Public health management equipment

Abstract

The invention relates to the field of public health, and particularly discloses public health management equipment, which comprises a processor, a memory, and an identity authentication device, a multi-parameter health sensor, a man-machine interaction device and a data communication interface which are respectively in communication connection with the processor, a computer program is stored in the memory, and when the computer program is executed by the processor, the following steps are implemented: S1, acquiring a user identity identifier through the identity authentication device; by integrating core components such as the processor, the memory, the identity authentication device, the multi-parameter health sensor, the man-machine interaction device and the data communication interface, the public health management equipment constructs an efficient and intelligent health management platform; the computer program preset in the memory can guide the processor to accurately execute various health management tasks, so that the full-process automation from user identity recognition to risk level evaluation is realized, and the efficiency and accuracy of health management are greatly improved.

Description

Technical Field

[0001] This invention belongs to the field of public health, specifically a public health management device. Background Technology

[0002] In the field of public health management, with the deep integration of information technology and biomedical engineering, intelligent and personalized health management devices are gradually becoming an important means of safeguarding public health. Traditional public health monitoring methods mostly rely on regular manual examinations or passively waiting for patients to seek medical attention. This approach is not only inefficient but also makes it difficult to achieve real-time, dynamic monitoring of the health status of large populations. The limitations of traditional methods are particularly pronounced when facing infectious disease outbreaks, chronic disease management, and public health emergencies.

[0003] In recent years, the development of IoT technology, big data analytics, and artificial intelligence algorithms has provided strong support for the innovation of public health management equipment. By integrating various biosensors, identity authentication technologies, and data communication modules, modern health management equipment can automatically collect, process, and analyze user health data, and then provide customized health management suggestions or early warning information based on individual health conditions. This proactive and preventative health management model is of great significance for improving public health and reducing the burden on the healthcare system.

[0004] However, existing public health management equipment still has certain shortcomings in achieving personalized health management. Specifically, while most devices can collect various health data, they are insufficient in dynamically adjusting testing parameters according to the user's risk level and achieving precise health monitoring. This results in high-risk users not receiving timely and comprehensive health assessments, while low-risk users may face unnecessary over-testing, wasting medical resources and reducing the efficiency and effectiveness of health management. This invention addresses this deficiency by proposing a device that can dynamically configure testing parameters based on the user's risk level, achieving precise and efficient public health management. Summary of the Invention

[0005] To address the aforementioned technical problems, this invention provides a public health management device that solves the problems in existing technologies where testing parameters cannot be dynamically adjusted according to the user's risk level to achieve accurate health monitoring, resulting in untimely and incomplete assessment of high-risk users and excessive testing of low-risk users, wasting medical resources and reducing the efficiency and effectiveness of health management.

[0006] A public health management device includes: a processor, a memory, and an authentication device, a multi-parameter health sensor, a human-computer interaction device, and a data communication interface, all of which are communicatively connected to the processor.

[0007] The memory stores a computer program, which, when executed by a processor, performs the following steps:

[0008] S1: Obtain the user's identity identifier through the identity authentication device;

[0009] S2: Based on the user's identity identifier, query the risk profile database stored in the memory to obtain the corresponding user's preset risk level;

[0010] S3: Based on the preset risk level, dynamically configure the detection parameters of the multi-parameter health sensor. If the preset risk level is high risk, more comprehensive detection items or higher detection accuracy will be enabled.

[0011] S4: Control the multi-parameter health sensor to collect the user's real-time health data according to the configured detection parameters;

[0012] S5: Perform anomaly analysis on real-time health data, and integrate the analysis results with preset risk levels to generate a comprehensive risk score;

[0013] S6: Based on the comprehensive risk score, query the predefined response strategy library to determine the corresponding response instructions;

[0014] S7: Executes response commands, outputs warning information through the human-machine interaction device, and sends alarms to the management platform through the data communication interface.

[0015] Preferably, in step S7, the response command further includes a command to control a physical actuator that is communicatively connected to the device;

[0016] The physical actuator includes at least one of the following: access control gate, guide indicator light, and environmental disinfection device.

[0017] Preferably, when the computer program is executed by the processor, it further performs the following steps:

[0018] S8: Receive feedback signals from the physical actuator. The feedback signals are used to indicate the success or failure status of instruction execution.

[0019] S9: If no success feedback signal is received within the preset time, the alarm level will be upgraded through the data communication interface and manual intervention will be notified.

[0020] Preferably, the identity authentication device is at least one of the following: a face recognition camera, a QR code scanner, or a radio frequency identification reader.

[0021] Preferably, the multi-parameter health sensor includes at least one of the following: a non-contact infrared body temperature sensor, a microphone array, and an image sensor.

[0022] Preferably, in step S5, anomaly analysis of the real-time health data is performed by inputting the real-time health data into a pre-trained machine learning model for calculation and outputting a health anomaly probability value.

[0023] Preferably, the specific method of fusion calculation in step S5 is as follows:

[0024] The preset risk level corresponds to a weighting coefficient. The probability value of the health abnormality corresponds to a weighting coefficient. ;

[0025] .

[0026] Preferably, the human-computer interaction device includes a display and a voice broadcaster;

[0027] The output of warning information in step S7 includes displaying personalized health tips on the display and broadcasting guidance content through the voice broadcaster.

[0028] A computer-readable storage medium storing a computer program that, when executed by a processor, performs the steps described above.

[0029] A public health management method, applied to the device described above, the method comprising steps S1 to S7.

[0030] Compared with the prior art, the present invention has the following beneficial effects:

[0031] By integrating core components such as processor, memory, identity authentication device, multi-parameter health sensor, human-computer interaction device and data communication interface, this public health management device constructs an efficient and intelligent health management platform; the computer program preset in the memory can guide the processor to accurately execute various health management tasks, realizing full-process automation from user identification to risk level assessment, which greatly improves the efficiency and accuracy of health management.

[0032] This device uses an identity authentication device to quickly obtain the user's identity and then queries the risk profile database to dynamically adjust the detection parameters of the multi-parameter health sensors. This risk-level-based personalized detection strategy ensures that high-risk users can receive more comprehensive and accurate health monitoring, effectively improving the ability to prevent and detect diseases early, and building a solid line of defense for public health security.

[0033] By analyzing real-time health data anomalies and calculating risk levels, the device can generate a comprehensive risk score and trigger corresponding response commands. These commands are displayed intuitively to users through a human-computer interaction device, while simultaneously sending alerts to the management platform, achieving timely warnings and effective interventions for health risks. This innovative design not only enhances users' health management awareness but also improves the emergency response speed of public health departments, jointly promoting a comprehensive improvement in public health standards. Attached Figure Description

[0034] Figure 1 This is a diagram of the architecture of the present invention;

[0035] Figure 2 This is a schematic diagram of the program execution flow of the present invention. Detailed Implementation

[0036] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0037] Example 1: As Figure 1 As shown, a public health management device includes: a processor, a memory, and an identity authentication device, a multi-parameter health sensor, a human-computer interaction device, and a data communication interface, all of which are communicatively connected to the processor.

[0038] Among them, the processor is the core computing and control unit of the entire device, responsible for coordinating the work of various components;

[0039] Memory is used to store various types of data and computer programs required for the operation of a device.

[0040] The identity authentication device communicates with the processor to accurately obtain user identity information, ensuring the security and relevance of device use;

[0041] The multi-parameter health sensor, also connected to the processor, can collect various types of health data from the user.

[0042] Human-computer interaction devices facilitate information exchange between devices and users, displaying relevant prompts, results, etc. to users;

[0043] The data communication interface enables data transmission between the device and the management platform for remote monitoring and management.

[0044] like Figure 2As shown, the memory stores a computer program, which, when executed by the processor, performs the following steps:

[0045] S1: Obtain the user's identity identifier through the identity authentication device;

[0046] In this step, the identity authentication device begins to work, using specific identification technologies such as fingerprint recognition, facial recognition, or card swiping to obtain the user's identity information.

[0047] S2: Based on the user's identity identifier, query the risk profile database stored in the memory to obtain the corresponding user's preset risk level;

[0048] In step S1, the processor queries a risk profile database pre-stored in memory based on the user's identity identifier obtained in step S1. The risk profile database stores a large amount of users' historical health data, medical history, lifestyle habits, and other information. This data is used to comprehensively assess the preset risk level for each user.

[0049] For example, users with a history of serious chronic diseases and unhealthy lifestyles may have a higher preset risk level; while users with good health and lifestyles may have a relatively lower preset risk level.

[0050] S3: Based on the preset risk level, dynamically configure the detection parameters of the multi-parameter health sensor. If the preset risk level is high risk, more comprehensive detection items or higher detection accuracy will be enabled.

[0051] The processor dynamically configures the detection parameters of the multi-parameter health sensor based on the preset risk level obtained in step S2; if the preset risk level is high risk, the device will enable more comprehensive detection items.

[0052] For example, in addition to routine body temperature and blood pressure checks, additional tests such as electrocardiogram and blood oxygen saturation may be added; or the accuracy of the tests may be improved, such as increasing the accuracy of body temperature detection from ±0.5℃ to ±0.2℃. This ensures that high-risk users receive more detailed and accurate health monitoring and can promptly detect potential health problems. For example, the elderly often suffer from multiple chronic diseases and belong to a high-risk group. By dynamically configuring the test parameters, their health status can be monitored more comprehensively.

[0053] S4: Control the multi-parameter health sensor to collect the user's real-time health data according to the configured detection parameters;

[0054] In step S4, the processor controls the multi-parameter health sensor to operate according to the detection parameters configured in step S3, collecting the user's real-time health data. The multi-parameter health sensor monitors multiple health indicators simultaneously.

[0055] For example, body temperature sensors measure a user's body temperature in real time, blood pressure sensors measure blood pressure, and heart rate sensors monitor heart rate; these sensors transmit the collected data to the processor in real time, providing accurate data support for subsequent health analysis.

[0056] S5: Perform anomaly analysis on real-time health data, and integrate the analysis results with preset risk levels to generate a comprehensive risk score;

[0057] The processor performs anomaly analysis on the real-time health data collected in step S4. It uses preset algorithms and models to assess various health indicators, checking for any deviations from normal ranges. Simultaneously, it integrates the analysis results with the preset risk level obtained in step S2 for further calculation.

[0058] For example, a user with a preset risk level of medium risk might have a slightly elevated body temperature. After considering both the initial risk level and the actual risk, a comprehensive risk score is generated. This score provides a more complete and accurate reflection of the user's current health risk status.

[0059] S6: Based on the comprehensive risk score, query the predefined response strategy library to determine the corresponding response instructions;

[0060] The processor queries a predefined response strategy library based on the comprehensive risk score generated in step S5. The response strategy library stores response instructions corresponding to different comprehensive risk scores, covering various situations from simple health reminders to emergency medical assistance.

[0061] For example, when the overall risk score is low, the response instruction might simply remind the user to rest and eat a healthy diet; while when the overall risk score is high, the response instruction might immediately contact the emergency center to notify relevant medical personnel. In this way, the device can respond appropriately based on the user's actual health risk situation.

[0062] S7: Executes response commands, outputs warning information through the human-machine interaction device, and sends alarms to the management platform through the data communication interface;

[0063] The processor executes response instructions determined from the response policy library.

[0064] On the one hand, warning information is output to users through human-computer interaction devices, including displays and voice broadcasters. The display shows personalized health tips, such as "Your blood pressure is high, please pay attention to reducing your salt intake"; the voice broadcaster simultaneously broadcasts guidance content, such as "Please remain quiet and wait for further examination by medical staff".

[0065] On the other hand, alerts are sent to a management platform via a data communication interface. This management platform could be a hospital monitoring center, a community health management organization, or similar entity. This allows relevant personnel to promptly understand the user's health status and take appropriate measures, thus achieving effective public health management.

[0066] As can be seen from the above, this device integrates components such as a processor, memory, identity authentication device, multi-parameter health sensor human-computer interaction device, and data communication interface; its memory stores a computer program, which can be executed by the processor to realize a series of health management functions;

[0067] The device first obtains the user's identity identifier through an identity authentication device, and then queries the risk database to determine the user's preset risk level. Based on this level, the device dynamically configures the detection parameters of the multi-parameter health sensors to ensure that high-risk users can receive more comprehensive or high-precision testing. Subsequently, the device controls the sensors to collect the user's real-time health data, performs anomaly analysis, and generates a comprehensive risk score by combining the preset risk level.

[0068] Based on the comprehensive risk score, the device will query the response strategy library to determine the corresponding response instructions, output warning information to the user through the human-machine interaction device, and send alarms to the management platform through the data communication interface, thereby achieving effective management of public health.

[0069] Example 2: This example is basically the same as the previous example, except that in step S7, the response instruction also includes an instruction to control the physical actuator that is communicatively connected to the device;

[0070] The physical actuator includes at least one of the following: an access control gate, a guide indicator light, and an environmental disinfection device;

[0071] Among them, access control turnstiles can be used to control the entry and exit of personnel. When a high-risk user is detected, the access control turnstile can be closed by command to prevent them from entering a specific area and prevent the spread of potential health risks.

[0072] Guidance indicator lights can provide clear directions for people to move around. For example, when an abnormal situation is detected, different colored lights can guide users to the isolation area or safe passage.

[0073] Environmental disinfection devices can automatically start disinfecting the surrounding environment after detecting that a user with health risks has passed by, reducing the possibility of germ transmission.

[0074] Taking a hospital outpatient hall as an example, if a suspected patient with an infectious disease is detected, the access control gate can restrict their movement, guide indicator lights to a special isolation area, and at the same time, environmental disinfection devices disinfect the relevant areas.

[0075] Specifically, when the computer program is executed by the processor, it further performs the following steps:

[0076] S8: Receive feedback signals from the physical actuator. The feedback signals are used to indicate the success or failure status of instruction execution.

[0077] After issuing instructions to control the physical execution mechanism, the processor continuously receives feedback signals from the physical execution mechanism. These feedback signals indicate the success or failure status of the instruction execution.

[0078] For example, when the processor issues a command to close the access control gate, the gate will send a signal informing the processor whether the command was successfully executed. If the gate fails to close due to a malfunction, the feedback signal will indicate execution failure. Similarly, the same applies to guide indicator lights and environmental disinfection devices. Through this feedback mechanism, the equipment can promptly understand the working status of the physical actuators, ensuring the effective implementation of various measures.

[0079] S9: If no success feedback signal is received within the preset time, the alarm level will be upgraded through the data communication interface and manual intervention will be notified.

[0080] The processor monitors the received feedback signals. If no success feedback signal is received within a preset time, it means that the physical actuator may have malfunctioned or failed to execute the instructions as expected. In this case, the processor will escalate the alarm level via the data communication interface and notify manual intervention.

[0081] For example, a system that initially sends a general alert to the management platform will escalate to an emergency alert if no successful feedback signal is received. This will simultaneously notify relevant maintenance or management personnel to immediately address the issue on-site. This allows for timely resolution of problems with the physical actuators, ensuring the continuous and effective operation of public health management equipment and preventing equipment malfunctions from impacting public health safety management.

[0082] As can be seen from the above, in step S7 of executing the response command, the device can not only output warning information and send alarms to the management platform through the human-machine interaction device, but also adds the function of controlling the physical actuators that are connected to the device for communication.

[0083] Physical actuators include, but are not limited to, access control gates, guidance indicator lights, and environmental disinfection devices. They can perform corresponding physical operations according to the instructions issued by the equipment, such as controlling personnel entry and exit, indicating the direction of movement, or carrying out environmental disinfection, thereby further enhancing the effectiveness and flexibility of public health management.

[0084] In addition, this device is also capable of receiving feedback signals from physical actuators, which are used to indicate the success or failure of instruction execution. If no successful feedback signal is received within a preset time, the device will automatically escalate the alarm level and notify human intervention to ensure the effective implementation and timely adjustment of public health management measures.

[0085] Example 3: This example is basically the same as the previous example, except that the identity authentication device is at least one of the following: a face recognition camera, a QR code scanner, or an RFID reader.

[0086] Specifically, the multi-parameter health sensor includes at least one of the following: a non-contact infrared body temperature sensor, a microphone array, and an image sensor.

[0087] Specifically, in step S5, anomaly analysis is performed on the real-time health data, which involves inputting the real-time health data into a pre-trained machine learning model for calculation and outputting a health anomaly probability value.

[0088] Specifically, the method of fusion calculation in step S5 is as follows:

[0089] The preset risk level corresponds to a weighting coefficient. The probability value of the health abnormality corresponds to a weighting coefficient. ;

[0090] .

[0091] Specifically, the human-computer interaction device includes a display and a voice broadcaster;

[0092] The output of warning information in step S7 includes displaying personalized health tips on the display and broadcasting guidance content through the voice broadcaster.

[0093] As can be seen from the above, the identity authentication device of this equipment can be selected from at least one of a face recognition camera, a QR code scanner, or an RFID reader to adapt to the identity verification needs in different scenarios. The multi-parameter health sensors include non-contact infrared body temperature sensors, microphone arrays, and image sensors, which can comprehensively collect the user's health data.

[0094] In terms of data processing, this embodiment introduces a pre-trained machine learning model to perform anomaly analysis on real-time health data and output a health anomaly probability value, thereby improving the accuracy and efficiency of anomaly detection. Simultaneously, in the fusion calculation stage, both the preset risk level and the health anomaly probability value are assigned corresponding weight coefficients to ensure the scientific validity and rationality of the comprehensive risk score.

[0095] Regarding the human-computer interaction device, this embodiment employs a combination of a display and a voice announcer. This not only displays personalized health tips on the display but also broadcasts guidance content via the voice announcer, providing users with a more intuitive and convenient interactive experience. When executing response commands, the device can fully utilize these interactive devices to promptly and effectively convey warning information to the user.

[0096] The embodiments of the present invention are given for the purposes of illustration and description. Although embodiments of the present invention have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present invention. Any changes, modifications, substitutions and variations made by those skilled in the art to the above embodiments within the scope of the present invention should be included within the protection scope of the present invention.

Claims

1. A public health management device, characterized by, The device comprises a processor, a memory, and an identity authentication device, a multi-parameter health sensor, a human-computer interaction device, and a data communication interface connected in communication with the processor, respectively. The memory stores a computer program, and the computer program, when executed by the processor, implements the following steps: S1: obtaining a user identity through the identity authentication device; S2: querying a preset risk profile library pre-stored in the memory according to the user identity to obtain a preset risk level of the user; S3: dynamically configuring detection parameters of the multi-parameter health sensor based on the preset risk level, wherein if the preset risk level is high risk, more comprehensive detection items or higher detection accuracy are enabled; S4: controlling the multi-parameter health sensor to collect real-time health data of the user according to the configured detection parameters; S5: performing abnormal analysis on the real-time health data and fusing the analysis result with the preset risk level to generate a comprehensive risk score; S6: querying a predefined response strategy library according to the comprehensive risk score to determine a corresponding response instruction; S7: executing the response instruction, outputting warning information through the human-computer interaction device, and sending an alarm to a management platform through the data communication interface. In step S7, the response instruction further comprises an instruction for controlling a physical execution mechanism connected in communication with the device; 2. The public health management device according to claim 1, wherein The physical execution mechanism comprises at least one of the following: an access control gate, a guide indicator light, and an environmental disinfection device. The computer program, when executed by the processor, further implements the following steps:

3. The public health management device of claim 2, wherein, S8: receiving a feedback signal from the physical execution mechanism, the feedback signal being used to indicate a success or failure state of the instruction execution; S9: if no feedback signal indicating success is received within a preset time, upgrading an alarm level through the data communication interface and notifying manual intervention. The identity authentication device is at least one of the following: a face recognition camera, a two-dimensional code scanner, and a radio frequency identification reader.

4. The public health management device of claim 1, wherein, The multi-parameter health sensor comprises at least one of the following: a non-contact infrared body temperature sensor, a microphone array, and an image sensor.

5. The public health management device of claim 1, wherein, In step S5, the real-time health data is input into a pre-trained machine learning model for calculation to output a health abnormality probability value.

6. The public health management device of claim 1, wherein, In step S5, the fusion calculation is performed in the following manner:

7. The public health management device of claim 6, wherein, The human-computer interaction device comprises a display and a voice broadcaster; The preset risk level corresponds to a weight coefficient The health anomaly probability value corresponds to a weight coefficient ; 。 8. The public health management device of claim 1, wherein, In step S7, the output of the warning information comprises displaying a personalized health prompt on the display and broadcasting guide content through the voice broadcaster. The computer program, when executed by the processor, implements the steps of any one of claims 1 to 8.

9. A computer readable storage medium storing a computer program, characterized in that, The method is applied to the device of any one of claims 1 to 8 and comprises steps S1 to S7.

10. A public health management method characterized by, ​

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