CN110600133A - Health monitoring method and equipment for old people in smart community and readable storage medium - Google Patents
Health monitoring method and equipment for old people in smart community and readable storage medium Download PDFInfo
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/02—Detecting, measuring or recording pulse, heart rate, blood pressure or blood flow; Combined pulse/heart-rate/blood pressure determination; Evaluating a cardiovascular condition not otherwise provided for, e.g. using combinations of techniques provided for in this group with electrocardiography or electroauscultation; Heart catheters for measuring blood pressure
- A61B5/024—Detecting, measuring or recording pulse rate or heart rate
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/74—Details of notification to user or communication with user or patient ; user input means
- A61B5/7465—Arrangements for interactive communication between patient and care services, e.g. by using a telephone network
- A61B5/747—Arrangements for interactive communication between patient and care services, e.g. by using a telephone network in case of emergency, i.e. alerting emergency services
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H40/00—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices
- G16H40/60—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices
- G16H40/67—ICT specially adapted for the management or administration of healthcare resources or facilities; ICT specially adapted for the management or operation of medical equipment or devices for the operation of medical equipment or devices for remote operation
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B2503/00—Evaluating a particular growth phase or type of persons or animals
- A61B2503/08—Elderly
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Abstract
The invention discloses a health monitoring method, computer equipment and a readable storage medium for the old in an intelligent community, wherein the method comprises the following steps: the method comprises the steps of automatically and accurately acquiring a target face picture set of a target old man under the current behavior of the current behavior identification unique identification, then sending target face pictures and picture acquisition time in the target face picture set to a server, determining the current heart rate of the target old man under the current behavior based on the target face pictures and the picture acquisition time when the server receives the target face pictures and the picture acquisition time, finally, accurately analyzing the current heart rate under each current behavior and the historical heart rate under the historical behavior corresponding to the current behavior to obtain a heart rate analysis result, and determining the health abnormality of the target old man when the received heart rate analysis result is abnormal, so that the health condition of the target old man is accurately determined, and the health monitoring accuracy of the old man in a smart community is improved.
Description
Technical Field
The invention relates to the field of data analysis, in particular to a health monitoring method for the old in an intelligent community, computer equipment and a readable storage medium.
Background
China increasingly enters an aging society, the aging problem is more and more prominent, namely, the monitoring of the health condition of the old people is more and more concerned.
In the traditional method, under the ordinary condition, the collecting equipment is adopted to collect the body condition of the old people in the smart community and report the collected body condition information to the monitoring system, but the collected body condition information is often inaccurate, and the monitoring system misreports the health condition of the old people, so that the health monitoring accuracy of the old people is low.
Therefore, finding an accurate method for monitoring the health of the elderly people becomes a problem to be solved by those skilled in the art.
Disclosure of Invention
The embodiment of the invention provides a health monitoring method, computer equipment and a readable storage medium for the old in an intelligent community, and aims to solve the problem of low accuracy in monitoring the health of the old.
A health monitoring method for the elderly in a smart community comprises the following steps:
acquiring a target face picture set of a target old man under a current behavior with a unique current behavior identifier, wherein each target face picture in the target face picture set comprises picture acquisition time;
sending the target face picture and the picture acquisition time in the target face picture set to a server side, so that the server side determines a heart rate analysis result of the target old man based on the target face picture and the picture acquisition time;
and when the received heart rate analysis result is abnormal, determining that the health of the target old man is abnormal.
A computer device comprises a memory, a processor and a computer program stored in the memory and capable of running on the processor, wherein the processor executes the computer program to realize the steps of the health monitoring method for the aged in the intelligent community.
A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, carries out the above-mentioned steps of the method for health monitoring of elderly persons in a smart community.
In the health monitoring method, the computer device and the readable storage medium for the elderly in the intelligent community, by automatically and accurately acquiring a target face picture set of a target old man under the current behavior with the unique current behavior identifier, then the target face picture in the target face picture set and the picture acquisition time are sent to a server, when the server receives the target face picture and the picture acquisition time, the current heart rate of the target old man under the current behaviors is determined based on the target face picture and the picture acquisition time, finally, the current heart rate under each current behavior is accurately analyzed with the historical heart rate under the historical behaviors corresponding to the current behaviors to obtain a heart rate analysis result, and when the received heart rate analysis result is abnormal, the health of the target old man is determined to be abnormal, therefore, the health condition of the target old people is accurately determined, and the health monitoring accuracy of the old people in the smart community is improved.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the drawings needed to be used in the description of the embodiments of the present invention will be briefly introduced below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art that other drawings can be obtained according to these drawings without inventive labor.
FIG. 1 is a schematic diagram of an application environment of a method for health monitoring of elderly people in a smart community according to an embodiment of the present invention;
FIG. 2 is a flowchart of a method for health monitoring of the elderly in the intelligent community according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a computer device according to an embodiment of the invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, not all, embodiments of the present invention. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The method for monitoring the health of the old in the intelligent community can be applied to an application environment shown in fig. 1, wherein the application environment comprises a server and a client, and the client is communicated with the server through a wired network or a wireless network. Among other things, the client may be, but is not limited to, various personal computers, laptops, smartphones, tablets, and portable wearable devices. The server can be implemented by an independent server or a server cluster composed of a plurality of servers. The client is used for collecting the current heart rate of the target old man, and the server is used for analyzing the current heart rate and determining the health condition of the target old man.
In an embodiment, as shown in fig. 2, a method for monitoring the health of the elderly in an intelligent community is provided, which is described by taking the method as an example of the client in fig. 1, and includes the following steps:
and S10, acquiring a target face picture set of the target old people under the current behavior of the current behavior identification unique identification, wherein each target face picture in the target face picture set comprises picture acquisition time.
Specifically, under a normal condition, many old people in an intelligent community are at home independently, the health condition of the old people may be abnormal at any time, in order to monitor the health condition of the old people in real time, a client needs to collect a current behavior picture of a target old person first, and simultaneously sends the collected current behavior picture to a server, when the server receives the current behavior picture, the current picture is input into a pre-trained behavior recognition model for behavior recognition processing, so as to obtain a current behavior with a unique identifier of a current behavior identifier, wherein the current behavior pictures are at least more than two, the behavior recognition model is obtained by training historical behavior pictures and historical behaviors of the target old person, and the behavior recognition model can be a deep learning model and can also be other models.
Preferably, the client acquires a target face picture set of the target old man under the current behavior of the current behavior identification unique identification in real time or within a preset target time period, wherein each target face picture in the target face picture set comprises picture acquisition time.
It should be noted that the client may be a camera or a digital camera, and the current behavior may be eating, doing housework or doing sports. The target time period may be 24 hours or 18 hours, and the image acquisition time is the time when the client acquires each target face image, and the specific content of the client, the current behavior, and the target time period may be set according to the actual application, which is not limited herein.
Further, the current behavior may be a current athletic behavior or a current non-athletic behavior, the historical behavior may be a historical athletic behavior or a historical non-athletic behavior, the current athletic behavior and the historical athletic behavior have a correspondence, and the current non-athletic behavior and the historical non-athletic behavior have a correspondence, where the current athletic behavior refers to a current behavior including an exercise, such as running, the current non-athletic behavior refers to a current behavior not including an exercise, such as sitting, the historical athletic behavior refers to a historical behavior including an exercise, and the historical non-athletic behavior refers to a historical behavior not including an exercise.
Further, the current athletic performance may be a current violent athletic performance or a current non-violent athletic performance, the historical athletic performance may be a historical violent athletic performance or a historical non-violent athletic performance, the current violent athletic performance and the historical violent athletic performance have a corresponding relationship, and the current non-violent athletic performance and the historical non-violent athletic performance have a corresponding relationship, where the current violent athletic performance refers to a current performance including violent exercises, such as fast running or basketball playing, the current non-violent athletic performance refers to a current performance not including violent exercises, such as yoga, the historical violent athletic performance refers to a historical performance including violent exercises, and the historical non-violent athletic performance refers to a historical performance not including violent exercises.
S20, sending the target face picture and the picture acquisition time in the target face picture set to the server, so that the server determines the heart rate analysis result of the target old man based on the target face picture and the picture acquisition time.
Specifically, in order to analyze whether the current heart rate of a target old man is abnormal, a client needs to firstly send a target face picture and picture acquisition time in a target face picture set to a server, and when the server receives the target face picture and the picture acquisition time, the target face picture in the target face picture set is preprocessed to obtain a preprocessed target face picture, that is, the target face picture in the target face picture set is filtered to obtain a filtered target face picture, and the filtered target face picture is subjected to color enhancement processing to obtain an enhanced target face picture as the preprocessed target face picture; then, carrying out face color extraction processing on each preprocessed target face picture to obtain a target face color value corresponding to each target face picture; finally, determining the average value of the target face color value as the current heart rate, namely, connecting the target face color value according to the sequence of the image acquisition time to obtain a target face color change signal, and calculating the average period of the target face color change signal; the median value in the average cycle is extracted as the current heart rate.
And then the server acquires a storage path of the historical heart rate of the target old man under the historical behavior corresponding to the current behavior in a historical database, wherein the storage path is acquired in advance, and then the historical heart rate is extracted according to the acquired storage path.
For example, the historical database is a MySQL database, the storage path of the historical heart rate is C: \ Program Files \ MySQL \ MySQL Server 5.0\ data \ and the C: \ Program Files \ MySQL \ MySQL Server 5.0\ data \ is firstly obtained in the MySQL database and then the historical heart rate is extracted according to the C: \ Program Files \ MySQL \ MySQL Server 5.0\ data'.
The server determines a heart rate analysis result of the target elderly based on the current heart rate and the historical heart rate. That is, if the current heart rate determined in step S20 is greater than the historical heart rate acquired in step S20, it is determined that the heart rate analysis result is abnormal. For example, if the current heart rate of the target elderly male determined in step S20 when watching tv is 110 times/minute and the normal historical heart rate of the target elderly male determined in step S20 when watching tv is 65 times/minute, the heart rate analysis result of the target elderly male is determined to be abnormal.
If the current heart rate determined in the step S20 is less than or equal to the historical heart rate acquired in the step S20 and is greater than the target heart rate acquired in advance, it is determined that the heart rate analysis result is normal, where the target heart rate is the lowest heart rate of the target elderly acquired in advance under normal conditions. The server collects the historical heart rate of the target old man under the historical behaviors in advance and stores the heart rate to a historical database.
It should be noted that the history database may be a MySQL database or an oracle database, and the specific content of the history database may be set according to the practical application, which is not limited herein.
And S30, determining that the health of the target old man is abnormal when the received heart rate analysis result is abnormal.
Before determining that the health of the target old man is abnormal, the client acquires other characteristics of the target old man, wherein the other characteristics are vital characteristics except the current heart rate; sending the collected other characteristics to a server, when the server receives the other characteristics, acquiring the historical characteristics collected in advance, comparing and analyzing the other characteristics and the historical characteristics to obtain other analysis results of a comparison difference value, when the comparison difference value is within a preset error range, determining that the other analysis results are normal, then sending a health condition conversation instruction to a client by the server, when the client receives the health condition conversation instruction, uploading the health condition conversation content of the target old man to the server through the health condition conversation instruction, when the server receives the health condition conversation content, carrying out voice recognition on the health condition conversation content to obtain the health condition conversation characters, analyzing and processing the health condition conversation characters, namely, judging whether the health condition conversation characters contain preset abnormal health keywords or not, if so, determining that the health analysis result of the target old man is abnormal, if not, determining that the health of the target old man is abnormal if the received heart rate analysis result is abnormal, and if not, determining that the health of the target old man is normal if the received heart rate analysis result is normal. The health abnormal keyword can be 'I feel uncomfortable' and/or 'I feel' and the like, and other characteristics can be blood pressure and/or blood sugar and the like.
Note that the target elderly people have different heart rates depending on their sex, and in general, the heart rate of women and elderly people is higher than that of men and elderly people.
And when the comparison difference is not within the preset error range, determining that other analysis results are abnormal, and simultaneously determining that the health of the target old man is abnormal.
Further, the server side sends the health monitoring continuing instruction to the client side, and when the client side receives the health monitoring continuing instruction, the health monitoring continuing instruction is output to remind the target old people to conduct health monitoring on the body.
The client acquires other characteristics of the target old man, sends the acquired other characteristics to the server, analyzes the other characteristics when the server receives the other characteristics to obtain other analysis results, and determines the health condition of the target old man according to the other analysis results, so that the accuracy of health monitoring of the target old man is improved.
Further, after determining the health abnormality of the target elderly, the method further comprises: the client outputs the health abnormity warning information and sends the health abnormity warning information to the server, when the server receives the health abnormity warning information, the health abnormity warning information is sent to a rescue system of the intelligent community, when the rescue system receives the health abnormity warning information, the target old people is rescued, and meanwhile, the health abnormity warning information is sent to a third-party client, when the third-party client receives the health abnormity warning information, the health abnormity warning information is output, the user carrying the third party client is reminded, for example, the user sends 'you are in abnormal health, please contact 120 immediately' to the smart phone, when the smart phone receives that 'the health of the old at home is abnormal and please contact 120 immediately', and outputting 'the health of the old people at home is abnormal, please contact 120 immediately' to remind relatives of the target old people carrying the smart phone.
It should be noted that, the specific content of the third-party client may be set according to the actual application, and is not limited here.
In the embodiment corresponding to fig. 2, a target face picture set of a target old man under a current behavior of a current behavior identification unique identification is automatically and accurately acquired, then the target face picture and picture acquisition time in the target face picture set are sent to a server, when the server receives the target face picture and picture acquisition time, the current heart rate of the target old man under the current behavior is determined based on the target face picture and picture acquisition time, finally, the current heart rate under each current behavior is accurately analyzed with the historical heart rate under the historical behavior corresponding to the current behavior to obtain a heart rate analysis result, and when the received heart rate analysis result is abnormal, the health abnormality of the target old man is determined, so that the health condition of the target old man is accurately determined, and the health monitoring accuracy of the old man in the smart community is improved.
It should be understood that, the sequence numbers of the steps in the foregoing embodiments do not imply an execution sequence, and the execution sequence of each process should be determined by its function and inherent logic, and should not constitute any limitation to the implementation process of the embodiments of the present invention.
In one embodiment, a computer device is provided, which may be a terminal, and its internal structure diagram may be as shown in fig. 3. The computer device includes a processor, a memory, a network interface, a display screen, and an input device connected by a system bus. Wherein the processor of the computer device is configured to provide computing and control capabilities. The memory of the computer device includes a non-volatile readable storage medium, an internal memory. The non-transitory readable storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of an operating system and computer programs in the non-volatile readable storage medium. The network interface of the computer equipment is used for connecting and communicating with an external server through a network. The computer program is executed by a processor to implement a method of health monitoring for the elderly in a smart community.
In one embodiment, a computer device is provided, which includes a memory, a processor and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement the steps of the method for monitoring health of the elderly people in the smart community, such as steps S10 to S30 shown in fig. 2.
In one embodiment, a computer-readable storage medium is provided, on which a computer program is stored, which, when executed by a processor, implements the method for health monitoring of elderly people in a smart community in the above-described method embodiments. It will be understood by those skilled in the art that all or part of the processes of the methods of the embodiments described above can be implemented by hardware instructions of a computer program, which can be stored in a non-volatile computer-readable storage medium, and when executed, can include the processes of the embodiments of the methods described above. Any reference to memory, storage, database, or other medium used in the embodiments provided herein may include non-volatile and/or volatile memory, among others. Non-volatile memory can include read-only memory (ROM), Programmable ROM (PROM), Electrically Programmable ROM (EPROM), Electrically Erasable Programmable ROM (EEPROM), or flash memory. Volatile memory can include Random Access Memory (RAM) or external cache memory. By way of illustration and not limitation, RAM is available in a variety of forms such as Static RAM (SRAM), Dynamic RAM (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDRSDRAM), Enhanced SDRAM (ESDRAM), Synchronous Link DRAM (SLDRAM), Rambus Direct RAM (RDRAM), direct bus dynamic RAM (DRDRAM), and memory bus dynamic RAM (RDRAM).
It will be apparent to those skilled in the art that, for convenience and brevity of description, only the above-mentioned division of the functional units and modules is illustrated, and in practical applications, the above-mentioned function distribution may be performed by different functional units and modules according to needs, that is, the internal structure of the apparatus is divided into different functional units or modules to perform all or part of the above-mentioned functions.
The above-mentioned embodiments are only used for illustrating the technical solutions of the present invention, and not for limiting the same; although the present invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; such modifications and substitutions do not substantially depart from the spirit and scope of the embodiments of the present invention, and are intended to be included within the scope of the present invention.
Claims (10)
1. A health monitoring method for the old in a smart community is characterized by comprising the following steps:
acquiring a target face picture set of a target old man under a current behavior with a unique current behavior identifier, wherein each target face picture in the target face picture set comprises picture acquisition time;
sending the target face picture and the picture acquisition time in the target face picture set to a server side, so that the server side determines a heart rate analysis result of the target old man based on the target face picture and the picture acquisition time;
and when the received heart rate analysis result is abnormal, determining that the health of the target old man is abnormal.
2. The method of claim 1, wherein the current activity is a current athletic activity or a current non-athletic activity.
3. The method of claim 2, wherein the current athletic performance is a current strenuous athletic performance or a current non-strenuous athletic performance.
4. The method for monitoring the health of the elderly in the smart community as claimed in claim 1, wherein before the collecting the target face picture set of the target elderly in the current behavior uniquely identified by the current behavior identifier, the method for monitoring the health of the elderly in the smart community further comprises:
acquiring current behavior pictures of the target old people, wherein at least more than two current behavior pictures exist;
sending the current behavior picture to the server, so that the server performs behavior recognition processing on the current behavior picture to obtain the current behavior identifier;
and receiving the current behavior identification of the target old man sent by the server.
5. The method of monitoring the health of the elderly in the smart community as claimed in claim 1, wherein after the determining the health abnormality of the target elderly, the method of monitoring the health of the elderly in the smart community further comprises:
outputting health abnormity warning information;
and sending the health abnormity warning information to the server side, so that the server side sends the health abnormity warning information to a rescue system of the intelligent community.
6. The method of monitoring the health of the elderly in the smart community as claimed in claim 1, wherein before the determining the health abnormality of the target elderly, the method of monitoring the health of the elderly in the smart community further comprises:
receiving a health condition conversation instruction sent by the server;
uploading the health condition conversation content of the target old man to the server by adopting the health condition conversation instruction, so that the server determines a health analysis result of the target old man based on the health condition conversation content;
and when the received health analysis result is abnormal, executing the step of determining that the target elderly is abnormal in health.
7. The method for monitoring the health of the elderly in the smart community as claimed in claim 6, wherein before receiving the health status dialog sent from the server, the method for monitoring the health of the elderly in the smart community further comprises:
collecting other characteristics of the target elderly, wherein the other characteristics are vital characteristics except the current heart rate;
sending the collected other characteristics to the server, so that the server determines other analysis results of the target old man based on the other characteristics;
when the received other analysis results are abnormal, determining that the health of the target old man is abnormal;
and when the received other analysis results are normal, executing the step of receiving the health condition conversation instruction sent by the server.
8. The method for monitoring the health of elderly people in smart community as claimed in any one of claims 1 to 7, wherein when the received heart rate analysis result is normal, it is determined that the target elderly people are healthy.
9. A computer device comprising a memory, a processor and a computer program stored in the memory and executable on the processor, characterized in that the processor, when executing the computer program, implements a method of health monitoring of elderly persons within a smart community as claimed in any of claims 1 to 8.
10. A computer-readable storage medium, in which a computer program is stored, which, when being executed by a processor, implements a method of health monitoring of elderly people in a smart community according to any of claims 1 to 8.
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| CN114493059B (en) * | 2022-04-19 | 2022-07-05 | 西安石油大学 | Personnel management and control method and system based on machine learning |
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