A 5G-based medical supervision system

Abstract

The present invention discloses a 5G-based medical supervision system, which relates to the field of medical service technology and is applied to a medical supervision platform, including a medical record analysis module, a vital sign analysis module and an associated early warning module; the medical record analysis module is used to receive and analyze the user's electronic medical record information, and calculate the diagnosis and treatment coefficient ZL; if ZL> the diagnosis and treatment coefficient threshold, a diagnosis and treatment signal is generated; after the medical supervision platform receives the diagnosis and treatment signal, it generates a vital sign analysis signal; in response to receiving the vital sign analysis signal, the vital sign analysis module is used to collect and analyze the user's vital sign parameter information at preset intervals, and evaluate the user's physical condition; the associated early warning module is used to transmit the vital sign abnormality signal and the user's vital sign parameter information to the mobile phone terminal of the corresponding family member for early warning, thereby increasing the family members' attention to the user's physical health, thereby providing timely treatment, which can effectively improve the user's medical safety and improve the efficiency of medical supervision.

Description

Technical Field

[0001] The present invention relates to the field of medical service technology, and in particular to a 5G-based medical supervision system. Background Art

[0002] In the existing technology, each hospital, each person and each medical device are relatively independent of each other. Every time a patient goes to a hospital, he needs to communicate with the doctor separately. The doctor knows nothing about the patient's previous medical history. In addition, he needs to wait for the physical examination report when he goes to the hospital for a physical examination, and then take the physical examination report to the doctor for communication. Relying on the 5G smart medical private network to access a variety of medical devices and terminals, it can improve the work efficiency of medical institutions and medical personnel for different medical application scenarios such as in-hospital, inter-hospital and out-of-hospital emergency treatment, and meet the medical application needs such as emergency treatment, consultation, nursing and visiting. To this end, we propose a 5G-based medical supervision system. Summary of the invention

[0003] In order to solve the problems existing in the above solutions, the present invention provides a 5G-based medical supervision system.

[0004] The purpose of the present invention can be achieved through the following technical solutions:

[0005] A 5G-based medical supervision system, applied to a medical supervision platform, including a medical record collection module, a medical record analysis module, a vital sign analysis module, and a related warning module;

[0006] The medical record collection module is used to collect the user's electronic medical record information and upload the collected electronic medical record information to the medical record analysis module through the 5G wireless transmission module;

[0007] The medical record analysis module is used to receive and analyze the user's electronic medical record information, and calculate the diagnosis and treatment coefficient ZL; if ZL> the diagnosis and treatment coefficient threshold, a diagnosis and treatment signal is generated and sent to the medical supervision platform;

[0008] After receiving the diagnosis and treatment signal, the medical supervision platform generates a vital sign analysis signal and sends the vital sign analysis signal to the vital sign analysis module; in response to receiving the vital sign analysis signal, the vital sign analysis module is used to collect and analyze the vital sign parameter information of the user at preset intervals, calculate the health impact coefficient Gm of the user, and evaluate the user's physical condition according to the change trend of Gm;

[0009] When the user's physical condition is abnormal, the associated warning module is used to transmit the abnormal physical sign signal and the user's physical sign parameter information to the mobile phone terminal of the corresponding family member for warning.

[0010] Furthermore, the specific analysis steps of the medical record analysis module are:

[0011] Obtain the electronic medical record information of users within six months before the current time of the system, mark the diagnosis and treatment time in each electronic medical record information as ZTi, and the disease threat level as ZWi; use the formula TWi=ZTi×a1+ZWi×a2 to calculate the medical record threat value TWi; where a1 and a2 are coefficient factors;

[0012] Obtain all medical record threat values ​​TWi to form a threat information group; calculate the time difference between the most recent diagnosis time and the current system time to obtain the delayed diagnosis time HT; calculate the standard deviation µ of the threat information group according to the standard deviation calculation formula. If µ≤the preset standard deviation threshold, calculate the diagnosis and treatment coefficient ZL using the formula ZL=TWn×a3+HT×a4; where a3 and a4 are coefficient factors; and TWn represents the disease threat level in the most recent electronic medical record information.

[0013] Furthermore, if µ> the preset standard deviation threshold, all TWi greater than TWn in the threat information group are obtained and marked as Zwi; Zwi minus TWn is used to obtain the excess threat value CXi; the time difference between the diagnosis time corresponding to Zwi and the current time of the system is calculated to obtain the impact duration Ywi; the radiation coefficient FWi is calculated using the formula FWi=(CXi×g1) / (Ywi×g2), where g1 and g2 are coefficient factors;

[0014] The total radiation value FZ is obtained by summing up all the radiation coefficients FWi; the diagnosis and treatment coefficient ZL is calculated using the formula ZL=TWn×a3+HT×a4+FZ×a5, where a5 is the coefficient factor.

[0015] Furthermore, the medical supervision platform is also used to send a reminder message to the user's mobile phone terminal after receiving the diagnosis and treatment signal, reminding the user to go to the hospital for a health check as soon as possible.

[0016] Furthermore, the specific analysis steps of the vital sign analysis signal are:

[0017] Collecting the user's vital sign parameter information at preset intervals, comparing the collected vital sign parameter values ​​with the safety data of the corresponding vital sign parameters stored in the database, and obtaining the data difference of the corresponding vital sign parameters;

[0018] Obtain the data difference of each physical sign parameter that is greater than zero, and calculate the user's health impact coefficient Gm by combining the impact factors of each physical sign parameter on physical health stored in the database;

[0019] The health impact coefficient Gm is compared with the preset coefficient threshold; within a preset time period, if the number of Gm≥preset coefficient threshold reaches a first preset number or a first predetermined proportion or the number of consecutive Gm≥preset coefficient threshold reaches a second preset number, it is determined that the user's physical condition is abnormal at this time, and an abnormal vital sign signal is generated; the physical sign analysis signal is used to feed back the abnormal vital sign signal to the medical supervision platform, and the medical supervision platform is used to send the abnormal vital sign signal to the user's mobile phone terminal.

[0020] Furthermore, the specific working steps of the associated warning module are:

[0021] With the user's location as the center, family members whose distance difference is less than a preset distance threshold are marked as preliminary candidates, and the mobile terminals of the preliminary candidates are marked as preliminary terminals;

[0022] Collect the historical records of data transmission from the associated warning module to the preliminary terminal; mark the delay of each data transmission as Hm, and calculate the total delay value YZ of the preliminary terminal; mark the code rate of data transmission from the associated warning module to the preliminary terminal as M1, and use the formula FS=(M1×k1) / (D1×k2+YZ×k3) to calculate the sending value FS of the preliminary terminal, where k1, k2, and k3 are coefficient factors;

[0023] The preliminary terminal with the largest sending value FS is selected as the selected terminal, and the associated warning module is used to transmit the abnormal vital sign signal and the vital sign parameter information of the corresponding user to the selected terminal for warning.

[0024] Furthermore, the total delay value YZ is calculated as follows:

[0025] Compare the delay Hm with the delay threshold; when the delay Hm is greater than the delay threshold, subtract the delay threshold from the delay Hm to obtain the excess delay value CH; calculate the time difference between the transmission time corresponding to the delay Hm and the current system time to obtain the buffering time length YT;

[0026] The delay coefficient YX is calculated using the formula YX=(CH×g3) / (YT×g4); g3 and g4 are coefficient factors; all delay coefficients YX are summed up to obtain the total delay value YZ.

[0027] Furthermore, the electronic medical record information includes diagnosis time, treatment duration and detailed description of the disease; wherein the detailed description of the disease carries information on the threat level of the disease; and the vital sign parameter information includes heart rate, body temperature, blood pressure, blood oxygen concentration and blood sugar.

[0028] Compared with the prior art, the present invention has the following beneficial effects:

[0029] 1. The medical record analysis module in the present invention is used to receive and analyze the electronic medical record information of the user, and calculate the diagnosis and treatment coefficient ZL; if ZL> the diagnosis and treatment coefficient threshold, a diagnosis and treatment signal is generated; after receiving the diagnosis and treatment signal, the medical supervision platform sends a reminder message to the user's mobile phone terminal, reminding the user to go to the hospital for a health check as soon as possible; at the same time, the medical supervision platform is also used to generate a vital sign analysis signal after receiving the diagnosis and treatment signal; in response to receiving the vital sign analysis signal, the vital sign analysis module is used to collect and analyze the user's vital sign parameter information at preset intervals; compare the collected vital sign parameter values ​​with the safety data of the corresponding vital sign parameters stored in the database, and calculate the user's health impact coefficient Gm; evaluate the user's physical condition according to the change trend of Gm, issue a timely warning, and remind the user to go to the hospital as soon as possible, evaluate the user's physical condition according to the change trend of Gm, and issue a timely warning, which can effectively improve the user's medical safety and improve the efficiency of medical supervision;

[0030] 2. When the user's physical condition is abnormal, the associated warning module is used to transmit the abnormal vital sign signal and the user's vital sign parameter information to the mobile phone terminal of the corresponding family member for warning. The sending value FS of the preliminary terminal is calculated based on the personal distance, total delay value, and bit rate, and the preliminary terminal with the largest sending value FS is selected as the selected terminal, so that the user's abnormal vital sign parameter information can be notified to the corresponding family members in the first time, thereby increasing family members' attention to the user's physical health, thereby providing timely treatment, and effectively improving the user's medical safety. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0032] Figure 1 This is a principle block diagram of the present invention. DETAILED DESCRIPTION

[0033] The technical scheme of the present invention will be clearly and completely described below in conjunction with the embodiments. Obviously, the described embodiments are only part of the embodiments of the present invention, rather than 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.

[0034] like Figure 1As shown, a 5G-based medical supervision system is applied to a medical supervision platform, including a medical record collection module, a medical record analysis module, a 5G wireless transmission module, a vital sign analysis module, and a related warning module;

[0035] Example 1

[0036] The medical record collection module is used to collect the user's electronic medical record information and upload the collected electronic medical record information to the medical record analysis module through the 5G wireless transmission module; the electronic medical record information includes the diagnosis time, treatment duration and detailed description of the disease; the detailed description of the disease carries the disease threat level information; the higher the disease threat level, the more serious the disease;

[0037] The medical record analysis module is used to receive and analyze the user's electronic medical record information. The specific analysis steps are as follows:

[0038] S11: Obtain the electronic medical record information of the user within six months before the current time of the system, mark the diagnosis and treatment time in each electronic medical record information as ZTi, and mark the disease threat level as ZWi;

[0039] The medical record threat value TWi is calculated using the formula TWi=ZTi×a1+ZWi×a2; where a1 and a2 are coefficient factors;

[0040] S12: Obtain all medical record threat values ​​TWi to form a threat information group; calculate the time difference between the most recent diagnosis time and the current system time to obtain the delayed diagnosis time HT;

[0041] The standard deviation µ of the threat information group is calculated according to the standard deviation calculation formula. If µ≤the preset standard deviation threshold, the diagnosis and treatment coefficient ZL is calculated using the formula ZL=TWn×a3+HT×a4; where a3 and a4 are coefficient factors; where TWn represents the disease threat level in the most recent electronic medical record information;

[0042] S13: If µ> the preset standard deviation threshold, obtain all TWi in the threat information group that is greater than TWn and mark them as Zwi; subtract TWn from Zwi to obtain the excess threat value CXi; calculate the time difference between the diagnosis time corresponding to Zwi and the current time of the system to obtain the impact duration Ywi;

[0043] The radiation coefficient FWi is calculated using the formula FWi=(CXi×g1) / (Ywi×g2), where g1 and g2 are coefficient factors; all radiation coefficients FWi are summed up to obtain the total radiation value FZ;

[0044] The diagnosis and treatment coefficient ZL is calculated using the formula ZL=TWn×a3+HT×a4+FZ×a5, where a5 is the coefficient factor;

[0045] S14: Compare the diagnosis and treatment coefficient ZL with the diagnosis and treatment coefficient threshold; if ZL> the diagnosis and treatment coefficient threshold, generate a diagnosis and treatment signal; the medical record analysis module is used to transmit the diagnosis and treatment signal to the medical supervision platform, and the medical supervision platform sends a reminder message to the user's mobile phone terminal after receiving the diagnosis and treatment signal, reminding the user to go to the hospital for a health check as soon as possible;

[0046] Example 2

[0047] The medical supervision platform is also used to generate a vital sign analysis signal after receiving the diagnosis and treatment signal and send the vital sign analysis signal to the vital sign analysis module;

[0048] In response to receiving the vital sign analysis signal, the vital sign analysis module is used to collect and analyze the user's vital sign parameter information at preset intervals; the vital sign parameter information includes heart rate, body temperature, blood pressure, blood oxygen concentration and blood sugar; the specific analysis steps are:

[0049] S21: collecting the user's vital sign parameter information at preset intervals, comparing the collected vital sign parameter values ​​with the safety data of the corresponding vital sign parameters stored in the database, and obtaining data differences of the corresponding vital sign parameters; wherein the data differences of the vital sign parameters include heart rate difference, body temperature difference, blood pressure difference, blood oxygen concentration difference and blood sugar difference;

[0050] In this embodiment, the safety data of each vital sign parameter is a range. If the vital sign parameter value is within the safety range, the corresponding data difference is zero; if the vital sign parameter value is outside the safety range, the upper and lower limits of the safety range are obtained, and the corresponding data difference is the difference between the vital sign parameter value and the upper or lower limit, which is a positive number; for example: if the vital sign parameter value is less than the lower limit, the data difference = lower limit - vital sign parameter value; if the vital sign parameter value is greater than the upper limit, the data difference = vital sign parameter value - upper limit;

[0051] S22: Obtain data differences of various physical sign parameters that are greater than zero, and calculate the health impact coefficient Gm of the user in combination with the impact factors of various physical sign parameters on physical health stored in the database;

[0052] S23: Compare the health impact coefficient Gm with the preset coefficient threshold; if Gm≥the preset coefficient threshold, set the comparison result SD=1; if Gm<the preset coefficient threshold, set the comparison result SD=0;

[0053] Within a preset time period, if the number of SD=1 reaches a first preset number or a first predetermined ratio or the number of consecutive SD=1 reaches a second preset number, it is determined that the user's physical state is abnormal at this time, and a physical sign abnormality signal is generated;

[0054] The vital sign analysis signal is used to feed back the abnormal vital sign signal to the medical supervision platform, and the medical supervision platform is used to send the abnormal vital sign signal to the user's mobile terminal, timely warning, reminding the user to go to the hospital as soon as possible; it can effectively improve the user's medical safety;

[0055] The present invention can refer to the user's electronic medical record information, evaluate the user's diagnosis and treatment coefficient, and promptly remind the user to go to the hospital for a health check-up. At the same time, it triggers physical sign analysis according to the diagnosis and treatment coefficient, collects the user's physical sign parameter information at preset intervals, compares the collected physical sign parameter information with the safety data of the corresponding physical sign parameters stored in the database, and calculates the user's health impact coefficient Gm; evaluates the user's physical condition according to the change trend of Gm, and issues a timely warning, which can effectively improve the user's medical safety and improve the efficiency of medical supervision;

[0056] Example 3

[0057] The medical supervision platform is also used to transmit the physical sign parameter information of the corresponding user to the associated warning module after receiving the abnormal physical sign signal; the associated warning module is used to transmit the abnormal physical sign signal and the physical sign parameter information of the corresponding user to the mobile phone terminal of the corresponding family member for warning; the specific steps are:

[0058] V1: The associated warning module sends a location acquisition command to the mobile phone terminal of the family member to obtain the current real-time location of the mobile phone terminal of the family member; the distance difference between the current real-time location of the family member and the user location is calculated to obtain the personnel distance D1;

[0059] The family members whose personal distance D1 is less than the preset distance threshold are marked as preliminary selection persons, and the mobile phone terminals of the preliminary selection persons are marked as preliminary selection terminals;

[0060] V2: Collect the historical records of data transmitted from the associated warning module to the primary terminal; the historical records carry the transmission time and the corresponding delay; mark the delay of each data transmission as Hm; the historical records can be the records of the last three months; compare the delay Hm with the delay threshold; when the delay Hm is greater than the delay threshold, execute step V3;

[0061] V3: Subtract the delay threshold from the delay Hm to get the overdelay value CH; calculate the time difference between the transmission time corresponding to the delay Hm and the current system time to get the buffer time YT; use the formula YX=(CH×g3) / (YT×g4) to calculate the delay coefficient YX; where g3 and g4 are coefficient factors; sum up all the delay coefficients YX to get the total delay value YZ;

[0062] V4: Mark the code rate of data transmitted from the associated warning module to the primary terminal as M1;

[0063] Normalize the personnel distance, total delay value, and bit rate and take their values. Use the formula FS=(M1×k1) / (D1×k2+YZ×k3) to calculate the sending value FS of the primary terminal, where k1, k2, and k3 are coefficient factors.

[0064] V5: The preliminary terminal with the largest sending value FS is selected as the selected terminal. The associated warning module is used to transmit the abnormal vital sign signal and the corresponding user's vital sign parameter information to the selected terminal for warning, so that the user's abnormal vital sign parameter information can be notified to the corresponding family members in the first time, thereby increasing family members' attention to the user's physical health, thereby timely treatment, and effectively improving the user's medical safety.

[0065] The above formulas are all calculated by removing dimensions and taking numerical values. The formula is a formula that is closest to the actual situation obtained by collecting a large amount of data and performing software simulation. The preset parameters and preset thresholds in the formula are set by technical personnel in this field according to actual conditions or obtained by simulating a large amount of data.

[0066] Working principle of the present invention:

[0067] A 5G-based medical supervision system, when working, firstly, the medical record collection module is used to collect the user's electronic medical record information, and upload the collected electronic medical record information to the medical record analysis module through the 5G wireless transmission module; the medical record analysis module is used to receive the user's electronic medical record information and analyze it, and calculate the diagnosis and treatment coefficient ZL; if ZL> the diagnosis and treatment coefficient threshold, a diagnosis and treatment signal is generated; after receiving the diagnosis and treatment signal, the medical supervision platform sends a reminder message to the user's mobile terminal, reminding the user to go to the hospital for a health check as soon as possible;

[0068] The medical supervision platform is also used to generate a vital sign analysis signal after receiving the diagnosis and treatment signal; in response to receiving the vital sign analysis signal, the vital sign analysis module is used to collect and analyze the user's vital sign parameter information at preset intervals; compare the collected vital sign parameter values ​​with the safety data of the corresponding vital sign parameters stored in the database, and calculate the user's health impact coefficient Gm; evaluate the user's physical condition according to the change trend of Gm, and generate a vital sign abnormality signal and send it to the user's mobile phone terminal, so as to issue a timely warning and remind the user to go to the hospital for treatment as soon as possible;

[0069] The medical supervision platform is also used to transmit the vital sign parameter information of the corresponding user to the associated early warning module after receiving the abnormal vital sign signal; the associated early warning module is used to transmit the abnormal vital sign signal and the vital sign parameter information of the corresponding user to the mobile phone terminal of the corresponding family member for early warning, and the sending value FS of the preliminary terminal is calculated by combining the personnel distance, total delay value and bit rate, and the preliminary terminal with the largest sending value FS is selected as the selected terminal, so that the user's abnormal vital sign parameter information can be notified to the corresponding family members in the first time, thereby increasing family members' attention to the user's physical health, thereby timely treatment, and effectively improving the user's medical safety.

[0070] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0071] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A 5G-based medical supervision system, applied to a medical supervision platform, characterized in that: It includes medical record collection module, medical record analysis module, database, vital sign analysis module and related warning module; The medical record collection module is used to collect the user's electronic medical record information and upload the collected electronic medical record information to the medical record analysis module through the 5G wireless transmission module; the electronic medical record information includes the diagnosis time, treatment duration and detailed description of the disease; wherein the detailed description of the disease carries information on the threat level of the disease; The medical record analysis module is used to receive and analyze the user's electronic medical record information and calculate the diagnosis and treatment coefficient ZL; the specific analysis steps are: S11: Obtain the electronic medical record information of the user within six months before the current time of the system, mark the diagnosis and treatment time in each electronic medical record information as ZTi, and mark the disease threat level as ZWi; The medical record threat value TWi is calculated using the formula TWi=ZTi×a1+ZWi×a2; where a1 and a2 are coefficient factors; S12: Obtain all medical record threat values ​​TWi to form a threat information group; calculate the time difference between the most recent diagnosis time and the current system time to obtain the delayed diagnosis time HT; The standard deviation µ of the threat information group is calculated according to the standard deviation calculation formula. If µ≤the preset standard deviation threshold, the diagnosis and treatment coefficient ZL is calculated using the formula ZL=TWn×a3+HT×a4; where a3 and a4 are coefficient factors; where TWn represents the disease threat level in the most recent electronic medical record information; S13: If µ> the preset standard deviation threshold, obtain all TWi in the threat information group that is greater than TWn and mark them as Zwi; subtract TWn from Zwi to obtain the excess threat value CXi; calculate the time difference between the diagnosis time corresponding to Zwi and the current time of the system to obtain the impact duration Ywi; The radiation coefficient FWi is calculated using the formula FWi=(CXi×g1) / (Ywi×g2), where g1 and g2 are coefficient factors; Sum all the radiation coefficients FWi to get the total radiation value FZ; The diagnosis and treatment coefficient ZL is calculated using the formula ZL=TWn×a3+HT×a4+FZ×a5, where a5 is the coefficient factor; S14: comparing the diagnosis and treatment coefficient ZL with the diagnosis and treatment coefficient threshold; If ZL> the diagnosis and treatment coefficient threshold, a diagnosis and treatment signal is generated; the medical record analysis module is used to transmit the diagnosis and treatment signal to the medical supervision platform. After receiving the diagnosis and treatment signal, the medical supervision platform sends a reminder message to the user's mobile terminal to remind the user to go to the hospital for a health check as soon as possible; The medical supervision platform is also used to generate a vital sign analysis signal after receiving the diagnosis and treatment signal and send the vital sign analysis signal to the vital sign analysis module; in response to receiving the vital sign analysis signal, the vital sign analysis module is used to collect and analyze the user's vital sign parameter information at preset intervals; the vital sign parameter information includes heart rate, body temperature, blood pressure, blood oxygen concentration and blood sugar; the specific analysis steps are: S21: collecting the user's vital sign parameter information at preset intervals, comparing the collected vital sign parameter values ​​with the safety data of the corresponding vital sign parameters stored in the database, and obtaining data differences of the corresponding vital sign parameters; wherein the data differences of the vital sign parameters include heart rate difference, body temperature difference, blood pressure difference, blood oxygen concentration difference and blood sugar difference; S22: Obtain data differences of various physical sign parameters that are greater than zero, and calculate the health impact coefficient Gm of the user in combination with the impact factors of various physical sign parameters on physical health stored in the database; S23: comparing the health impact coefficient Gm with a preset coefficient threshold; If Gm≥preset coefficient threshold, the comparison result SD=1; if Gm<preset coefficient threshold, the comparison result SD=0; Within a preset time period, if the number of SD=1 reaches a first preset number or a first predetermined ratio or the number of consecutive SD=1 reaches a second preset number, it is determined that the user's physical state is abnormal at this time, and a physical sign abnormality signal is generated; The vital sign analysis signal is used to feed back the abnormal vital sign signal to the medical supervision platform, and the medical supervision platform is used to send the abnormal vital sign signal to the user's mobile terminal to remind the user to go to the hospital for treatment as soon as possible; The medical supervision platform is also used to transmit the physical sign parameter information of the corresponding user to the associated warning module after receiving the abnormal physical sign signal; the associated warning module is used to transmit the abnormal physical sign signal and the physical sign parameter information of the corresponding user to the mobile phone terminal of the corresponding family member for warning; the specific steps are: V1: The associated warning module sends a location acquisition command to the mobile phone terminal of the family member to obtain the current real-time location of the mobile phone terminal of the family member; the distance difference between the current real-time location of the family member and the user location is calculated to obtain the personnel distance D1; The family members whose personal distance D1 is less than the preset distance threshold are marked as preliminary selection persons, and the mobile phone terminals of the preliminary selection persons are marked as preliminary selection terminals; V2: Collect the historical records of data transmitted from the associated warning module to the primary terminal; the historical records carry the transmission time and the corresponding delay; mark the delay of each data transmission as Hm; compare the delay Hm with the delay threshold; when the delay Hm is greater than the delay threshold, execute step V3; V3: Subtract the delay threshold from the delay Hm to get the overdelay value CH; calculate the time difference between the transmission time corresponding to the delay Hm and the current system time to get the buffer time YT; use the formula YX=(CH×g3) / (YT×g4) to calculate the delay coefficient YX; where g3 and g4 are coefficient factors; sum up all the delay coefficients YX to get the total delay value YZ; V4: Mark the code rate of data transmitted from the associated warning module to the primary terminal as M1; Normalize the personnel distance, total delay value, and bit rate and take their values. Use the formula FS=(M1×k1) / (D1×k2+YZ×k3) to calculate the sending value FS of the primary terminal, where k1, k2, and k3 are coefficient factors. V5: The preliminary terminal with the largest sending value FS is selected as the selected terminal, and the associated warning module is used to transmit the abnormal vital sign signal and the vital sign parameter information of the corresponding user to the selected terminal for warning.

Images