CN115251859A

CN115251859A - Human respiratory system risk management and control early warning method and device and storage medium

Info

Publication number: CN115251859A
Application number: CN202210779171.3A
Authority: CN
Inventors: 饶定东
Original assignee: Hubei Zhiao Internet Of Things Technology Co ltd
Current assignee: Hubei Zhiao Internet Of Things Technology Co ltd
Priority date: 2022-07-04
Filing date: 2022-07-04
Publication date: 2022-11-01

Abstract

The invention discloses a human respiratory system risk management and control early warning method, a device and a storage medium, wherein the method comprises the following steps: collecting multi-vital sign data of a user to be detected; determining the high-order duration of the multi-vital sign data corresponding to the preset high-order state of the vital signs; determining the target breathing frequency of the user to be detected according to the high-order duration; and carrying out human respiratory system risk management, control and early warning on the user to be detected according to the high-order duration and the target respiratory frequency. Compared with the existing respiratory system monitoring technology which mainly depends on a thermometer, an oximeter or an imaging technology to diagnose whether the lung of an individual of a user is infected or not, the method and the device realize the accurate acquisition of the multi-vital sign data and the target respiratory frequency of the individual by acquiring the multi-vital sign data and the target respiratory frequency of the user to be detected in real time through the terminal, and then carry out human respiratory system risk control early warning on the user according to the high-position duration and the target respiratory frequency, so that the user can observe the abnormal condition of the body in time.

Description

Human respiratory system risk management and control early warning method and device and storage medium

Technical Field

The invention relates to the technical field of respiratory system monitoring, in particular to a human respiratory system risk management and control early warning method, a human respiratory system risk management and control early warning device and a storage medium.

Background

With the great change of global environment and climate, the abnormal condition of human respiratory system and the infection of lung frequently occur, the existing respiratory system monitoring technology mainly depends on a thermometer, an oximeter or an imaging technology to diagnose whether the lung of an individual user is infected, the diagnosis data is single-point data, the image diagnosis needs to be checked by a professional at a specific place, the diagnosis data is single-point data at a certain moment, and the abnormal condition and the development trend of the respiratory system of the user cannot be observed in time.

The above is only for the purpose of assisting understanding of the technical aspects of the present invention, and does not represent an admission that the above is prior art.

Disclosure of Invention

The invention mainly aims to provide a human respiratory system risk management and control early warning method, a human respiratory system risk management and control early warning device and a storage medium, and aims to solve the technical problem of how to accurately obtain individual vital sign data and target respiratory frequency and facilitate a user to observe abnormal conditions of the body in time.

In order to achieve the purpose, the invention provides a human respiratory system risk management and control early warning method, which comprises the following steps:

collecting multi-vital sign data of a user to be detected, wherein the multi-vital sign data comprise: heart rate, blood oxygen, body temperature, and cardiopulmonary function;

determining the high-order duration corresponding to the preset high-order state of the vital signs of the multi-vital sign data;

determining the target breathing frequency of the user to be detected according to the high-order duration;

and carrying out human respiratory system risk management and control early warning on the user to be detected according to the high-position duration and the target respiratory frequency.

Optionally, the step of determining that the multi-vital sign data is in a high-order duration corresponding to a preset high-order state of the vital sign includes:

determining identity information of the user to be detected;

determining a corresponding preset high-order state condition according to the identity information;

extracting a plurality of vital sign data to be monitored from the multi-vital sign data according to the preset high-order state condition;

and determining the high-order duration corresponding to the preset high-order state of the vital sign data to be monitored.

Optionally, the step of determining the target breathing frequency of the user to be detected according to the high duration includes:

when the high-order duration is longer than a preset duration, generating a vital sign curve graph according to the plurality of vital sign data to be monitored;

and determining the target breathing frequency of the user to be detected according to the trend of the vital sign curve graph.

Optionally, the step of determining the target breathing frequency of the user to be detected according to the trend of the vital sign graph includes:

when the trend of the vital sign graph is in a gentle trend or an ascending trend, determining a plurality of respiratory frequencies to be processed according to the plurality of vital sign data to be monitored;

determining a corresponding normal breathing frequency according to the identity information;

judging whether abnormal breathing frequency exists in the plurality of breathing frequencies to be processed according to the normal breathing frequency;

if abnormal breathing frequency exists in the plurality of breathing frequencies to be processed, selecting a plurality of abnormal breathing frequencies to be processed from the plurality of breathing frequencies to be processed;

and determining the target breathing frequency of the user to be detected according to the plurality of abnormal breathing frequencies to be processed.

Optionally, after the step of determining whether there is an abnormal respiratory rate in the plurality of respiratory rates to be processed according to the normal respiratory rate, the method further includes:

if abnormal breathing frequency does not exist in the plurality of breathing frequencies to be processed, determining a health strategy according to the vital sign curve graph and the identity information of the user to be detected;

and carrying out emergency treatment on the user to be detected according to the health strategy.

Optionally, the step of determining the target breathing frequency of the user to be detected according to the trend of the vital sign graph further includes:

when the trend of the vital sign graph is in a descending trend, determining a plurality of respiratory frequencies to be processed according to the plurality of vital sign data to be monitored;

selecting the lowest respiratory frequency from the plurality of respiratory frequencies to be treated;

and taking the lowest breathing frequency as the target breathing frequency of the user to be detected.

Optionally, the step of performing human respiratory system risk management and control early warning on the user to be detected according to the high-order duration and the target respiratory frequency includes:

determining body abnormal state information according to the high-order duration and the target respiratory frequency;

analyzing the multi-vital sign data according to the body abnormal state information to obtain a vital sign abnormal report;

and carrying out human respiratory system risk management, control and early warning on the user to be detected based on the vital sign abnormal report.

In addition, in order to achieve the above object, the present invention further provides a human respiratory system risk management and control early warning device, including:

the acquisition module is used for acquiring multi-vital sign data of a user to be detected, wherein the multi-vital sign data comprises: heart rate, blood oxygen, body temperature, and cardiopulmonary function;

the determining module is used for determining the high-order duration of the multi-vital sign data corresponding to the preset high-order state of the vital sign;

the determining module is further configured to determine a target breathing frequency of the user to be detected according to the high-order duration;

and the management and control early warning module is used for carrying out human respiratory system risk management and control early warning on the user to be detected according to the high-order duration and the target respiratory frequency.

In addition, in order to achieve the above object, the present invention further provides a human respiratory system risk management and control early warning device, which comprises: the human respiratory system risk management and control early warning method comprises a memory, a processor and a human respiratory system risk management and control early warning program which is stored on the memory and can be operated on the processor, wherein the human respiratory system risk management and control early warning program is configured to realize the steps of the human respiratory system risk management and control early warning method.

In addition, in order to achieve the above object, the present invention further provides a storage medium, where the storage medium stores a human respiratory system risk management and control early warning program, and when the human respiratory system risk management and control early warning program is executed by a processor, the steps of the human respiratory system risk management and control early warning method as described above are implemented.

The method comprises the steps of firstly collecting multi-vital sign data of a user to be detected, wherein the multi-vital sign data comprise: heart rate, blood oxygen, body temperature and heart and lung function, then determine that many vital sign data are in the high position duration that predetermines the high position state of vital sign and correspond to, and confirm the target respiratory frequency of waiting to detect the user according to high position duration, later treat to detect the user according to high position duration and target respiratory frequency and carry out human respiratory system risk management and control early warning. Compared with the existing respiratory system monitoring technology, whether the lung of an individual user is infected or not is diagnosed mainly by means of a thermometer, an oximeter or an imaging technology, the diagnosis data are single-point data, the image diagnosis needs to be checked by a professional at a specific place, the diagnosis data are single-point data at a certain moment, the abnormal condition and the development trend of the respiratory system of the user cannot be observed in time, and then corresponding treatment measures cannot be taken.

Drawings

Fig. 1 is a schematic structural diagram of a human respiratory system risk management and control early warning device in a hardware operating environment according to an embodiment of the present invention;

FIG. 2 is a schematic flow chart illustrating a risk management and control early warning method for a respiratory system of a human body according to a first embodiment of the present invention;

FIG. 3 is a schematic flowchart illustrating a risk management and control early warning method for a respiratory system of a human body according to a second embodiment of the present invention;

FIG. 4 is a flowchart illustrating a risk management and control early warning method for a respiratory system of a human body according to a third embodiment of the present invention;

fig. 5 is a block diagram of a risk management and control early warning device for a respiratory system of a human body according to a first embodiment of the present invention.

The implementation, functional features and advantages of the objects of the present invention will be further explained with reference to the accompanying drawings.

Detailed Description

It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.

Referring to fig. 1, fig. 1 is a schematic structural diagram of a human respiratory system risk management and control early warning device in a hardware operating environment according to an embodiment of the present invention.

As shown in fig. 1, the human respiratory system risk management and control early warning device may include: a processor 1001, such as a Central Processing Unit (CPU), a communication bus 1002, a user interface 1003, a network interface 1004, and a memory 1005. Wherein a communication bus 1002 is used to enable connective communication between these components. The user interface 1003 may include a Display screen (Display), an input unit such as a Keyboard (Keyboard), and the optional user interface 1003 may also include a standard wired interface, a wireless interface. The network interface 1004 may optionally include a standard wired interface, a Wireless interface (e.g., a Wireless-Fidelity (Wi-Fi) interface). The Memory 1005 may be a high-speed Random Access Memory (RAM) or a Non-Volatile Memory (NVM), such as a disk Memory. The memory 1005 may alternatively be a storage device separate from the processor 1001.

It will be appreciated by those skilled in the art that the arrangement shown in figure 1 does not constitute a limitation of the human respiratory risk management warning device and may include more or fewer components than shown, or some components in combination, or a different arrangement of components.

As shown in fig. 1, a memory 1005 as a storage medium may include an operating system, a network communication module, a user interface module, and a human respiratory system risk management and early warning program.

In the human respiratory system risk management and control early warning device shown in fig. 1, the network interface 1004 is mainly used for data communication with a network server; the user interface 1003 is mainly used for data interaction with a user; the processor 1001 and the memory 1005 of the human respiratory system risk management and control early warning device can be arranged in the human respiratory system risk management and control early warning device, and the human respiratory system risk management and control early warning device calls the human respiratory system risk management and control early warning program stored in the memory 1005 through the processor 1001 and executes the human respiratory system risk management and control early warning method provided by the embodiment of the invention.

An embodiment of the present invention provides a human respiratory system risk management and control early warning method, and referring to fig. 2, fig. 2 is a schematic flow diagram of a first embodiment of the human respiratory system risk management and control early warning method according to the present invention.

In this embodiment, the human respiratory system risk management and control early warning method includes the following steps:

step S10: collecting multi-vital sign data of a user to be detected, wherein the multi-vital sign data comprise: heart rate, blood oxygen, body temperature, and cardiopulmonary function.

It is easily understood that, the execution main part of this embodiment can be human respiratory system risk management and control early warning device that has functions such as data processing, network communication and program operation, for example, the wrist-watch is dressed to intelligence, clothing or intelligent house etc. are dressed to intelligence, this embodiment does not make the restriction to this, this embodiment explains with the wrist-watch is dressed to intelligence as an example, wherein, human respiratory system risk management and control early warning device is saved with medical grade heart rate sensor, human respiratory system risk management and control early warning device can also understand to the equipment of the built-in human respiratory system risk management and control early warning function of intelligence dress wrist-watch, intelligence dress wrist-watch collection terminal can gather human many vital sign data and monitor in real time, provide convenient health management data reference etc. for respiratory system disease patient, this embodiment is not restricted.

It should be further noted that the user to be detected can be the user wearing the intelligent wearable watch, and the multi-vital sign data can be heart rate data, blood oxygen data, body temperature data, cardiopulmonary function data (i.e. respiratory rate) and the like acquired in real time by using the medical grade sensor.

Step S20: and determining the high-order duration corresponding to the preset high-order state of the vital signs of the multi-vital-sign data.

It should be understood that the preset high vital sign state is a state in which the multi-vital sign data of the individual is higher than the normal multi-vital sign data, and the high duration time may be a continuous time in which the multi-vital sign data of the individual is higher than the normal multi-vital sign data, and the high duration time may be 36h, or may also be 24h, 48h, and the like.

In specific implementation, due to the fact that normal multi-vital sign data corresponding to users of all age groups are different, in order to accurately monitor a user to be detected, the processing mode for determining the high-order duration corresponding to the high-order state of the multi-vital sign data can be used for determining the identity information of the user to be detected, then the corresponding preset high-order state condition is determined according to the identity information, a plurality of pieces of vital sign data to be monitored are extracted from the multi-vital sign data according to the preset high-order state condition, and the high-order duration corresponding to the high-order state of the multi-vital sign data to be monitored is determined.

It should be noted that the identity information of the user to be detected may be the age, the historical health information, and the like of the user to be detected, the preset high-order state condition may be abnormal multi-vital-sign data corresponding to the user to be detected, and the abnormal multi-vital-sign data is different from the normal multi-vital-sign data. The respiratory frequency of the newborn is assumed to be 40-45 times/minute; the respiratory frequency of children of 1 month to 1 year is about 30 times/minute; the respiratory frequency of children of 1-3 years old is about 24 times/minute; the respiratory frequency of children of 4-7 years old is 20-25 times/minute; the breathing frequency of the children aged 8-14 years is about 20 times/minute, the breathing frequency of the corresponding preset high-position state condition of the newborn is more than 45 times/minute, and the breathing frequency of the preset high-position state condition of the children aged 1 month-1 year is more than 30 times/minute; the respiratory rate of the children of 1-3 years old under the preset high-position state condition is more than 24 times/minute, and the like.

In this embodiment, assume that the identity information of the user to be detected is a healthy adult, collect multiple vital sign data corresponding to the healthy adult through the smart wearable watch, if the heart rate data is 75, 80, 90, 110 each minute within 1-5 minutes, the blood oxygen data is 98, 96, 94, 93, 92 each minute within 1-5 minutes, the body temperature data is 37.5 degrees within 5 minutes, the respiratory rate is 25 times/minute, 26 times/minute, 27 times/minute within 1-5 minutes, the preset high-order state condition corresponding to the adult is that the heart rate data is more than 90, the blood oxygen data is 94 degrees or less, the body temperature data is more than 37.3 degrees, extract multiple vital sign data to be monitored from the multiple vital sign data according to the preset high-order state condition, wherein the multiple vital sign data to be monitored include the heart rate data of 4 minutes 110 and 5 minutes 110, the blood oxygen data of 4 minutes 93 and 5 minutes 92, the body temperature data of 37.5 degrees within 5 minutes, the vital sign data to be monitored lasts for 2 minutes (i.e., 4 minutes and 5 minutes).

Step S30: and determining the target breathing frequency of the user to be detected according to the high position duration.

It should be noted that when it is detected that the high-order duration reaches the preset duration, in order to accurately observe the physical condition of the user, a vital sign graph may be generated according to a plurality of vital sign data to be monitored, and then the target respiratory frequency of the user to be detected is determined according to the trend of the vital sign graph. The preset duration can be set by a user in a self-defined way, and can be 36h, 24h, 48h and the like.

It should be understood that, since the plurality of vital sign data to be monitored includes heart rate data, blood oxygen data, body temperature data and cardiopulmonary function data, it is necessary to generate a heart rate curve, a blood oxygen curve and a body temperature curve according to the plurality of vital sign data to be monitored, and then generate a vital sign graph according to the heart rate curve, the blood oxygen curve and the body temperature curve.

In this embodiment, the heart rate curve, the blood oxygen curve and the body temperature curve, including the rising trend, the falling trend or the gentle trend, can be observed according to the vital sign graph. When the heart rate curve of the vital sign graph is in a gentle trend, the blood oxygen curve is in a gentle trend and the body temperature curve is in a gentle trend, judging that the vital sign graph is in a gentle trend; when the heart rate curve of the vital sign graph is in an ascending trend, the blood oxygen curve is in a gentle trend or a descending trend, and the body temperature curve is in a gentle trend or an ascending trend, judging that the vital sign graph is in an ascending trend; and when the center rate curve of the vital sign graph is in a descending trend, the blood oxygen curve is in a descending trend and the body temperature curve is in a descending trend, judging that the vital sign graph is in a descending trend and the like.

It should also be understood that when the trend of the vital sign graph is in a gentle trend or an ascending trend, the target respiratory frequency of the user to be detected can be determined according to a plurality of to-be-processed respiratory frequencies corresponding to the time period for acquiring the vital sign data to be monitored, and whether the respiratory system of the user is abnormal or not can be judged according to the target respiratory frequency; when the vital sign curve diagram is in a descending trend, the lowest breathing frequency can be used as the target breathing frequency of the user to be detected, the target breathing frequency is compared with the too slow breathing frequency range, when the target breathing frequency is in the too slow breathing frequency range for a period of time, the respiratory system of the user at the moment is judged to be abnormal, the physical condition of the user is further detected, and the type of the respiratory system abnormality of the user is determined.

Step S40: and carrying out human respiratory system risk management and control early warning on the user to be detected according to the high-position duration and the target respiratory frequency.

It should be further noted that, in order to accurately perform risk management, control and early warning on the respiratory system of the human body, abnormal body state information can be determined according to the high-order duration and the target respiratory frequency, and then multiple vital sign data are analyzed according to the abnormal body state information to obtain a vital sign abnormal report and perform risk management, control and early warning on the respiratory system of the human body.

In the specific implementation, the high heart rate and the low blood oxygen are achieved, the high body temperature lasts for more than 36 hours at the high position, the respiratory frequency exceeds a normal value, the respiratory system infection abnormality is judged, namely abnormal body state information is determined, a user monitors and manages according to the abnormal body state information and multiple vital sign data, a reference effect is provided for treatment of a doctor, then the multiple vital sign data can be analyzed according to the abnormal body state information, a vital sign abnormal report is obtained, corresponding measures are taken according to the abnormal vital sign report to process, the doctor can see a doctor timely, lung slow resistance is prevented, bronchitis and pneumonia are reduced, meanwhile, a convenient health management data reference is provided for respiratory system disease patients, and the like.

In this embodiment, when the intelligence was dressed wrist-watch collection terminal still can be when the user sleeps at night, gather human vital sign data, gather user's heart rate data, blood oxygen data, body temperature data and respiratory frequency data, when monitoring that user's respiratory frequency is in respiratory frequency bradyscope a period, judge that user's respiratory is unusual, can carry out the early warning, for example respiratory frequency bradyscope is 0-12 times/minute, and duration can be 1min, 3min etc. this embodiment does not do the restriction to this. In specific implementation, a control early warning module can be arranged in the intelligent wearable watch, the control early warning module can be connected with a mobile phone of a user or can be connected with a guardian (doctor) of the user, the control early warning module can store the contact information of the user or the guardian (doctor) of the user, when the respiratory system of the user is monitored to be abnormal, the control early warning module can dial the mobile phone of the user or the mobile phone of the guardian (doctor) of the user to remind, the user can be awakened in time, early warning is carried out on the respiratory frequency of the user, and the safety risk event of the user is avoided.

In this embodiment, first, multi-vital sign data of a user to be detected is collected, then, high duration corresponding to a preset high state of vital signs of the multi-vital sign data is determined, a target respiratory frequency of the user to be detected is determined according to the high duration, and then, human respiratory system risk management and control early warning is performed on the user to be detected according to the high duration and the target respiratory frequency. Compared with the existing respiratory system monitoring technology, whether the lung of an individual user is infected or not is diagnosed mainly by means of a thermometer, an oximeter or an imaging technology, diagnosis data are single-point data, the image diagnosis needs to be checked by a professional at a specific place, the diagnosis data are single-point data at a certain moment, abnormal conditions and development trends of the respiratory system of the user cannot be observed in time, and then corresponding treatment measures cannot be taken.

Referring to fig. 3, fig. 3 is a schematic flow chart of a human respiratory system risk management and warning method according to a second embodiment of the present invention.

Based on the first embodiment, in this embodiment, the step S20 further includes:

step S201: and determining the identity information of the user to be detected.

Still need explain, wait to detect the user and when using intelligence to dress many vital sign data of wrist-watch monitoring, need set up in advance in intelligence dress wrist-watch and wait to detect user's identity information to it can carry out many vital sign data management according to the identity information who waits to detect the user to intelligence dress wrist-watch. For example, the age, the historical health status, and other information of the user to be detected may be determined, different preset high-level status conditions may be determined according to the identity information of the user, for example, if the user has heart disease, the preset high-level status conditions may be set to be higher than 10% of the normal heart rate value or lower than 10% of the normal heart rate value, the blood oxygen data is lower than the normal blood oxygen value, the body temperature data is higher than the normal body temperature value, and the breathing frequency is higher than the normal breathing frequency range, and if the historical health status information of the user is good, the preset high-level status conditions may be set to be higher than the normal heart rate value, the blood oxygen data is lower than the normal blood oxygen value, the body temperature data is higher than the normal body temperature value, and the breathing frequency is higher than the normal breathing frequency range.

Step S202: and determining a corresponding preset high-order state condition according to the identity information.

It should be understood that the preset high-order state condition may be abnormal multi-vital sign data corresponding to the user to be detected, and the abnormal multi-vital sign data is different from the normal multi-vital sign data. The preset high state condition may be understood as a heart rate higher than a preset heart rate value, a blood oxygen lower than a preset blood oxygen value, a body temperature higher than a preset body temperature value, and a respiratory rate higher than a preset respiratory rate value. The preset heart rate value, the preset blood oxygen value, the preset body temperature value and the preset breathing frequency value can be set and modified according to the identity information of the user, and the embodiment is not limited to the next time. For example, the high-order status condition preset by a healthy adult user may be understood as heart rate data of 90 or more, blood oxygen data of 94 or less, body temperature data of 37.3 ° or more, respiratory rate of 25 times/minute or more, and the like.

The normal respiratory frequency of the newborn is assumed to be 40-45 times/minute; the normal respiratory frequency of children of 1 month to 1 year old is about 30 times/minute; the normal respiratory frequency of children of 1-3 years old is about 24 times/minute; the normal respiratory frequency of children of 4-7 years old is 20-25 times/minute; the normal respiratory frequency of the children aged 8-14 years is about 20 times/minute, the corresponding preset high-position state condition of the newborn is that the respiratory frequency is more than 45 times/minute, and the preset high-position state condition of the children aged 1 month-1 year is that the respiratory frequency is more than 30 times/minute; the preset high state condition of the children of 1-3 years old is that the respiratory frequency is more than 25 times/minute, and the like.

Step S203: and extracting a plurality of vital sign data to be monitored from the multi-vital sign data according to the preset high-order state condition.

In this embodiment, it is assumed that the identity information of the user to be detected is an adult with a healthy body, multiple vital sign data corresponding to the adult are collected through the smart wearable watch, if the heart rate data are 75, 80, 90, 110 and 110 each minute within 1 to 5 minutes, the blood oxygen data are 98, 96, 94, 93 and 92 each minute within 1 to 5 minutes, the body temperature data are 37.5 degrees within 5 minutes, and the respiratory frequency data are 25/min, 26/min and 27/min each minute within 1 to 5 minutes, the preset high-order state condition corresponding to the adult is that the heart rate data are more than 90 degrees, the blood oxygen data are less than 94 degrees, the body temperature data are more than 37.3 degrees, and the respiratory frequency data are more than 25 times/min, multiple vital sign data to be monitored are extracted from the multiple vital sign data according to the preset high-order state condition, wherein the multiple vital sign data to be monitored include the heart rate data 110 and 110, the blood oxygen data 93 and 92, and the body temperature data are 37.5 degrees.

Step S204: and determining the high-order duration corresponding to the preset high-order state of the vital sign data to be monitored.

It should be further noted that, since the multiple vital sign data to be monitored includes heart rate data, blood oxygen data, body temperature data and cardiopulmonary function data, the corresponding time when the heart rate data, the blood oxygen data, the body temperature data and the cardiopulmonary function data all satisfy the preset high-level state condition can be counted, and then the high-level duration corresponding to the preset vital sign high-level state of the heart rate data, the blood oxygen data and the body temperature data needs to be counted.

In a specific implementation, assuming that the heart rate data in the plurality of vital sign data to be monitored is at 4 minutes 110 and 5 minutes 110, the blood oxygen data at 4 minutes 94 and 5 minutes 93, and the body temperature data at 37.5 ° within 5 minutes, the duration of the high bit corresponding to the vital sign data to be monitored is 2 minutes (i.e., at 4 minutes and 5 minutes).

In this embodiment, identity information of a user to be detected is first determined, then a corresponding preset high-order state condition is determined according to the identity information, a plurality of vital sign data to be monitored are extracted from the multi-vital sign data according to the preset high-order state condition, and then it is determined that the plurality of vital sign data to be monitored are in a high-order duration corresponding to the preset vital sign high-order state.

Referring to fig. 4, fig. 4 is a schematic flowchart illustrating a risk management and control early warning method for a respiratory system of a human body according to a third embodiment of the present invention.

Based on the second embodiment, in this embodiment, the step S30 further includes:

step S301: and when the high-order duration is longer than the preset duration, generating a vital sign curve graph according to the plurality of vital sign data to be monitored.

It should be understood that, since the plurality of vital sign data to be monitored includes heart rate data, blood oxygen data, body temperature data and cardiopulmonary function data, a heart rate curve, a blood oxygen curve and a body temperature curve need to be generated according to the plurality of vital sign data to be monitored, and then a vital sign graph is generated according to the heart rate curve, the blood oxygen curve and the body temperature curve.

Step S302: and determining the target breathing frequency of the user to be detected according to the trend of the vital sign curve graph.

In this embodiment, the heart rate curve, the blood oxygen curve and the body temperature curve, including the rising trend, the falling trend or the gentle trend, can be observed according to the vital sign graph. When the heart rate curve of the vital sign graph is in a gentle trend, the blood oxygen curve is in a gentle trend and the body temperature curve is in a gentle trend, judging that the vital sign graph is in a gentle trend; when the central rate curve of the vital sign graph is in an ascending trend, the blood oxygen curve is in a gentle trend or a descending trend, and the body temperature curve is in a gentle trend or an ascending trend, judging that the vital sign graph is in an ascending trend; and when the center rate curve of the vital sign graph is in a descending trend, the blood oxygen curve is in a descending trend and the body temperature curve is in a descending trend, judging that the vital sign graph is in a descending trend, and the like.

It is further noted that when the trend of the vital sign graph is in a gentle trend or an ascending trend, it is determined that a high heart rate and a low blood oxygen are to be detected, a high body temperature continues for more than a preset high duration, and it is further determined whether a respiratory system infection exists in the user, the determination may be performed in a manner of determining a plurality of respiratory frequencies to be processed according to a plurality of vital sign data to be detected, determining a corresponding normal respiratory frequency according to the identity information, determining whether an abnormal respiratory frequency exists in the plurality of respiratory frequencies to be processed according to the normal respiratory frequency, and if an abnormal respiratory frequency exists in the plurality of respiratory frequencies to be processed, indicating that the respiratory system infection may exist in the user to be detected, selecting a plurality of abnormal respiratory frequencies to be processed from the plurality of respiratory frequencies to be processed, and determining a target respiratory frequency of the user to be detected according to an average value of the plurality of abnormal respiratory frequencies to be processed; if the abnormal respiratory frequency does not exist in the plurality of respiratory frequencies to be processed, the situation that the respiratory system infection does not exist in the user to be detected is shown, a health strategy needs to be determined according to the vital sign curve graph and the identity information of the user to be detected, and then emergency processing and the like are carried out on the user to be detected according to the health strategy.

It should be understood that the health policy may be a disease treatment measure formulated by a doctor for the vital sign graph and the identity information of the user to be detected, and the user to be detected may perform emergency treatment according to the health policy at an emergency time, etc.

It should be further noted that when the trend of the vital sign graph is in a downward trend, which indicates that a respiratory system of the user may be abnormal at this time, a plurality of periods corresponding to the vital sign data to be monitored may be collected to determine a plurality of corresponding respiratory frequencies to be processed, wherein the time for collecting the respiratory frequencies to be processed is consistent with the time for collecting the vital sign data to be monitored, then a lowest respiratory frequency is selected from the plurality of respiratory frequencies to be processed, the lowest respiratory frequency is used as a target respiratory frequency of the user to be detected, the target respiratory frequency is compared with an excessively slow respiratory frequency range, when the target respiratory frequency is in the excessively slow respiratory frequency range for a period of time, it is determined that the respiratory system of the user is abnormal at this time, the physical condition of the user may be further detected, and the type of the respiratory system abnormality of the user may be determined.

In this embodiment, when the high-order duration is longer than the preset duration, a vital sign graph is generated according to a plurality of vital sign data to be monitored, and then the target respiratory frequency of the user to be detected is determined according to the trend of the vital sign graph.

In addition, the embodiment of the present invention further provides a storage medium, where a human respiratory system risk management and control early warning program is stored on the storage medium, and when being executed by a processor, the human respiratory system risk management and control early warning program implements the steps of the human respiratory system risk management and control early warning method described above.

Referring to fig. 5, fig. 5 is a block diagram illustrating a first embodiment of a human respiratory system risk management and control early warning device according to the present invention.

As shown in fig. 5, the risk management and control early warning device for a respiratory system of a human body according to an embodiment of the present invention includes:

the acquisition module 5001 is configured to acquire multiple vital sign data of a user to be detected.

A determining module 5002 is configured to determine a high-order duration corresponding to that the multi-vital sign data is in a preset high-order state of the vital sign.

It should be understood that the preset high vital sign state is a state in which the individual multi-vital sign data is higher than the normal multi-vital sign data, and the high-order duration may be a continuous duration in which the combined multi-vital sign data is higher than the normal multi-vital sign data, and the high-order duration may be 36h, or may be 24h, 48h, and the like.

It should be noted that the identity information of the user to be detected may be the age, the historical health information, and the like of the user to be detected, the preset high-order state condition may be abnormal multi-vital-sign data corresponding to the user to be detected, and the abnormal multi-vital-sign data is different from the normal multi-vital-sign data. The respiratory frequency of the newborn is assumed to be 40-45 times/minute; the respiratory frequency of children of 1 month to 1 year old is about 30 times/minute; the respiratory frequency of children of 1-3 years old is about 24 times/minute; the respiratory frequency of children of 4-7 years old is 20-25 times/minute; the respiratory frequency of the children aged 8-14 years is about 20 times/minute, the respiratory frequency of the corresponding preset high-level state condition of the newborn is more than 45 times/minute, and the respiratory frequency of the preset high-level state condition of the children aged 1 month-1 year is more than 30 times/minute; the respiratory rate of the children of 1-3 years old under the preset high-position state condition is more than 24 times/minute, and the like.

The determining module 5002 is further configured to determine the target breathing frequency of the user to be detected according to the high duration.

It should be noted that when it is detected that the high-order duration reaches the preset duration, in order to accurately observe the physical condition of the user, a vital sign graph may be generated according to a plurality of vital sign data to be monitored, and then the target respiratory frequency of the user to be detected is determined according to the trend of the vital sign graph. The preset duration can be set by a user in a customized manner, and can be 36h, 24h, 48h and the like.

In this embodiment, the heart rate curve, the blood oxygen curve and the body temperature curve may be observed according to the vital sign graph, and the trends include an ascending trend, a descending trend or a gradual trend. When the heart rate curve of the vital sign graph is in a gentle trend, the blood oxygen curve is in a gentle trend and the body temperature curve is in a gentle trend, judging that the vital sign graph is in a gentle trend; when the heart rate curve of the vital sign graph is in an ascending trend, the blood oxygen curve is in a gentle trend or a descending trend, and the body temperature curve is in a gentle trend or an ascending trend, judging that the vital sign graph is in an ascending trend; and when the center rate curve of the vital sign graph is in a descending trend, the blood oxygen curve is in a descending trend and the body temperature curve is in a descending trend, judging that the vital sign graph is in a descending trend and the like.

It should also be understood that when the trend of the vital sign graph is in a gentle trend or an ascending trend, the target respiratory frequency of the user to be detected can be determined according to a plurality of to-be-processed respiratory frequencies corresponding to the time period for acquiring the vital sign data to be monitored, and whether the respiratory system of the user is abnormal or not can be judged according to the target respiratory frequency; when the vital sign curve diagram is in a descending trend, the lowest breathing frequency can be used as the target breathing frequency of the user to be detected, the target breathing frequency is compared with the too slow breathing frequency range, when the target breathing frequency is in the too slow breathing frequency range for a period of time, the respiratory system of the user at the moment is judged to be abnormal, the physical condition of the user can be further detected, and the type of the respiratory system abnormality of the user is determined.

A control early warning module 5003, configured to perform human respiratory system risk control early warning on the user to be detected according to the high-level duration and the target respiratory frequency.

It should be further noted that, in order to accurately perform risk management, control and early warning on the respiratory system of the human body, abnormal body state information may be determined according to the high-order duration and the target respiratory frequency, and then multiple vital sign data are analyzed according to the abnormal body state information to obtain an abnormal vital sign report, and perform risk management, control and early warning on the respiratory system of the human body.

In specific implementation, the control and early warning module 5003 may be connected to a mobile phone of the user or to a guardian (doctor) of the user, and the control and early warning module may store a contact manner of the user or the guardian (doctor) of the user. When the respiratory frequency of the user is monitored to be in a respiratory frequency over-slow range for a period of time, the respiratory system of the user is judged to be abnormal, early warning can be carried out, the control early warning module can dial the mobile phone of the user or the mobile phone of a guardian (doctor) of the user to remind, the user is awakened in time, and safety risk events of the user are avoided by early warning the respiratory frequency of the user.

In this embodiment, first, multi-vital sign data of a user to be detected is collected, then, high duration corresponding to a preset high state of vital signs of the multi-vital sign data is determined, a target respiratory frequency of the user to be detected is determined according to the high duration, and then, human respiratory system risk management and control early warning is performed on the user to be detected according to the high duration and the target respiratory frequency. Compared with the existing respiratory system monitoring technology, whether the lung of an individual user is infected or not is diagnosed mainly by means of a thermometer, an oximeter or an imaging technology, the diagnosis data are single-point data, the image diagnosis needs to be checked by a professional at a specific place, the diagnosis data are single-point data at a certain moment, abnormal conditions and development trends of the respiratory system of the user cannot be observed in time, and then corresponding treatment measures cannot be taken.

Other embodiments or specific implementation manners of the risk management and control early warning device for the respiratory system of the human body can refer to the above method embodiments, and are not described herein again.

It should be noted that, in this document, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or system that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or system. Without further limitation, an element defined by the phrases "comprising a," "8230," "8230," or "comprising" does not exclude the presence of other like elements in a process, method, article, or system comprising the element.

The above-mentioned serial numbers of the embodiments of the present invention are only for description, and do not represent the advantages and disadvantages of the embodiments.

Through the above description of the embodiments, those skilled in the art will clearly understand that the method of the above embodiments can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware, but in many cases, the former is a better implementation manner. Based on such understanding, the technical solutions of the present invention or portions thereof contributing to the prior art may be embodied in the form of a software product, which is stored in a storage medium (such as a rom/ram, a magnetic disk, and an optical disk) and includes instructions for enabling a terminal device (such as a mobile phone, a computer, a server, or a network device) to execute the methods according to the embodiments of the present invention.

The above description is only a preferred embodiment of the present invention, and not intended to limit the scope of the present invention, and all modifications of equivalent structures and equivalent processes, which are made by using the contents of the present specification and the accompanying drawings, or directly or indirectly applied to other related technical fields, are included in the scope of the present invention.

Claims

1. A human respiratory system risk management and control early warning method is characterized by comprising the following steps:

2. The method of claim 1, wherein the step of determining the high duration corresponding to the multi-vital sign data being in the preset high state of the vital sign comprises:

determining identity information of the user to be detected;

3. The method of claim 2, wherein the step of determining the target breathing frequency of the user to be detected based on the high duration comprises:

4. The method according to claim 3, wherein the step of determining the target breathing frequency of the user to be detected from the trend of the vital sign graph comprises:

5. The method according to claim 4, wherein the step of determining whether there is an abnormal breathing frequency in the plurality of the to-be-treated breathing frequencies according to the normal breathing frequency further comprises:

6. The method according to claim 3, wherein the step of determining the target breathing frequency of the user to be detected from the trend of the vital sign graph further comprises:

7. The method according to any one of claims 1 to 6, wherein the step of performing human respiratory system risk management and control early warning on the user to be detected according to the high-position duration and the target respiratory frequency comprises:

determining body abnormal state information according to the high position duration and the target respiratory frequency;

8. The utility model provides a human respiratory risk management and control early warning device which characterized in that, human respiratory risk management and control early warning device includes:

the acquisition module is used for acquiring multi-vital sign data of a user to be detected;

9. The utility model provides a human respiratory risk management and control early warning equipment which characterized in that, equipment includes: a memory, a processor and a human respiratory system risk management and control early warning program stored on the memory and operable on the processor, the human respiratory system risk management and control early warning program being configured to implement the steps of the human respiratory system risk management and control early warning method according to any one of claims 1 to 7.

10. A storage medium, wherein the storage medium stores thereon a human respiratory system risk management and control early warning program, and when the human respiratory system risk management and control early warning program is executed by a processor, the steps of the human respiratory system risk management and control early warning method according to any one of claims 1 to 7 are implemented.