CN113080901A - Health management system based on AI technology - Google Patents
Health management system based on AI technology Download PDFInfo
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- CN113080901A CN113080901A CN202110472961.2A CN202110472961A CN113080901A CN 113080901 A CN113080901 A CN 113080901A CN 202110472961 A CN202110472961 A CN 202110472961A CN 113080901 A CN113080901 A CN 113080901A
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- 230000036541 health Effects 0.000 title claims abstract description 87
- 238000005516 engineering process Methods 0.000 title claims abstract description 15
- 230000005802 health problem Effects 0.000 claims abstract description 36
- 238000012545 processing Methods 0.000 claims abstract description 17
- 238000003062 neural network model Methods 0.000 claims abstract description 10
- 238000004891 communication Methods 0.000 claims description 52
- 238000012544 monitoring process Methods 0.000 claims description 24
- 230000005540 biological transmission Effects 0.000 claims description 18
- 239000013307 optical fiber Substances 0.000 claims description 12
- 238000012546 transfer Methods 0.000 claims description 6
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- 238000000034 method Methods 0.000 abstract description 5
- 241000854291 Dianthus carthusianorum Species 0.000 description 5
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- 230000002349 favourable effect Effects 0.000 description 3
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- 238000005265 energy consumption Methods 0.000 description 2
- 230000008569 process Effects 0.000 description 2
- WQZGKKKJIJFFOK-GASJEMHNSA-N Glucose Natural products OC[C@H]1OC(O)[C@H](O)[C@@H](O)[C@@H]1O WQZGKKKJIJFFOK-GASJEMHNSA-N 0.000 description 1
- 230000004075 alteration Effects 0.000 description 1
- 239000008280 blood Substances 0.000 description 1
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- 230000036760 body temperature Effects 0.000 description 1
- 238000004364 calculation method Methods 0.000 description 1
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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
- A61B5/0205—Simultaneously evaluating both cardiovascular conditions and different types of body conditions, e.g. heart and respiratory condition
- A61B5/02055—Simultaneously evaluating both cardiovascular condition and temperature
-
- 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
- A61B5/02438—Detecting, measuring or recording pulse rate or heart rate with portable devices, e.g. worn by the patient
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/05—Detecting, measuring or recording for diagnosis by means of electric currents or magnetic fields; Measuring using microwaves or radio waves
- A61B5/053—Measuring electrical impedance or conductance of a portion of the body
- A61B5/0537—Measuring body composition by impedance, e.g. tissue hydration or fat content
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/145—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue
- A61B5/14532—Measuring characteristics of blood in vivo, e.g. gas concentration, pH value; Measuring characteristics of body fluids or tissues, e.g. interstitial fluid, cerebral tissue for measuring glucose, e.g. by tissue impedance measurement
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/48—Other medical applications
- A61B5/4806—Sleep evaluation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
- A61B5/00—Measuring for diagnostic purposes; Identification of persons
- A61B5/68—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient
- A61B5/6801—Arrangements of detecting, measuring or recording means, e.g. sensors, in relation to patient specially adapted to be attached to or worn on the body surface
- A61B5/6802—Sensor mounted on worn items
- A61B5/681—Wristwatch-type devices
-
- 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
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W16/00—Network planning, e.g. coverage or traffic planning tools; Network deployment, e.g. resource partitioning or cells structures
- H04W16/18—Network planning tools
- H04W16/20—Network planning tools for indoor coverage or short range network deployment
-
- H—ELECTRICITY
- H04—ELECTRIC COMMUNICATION TECHNIQUE
- H04W—WIRELESS COMMUNICATION NETWORKS
- H04W4/00—Services specially adapted for wireless communication networks; Facilities therefor
- H04W4/30—Services specially adapted for particular environments, situations or purposes
- H04W4/38—Services specially adapted for particular environments, situations or purposes for collecting sensor information
Abstract
The invention provides a health management system based on an AI technology, which comprises a parameter acquisition module, a parameter storage module, an AI processing module and a prompt module; the parameter acquisition module is used for acquiring the health state parameters of the user; the parameter storage module is used for storing the health state parameters; the AI processing module is used for reading the health state parameters from the parameter storage module and predicting the possible health problems of the body of the user by using a preset neural network model; the prompting module is used for displaying the possible health problems and corresponding treatment measures to a user. The method and the device realize the prediction of the health problems possibly occurring on the body of the user, can give corresponding treatment measures based on the health problems, can kill the health problems in the sprouting stage, and effectively protect the health of the body of the user.
Description
Technical Field
The invention relates to the field of management, in particular to a health management system based on an AI technology.
Background
The existing health management system generally obtains the health state parameters of the user, and then gives health management opinions to the user based on the health state parameters. The setting mode has certain disadvantages, and reasonable suggestions cannot be given before the health problem of the body of the user occurs. The user is not favorable to take corresponding avoidance measures for the possible health problems in advance.
Disclosure of Invention
In view of the above problems, an object of the present invention is to provide a health management system based on AI technology.
The invention provides a health management system based on an AI technology, which comprises a parameter acquisition module, a parameter storage module, an AI processing module and a prompt module;
the parameter acquisition module is used for acquiring the health state parameters of the user and transmitting the health state parameters to the parameter storage module;
the parameter storage module is used for storing the health state parameters;
the AI processing module is used for reading the health state parameters from the parameter storage module and predicting the possible health problems of the body of the user by using a preset neural network model;
the prompting module is used for displaying the possible health problems and corresponding treatment measures to a user.
Preferably, the parameter acquisition module comprises a monitoring terminal device and a data transmission network;
the monitoring terminal equipment is used for acquiring the health state parameters of the user and transmitting the health state parameters to the data transmission network;
and the data transmission network user transmits the health state parameters to the parameter storage module.
Preferably, the parameter storage module and the AI processing module are both arranged in a cloud server.
Preferably, the predicting the health problem which may occur to the body of the user by using the preset neural network model comprises:
predicting the future value of the health state parameter by using a hidden Markov model to obtain a predicted value;
inputting the predicted value into a preset neural network model for recognition, and acquiring a health problem corresponding to the predicted value;
and taking the health problem corresponding to the predicted value as a health problem which may appear on the body of the user.
Preferably, the AI processing module is further configured to retrieve, from the parameter storage module, a processing measure corresponding to the health issue that may occur.
Preferably, the monitoring terminal comprises a bracelet, an infrared temperature measuring device, a glucometer and a body fat scale;
the data transmission network comprises a local wireless communication network and an optical fiber communication network;
the monitoring terminal transmits the acquired health state parameters to the local wireless communication network;
the local wireless communication network is used for transmitting the health state parameters to the optical fiber communication network;
the optical fiber communication network is used for forwarding the health state parameters to the parameter storage module.
Preferably, the local wireless communication network comprises a wireless communication node and a relay base station;
the wireless communication node is used for communicating with the monitoring terminal, receiving the health state parameters sent from the monitoring terminal and transmitting the health state parameters to the transfer base station;
and the transit base station is used for transmitting the health state parameters to the optical fiber communication network.
Compared with the prior art, the invention has the advantages that:
the method and the device realize the prediction of the health problems possibly occurring on the body of the user, can give corresponding treatment measures based on the health problems, can kill the health problems in the sprouting stage, and effectively protect the health of the body of the user. However, in the prior art, corresponding health advice is generally given for the existing health state parameters, and only after the body of the user has a certain degree of health problems, treatment measures are given, which is not beneficial to protecting the body health of the user.
Drawings
The invention is further illustrated by means of the attached drawings, but the embodiments in the drawings do not constitute any limitation to the invention, and for a person skilled in the art, other drawings can be obtained on the basis of the following drawings without inventive effort.
Fig. 1 is a diagram of an exemplary embodiment of a health management system based on AI technology according to the present invention.
Detailed Description
Reference will now be made in detail to embodiments of the present invention, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar function throughout. The embodiments described below with reference to the accompanying drawings are illustrative only for the purpose of explaining the present invention, and are not to be construed as limiting the present invention.
As shown in fig. 1, in an embodiment, the present invention provides a health management system based on AI technology, which includes a parameter obtaining module, a parameter storing module, an AI processing module, and a prompting module;
the parameter acquisition module is used for acquiring the health state parameters of the user and transmitting the health state parameters to the parameter storage module;
the parameter storage module is used for storing the health state parameters;
the AI processing module is used for reading the health state parameters from the parameter storage module and predicting the possible health problems of the body of the user by using a preset neural network model;
the prompting module is used for displaying the possible health problems and corresponding treatment measures to a user.
Preferably, the parameter acquisition module comprises a monitoring terminal device and a data transmission network;
the monitoring terminal equipment is used for acquiring the health state parameters of the user and transmitting the health state parameters to the data transmission network;
and the data transmission network user transmits the health state parameters to the parameter storage module.
Preferably, the parameter storage module and the AI processing module are both arranged in a cloud server.
Preferably, the predicting the health problem which may occur to the body of the user by using the preset neural network model comprises:
predicting the future value of the health state parameter by using a hidden Markov model to obtain a predicted value;
inputting the predicted value into a preset neural network model for recognition, and acquiring a health problem corresponding to the predicted value;
and taking the health problem corresponding to the predicted value as a health problem which may appear on the body of the user.
Preferably, the AI processing module is further configured to retrieve, from the parameter storage module, a processing measure corresponding to the health issue that may occur.
Preferably, the monitoring terminal comprises a bracelet, an infrared temperature measuring device, a glucometer and a body fat scale;
the data transmission network comprises a local wireless communication network and an optical fiber communication network;
the monitoring terminal transmits the acquired health state parameters to the local wireless communication network;
the local wireless communication network is used for transmitting the health state parameters to the optical fiber communication network;
the optical fiber communication network is used for forwarding the health state parameters to the parameter storage module.
The health state parameters include heart rate, sleep time, body temperature, blood glucose concentration, body fat rate, etc. The monitoring terminal can effectively acquire the health state parameters.
Preferably, the local wireless communication network comprises a wireless communication node and a relay base station;
the wireless communication node is used for communicating with the monitoring terminal, receiving the health state parameters sent from the monitoring terminal and transmitting the health state parameters to the transfer base station;
and the transit base station is used for transmitting the health state parameters to the optical fiber communication network.
Preferably, the relay base station performs clustering processing on the wireless communication nodes based on a division time interval, and divides the wireless communication nodes into member communication nodes and cluster head communication nodes;
the member communication node is used for communicating with the monitoring terminal, receiving the health state parameters sent from the monitoring terminal and sending the health state parameters to the cluster head communication node;
and the cluster head communication node is used for transmitting the health state parameters to the transfer base station.
The existing monitoring terminal generally adopts a Bluetooth mode to communicate with devices such as a smart phone, and the like, so that health state parameters are sent to a cloud platform. However, if the bluetooth is not opened in the mobile phone of the user, the monitoring terminal cannot timely send the health state parameters to the cloud platform, so the existing setting mode is not favorable for timely obtaining the health state parameters of the user, and is not favorable for timely discovering health problems of the body of the user.
The wireless communication nodes are arranged in the indoor space where the user frequently moves, for example, in a residence in a distributed mode, the coverage rate can be guaranteed, the monitoring terminal can send the health state parameters to the parameter storage module anytime and anywhere, and the health problems of the user can be found timely.
In addition, the local wireless communication network is set through the wireless communication nodes, so that the difficulty in subsequent maintenance caused by excessive communication lines can be avoided.
Preferably, the relay base station determines the division time interval by:
hqti＝hqti-1+qhi×bsdata
in the formula, hqtiAnd hqti-1Respectively representing the ith division time interval and the (i-1) th division time interval, wherein i is more than or equal to 2, and bsdata represents the preset unit time length;
thre represents a preset comparison threshold value,
in the formula, w1、w2、w3Representing a preset weight coefficient, and recording the moment of determining the division time interval from the ith time as tstart,iThe time when the i-1 st clustering process is completed is denoted as tend,i-1，persdiRepresents a time interval tend,i-1,tstart,i]The average unit time data throughput of the relay base station; persdjRepresenting a time interval
Average unit time data throughput of the internal transfer base station; ctcmtiRepresenting a time interval
Length of (d); ctcmtjRepresenting a time interval
Length of (d); ene ciIs shown at time tstart,iStandard deviation of residual energy of member communication node and cluster head communication node, enecjIs shown at time tstart,jMember communication node and cluster head communication nodeStandard deviation of energy; t is tend,j-1Indicates the time when the j-1 st clustering process is completed, tstart,iIndicating the moment when the jth start of the determination of the divided time interval is determined.
The embodiment of the invention realizes the self-adaptive change of the division time interval and the busy degree of data transmission, and txy is obtained when the data transmission is busyiWhen > thre, hqt was obtainediWill be compared hqti-1The small time interval is divided, namely the time interval is correspondingly shortened, so that the situation that a single wireless communication node bears an overweight data transmission task is avoided, energy is consumed quickly, and the coverage rate of the local wireless communication network is reduced, because if the coverage rate is reduced, the health state parameters can not be transmitted to the parameter storage module in time, the health problems existing in the body of the user can not be found in time, and the body health of the user is not protected;
when txyiWhen the data transmission rate is less than or equal to thre, the data transmission is not busy, the division time interval is correspondingly increased, and the influence on the service life of the wireless communication node due to frequent clustering is avoided, so that the service life of the ground wireless communication network is prolonged, the energy is saved, and the operation cost of the ground wireless communication network is reduced.
At txyiIn the calculation, besides the data throughput of unit time, parameters such as residual energy difference of wireless communication nodes, continuous working time of a transfer base station and the like are also considered, the data transmission and energy consumption conditions can be comprehensively reflected, the real-time state condition of the local wireless communication network is further comprehensively reflected, the data throughput and the energy consumption speed are comprehensively reflected, and the judgment accuracy is effectively improved.
Compared with the prior art, the invention has the advantages that:
the method and the device realize the prediction of the health problems possibly occurring on the body of the user, can give corresponding treatment measures based on the health problems, can kill the health problems in the sprouting stage, and effectively protect the health of the body of the user. However, in the prior art, corresponding health advice is generally given for the existing health state parameters, and only after the body of the user has a certain degree of health problems, treatment measures are given, which is not beneficial to protecting the body health of the user.
While embodiments of the invention have been shown and described, it will be understood by those skilled in the art that: various changes, modifications, substitutions and alterations can be made to the embodiments without departing from the principles and spirit of the invention, the scope of which is defined by the claims and their equivalents.
Claims (7)
1. A health management system based on AI technology is characterized by comprising a parameter acquisition module, a parameter storage module, an AI processing module and a prompt module;
the parameter acquisition module is used for acquiring the health state parameters of the user and transmitting the health state parameters to the parameter storage module;
the parameter storage module is used for storing the health state parameters;
the AI processing module is used for reading the health state parameters from the parameter storage module and predicting the possible health problems of the body of the user by using a preset neural network model;
the prompting module is used for displaying the possible health problems and corresponding treatment measures to a user.
2. The AI technology-based health management system of claim 1, wherein the parameter acquisition module comprises a monitoring terminal device and a data transmission network;
the monitoring terminal equipment is used for acquiring the health state parameters of the user and transmitting the health state parameters to the data transmission network;
and the data transmission network user transmits the health state parameters to the parameter storage module.
3. The AI technology-based health management system of claim 1, wherein the parameter storage module and the AI processing module are both disposed in a cloud server.
4. The AI technology-based health management system of claim 1, wherein the predicting the health problem of the body of the user using the preset neural network model comprises:
predicting the future value of the health state parameter by using a hidden Markov model to obtain a predicted value;
inputting the predicted value into a preset neural network model for recognition, and acquiring a health problem corresponding to the predicted value;
and taking the health problem corresponding to the predicted value as a health problem which may appear on the body of the user.
5. The AI-technology-based health management system of claim 4, wherein the AI processing module is further configured to retrieve from the parameter storage module a treatment corresponding to the potential health issue.
6. The AI technology based health management system of claim 2 wherein said monitoring terminal comprises a bracelet, an infrared temperature measuring device, a glucometer and a body fat scale;
the data transmission network comprises a local wireless communication network and an optical fiber communication network;
the monitoring terminal transmits the acquired health state parameters to the local wireless communication network;
the local wireless communication network is used for transmitting the health state parameters to the optical fiber communication network;
the optical fiber communication network is used for forwarding the health state parameters to the parameter storage module.
7. The AI technology-based health management system of claim 6, wherein the local wireless communication network comprises a wireless communication node and a relay base station;
the wireless communication node is used for communicating with the monitoring terminal, receiving the health state parameters sent from the monitoring terminal and transmitting the health state parameters to the transfer base station;
and the transit base station is used for transmitting the health state parameters to the optical fiber communication network.
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| CN202110472961.2A CN113080901A (en) | 2021-04-29 | 2021-04-29 | Health management system based on AI technology |
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| CN113628710A (en) * | 2021-07-22 | 2021-11-09 | 海信集团控股股份有限公司 | Data processing method of household health equipment, terminal equipment and server |
| CN114614525A (en) * | 2022-02-22 | 2022-06-10 | 南京安充智能科技有限公司 | Intelligent charging pile management system |
| CN117530698B (en) * | 2024-01-05 | 2024-03-22 | 深圳市双佳医疗科技有限公司 | Physiological signal acquisition and processing system based on artificial intelligence |
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Application publication date: 20210709 |