Remote internet big data smart medical system based on block chain

Abstract

The invention discloses a block chain-based remote internet big data intelligent medical system, which comprises a rapid registration module, a patient picture analysis module and a remote control terminal, and is characterized in that the rapid registration module is used for acquiring medical health information registered when a patient sees a doctor; the patient picture analysis module is used for analyzing a doctor seeing process picture of a patient and judging whether a help seeking behavior exists or not, and the remote control terminal is used for remotely checking the concerned patient and helping the patient to prompt a nurse to accept help seeking according to an analysis result of the patient picture analysis module. The rapid registration module is in network connection with the patient picture analysis module, the patient picture analysis module is in network connection with the remote control terminal, and the rapid registration module comprises a monitoring acquisition module, an information block creation module and a space display module.

Description

Technical Field

[0001] The present invention relates to the technical field of intelligent healthcare, and specifically to a remote Internet big data intelligent healthcare system based on blockchain. Background Art

[0002] With the progress of technology, the improvement of living standards, and the intensification of social aging, the human demand for medical health and elderly care assistance is increasing day by day. According to statistics and predictions, the global expenditure on intelligent healthcare services will increase rapidly. Intelligent healthcare is an important part of smart cities, which comprehensively applies technologies such as the Internet of Things, big data, cloud computing, and artificial intelligence to integrate medical infrastructure and IT infrastructure through data transmission.

[0003] Currently, there are more and more patients in hospitals, and it is necessary to design a remote Internet big data intelligent healthcare system based on blockchain with strong practicality and high convenience. Summary of the Invention

[0004] The purpose of the present invention is to provide a remote Internet big data intelligent healthcare system based on blockchain to solve the problems raised in the above background art.

[0005] To solve the above technical problems, the present invention provides the following technical solution: A remote Internet big data intelligent healthcare system based on blockchain, including a quick registration module, a patient picture analysis module, and a remote control terminal. The quick registration module is used to obtain the medical health information registered by the patient when seeking medical treatment. The patient picture analysis module is used to analyze the picture of the patient's medical treatment process and determine whether there is a help-seeking behavior. The remote control terminal is used to remotely view and take care of the patient, and help the patient prompt the nurse to accept the help according to the analysis result of the patient picture analysis module. The quick registration module is network-connected to the patient picture analysis module, and the patient picture analysis module is network-connected to the remote control terminal.

[0006] According to the above technical solution, the quick registration module includes a monitoring and acquisition module, an information block creation module, and a space display module. The monitoring and acquisition module is used to collect the monitoring picture information deployed in the hospital. The information block creation module is used to obtain the medical information registered by the patient when seeking medical treatment and create an information block to store it in the blockchain service network. The space display module is network-connected to both the monitoring and acquisition module and the information block creation module. The space display module is used to quickly obtain and display the patient information in space in the hospital public area by using the monitoring picture and the information block.

[0007] According to the above technical solution, the patient video analysis module includes a data transmission module, an image recognition module, a feature analysis module, and a logic judgment module. The data transmission module is used to provide a data transmission channel. The image recognition module is used to recognize the monitoring video images. The feature analysis module is used to infer and analyze the feature items in the recognized images. The logic judgment module is used to perform logical judgment on the patient videos and output the judgment results.

[0008] According to the above technical solution, the remote control terminal includes a monitoring video priority display module and an alarm prompt module. The monitoring video priority display module is used to control the display priorities of the monitoring videos on the remote monitoring video display end. The alarm prompt module is used to provide an alarm prompt for the monitoring videos corresponding to the patients judged to have help-seeking behaviors, for the management staff to view and dispatch personnel.

[0009] According to the above technical solution, the operation method of the blockchain-based remote Internet big data intelligent medical system includes the following steps:

[0010] Step S1: Deploy monitoring modules in the public areas of the hospital based on remote Internet big data technology, collect the monitoring videos of all public areas of the hospital, and transmit them to the system;

[0011] Step S2: Obtain the medical health information registered by the patient during medical treatment and perform rapid registration of medical information;

[0012] Step S3: Further identify all the monitoring video information and start analyzing and judging whether the patient has help-seeking behaviors;

[0013] Step S4: According to the analysis results, remotely control the monitoring videos to schedule the monitoring videos that meet the judgment conditions to be displayed with high priority, and at the same time give a remote alarm to remind the nearby medical staff to go there.

[0014] According to the above technical solution, step S2 further includes the following steps:

[0015] Step S21: During the patient's hospital visit, establish a patient personal information block, and store the patient-related information entered by the hospital end during the visit and the monitoring videos during the visit in the patient personal information block;

[0016] Step S22: Establish a public area model of the hospital. After the patient's monitoring module captures the patient's monitoring video, identify and track the monitoring video image through the data transmission module;

[0017] Step S23: In the videos captured by all the camera modules, continuously update and identify the location of the camera module corresponding to the currently tracked patient's captured video, combine it with the public area model of the hospital, and add the corresponding patient's personal information block to the corresponding model at this location;

[0018] Step S24: Repeat step S23 to match and display the personal information blocks of all patients in the hospital in the real-time positions in the hospital public area model.

[0019] Step S25: At the same time, the positions of medical staff are updated and displayed in real time in the hospital public area model. When a medical staff approaches a certain patient, the medical staff can quickly obtain one or more personal information blocks of the patients close to his / her position through the system's quick registration module, and quickly authorize the retrieval of the relevant information stored in the personal information blocks of the corresponding patients.

[0020] According to the above technical solution, step S3 further includes the following steps:

[0021] Step S31: Identify the monitoring screen and respectively identify the head and limb features of the patients in the screen.

[0022] Step S32: Track and identify the patient's screen, retrieve the personal information block of the corresponding patient, and read the disease classification of the patient. The disease classification is divided into three categories by medical staff according to the patient's condition and age during the consultation, including routine symptoms, mild cases, and severe cases.

[0023] The feature analysis module obtains the identified head and limb features of the patient, conducts dynamic signal statistics on the head and limb features. When the head and limb features change dynamically, the feature analysis module triggers an electrical signal, and the recognition period is 1 second. If continuous dynamic changes occur, continuous electrical signals are triggered.

[0024] Step S34: Respectively establish a trigger signal statistical chart of the head and limb features on the time axis, and make a logical judgment on whether the patient has a help-seeking behavior according to the statistical chart.

[0025] According to the above technical solution, step S34 further includes the following steps:

[0026] Step S341: When the patient belongs to the severe case type, when there is one captured trigger electrical signal in the trigger signal statistical chart of the head and limb features, it is determined that the patient has a help-seeking behavior.

[0027] Step S342: When the patient belongs to the mild case type, when any one of the trigger signal statistical charts of the head or limb features captures 10 or more trigger electrical signals within a continuous 1-minute period, it is determined that the patient has a help-seeking behavior.

[0028] Step S343: When the patient belongs to the conventional symptom type, when the chart in the head body feature trigger signal statistical chart captures 10 or more trigger electrical signals within a continuous 1-minute period, and at the same time, when the chart in the limb feature trigger signal statistical chart captures less than 20 trigger electrical signals within a continuous 1-minute period, it is determined that the patient has a help-seeking behavior.

[0029] Compared with the prior art, the beneficial effects achieved by the present invention are as follows: In the present invention, by providing a quick registration module, a patient picture analysis module, and a remote control terminal, monitoring modules can be deployed in the public areas of the hospital through remote Internet big data technology, remotely view and inspect the pictures of all patients during the medical treatment period, further analyze the pictures, deeply analyze the dynamic feature status of the heads and limbs of the patients, and at the same time retrieve the patient's condition to achieve more accurate logical judgment. Thus, patients with help-seeking behaviors can be accurately analyzed, and hospital staff nearby can be notified to provide help, effectively solving the problems of chaos in the hospital during the medical run, the disorderly busyness of medical staff, and the failure to timely solve the needs of patients, achieving the effects of strong practicability and high convenience. BRIEF DESCRIPTION OF THE DRAWINGS

[0030] The drawings are used to provide a further understanding of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention and do not constitute a limitation to the present invention. In the drawings:

[0031] Figure 1 It is a schematic diagram of the system module composition of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0032] The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0033] Please refer to Figure 1 , the present invention provides a technical solution: A remote Internet big data intelligent medical system based on blockchain, including a quick registration module, a patient picture analysis module, and a remote control terminal. The quick registration module is used to obtain the medical health information registered when the patient seeks medical treatment. The patient picture analysis module is used to analyze the pictures of the patient's medical treatment process and determine whether there is a help-seeking behavior. The remote control terminal is used to remotely view and care for the patient and help the patient prompt the nurse to accept the help according to the analysis result of the patient picture analysis module. The quick registration module is network-connected to the patient picture analysis module, and the patient picture analysis module is network-connected to the remote control terminal.

[0034] The quick registration module includes a monitoring and acquisition module, an information block creation module, and a spatial display module. The monitoring and acquisition module is used to collect the monitoring screen information deployed in the hospital. The information block creation module is used by the user to obtain the medical information registered when the patient seeks medical treatment and create an information block to store it in the blockchain service network. The spatial display module is network-connected to the monitoring and acquisition module and the information block creation module respectively. The spatial display module is used to quickly obtain and display the patient information in space in the hospital public area by using the monitoring screen and the information block.

[0035] The patient screen analysis module includes a data transmission module, an image recognition module, a feature analysis module, and a logical judgment module. The data transmission module is used to provide a data transmission channel. The image recognition module is used to recognize the images of the monitoring screen. The feature analysis module is used to infer and analyze the feature items in the recognized screen. The logical judgment module is used to make a logical judgment on the patient screen and output a judgment result.

[0036] The remote control terminal includes a monitoring screen priority display module and an alarm prompt module. The monitoring screen priority display module is used to control the display priority of each monitoring screen of the remote monitoring screen display terminal. The alarm prompt module is used to provide an alarm prompt for the monitoring screen corresponding to the patient judged to have a help-seeking behavior for the management personnel to view and dispatch personnel.

[0037] The operation method of the blockchain-based remote Internet big data intelligent medical system includes the following steps:

[0038] Step S1: Deploy monitoring modules in the hospital public area based on remote Internet big data technology, collect the monitoring screens of all hospital public areas and transmit them to the system;

[0039] Step S2: Obtain the medical and health information registered when the patient seeks medical treatment and perform quick registration of medical information;

[0040] Step S3: Further identify all monitoring screen information and start analyzing and judging whether the patient has a help-seeking behavior;

[0041] Step S4: According to the analysis result, remotely control the monitoring screen to schedule the monitoring screens that meet the judgment conditions to be displayed with high priority, and at the same time give a remote alarm to remind the nearby medical staff to go there.

[0042] Step S2 further includes the following steps:

[0043] Step S21: During the patient's visit to the hospital, create a personal information block for the patient, and merge the patient-related information entered by the hospital side during the visit and the monitoring screens during the visit and store them in the patient's personal information block;

[0044] Step S22: Establish a hospital public area model. After the monitoring module of the patient captures the patient monitoring image, the monitoring image is recognized and tracked through the data transmission module;

[0045] Step S23: In the images captured by all camera modules, continuously update and identify the location of the camera module corresponding to the currently tracked patient's captured image. Combine it with the hospital public area model, and add a personal information block of the corresponding patient to the model at this location;

[0046] Step S24: Repeat Step S23 to match and display the personal information blocks of all patients in the hospital in real-time positions in the hospital public area model;

[0047] Step S25: At the same time, the location of medical staff is updated and displayed in real-time in the hospital public area model. When a medical staff approaches a certain patient, the medical staff can quickly obtain one or more personal information blocks of the patients close to their location through the system's quick registration module, and quickly authorize the retrieval of the relevant information stored in the personal information blocks of the corresponding patients; Through the above steps, the spatial display module can be used to cooperate with the personal information blocks of all patients in the blockchain service network to achieve spatial information display. Then, when medical staff go to the side of the patients who need to be registered or treated, there is no need to ask and check the patient information one by one. Therefore, in the case of patients in non-fixed positions such as aisles and corners during the medical rush, there is no need to rely on bed numbers and other identifiers to quickly find the target, and it can reduce the communication between doctors and patients, avoid cross-infection, achieve the function of quick registration, and achieve the effect of high efficiency and safety.

[0048] Step S3 further includes the following steps:

[0049] Step S31: Recognize the monitoring image and respectively recognize the head and limb features of the patients in the image;

[0050] Step S32: Track and recognize the patient image, retrieve the personal information block of the corresponding patient, and read the disease classification of the patient. The disease classification is divided into three categories by medical staff according to the patient's condition and age during the visit, including routine symptoms, mild cases, and severe cases;

[0051] Step S33: The feature analysis module obtains the recognized head and limb features of the patient, conducts dynamic signal statistics on the head and limb features. When the head and limb features change dynamically, the feature analysis module triggers an electrical signal. The recognition period is 1 second. If continuous dynamic changes occur, continuous electrical signals will be triggered;

[0052] Step S34: Respectively establish a trigger signal statistical chart of the head and limb features on the time axis. According to the statistical chart, conduct a logical judgment on whether the patient has a help-seeking behavior.

[0053] Step S34 further includes the following steps:

[0054] Step S341: When the patient belongs to the severe type, when there is a captured triggered electrical signal in the statistical chart of head and limb feature trigger signals, it is determined that the patient has a help-seeking behavior;

[0055] Step S342: When the patient belongs to the mild type, when any one of the statistical charts in the statistical chart of head or limb feature trigger signals captures 10 or more triggered electrical signals within a continuous 1-minute period, it is determined that the patient has a help-seeking behavior;

[0056] Step S343: When the patient belongs to the routine symptom type, when the statistical chart in the statistical chart of head feature trigger signals captures 10 or more triggered electrical signals within a continuous 1-minute period, and at the same time, when the statistical chart in the statistical chart of limb feature trigger signals captures less than 20 triggered electrical signals within a continuous 1-minute period, it is determined that the patient has a help-seeking behavior; When patients with routine symptoms seek help from medical staff, they are generally in a state of looking around in place, repeatedly observing the medical staff around them and seeking help. Through the logical judgment of this step, it conforms to the actual limb behavior scenario, can accurately capture patients with help-seeking behavior, and through the judgment of dynamically restricting limb features, effectively reduces the situation where patients with routine symptoms move around by themselves or go to the front desk to seek help from hospital staff, so that the judgment of non-actual needs can be reduced according to the severity of the user's illness, achieving a strong practical effect;

[0057] Through the above steps, monitoring modules can be deployed in the public areas of the hospital through remote Internet big data technology, remotely view and inspect the pictures of all patients during the treatment period, further analyze the pictures, deeply analyze the dynamic feature status of the heads and limbs of the patients, and at the same time retrieve the patients' conditions to achieve more accurate logical judgment, so that patients with help-seeking behavior can be accurately analyzed, and the nearby hospital staff can be notified to provide help, effectively solving the problems of chaos in the hospital during the medical crush, the medical staff being busy without a clue, and the patients' needs not being solved in time, achieving the effects of strong practicality and high convenience.

[0058] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the term "comprising", "including" or any other variant thereof is intended to cover non-exclusive inclusion, so that a process, method, article or device comprising a series of elements not only includes those elements, but also includes other elements not expressly listed, or elements inherent to such process, method, article or device.

[0059] Finally, it should be noted that the above are only preferred embodiments of the present invention and are not used to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements for some of the technical features. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included within the protection scope of the present invention.

Claims

1. A remote Internet big data intelligent medical system based on blockchain, comprising a quick registration module, a patient picture analysis module and a remote control terminal, characterized in that: The quick registration module is used to obtain the medical and health information registered when a patient seeks medical treatment. The patient scene analysis module is used to analyze the scene of the patient's medical treatment process and determine whether there is a help-seeking behavior. The remote control terminal is used to remotely view and take care of the patient, and according to the analysis result of the patient scene analysis module, help the patient prompt the nurse to accept the help. The quick registration module is network-connected to the patient scene analysis module, and the patient scene analysis module is network-connected to the remote control terminal.

2. The remote Internet big data intelligent medical system based on blockchain according to claim 1, wherein: The quick registration module includes a monitoring and acquisition module, an information block creation module, and a space display module. The monitoring and acquisition module is used to collect the monitoring screen information deployed in the hospital. The information block creation module is used to obtain the medical information registered when a patient seeks medical treatment and create an information block to store it in the blockchain service network. The space display module is network-connected to both the monitoring and acquisition module and the information block creation module. The space display module is used to quickly obtain and display the patient information in space in the hospital public area by using the monitoring screen and the information block.

3. The remote Internet big data intelligent medical system based on blockchain according to claim 2, characterized in that: The patient scene analysis module includes a data transmission module, an image recognition module, a feature analysis module, and a logical judgment module. The data transmission module is used to provide a data transmission channel. The image recognition module is used to recognize the images of the monitoring screen. The feature analysis module is used to infer and analyze the feature items in the recognized screen. The logical judgment module is used to perform logical judgment on the patient scene and output a judgment result.

4. The blockchain-based remote Internet big data intelligent medical system according to claim 3, characterized in that: The remote control terminal includes a monitoring screen priority display module and an alarm prompt module. The monitoring screen priority display module is used to control the display priority of each monitoring screen of the remote monitoring screen display terminal. The alarm prompt module is used to provide an alarm prompt for the monitoring screen corresponding to the patient judged to have a help-seeking behavior for the management personnel to view and dispatch personnel.

5. The remote Internet big data intelligent medical system based on blockchain according to claim 4, characterized in that: The operation method of the blockchain-based remote Internet big data intelligent medical system includes the following steps: Step S1: Based on the remote Internet big data technology, deploy monitoring modules in the hospital public area, collect the monitoring screens of all hospital public areas and transmit them to the system; Step S2: Obtain the medical and health information registered when a patient seeks medical treatment and perform quick registration of medical information; Step S3: Further identify all the monitoring screen information and start to analyze and judge whether the patient has a help-seeking behavior; Step S4: According to the analysis result, remotely control the monitoring screen to schedule the monitoring screens that meet the judgment conditions to be displayed with high priority, and at the same time give a remote alarm to remind the nearby medical staff to go there.

6. The blockchain-based remote Internet big data intelligent medical system according to claim 5, characterized in that: The step S2 further includes the following steps: Step S21: During the patient's visit to the hospital, establish a personal information block for the patient, and merge the patient-related information entered by the hospital side during the visit and the monitoring screen during the visit and store them in the patient's personal information block; Step S22: Establish a hospital public area model. After the patient's monitoring module captures the patient's monitoring screen, identify and track the monitoring screen image through the data transmission module; Step S23: In the images captured by all camera modules, continuously update the location of the camera module corresponding to the currently tracked patient's captured image, combine it with the hospital public area model, and add a personal information block of the corresponding patient to the model at that location; Step S24: Repeat Step S23 to match and display the real-time locations of the personal information blocks of all patients in the hospital in the hospital public area model; Step S25: At the same time, the location of medical staff is updated and displayed in real time in the hospital public area model. When a medical staff approaches a certain patient, the medical staff can quickly obtain the personal information blocks of one or more patients close to their location through the system's quick registration module, and quickly authorize the retrieval of the relevant information stored in the personal information blocks of the corresponding patients.

7. The blockchain-based remote Internet big data intelligent medical system according to claim 6, characterized in that: Step S3 further includes the following steps: Step S31: Identify the monitoring image and respectively identify the head and limb features of the patients in the image; Step S32: Track and identify the patient's image, retrieve the personal information block of the corresponding patient, and read the disease classification of the patient. The disease classification is divided into three categories by medical staff at the time of diagnosis according to the patient's condition and age, including routine symptoms, mild cases, and severe cases; Step S33: The feature analysis module obtains the identified head and limb features of the patient, performs dynamic signal statistics on the head and limb features. When the head and limb features change dynamically, the feature analysis module triggers an electrical signal, and the recognition period is 1 second. If continuous dynamic changes occur, continuous electrical signals are triggered; Step S34: Establish trigger signal statistical charts of the head and limb features on the time axis respectively, and make a logical judgment on whether the patient has a help-seeking behavior according to the statistical charts.

8. The remote Internet big data intelligent medical system based on blockchain according to claim 7, wherein: Step S34 further includes the following steps: Step S341: When the patient belongs to the severe case type, when there is one captured electrical signal trigger in the trigger signal statistical chart of the head and limb features, it is determined that the patient has a help-seeking behavior; Step S342: When the patient belongs to the mild case type, when any one of the trigger signal statistical charts of the head or limb features captures 10 or more electrical signals within a continuous 1-minute period, it is determined that the patient has a help-seeking behavior; Step S343: When the patient belongs to the routine symptom type, when the trigger signal statistical chart of the head features captures 10 or more electrical signals within a continuous 1-minute period, and at the same time, when the trigger signal statistical chart of the limb features captures less than 20 electrical signals within a continuous 1-minute period, it is determined that the patient has a help-seeking behavior.

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