CN111798982A - Police health management system and health management method - Google Patents
Police health management system and health management method Download PDFInfo
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Abstract
The invention discloses a police health management system and a police health management method, which comprise a police intelligent bracelet, an APP and a health management cloud end, wherein the APP and the health management cloud end are loaded on police mobile equipment, the police intelligent bracelet is in communication connection with the APP, the APP and the health management cloud end are in communication connection, real-time physiological index data and psychological scale data of police officers are collected through the police intelligent bracelet, a health classification model is established after deep learning is carried out on the health management cloud end, the real-time physiological and psychological health data are analyzed through the established health model to obtain the current physical health condition of the police officers, and life work and rest prompting, body building planning and health correction are carried out according to the health condition of the police officers, so that the aim of improving the physical and psychological health quality of the police officers is fulfilled. According to the invention, the health risk of the police officers can be found in time according to the real-time collected data, and particularly, the emergency quick response is realized for sudden diseases, so that the sacrifice of the police officers due to health crisis can be reduced.
Description
Technical Field
The invention relates to the technical field of health management, in particular to a police health management system and a health management method.
Background
In recent years, wearable intelligent devices have entered people's lives, and related products emerge endlessly: intelligent glasses, intelligent wrist-watch, intelligent earphone, intelligent belt, intelligent bracelet, intelligent dress even dresses the smart machine and has become a life fashion. By wearing the intelligent equipment, people can better sense external and self information, and process the information more professionally and more efficiently under the assistance of a network and a computer, so that the life quality and the working efficiency are improved.
Most of the smart bracelets in the current market are applied to the field of fitness and sports, and although the smart bracelets are related to the field of medical health, the smart bracelets are rarely applied to the health of specific professional groups. The civil police are the middle and high strength for maintaining the social stability, and due to the professional particularity and irregular long-term life and frequent overload work, the bodies of a great number of police officers are in sub-health conditions. Police officers often work with illness for a variety of reasons, which presents them with a serious health crisis: sudden death occurs frequently. Wherein, the cardiac death becomes the main reason for the sacrifice of first-line police officers, and the people police become healthy and high-risk professions. Therefore, technical means are urgently needed to improve physical and mental quality of police officers, timely discover and cure critical cases and reduce the number of staff sacrificed by front-line police officers due to health crisis. Currently, the people lack relevant technical means to maintain the health of the people police professional group.
Disclosure of Invention
In view of the above, the present invention provides a police health management system and method to solve the technical problem of managing the health of police officers.
The invention relates to a police health management system which comprises a police intelligent bracelet, an APP and a health management cloud, wherein the APP is loaded on police mobile equipment;
the police intelligent bracelet comprises a physiological index detection module, a motion behavior detection module, an interaction module, a micro control unit and a power supply module; the physiological index detection module is used for acquiring physiological index data of the police officer; the motion behavior detection module is used for acquiring motion data and position data of police officers; the interaction module is used for interacting information with police officers; the micro control unit is respectively connected with the physiological index detection module, the motion behavior detection module and the interaction module so as to control the modules to work; the power supply module is respectively connected with the physiological index detection module, the motion behavior detection module, the interaction module and the micro control unit so as to supply power to the modules;
the APP comprises a physiological index module, a motion function module, a psychological index module, a comprehensive display module and a personal setting module; the physiological index module is used for processing the physiological index data acquired by the bracelet, formatting the physiological index data, sending the physiological index data to the health management cloud, and receiving and processing a physiological health conclusion returned by the health management cloud; the motion function module is used for processing data collected by the motion behavior detection module of the bracelet, calculating the current position, motion state and energy consumption of an officer and sending the motion behavior data to the health management cloud; the mental index module is used for acquiring mental health scale information data, formatting the mental health scale information data, sending the formatted mental health scale information data to the health management cloud, and receiving and processing a mental health conclusion returned by the health management cloud; the comprehensive display module is used for displaying the comprehensive health state and the latest push message of the policeman; the personal setting module is used for displaying personal identity information and providing a GUI (graphical user interface) for personal parameter setting and system parameter setting of the APP;
the health management cloud comprises an account management module, a data storage module, a deep learning module, a data analysis module and a monitoring module;
the account management module is used for identifying and verifying the identity information of the APP police officer and opening the data exchange authority between the APP and the health management cloud terminal for the police officer passing the verification;
the data management module is used for processing a data interaction protocol and then routing data to different data processing modules;
the data storage module realizes the formatting and access functions of the landing data of the health management cloud;
the deep learning module takes the data stored by the data storage module as a sample, carries out deep convolutional neural network model training and establishes a health classification model according to the data characteristics;
the data analysis module compares the physiological index data and the psychological index data sent by the APP and received in real time with a health classification model established by the deep learning module for analysis to obtain a health analysis result;
and the monitoring module is used for sending response information to corresponding policemen or departments according to the health analysis result obtained by the data analysis module.
Further, it is alert with intelligent bracelet still includes the environmental monitoring module who is used for detecting police officer's surrounding environment data.
Further, it is alert with physiological index detection module of intelligent bracelet including rhythm of the heart sensor, blood oxygen sensor, skin electricity sensor and body fat sensor.
Further, the motion behavior detection module of the police intelligent bracelet comprises an acceleration sensor assembly and a GPS module; the GPS module acquires current position data of the police officer for calculating and positioning the motion state; the acceleration sensor assembly is used for acquiring wrist movement data of the police officer, so that whether the police officer stays at a certain position and is in a moving state or a static state is calculated.
Further, the interaction module of the intelligent police bracelet comprises a vibration motor, an LED dot matrix, a key module and a BLE Bluetooth module; the vibration motor is used for message reminding; the LED dot matrix is used for displaying time, messages and health data; the key module is used for obtaining the input of the police; BLE bluetooth module be used for exchanging data between bracelet and the APP.
Further, the physiological index module of the APP is also used for comparing and analyzing the physiological index data collected by the bracelet with the local health normal standard to form a preliminary physiological health analysis result; the psychological index module of the APP is further used for comparing and analyzing the collected mental health scale information data with a local health normal standard to form a preliminary mental health analysis result.
Further, the APP also comprises a health encyclopedia module, a health plan module and a consultation interaction module; the health encyclopedia module is used for providing health encyclopedia knowledge; the health plan module is used for planning a health task and recording the completion condition of police officers; the consultation interaction is used for the police to actively seek help and consult healthily.
The invention relates to a health management method using a police health management system, which comprises the following steps:
s1: establishing communication connection between a police intelligent bracelet and an APP running on police mobile equipment;
s2: the APP of the police mobile equipment is in communication connection with the health management cloud; after the health management cloud verifies the identity of the police officer, sending a corresponding matched mental health scale, health plan and message to the APP;
s3: the APP of the police mobile equipment reminds the police officers of completing the mental health scale received in the step S2, and sends the collected mental index data to the health management cloud end;
s4: the method comprises the steps that a police intelligent bracelet collects physiological index data of police personnel and sends the physiological index data to an APP of police mobile equipment;
s5: the APP of the police affair mobile device processes the received physiological index data collected in the step S4 and sends the processed physiological index data to the cloud end of the health management platform;
s6: the health management cloud receives the psychological index data sent in the step S3, and the psychological index data falls to a database to serve as sample data of deep learning;
s7: the health management cloud receives the physiological index data sent in the step S5, and the physiological index data falls to the database to serve as sample data of deep learning;
s8: the health management cloud carries out deep convolutional neural network model training by adopting the sample data of the step S6 and the step S7 to establish a classification health model;
s9: the health management cloud carries out comparison analysis on the physiological index data and the mental health acquisition data uploaded by the APP in real time by using the classified health model obtained in the step S8 to obtain a health analysis result;
s10: the health management cloud performs a hierarchical response according to the health analysis result obtained in step S9:
when the health analysis result is a mild risk, the health management cloud sends work and rest rule, reasonable diet and body-building reminding to the police APP;
when the health analysis result is moderate risk, the health management cloud sends work and rest rule, reasonable diet and body-building reminding to the police officers APP, and synchronously pushes the health analysis result to the management department of the police officers to be collected to remind the police officers of carrying out reasonable work arrangement;
when health analysis result is severe risk, the health management high in the clouds guides with saving oneself to APP propelling movement emergency alarm, and APP plays with pronunciation and video mode and saves oneself and guides, informs the colleague in health emergency department and near simultaneously emergency alarm and identity position information, accomplishes emergency response fast.
Further, in step S8, the health management cloud performs deep convolutional neural network model training according to the sample data of step S6 and step S7 to establish a classification health model, including the following steps:
t 1: the deep learning module loads the original sample data of the ground from the database;
t 2: the deep learning module loads the electronic health file of the original sample data owner in the step t1 from the database;
t 3: the deep learning module carries out abnormal data elimination processing on the data loaded in the step t 1;
t 4: the deep learning module performs multi-dimensional classification on the data preprocessed in the step t2, and generates a series of data fragment sets according to the classification;
t 5: the deep learning module performs feature standardization processing on the multi-dimensional data fragment set generated in the step t3, so that the features of the data fragment set of each dimension have zero mean and unit variance;
t 6: the deep learning module marks the result data of step t5 with the electronic health profile of step t 2;
t 7: the deep learning module inputs the result data of the step t5 or the step t6 into a convolution kernel, and outputs characteristic data after multi-layer characteristic mapping;
t 8: the deep learning module reversely adjusts the parameters of each layer of the convolution kernel according to the average distribution probability of the feature data in the step t 7;
t 9: the deep learning module repeats the steps from t1 to t8, all data are processed, and feature training is completed;
t 10: the deep learning module establishes a classification health model by using a series of characteristic data obtained in the step t 9.
Further, in step S3, the APP of the police mobile device further compares the collected psychological index data with the local health normative standard and analyzes the psychological index data to form a preliminary psychological health analysis result;
in step S5, the APP of the police mobile device further analyzes the received physiological index data against the local health normative standard to form a preliminary physiological health analysis result.
Further, the health management method of the police health management system further includes the following step S11: the health management cloud end periodically counts the health states and behaviors of police officer groups and individuals, and provides a data statistical report form for management and functional departments.
The invention has the beneficial effects that:
the police health management system and the police health management method collect real-time physiological index data and psychological scale data of police officers through a police intelligent bracelet, build a health classification model after deep learning is carried out at a health management cloud, analyze the real-time physiological and psychological health data through the built health model to obtain the current physical health condition of the police officers, and carry out life and work prompting, body building plan arrangement and health problem guiding and correcting according to the health condition of the police officers so as to achieve the purpose of improving the physical and psychological health quality of the police officers. According to the invention, the health risk of the police officers can be found in time according to the real-time collected data, and particularly, the emergency quick response is realized for sudden diseases, so that the number of the police officers who sacrifice the health crisis can be reduced; the invention can also provide data support for the health management of police.
Drawings
FIG. 1 is a functional block diagram of the present invention;
FIG. 2 is a schematic diagram of a police smart bracelet of the present invention;
fig. 3 is a schematic diagram of a policing mobile device APP of the invention;
fig. 4 is a schematic diagram of a health management cloud according to the present invention.
Detailed Description
The invention is further described below with reference to the figures and examples.
As shown in fig. 1, the police health management system of the embodiment includes a police smart bracelet 1, an APP2 and a health management cloud 3, which are loaded on a police mobile device, and the police smart bracelet and the APP are in communication connection, and the APP and the health management cloud are in communication connection. Specifically, in this embodiment, adopt the bluetooth communication between alert intelligent bracelet 1 and the APP, adopt wireless network communication between APP and the health management high in the clouds.
The police intelligent bracelet comprises a physiological index detection module 11, an exercise behavior detection module 12, an interaction module 14, a micro-control unit 16 and a power supply module 15; the physiological index detection module is used for acquiring physiological index data of the police officer; the motion behavior detection module is used for acquiring motion data and position data of police officers; the interaction module is used for interacting information with police officers; the micro control unit is respectively connected with the physiological index detection module, the motion behavior detection module and the interaction module so as to control the modules to work; the power supply module is respectively connected with the physiological index detection module, the motion behavior detection module, the interaction module and the micro control unit so as to supply power to the modules. In this embodiment, the power module includes a charging and protecting module 151, a polymer battery 152, and a power management module 153. The high polymer battery stores electric energy and provides continuous electric energy for the operation of the bracelet. The charging and protecting module is used for charging the high polymer battery and protecting the battery, so that the battery is prevented from being damaged due to overlarge input current. The power management module adjusts the voltage and current of the circuit loop and provides the battery state for the control unit.
The APP comprises a physiological index module 21, a motion function module 22, a psychological index module 23, a comprehensive display module 27 and a personal setting module 28; the physiological index module is used for processing the physiological index data acquired by the bracelet, formatting the physiological index data, sending the physiological index data to the health management cloud, and receiving and processing a physiological health conclusion returned by the health management cloud; the motion function module is used for processing data collected by the motion behavior detection module of the bracelet, calculating the current position, motion state and energy consumption of an officer and sending the motion behavior data to the health management cloud; the mental index module is used for acquiring mental health scale information data, formatting the mental health scale information data, sending the formatted mental health scale information data to the health management cloud, and receiving and processing a mental health conclusion returned by the health management cloud; the comprehensive display module is used for displaying the comprehensive health state and the latest push message of the policeman; the personal setting module is used for displaying personal identity information and providing a personal parameter setting and system parameter setting GUI interface of the APP.
The health management cloud 3 comprises an account management module 31, a data management module 32, a data storage module 33, a deep learning module 34, a data analysis module 35 and a monitoring module 37. The account management module is used for identifying and verifying the identity information of the APP police officers and opening data exchange permission between the APP and the health management cloud end for the police officers passing the verification. The data management module is used for processing a data interaction protocol and then routing data to different data processing modules. The data storage module realizes the formatting and access functions of the ground data of the health management cloud. The deep learning module takes the data stored by the data storage module as a sample, carries out deep convolutional neural network model training, and establishes a health classification model according to the data characteristics. And the data analysis module compares the physiological index data and the psychological index data sent by the APP and received in real time with the health classification model established by the deep learning module for analysis to obtain a health analysis result. And the monitoring module is used for sending response information to corresponding policemen or departments according to the health analysis result obtained by the data analysis module.
In this embodiment, the health management cloud 3 further includes a data statistics module 36, and the data statistics module periodically sends data stored in the data storage module to the health management department, so as to provide data support for the health management part to perform health management work.
In this embodiment, it is alert with intelligent bracelet still includes the environmental monitoring module 13 that is used for detecting police officer's surrounding environment data, the environmental monitoring module includes ambient light sensor 131, temperature sensor 132 and humidity transducer 133. The ambient light sensor is used for acquiring the intensity change value of ambient light. The temperature sensor is used for acquiring an environmental temperature value. The environment humidity sensor is used for acquiring an environment humidity value. Environmental changes can also threaten the physical health and the mental health of the police officers, so that the data of the surrounding environment of the police officers are collected, and the health management cloud can send a more targeted response scheme aiming at the physical health and the mental health problems caused by the environmental changes.
In this embodiment, the physiological index detection module 11 of the smart bracelet for police includes a heart rate sensor 111, a blood oxygen sensor 112, a skin electrical sensor 113, and a body fat sensor 114. The heart rate sensor collects pulse PPG and electrocardio ECG signals of the wrist part of the bracelet wearer. The blood oxygen sensor detects the blood oxygen saturation degree of the blood of the bracelet wearer. The skin electric sensor collects skin electric signals reflecting the emotion changes of a wearer. The body fat sensor detects parameters such as body fat of a bracelet wearer.
In this embodiment, the athletic performance detecting module 12 of the smart band for police includes an acceleration sensor assembly 121 and a GPS module 122. The GPS module acquires the current position data of the police officer for calculating and positioning the motion state. The acceleration sensor assembly is used for acquiring wrist movement data of the police officer, so that whether the police officer stays at a certain position and is in a moving state or a static state can be calculated.
In this embodiment, the interaction module 14 of the smart bracelet for police includes a vibration motor 141, an LED dot matrix 142, a key module 143, and a BLE bluetooth module 144; the vibration motor is used for message reminding; the LED dot matrix is used for displaying time, messages and health data; the key module is used for obtaining the input of the police; BLE bluetooth module be used for exchanging data between bracelet and the APP.
In this embodiment, the physiological index module 21 of the APP is further configured to compare and analyze the physiological index data acquired by the wristband with a local health normative standard to form a preliminary physiological health analysis result; the psychological index module of the APP is further used for comparing and analyzing the collected mental health scale information data with a local health normal standard to form a preliminary mental health analysis result.
In this embodiment, the APP further includes a health encyclopedia module 24, a health plan module 25 and a consultation interaction module 26; the health encyclopedia module is used for providing health encyclopedia knowledge; the health plan module is used for planning a health task and recording the completion condition of police officers; the consultation interaction is used for the police to actively seek help and consult healthily.
In this embodiment, the health management method using the police health management system includes the following steps:
s1: police establishes communication connection with intelligent bracelet and the APP who operates in police affairs mobile device.
S2: the APP of the police mobile equipment is in communication connection with the health management cloud; after the health management cloud verifies the identity of the police officer, the corresponding matched mental health scale, health plan and message are sent to the APP.
S3: the APP of the police mobile device reminds the police officers of completing the mental health scale received in step S2, and sends the collected mental index data to the health management cloud.
S4: police wears police service personnel's physiological index data with intelligent bracelet collection to send the APP for police service mobile device.
S5: and the APP of the police affair mobile device processes the received physiological index data collected in the step S4 and sends the processed physiological index data to the cloud of the health management platform.
S6: the health management cloud receives the psychological index data sent in step S3, and falls to the database as sample data for deep learning.
S7: the health management cloud receives the physiological index data sent in step S5, and falls to the database as sample data for deep learning.
S8: the health management cloud carries out deep convolutional neural network model training by adopting the sample data of the step S6 and the step S7 to establish a classification health model, and specifically comprises the following steps:
t 1: the deep learning module loads the original sample data of the ground from the database;
t 2: the deep learning module loads the electronic health file of the original sample data owner in the step t1 from the database;
t 3: the deep learning module performs abnormal data elimination processing on the data loaded in the step t1, wherein the abnormal data elimination processing includes removing repeated data, error data which are not in a normal range and discrete data which are not significant;
t 4: the deep learning module performs multi-dimensional classification on the data preprocessed in the step t2, and generates a series of data fragment sets according to the classification;
t 5: the deep learning module performs feature standardization processing on the multi-dimensional data fragment set generated in the step t3, so that the features of the data fragment set of each dimension have zero mean and unit variance;
t 6: the deep learning module marks the result data of step t5 with the electronic health profile of step t 2;
t 7: the deep learning module inputs the result data of the step t5 or the step t6 into a convolution kernel, and outputs characteristic data after multi-layer characteristic mapping;
t 8: the deep learning module reversely adjusts the parameters of each layer of the convolution kernel according to the average distribution probability of the feature data in the step t 7;
t 9: the deep learning module repeats the steps from t1 to t8, all data are processed, and feature training is completed;
t 10: the deep learning module establishes a classification health model by using a series of characteristic data obtained in the step t 9.
S9: and the health management cloud carries out comparison analysis on the physiological index data and the mental health acquisition data uploaded by the APP in real time by using the classified health model obtained in the step S8 to obtain a health analysis result.
S10: the health management cloud performs a hierarchical response according to the health analysis result obtained in step S9:
when the health analysis result is a mild risk, the health management cloud sends work and rest rule, reasonable diet and body-building reminding to the police APP;
when the health analysis result is moderate risk, the health management cloud sends work and rest rule, reasonable diet and body-building reminding to the police officers APP, and synchronously pushes the health analysis result to the management department of the police officers to be collected to remind the police officers of carrying out reasonable work arrangement;
when health analysis result is severe risk, the health management high in the clouds guides with saving oneself to APP propelling movement emergency alarm, and APP plays with pronunciation and video mode and saves oneself and guides, informs the colleague in health emergency department and near simultaneously emergency alarm and identity position information, accomplishes emergency response fast.
In this embodiment, the health management method using the police health management system further includes the following step S11: the health management cloud end periodically counts the health states and behaviors of police officer groups and individuals, and provides a data statistical report form for management and functional departments.
In step S3, the APP of the police mobile device further compares the collected psychological index data with the local health normative standard and analyzes the psychological index data to form a preliminary psychological health analysis result; in step S5, the APP of the police mobile device further analyzes the received physiological index data against the local health normative standard to form a preliminary physiological health analysis result. This improvement makes under the APP of police affairs mobile device and the health management high in the clouds condition of not establishing the communication connection, also can carry out health detection and management.
Finally, the above embodiments are only for illustrating the technical solutions of the present invention and not for limiting, although the present invention has been described in detail with reference to the preferred embodiments, it should be understood by those skilled in the art that modifications or equivalent substitutions may be made to the technical solutions of the present invention without departing from the spirit and scope of the technical solutions of the present invention, and all of them should be covered in the claims of the present invention.
Claims (10)
1. A police health management system is characterized in that: the mobile police mobile phone comprises a police smart bracelet, an APP and a health management cloud which are loaded on police mobile equipment, wherein the police smart bracelet is in communication connection with the APP, and the APP is in communication connection with the health management cloud;
the police intelligent bracelet comprises a physiological index detection module, a motion behavior detection module, an interaction module, a micro control unit and a power supply module; the physiological index detection module is used for acquiring physiological index data of the police officer; the motion behavior detection module is used for acquiring motion data and position data of police officers; the interaction module is used for interacting information with police officers; the micro control unit is respectively connected with the physiological index detection module, the motion behavior detection module and the interaction module so as to control the modules to work; the power supply module is respectively connected with the physiological index detection module, the motion behavior detection module, the interaction module and the micro control unit so as to supply power to the modules;
the APP comprises a physiological index module, a motion function module, a psychological index module, a comprehensive display module and a personal setting module; the physiological index module is used for processing the physiological index data acquired by the bracelet, formatting the physiological index data, sending the physiological index data to the health management cloud, and receiving and processing a physiological health conclusion returned by the health management cloud; the motion function module is used for processing data collected by the motion behavior detection module of the bracelet, calculating the current position, motion state and energy consumption of an officer and sending the motion behavior data to the health management cloud; the mental index module is used for acquiring mental health scale information data, formatting the mental health scale information data, sending the formatted mental health scale information data to the health management cloud, and receiving and processing a mental health conclusion returned by the health management cloud; the comprehensive display module is used for displaying the comprehensive health state and the latest push message of the policeman; the personal setting module is used for displaying personal identity information and providing a GUI (graphical user interface) for personal parameter setting and system parameter setting of the APP;
the health management cloud comprises an account management module, a data storage module, a deep learning module, a data analysis module and a monitoring module;
the account management module is used for identifying and verifying the identity information of the APP police officer and opening the data exchange authority between the APP and the health management cloud terminal for the police officer passing the verification;
the data management module is used for processing a data interaction protocol and then routing data to different data processing modules;
the data storage module realizes the formatting and access functions of the landing data of the health management cloud;
the deep learning module takes the data stored by the data storage module as a sample, carries out deep convolutional neural network model training and establishes a health classification model according to the data characteristics;
the data analysis module compares the physiological index data and the psychological index data sent by the APP and received in real time with a health classification model established by the deep learning module for analysis to obtain a health analysis result;
and the monitoring module is used for sending response information to corresponding policemen or departments according to the health analysis result obtained by the data analysis module.
2. A police health management system as claimed in claim 1 wherein: police uses intelligent bracelet still includes the environmental monitoring module who is used for detecting police officer's surrounding environment data.
3. A police health management system as claimed in claim 1 wherein: it is alert with physiological index detection module of intelligent bracelet including rhythm of the heart sensor, blood oxygen sensor, skin electricity sensor and body fat sensor.
4. A police health management system as claimed in claim 1 wherein: the motion behavior detection module of the intelligent police bracelet comprises an acceleration sensor assembly and a GPS module; the GPS module acquires current position data of the police officer for calculating and positioning the motion state; the acceleration sensor assembly is used for acquiring wrist movement data of the police officer, so that whether the police officer stays at a certain position and is in a moving state or a static state is calculated.
5. A police health management system as claimed in claim 1 wherein: the interaction module of the police intelligent bracelet comprises a vibration motor, an LED dot matrix, a key module and a BLE Bluetooth module; the vibration motor is used for message reminding; the LED dot matrix is used for displaying time, messages and health data; the key module is used for obtaining the input of the police; BLE bluetooth module be used for exchanging data between bracelet and the APP.
6. A police health management system as claimed in claim 1 wherein: the physiological index module of the APP is also used for comparing and analyzing the physiological index data acquired by the bracelet with the local health normal mode standard to form a preliminary physiological health analysis result; the psychological index module of the APP is further used for comparing and analyzing the collected mental health scale information data with a local health normal standard to form a preliminary mental health analysis result.
7. A police health management system as claimed in claim 1 wherein: the APP also comprises a health encyclopedia module, a health plan module and a consultation interaction module; the health encyclopedia module is used for providing health encyclopedia knowledge; the health plan module is used for planning a health task and recording the completion condition of police officers; the consultation interaction is used for the police to actively seek help and consult healthily.
8. A health management method using the police health management system as set forth in any one of claims 1 to 7, comprising the steps of:
s1: establishing communication connection between a police intelligent bracelet and an APP running on police mobile equipment;
s2: the APP of the police mobile equipment is in communication connection with the health management cloud; after the health management cloud verifies the identity of the police officer, sending a corresponding matched mental health scale, health plan and message to the APP;
s3: the APP of the police mobile equipment reminds the police officers of completing the mental health scale received in the step S2, and sends the collected mental index data to the health management cloud end;
s4: the method comprises the steps that a police intelligent bracelet collects physiological index data of police personnel and sends the physiological index data to an APP of police mobile equipment;
s5: the APP of the police affair mobile device processes the received physiological index data collected in the step S4 and sends the processed physiological index data to the cloud end of the health management platform;
s6: the health management cloud receives the psychological index data sent in the step S3, and the psychological index data falls to a database to serve as sample data of deep learning;
s7: the health management cloud receives the physiological index data sent in the step S5, and the physiological index data falls to the database to serve as sample data of deep learning;
s8: the health management cloud carries out deep convolutional neural network model training by adopting the sample data of the step S6 and the step S7 to establish a classification health model;
s9: the health management cloud carries out comparison analysis on the physiological index data and the mental health acquisition data uploaded by the APP in real time by using the classified health model obtained in the step S8 to obtain a health analysis result;
s10: the health management cloud performs a hierarchical response according to the health analysis result obtained in step S9:
when the health analysis result is a mild risk, the health management cloud sends work and rest rule, reasonable diet and body-building reminding to the police APP;
when the health analysis result is moderate risk, the health management cloud sends work and rest rule, reasonable diet and body-building reminding to the police officers APP, and synchronously pushes the health analysis result to the management department of the police officers to be collected to remind the police officers of carrying out reasonable work arrangement;
when health analysis result is severe risk, the health management high in the clouds guides with saving oneself to APP propelling movement emergency alarm, and APP plays with pronunciation and video mode and saves oneself and guides, informs the colleague in health emergency department and near simultaneously emergency alarm and identity position information, accomplishes emergency response fast.
9. The health management method of the police health management system of claim 8, wherein: in step S8, the health management cloud performs deep convolutional neural network model training according to the sample data in step S6 and step S7 to establish a classification health model, including the following steps:
t 1: the deep learning module loads the original sample data of the ground from the database;
t 2: the deep learning module loads the electronic health file of the original sample data owner in the step t1 from the database;
t 3: the deep learning module carries out abnormal data elimination processing on the data loaded in the step t 1;
t 4: the deep learning module performs multi-dimensional classification on the data preprocessed in the step t2, and generates a series of data fragment sets according to the classification;
t 5: the deep learning module performs feature standardization processing on the multi-dimensional data fragment set generated in the step t3, so that the features of the data fragment set of each dimension have zero mean and unit variance;
t 6: the deep learning module marks the result data of step t5 with the electronic health profile of step t 2;
t 7: the deep learning module inputs the result data of the step t5 or the step t6 into a convolution kernel, and outputs characteristic data after multi-layer characteristic mapping;
t 8: the deep learning module reversely adjusts the parameters of each layer of the convolution kernel according to the average distribution probability of the feature data in the step t 7;
t 9: the deep learning module repeats the steps from t1 to t8, all data are processed, and feature training is completed;
t 10: the deep learning module establishes a classification health model by using a series of characteristic data obtained in the step t 9.
10. The health management method of the police health management system of claim 8, wherein in step S3, the APP of the police mobile device further analyzes the collected psychological index data against the local health normative standard to form a preliminary psychological health analysis result;
in step S5, the APP of the police mobile device further analyzes the received physiological index data against the local health normative standard to form a preliminary physiological health analysis result.
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