + λ × a6, where a5 and a6 represent the weight factors corresponding to the set body fat assessment coefficient and basal metabolic assessment coefficient respectively;

[0098] From the activity data of the target elderly corresponding to the current monitoring period, the activity intensity, the number of body posture changes, and the emotional state feedback values ​​of the target elderly corresponding to each temperature marking period in the current monitoring period are extracted and marked as ZD i 、N i , QX i , i represents the number of each temperature marking period, i=1,2,....,m, m represents the total number of temperature marking period numbers;

[0099] It should be noted that the method for obtaining the activity intensity of the target elderly person corresponding to each temperature marking period in the current monitoring period is as follows:

[0100] Obtain the activity type of the target elderly corresponding to each temperature marked period in the current monitoring period, and match it with the activity intensity assignment corresponding to each set activity type, thereby obtaining the activity intensity of the target elderly corresponding to each temperature marked period in the current monitoring period, where the activity types include but are not limited to: running, fitness, brisk walking, cleaning, walking, standing;

[0101] The method for obtaining the emotional state feedback value of the target elderly corresponding to each temperature mark period in the current monitoring period is as follows:

[0102] Obtain the emotional state of the target elderly person corresponding to each temperature marking period in the current monitoring period, and match it with the emotional state assignment corresponding to each set emotional state, thereby obtaining the emotional state feedback value of the target elderly person corresponding to each temperature marking period in the current monitoring period, where the emotional state includes but is not limited to: tension, anxiety, excitement, agitation, calmness, and anger;

[0103] According to the formula Calculate the activity data impact index of the target elderly corresponding to each temperature marking period ZD', N', QX' represent the set reference activity intensity, number of body posture changes, and emotional state feedback value, respectively; b1, b2, and b3 represent the weight factors corresponding to the set activity intensity, number of body posture changes, and emotional state feedback value, respectively;

[0104] The atmospheric temperature and humidity at each marked time point in each temperature marked period of the target elderly person corresponding to the current monitoring period are extracted from the environmental data of the target elderly person corresponding to the current monitoring period, and the averages are calculated respectively to obtain the average atmospheric temperature and average atmospheric humidity of each temperature marked period of the target elderly person corresponding to the current monitoring period, which are recorded as WD i , SD i ;

[0105] According to the formula Calculate the environmental data impact index σ for each temperature mark period of the target elderly i , WD', SD' represent the set reference atmospheric temperature and reference atmospheric humidity respectively, c1, c2 represent the weight factors corresponding to the set atmospheric temperature and atmospheric humidity respectively;

[0106] According to the formula Calculate the comprehensive data impact index ω of the target elderly corresponding to each temperature marking period i , d1, d2, and d3 represent the weight factors corresponding to the set physiological characteristics impact index, activity data impact index, and environmental data impact index, respectively;

[0107] The comprehensive data impact index of the target elderly corresponding to each temperature mark period is matched with the set temperature impact value corresponding to each comprehensive data impact index to obtain the temperature impact value ΔTW of the target elderly corresponding to each temperature mark period i ;

[0108] The body temperature of the target elderly at each time point in each temperature mark period is extracted from the temperature change curve of the target elderly corresponding to the current monitoring period, and recorded as j represents the number of each time point, j = 1, 2, ...., n, n represents the total number of time point numbers;

[0109] According to the formula The temperature health assessment index μ of the target elderly person corresponding to the current monitoring period is calculated, and TW' is represented as the set reference temperature.

[0110] In a specific embodiment, the present invention performs real-time monitoring of the body temperature and influence data of the target elderly person corresponding to the current monitoring period, and thereby analyzes the body temperature status of the target elderly person corresponding to the current monitoring period. The analysis result is more targeted, and the influence of physiological sign data, activity data and environmental data on the body temperature of the target elderly person is comprehensively considered, so that the analysis result is more scientifically representative and comprehensive, reducing the risk of misjudgment of body temperature due to a single factor, and achieving the accuracy of the corresponding body temperature health analysis of the target elderly person.

[0111] The health status analysis module is used to analyze the temperature health status of the target elderly corresponding to the current monitoring period. The specific analysis method is as follows:

[0112] The temperature health assessment index of the target elderly person corresponding to the current monitoring period is compared with the set temperature health assessment index threshold. If the temperature health assessment index of the target elderly person corresponding to the current monitoring period is less than the set temperature health assessment index threshold, the temperature health status of the target elderly person corresponding to the current monitoring period is determined to be abnormal; otherwise, the temperature status of the target elderly person corresponding to the current monitoring period is determined to be normal;

[0113] If the temperature health status of the target elderly person corresponding to the current monitoring period is abnormal, the abnormal level analysis module is executed. Otherwise, the temperature health status of the target elderly person corresponding to the current monitoring period is sent to the remote monitoring display terminal.

[0114] The abnormal level analysis module is used to analyze the abnormal level of the target elderly person corresponding to the current monitoring period and send it to the remote monitoring warning terminal. The specific analysis method is as follows:

[0115] If the temperature health status of the target elderly person corresponding to the current monitoring period is abnormal, the temperature health status assessment index of the target elderly person corresponding to the current monitoring period is subtracted from the set temperature health status assessment index threshold to obtain the temperature health status assessment index difference of the target elderly person corresponding to the current monitoring period;

[0116] The temperature health status assessment index difference of the target elderly person corresponding to the current monitoring period is matched with the temperature health status assessment index difference corresponding to each set abnormal level to obtain the abnormal level of the target elderly person corresponding to the current monitoring period.

[0117] In a specific embodiment, the present invention helps to timely discover potential health problems by analyzing the corresponding body temperature health status of the target elderly and performing corresponding display and early warning processing. Through abnormal level analysis, the severity of the abnormality can be understood more accurately, providing a basis for taking corresponding treatment measures, and helping to achieve more targeted medical intervention and care, avoiding excessive investment in mild abnormalities or insufficient investment in severe abnormalities, and to a certain extent improving the timeliness of response to health risks of the target elderly and the safety of living alone, thereby reducing the risk of living alone for the target elderly.

[0118] The remote monitoring and early warning terminal is used to send remote early warning information to the designated device of the guardian of the target elderly person and perform corresponding early warning operations at the same time.

[0119] The remote monitoring display terminal is used to send remote display information to the designated device of the guardian corresponding to the target elderly person and display it accordingly.

[0120] The system storage library is used to store the motion amplitude waveform corresponding to each usage state, store the actual time periods corresponding to the sleep state of the target elderly in the historical cycle, and store the physiological characteristic data corresponding to the target elderly.

[0121] The specific sizes of weight factors and coefficient factors involved in the present invention are not given. Their sizes are customized by technicians in this field according to actual use and stored in the system repository. The formulas involved are all customized empirical formulas, which are pre-stored in the system repository.

[0122] The above contents are merely examples and explanations of the structure of the present invention. The technicians in this technical field may make various modifications or additions to the specific embodiments described or replace them in a similar manner. As long as they do not deviate from the structure of the invention or exceed the scope defined by the claims, they should all fall within the protection scope of the present invention.

Claims

1. A temperature monitoring remote monitoring system based on real-time data, characterized in that: include: The temperature measurement status monitoring module is used to monitor and analyze the measurement status of the temperature monitor corresponding to the target elderly. If the measurement status of the temperature monitor corresponding to the target elderly is not measured, the remote monitoring early warning terminal is started. On the contrary, if the measurement status of the temperature monitor corresponding to the target elderly is measured, the use status monitoring and analysis module is executed; The usage status monitoring and analysis module is used to monitor and analyze the usage status of the target elderly person corresponding to the current monitoring period. If the usage status of the target elderly person corresponding to the current monitoring period is a sleeping state, the smart camera is started to monitor the sleeping posture of the target elderly person corresponding to the current monitoring period and send it to the remote monitoring display terminal. Otherwise, the body temperature data monitoring module is started; The body temperature data monitoring module is used to monitor the body temperature data of the target elderly person in real time during the current monitoring period and send it to the remote monitoring display terminal; The impact data monitoring module is used to monitor the impact data of the target elderly person corresponding to the current monitoring period in real time and send it to the remote monitoring display terminal; The body temperature status analysis module is used to analyze the body temperature health assessment index of the target elderly person corresponding to the current monitoring period, and obtain the body temperature health assessment index of the target elderly person corresponding to the current monitoring period; The health status analysis module is used to analyze the temperature health status of the target elderly person corresponding to the current monitoring period. If the temperature health status of the target elderly person corresponding to the current monitoring period is abnormal, the abnormal level analysis module is executed. Otherwise, the temperature health status of the target elderly person corresponding to the current monitoring period is sent to the remote monitoring display terminal; The abnormal level analysis module is used to analyze the abnormal level of the target elderly person corresponding to the current monitoring period and send it to the remote monitoring early warning terminal; Remote monitoring and early warning terminal, used to send remote early warning information to the designated device of the guardian of the target elderly person, and perform corresponding early warning operations at the same time; Remote monitoring display terminal, used to send remote display information to the designated device of the guardian of the target elderly person, and display it accordingly; The system storage library is used to store the motion amplitude waveform corresponding to each usage state, store the actual time periods corresponding to the sleep state of the target elderly in the historical cycle, and store the physiological characteristic data corresponding to the target elderly.

2. A temperature monitoring remote monitoring system based on real-time data according to claim 1, characterized in that: The monitoring and analysis of the measurement status of the temperature monitor corresponding to the target elderly person is specifically performed in the following steps: The contact pressure between the temperature monitor and the target elderly person is detected by a pressure sensor in the temperature monitor, and a contact pressure value of the temperature monitor corresponding to the target elderly person is obtained, which is recorded as a marking pressure; The marked pressure of the temperature monitor corresponding to the target elderly person is compared with the set reference marked pressure. If the marked pressure of the temperature monitor corresponding to the target elderly person is less than the set reference marked pressure, the measurement state of the temperature monitor corresponding to the target elderly person is determined to be an unmeasured state. Otherwise, the measurement state of the temperature monitor corresponding to the target elderly person is determined to be a measured state.

3. A temperature monitoring remote monitoring system based on real-time data according to claim 1, characterized in that: The specific steps of monitoring and analyzing the usage status of the target elderly person corresponding to the current monitoring period are as follows: The motion sensor is used to monitor the motion amplitude of the target elderly person at each monitoring time point in the current monitoring period, and the motion amplitude of the target elderly person at each monitoring time point in the current monitoring period is obtained; With each monitoring time point as the horizontal coordinate and the movement amplitude at each monitoring time point as the vertical coordinate, a two-dimensional dynamic coordinate system is constructed, and the movement amplitude of the target elderly corresponding to each monitoring time point in the current monitoring period is plotted in the two-dimensional dynamic coordinate system and connected by lines to obtain a waveform diagram of the movement amplitude of the target elderly corresponding to the current monitoring period; The motion amplitude waveform diagram of the target elderly corresponding to the current monitoring period is matched with the motion amplitude waveform diagrams corresponding to each usage status stored in the system storage library to obtain the usage status of the target elderly corresponding to the current monitoring period.

4. A temperature monitoring remote monitoring system based on real-time data according to claim 1, characterized in that: The temperature health assessment index of the target elderly corresponding to the current monitoring period is analyzed, and the specific analysis method is as follows: Extract the body temperature of the target elderly person at each monitoring time point in the current monitoring period from the body temperature data of the target elderly person in the current monitoring period, and construct a body temperature change curve graph of the target elderly person in the current monitoring period; Extract each abnormal temperature period from the temperature change curve diagram of the target elderly corresponding to the current monitoring period, obtain the duration of each abnormal temperature period in the current monitoring period of the target elderly, and obtain the previous period of each abnormal temperature period, and at the same time make the duration of the previous period equal to the duration of the corresponding abnormal temperature period, and then form each abnormal temperature period and its corresponding previous period into an overall period, recorded as a temperature marking period, thereby obtaining each temperature marking period of the target elderly corresponding to the current monitoring period; Extracting the waist circumference, height, weight, age and gender of the target elderly from the physiological characteristic data of the target elderly stored in the system repository, matching the gender of the target elderly with the first body fat influence value corresponding to each gender stored, and obtaining the first body fat influence value X1 of the target elderly; The first body fat assessment index κ1 corresponding to the target elderly is calculated by the formula; Match the gender corresponding to the target elderly person with the stored second body fat influence value corresponding to each gender to obtain the second body fat influence value X2 corresponding to the target elderly person; The second body fat assessment index κ2 corresponding to the target elderly is calculated by the formula; According to the formula Calculate the body fat assessment coefficient κ of the target person, a1 and a2 are It is expressed as the coefficient factors corresponding to the set first body fat assessment index and second body fat assessment index. Matching the gender corresponding to the target elderly with the stored first metabolic impact values ​​corresponding to each gender to obtain the first metabolic impact value Y1 corresponding to the target elderly; The first basic metabolic assessment index λ1 corresponding to the target elderly is calculated by the formula; Matching the gender corresponding to the target elderly with the stored second metabolic impact values ​​corresponding to each gender to obtain the second metabolic impact value Y2 corresponding to the target elderly; The second basic metabolic assessment index λ2 corresponding to the target elderly is calculated by the formula; According to the formula Calculate the basal metabolic assessment coefficient λ corresponding to the target elderly, where a3 and a4 represent the coefficient factors corresponding to the set first basal metabolic assessment index and second basal metabolic assessment index, respectively; The physiological sign impact index γ corresponding to the target elderly is calculated according to the formula γ = κ × a5 + λ × a6, where a5 and a6 represent the weight factors corresponding to the set body fat assessment coefficient and basal metabolic assessment coefficient respectively; From the activity data of the target elderly corresponding to the current monitoring period, the activity intensity, the number of body posture changes, and the emotional state feedback values ​​of the target elderly corresponding to each temperature marking period in the current monitoring period are extracted and marked as ZD i 、N i , QX i , i represents the number of each temperature marking period, i=1,2,....,m, m represents the total number of temperature marking period numbers; According to the formula Calculate the activity data impact index of the target elderly corresponding to each temperature marking period ZD', N', QX' represent the set reference activity intensity, number of body posture changes, and emotional state feedback value, respectively; b1, b2, and b3 represent the weight factors corresponding to the set activity intensity, number of body posture changes, and emotional state feedback value, respectively; The atmospheric temperature and humidity at each marked time point in each temperature marked period of the target elderly person corresponding to the current monitoring period are extracted from the environmental data of the target elderly person corresponding to the current monitoring period, and the average values ​​are calculated respectively to obtain the average atmospheric temperature and average atmospheric humidity of each temperature marked period of the target elderly person corresponding to the current monitoring period, which are recorded as WD i , SD i ; According to the formula Calculate the environmental data impact index σ for each temperature mark period of the target elderly i , WD', SD' represent the set reference atmospheric temperature and reference atmospheric humidity respectively, b4, b5 represent the weight factors corresponding to the set atmospheric temperature and atmospheric humidity respectively; According to the formula Calculate the comprehensive data impact index ω of the target elderly corresponding to each abnormal temperature period i , c1, c2, and c3 represent the weight factors corresponding to the set physiological characteristics impact index, activity data impact index, and environmental data impact index, respectively; The comprehensive data impact index of the target elderly corresponding to each abnormal temperature period is matched with the temperature impact value corresponding to each set comprehensive data impact index to obtain the temperature impact value ΔTW of the target elderly corresponding to each abnormal temperature period i ; The body temperature of the target elderly at each time point in each temperature mark period is extracted from the body temperature change curve of the target elderly corresponding to the current monitoring period, and recorded as According to the formula The temperature health assessment index μ of the target elderly person corresponding to the current monitoring period is calculated, and TW' is represented as the set reference temperature.

5. A temperature monitoring remote monitoring system based on real-time data according to claim 1, characterized in that: The temperature health status of the target elderly person corresponding to the current monitoring period is analyzed in the following specific analysis methods: The body temperature health assessment index of the target elderly person corresponding to the current monitoring period is compared with the set body temperature health assessment index threshold. If the body temperature health assessment index of the target elderly person corresponding to the current monitoring period is less than the set body temperature health assessment index threshold, the body temperature health status of the target elderly person corresponding to the current monitoring period is judged to be abnormal; otherwise, the body temperature status of the target elderly person corresponding to the current monitoring period is judged to be normal.

6. A temperature monitoring remote monitoring system based on real-time data according to claim 1, characterized in that: The abnormal level of the target elderly corresponding to the current monitoring period is analyzed in the following specific analysis methods: If the temperature health status of the target elderly person corresponding to the current monitoring period is abnormal, the temperature health status assessment index of the target elderly person corresponding to the current monitoring period is subtracted from the set temperature health status assessment index threshold to obtain the temperature health status assessment index difference of the target elderly person corresponding to the current monitoring period; The temperature health status assessment index difference of the target elderly person corresponding to the current monitoring period is matched with the temperature health status assessment index difference corresponding to each set abnormal level to obtain the abnormal level of the target elderly person corresponding to the current monitoring period.

Images