CN114640696A - Oral cavity data information monitoring method capable of realizing remote data interaction and instant analysis - Google Patents

Oral cavity data information monitoring method capable of realizing remote data interaction and instant analysis Download PDF

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CN114640696A
CN114640696A CN202210541356.0A CN202210541356A CN114640696A CN 114640696 A CN114640696 A CN 114640696A CN 202210541356 A CN202210541356 A CN 202210541356A CN 114640696 A CN114640696 A CN 114640696A
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data
patient
oral cavity
data information
block chain
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CN114640696B (en
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汪伟明
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Xiangya Hospital of Central South University
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    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L67/00—Network arrangements or protocols for supporting network services or applications
    • H04L67/01—Protocols
    • H04L67/12—Protocols specially adapted for proprietary or special-purpose networking environments, e.g. medical networks, sensor networks, networks in vehicles or remote metering networks
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B1/00—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor
    • A61B1/24—Instruments for performing medical examinations of the interior of cavities or tubes of the body by visual or photographical inspection, e.g. endoscopes; Illuminating arrangements therefor for the mouth, i.e. stomatoscopes, e.g. with tongue depressors; Instruments for opening or keeping open the mouth
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/0059—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence
    • A61B5/0082—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes
    • A61B5/0088—Measuring for diagnostic purposes; Identification of persons using light, e.g. diagnosis by transillumination, diascopy, fluorescence adapted for particular medical purposes for oral or dental tissue
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61B—DIAGNOSIS; SURGERY; IDENTIFICATION
    • A61B5/00—Measuring for diagnostic purposes; Identification of persons
    • A61B5/45—For evaluating or diagnosing the musculoskeletal system or teeth
    • A61B5/4538—Evaluating a particular part of the muscoloskeletal system or a particular medical condition
    • A61B5/4542—Evaluating the mouth, e.g. the jaw
    • A—HUMAN NECESSITIES
    • A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
    • A61C—DENTISTRY; APPARATUS OR METHODS FOR ORAL OR DENTAL HYGIENE
    • A61C19/00—Dental auxiliary appliances
    • A61C19/04—Measuring instruments specially adapted for dentistry
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06N—COMPUTING ARRANGEMENTS BASED ON SPECIFIC COMPUTATIONAL MODELS
    • G06N7/00—Computing arrangements based on specific mathematical models
    • G06N7/01—Probabilistic graphical models, e.g. probabilistic networks
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T7/00—Image analysis
    • G06T7/0002—Inspection of images, e.g. flaw detection
    • G06T7/0012—Biomedical image inspection
    • 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
    • G16H30/00—ICT specially adapted for the handling or processing of medical images
    • G16H30/20—ICT specially adapted for the handling or processing of medical images for handling medical images, e.g. DICOM, HL7 or PACS
    • 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
    • G16H50/20—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for computer-aided diagnosis, e.g. based on medical expert systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04N—PICTORIAL COMMUNICATION, e.g. TELEVISION
    • H04N7/00—Television systems
    • H04N7/18—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast
    • H04N7/181—Closed-circuit television [CCTV] systems, i.e. systems in which the video signal is not broadcast for receiving images from a plurality of remote sources
    • G—PHYSICS
    • G06—COMPUTING; CALCULATING OR COUNTING
    • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
    • G06T2207/00—Indexing scheme for image analysis or image enhancement
    • G06T2207/30—Subject of image; Context of image processing
    • G06T2207/30004—Biomedical image processing
    • G06T2207/30036—Dental; Teeth

Abstract

The invention discloses an oral cavity data information monitoring method capable of realizing remote data interaction and instant analysis, which comprises the steps of detecting the oral cavity of a patient through an oral cavity detection device, and extracting oral cavity disease information through a probe; the oral disease data information is transmitted to the intelligent terminal through a wireless communication method, so that the interaction of the oral data of the patient with the block chain can be realized, and the receiving and transmitting capacity of the disease data information detected in the oral cavity of the patient is improved. The retrieved patient disease data are transmitted to other block chain terminal equipment through the block chain nodes so as to realize the analysis and transmission of the patient disease data in the block chain nodes; the analysis of the patient disease data is realized through different block chain nodes, the diagnosis and the analysis of the oral disease information are realized through a Bayesian algorithm model, and the data analysis capability and the application capability of the patient disease data are improved.

Description

Oral cavity data information monitoring method capable of realizing remote data interaction and instant analysis
Technical Field
The invention relates to the technical field of oral medical treatment, in particular to an oral data information monitoring method capable of realizing remote data interaction and instant analysis.
Background
The content of oral treatment includes diseases of hard tooth tissue, soft oral mucosa tissue, salivary gland and the like. The oral diseases usually comprise deep caries, pulpitis and periapical inflammation, oral ulcer, oral white plug, lichen planus, xerosis, halitosis, cheilitis, glossitis, angular stomatitis, oral mucositis, burning mouth syndrome, oral leukoplakia, xerostomia and other diseases, and how to realize the monitoring of oral data information, comfort, humanitarian detection and monitoring are realized, and the body benefit of each patient is concerned.
In the conventional technology, a doctor directly monitors the oral data information of a patient through a handheld device, and the method is relatively original, cannot realize remote data monitoring of the oral data information of the patient, and cannot realize information sharing of various relationships such as hospitals, family members and the like.
Disclosure of Invention
Aiming at the defects of the technology, the invention discloses an oral cavity data information monitoring method capable of realizing remote data interaction and instant analysis, which realizes instant acquisition, transmission and diagnosis analysis of oral cavity diagnosis data information in a block chain technology and wireless data communication mode, an instant doctor is not on the spot, and the diagnosed medical data information can be quickly acquired through the oral cavity data information diagnosis result, so that the data interaction capacity of patients, doctors, hospitals and patients is realized.
In order to realize the technical effects, the invention adopts the following technical scheme:
a method for monitoring oral cavity data information capable of realizing remote data interaction and instant analysis comprises the following steps:
step 1, detecting the oral cavity of a patient through an oral cavity detection device, and extracting oral disease information through a probe; the extraction or acquisition of the patient disease data information is realized by manually controlling the data information acquisition, the extraction mode comprises the extraction of gum data information images or the extraction of tooth visual screen image data information, and the extracted oral disease simulation data information is converted into data information;
step 2, transmitting the disease data information of the patient to an intelligent terminal through a wireless communication method, wherein the intelligent terminal is arranged in a data block chain to receive and transmit the disease data information detected in the oral cavity of the patient;
step 3, the retrieved patient disease data are transmitted to other block chain terminal equipment through the block chain nodes so as to realize the analysis and transmission of the patient disease data in the block chain nodes;
and 4, analyzing the disease data of the patient through different block chain nodes, and diagnosing and analyzing the oral disease information through a Bayesian algorithm model.
As a further technical scheme, the oral cavity detection device comprises an MSP430FG4619 processor, a communication module, a data acquisition, power supply module, a sensor interface and block chain nodes, wherein the MSP430FG4619 processor is respectively connected with the communication module, the data acquisition, the power supply module, the sensor interface and the block chain nodes, and the sensor interface and the block chain nodes are in interactive communication with each other.
As a further technical scheme of the invention, data information is transmitted to realize data communication with the intelligent terminal through the embedded board card.
As a further technical scheme of the invention, the embedded board card is also provided with a block chain node.
As a further technical scheme of the invention, the block link point is provided with an interaction method of a consensus mechanism.
As a further technical scheme of the invention, the Bayesian algorithm model is an oral cavity affection factor evaluation method of a fusion comparison matrix model.
As a further technical scheme of the invention, the working method of the Bayesian algorithm model comprises the following steps:
hypothetical portInformation of cavity diseases is recorded asX={X 1,X 2,…,X i …,X n }，X i Expressing the oral cavity disease data information acquired by different nodes of the patient oral cavity data in the block chain structure, recording the random factors influencing the oral cavity data acquisition information of the patient as X, Y and Z, and recording the X, Y and Z oral cavity data acquisition information of the patient not enough to influence the oral cavity data acquisition information of the patient1Patient sex fault log X2Or age X of patient3The influencing factor of the remote transmission of the patient oral cavity data block chain comprises communication fault data information Z1Or block link point setting Z2Y represents the patient without oral disease, a Bayesian algorithm model is constructed, relative entropy is set in the model, and the expression is as follows:
Figure 371021DEST_PATH_IMAGE001
（1）
in the formula (1), the reaction mixture is, p(x)、q(x)respectively representing different probability values of a block link point data set X influencing the remote transmission of the oral cavity data of the patient, representing the relation between p and q as the relative entropy of factors influencing the remote transmission of the oral cavity data of the patient, and constructing a Bayesian algorithm model to ensure that the leakage probability of the oral cavity data of the patient is as follows:
Figure 784730DEST_PATH_IMAGE002
(2)
in the formula (2), whereinB 1 、B 2 、.........B n For various forms of failure probability occurring during the remote transmission of the patient oral data blockchain,Athe influence factor of the patient oral cavity data set through the Bayesian algorithm model by external information is obtained;
suppose again thatX iThe random variable representing the safety of the patient oral data transmission is recorded asX 1，X 2，…,X n Then, then
Figure 370432DEST_PATH_IMAGE003
To take place of
Figure 613325DEST_PATH_IMAGE004
Under the condition of transmitting fault probability, the probability of the oral cavity of the patient with the highest probability is expressed by the formula:
Figure 917268DEST_PATH_IMAGE005
（3）
in the formula (3), the Bayesian data model is set to different nodes in the block chain topological structure, so that the block chain remote transmission safety analysis of the patient oral cavity data is calculated, the condition probability or the posterior probability in the patient oral cavity data information is calculated, and the evaluation of the maximum probability is output.
As a further technical scheme of the invention, the method for realizing diagnosis by the estimation algorithm model comprises the following steps:
(a) determining the type of oral diseases of a patient, setting different disease types and data transmission safety indexes,
(b) according to the loopholes with different information transmission grades, different loophole judgment standards are formulated;
(c) various node data information remotely transmitted by the oral cavity data of the patient is used for refining a vulnerability decision standard from A to k through constructing an evaluation algorithm; expressed by the following formula:
Figure 5441DEST_PATH_IMAGE006
（4）
(d) then, each criterion w = (w) in the hierarchical structure is obtained from the equation1，w2，…，wk) The weight vector of (a), as shown in equation (5);
Figure 711229DEST_PATH_IMAGE007
（5）
(e) the consistency is checked according to the final consistency ratio CR, and expressed by formula (6), there are:
Figure 859444DEST_PATH_IMAGE008
（6）
Figure 650683DEST_PATH_IMAGE009
（7）
in the formula (7), w represents the characteristic value of the patient oral cavity data transmission leak event in the matrix A,
Figure 542547DEST_PATH_IMAGE010
represents a vulnerability decision criterion eigenvalue, λmaxAnd when CR is more than or equal to 0.1, the patient oral cavity data transmission security vulnerability data information does not conform to the receiving and judging matrix condition, and no hole leakage exists in the patient oral cavity data transmission process.
The invention has the following positive beneficial effects:
detecting the oral cavity of a patient through an oral cavity detection device, and extracting oral disease information through a probe; the patient disease data information is transmitted to the intelligent terminal through the intra-oral disease data information by a wireless communication method, so that the interaction of the block chain patient oral data can be realized, and the receiving and transmitting capacity of the disease data information detected in the oral cavity of the patient is improved. The retrieved patient disease data are transmitted to other block chain terminal equipment through the block chain nodes so as to realize the analysis and transmission of the patient disease data in the block chain nodes; the analysis of the patient disease data is realized through different block chain nodes, the diagnosis and the analysis of the oral disease information are realized through a Bayesian algorithm model, and the data analysis capability and the application capability of the patient disease data are improved.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without inventive exercise, wherein:
FIG. 1 is a schematic flow diagram of the process of the present invention;
FIG. 2 is a schematic view of the oral cavity detecting device of the present invention;
FIG. 3 is a schematic diagram of the communication principle of the embedded board card of the present invention;
FIG. 4 is a schematic diagram of a local area link network structure according to the present invention;
FIG. 5 is a block chain system based on a sharing mechanism according to the present invention;
FIG. 6 is a Bayesian model of the invention.
Detailed Description
The preferred embodiments of the present invention will be described below with reference to the accompanying drawings, and it should be understood that the embodiments described herein are merely for the purpose of illustrating and explaining the present invention and are not intended to limit the present invention.
As shown in fig. 1, a method for monitoring oral cavity data information capable of implementing remote data interaction and instant analysis includes the following steps:
step 1, detecting the oral cavity of a patient through an oral cavity detection device, and extracting oral disease information through a probe; the extraction or acquisition of the patient disease data information is realized by manually controlling the data information acquisition, the extraction mode comprises the extraction of gum data information images or the extraction of tooth visual screen image data information, and the extracted oral disease simulation data information is converted into data information;
step 2, transmitting the disease data information of the patient to an intelligent terminal through a wireless communication method, wherein the intelligent terminal is arranged in a data block chain to receive and transmit the disease data information detected in the oral cavity of the patient;
step 3, the retrieved patient disease data are transmitted to other block chain terminal equipment through the block chain nodes so as to realize the analysis and transmission of the patient disease data in the block chain nodes;
and 4, analyzing the disease data of the patient through different block chain nodes, and diagnosing and analyzing the oral disease information through a Bayesian algorithm model.
In one embodiment, the chain of data blocks is a chain of blocks. Each block holds certain information, which are linked in a chain according to the respective generated time sequence. This chain is maintained in all servers, and as long as one server can work in the entire system, the entire blockchain is secure. These servers, referred to as nodes in the blockchain system, provide storage space and computational support for the entire blockchain system. The blockchain terminal device is an intelligent device provided with a blockchain network and data nodes, and is generally arranged in the blockchain network to implement interaction of different data information, such as a blockchain server arranged in the blockchain network or having the blockchain nodes.
The intelligent terminal is an electronic terminal device commonly used by users, such as a PC, a tablet computer, a smart phone, and the like, and can realize data information transmission through wireless communication or bluetooth communication to improve wireless data interaction capability and transmission capability. In a specific application, disease data information in the oral cavity can be acquired through Bluetooth or wireless communication.
In step 1, as shown in fig. 2, the oral cavity detection device comprises an MSP430FG4619 processor, a communication module, a data acquisition, a power supply module, a sensor interface and a block chain node, wherein the MSP430FG4619 processor is respectively connected with the communication module, the data acquisition, the power supply module, the sensor interface and the block chain node, wherein the sensor interface and the block chain node are in interactive communication with each other.
During data acquisition, the MSP430FG4619 processor is used for realizing the interaction of different data information of a synchronous serial port of the gum data information of a patient, and the acquired gum data information of the patient is written into a SPORT register, a memory mapping register SPORTx _ TX register and other methods for registering when being transmitted. And then after the data information is moved out of the DT pin of the SPORT, the interaction of the data information and other data information is realized. When necessary, the PGA amplification circuit is designed to enhance the amplification capability of the data information, so as to be able to detect the data information parameters of the gum of the patient, which is generally set at 1000: 1, the linearity can reach the precision of +/-0.1%. The two channels of the AD converter AD 738058 are strictly synchronous sampling.
During specific information acquisition, a Cortex-A9 four-core processor is integrated, the working frequency can reach 1GHz, and a 2GB DDR3 memory and an 8GB eMMC flash are carried; meanwhile, the system supports interface drives such as Ethernet, CAN bus, UART and the like; and a Linux operating system is supported, and the requirement of remote data acquisition of the device is met. The power supply module adopts 24VDC power supply input and outputs 5V and 3.3V power supplies in a voltage stabilizing way, and power supply for a processor of the remote data acquisition system and each control chip is realized. In the acquisition interface module, the device adopts a plurality of sensors for data acquisition, and the device is connected with the sensors by adopting an RS-232 interface and CAN bus interface circuit module, which mainly comprises an RS-232 module, a CAN bus and an Ethernet. The RS-232 module mainly uses an MAX232 chip to convert the logic signal level and the RS-232 level, and the TTL level is directly connected with a serial port input/output interface of the core module. The REMOTE server TCP connection is established, heartbeat is sent at fixed time, and data is sent in a packaging mode by adopting a REMOTE process, because the acquisition frequency of each sensor is different, the REMOTE process can acquire the waveform of the ring buffer symmetrical multivibrator circuit at fixed time according to the uniform frequency, and the REMOTE acquisition of real-time data is realized. In order to strengthen the coverage range of a CAN bus communication system, the system coverage is improved by designing an embedded board card structure, a hardware system designed by NI company is mainly adopted to establish a high-speed transmission CAN communication channel, and a communication template is built in an embedded manner to achieve the highest signal coverage of the arrangement range of the electric instrument, so that the data of the electric instrument is fully recorded and recorded, and data signal support is provided for subsequent CAN communication.
In the above embodiment, as shown in fig. 3, data communication with the intelligent terminal is implemented through the embedded board card.
In the specific embodiment, the embedded board card communication design adopts a combined construction scheme of a micro-control + CAN centralized control mode and a transceiver board card. The CAN9853 adopts a two-path communication mode to ensure the high speed of a transmission channel, and is integrated into an sbRIO board structure, so that the purpose of improving the communication coverage is achieved. In the board card communication design process, two main channels CAN0 and CAN1 are connected in parallel, a channel 0 is responsible for the external transmission of instrument data, a channel is responsible for the receiving process of an internal system, and the two channel control modes are integrated control, so that the pressure of the internal space of the instrument is reduced. The programming procedure of the communication process adopts a cluster transmission mode, and sets up 0 and 1 transmission frames respectively according to CAN communication rules, and establishes an unsigned identification procedure. The cluster communication program divides the meter data into two forms of data and remote instructions, and the data and the remote instructions are read and written through an I/O port of the integrated chip respectively, while the conversion program is completed through a while program, and a cycle program is established in each structure, so that the communication process reaches the transmission frequency once per second.
The embedded board communication structure takes sbRIO as a main control center, takes an isolation power supply as an energy supply device, utilizes two sets of CAN controllers and transceivers to build a wide coverage surface for collecting data of the electric instrument, reserves expansion nodes, CAN expand according to the number of the instruments, designs a Reg5V external power supply between two sets of equipment, supplies energy for signal conversion, and ensures smooth remote transmission of the board communication structure.
In the above embodiment, the embedded board card is further provided with a block chain node.
In the above embodiments, the block link points are provided with an interactive method of consensus mechanism.
As shown in fig. 4 and 5, the dental data application block chain technology adopts a decentralized and decentralized accounting mode, so that the operation and maintenance costs of manpower and material resources of the original central transaction platform are reduced, individuals in the whole data chain have no authority to modify data information of other blocks, and the fairness and justness of the dental detection data information of patients are ensured. The system block chain patient oral cavity data block chains can realize point-to-point and multipoint transmission, communication is carried out among different patient oral cavity data block chains through gateways, interconnection and intercommunication of patient oral cavity data block chains with different architectures are realized, a party with a patient tooth detection data information requirement sends a transaction request in a block chain node mode, and after each node in the block chain patient oral cavity data block chains receives the transaction request, nodes meeting transaction service reply and send patient tooth detection data information. The patient tooth detection data information system uses a Multchain technology, system information interconnection is achieved in a multi-chain mode, and the patient tooth detection data information has safety and openness under the support of a block chain technology. The system architecture is provided with four main nodes of a patient, a doctor, a hospital and family members, a main-slave architecture is adopted between each main node and each slave node, and any node exchanges information through a P2P patient oral cavity data block chain. According to different importance degrees of each node in the patient tooth detection data information, a consensus mechanism POSS (proof of sharing) is added to establish a point-to-point interaction mode, and the patient tooth detection data information related service can be performed after agreement is achieved. The patient, the doctor, the hospital and the family adopt a consensus mode of B2B among four main nodes, the consensus content comprises patient oral cavity data information transaction and data transaction, valuable data for transaction is subjected to HASH and packaged into blocks, and then the blocks are added into the nodes and encrypted and uploaded to a main chain. A digital signature is generated by using a Hash algorithm and asymmetric encryption functions such as an RSA function, an Elgamal function, an ECC function and the like in a system block chain, a party who issues transactions in the process of detecting the data information of the teeth of the patient generates a data abstract through Hash function processing, and then the digital signature containing the node information and the information demand information of the teeth detection data of the patient is generated through asymmetric encryption, so that the interaction capacity of the teeth data information is improved.
In step 4, as shown in fig. 6, the bayesian algorithm model is an oral cavity affection factor evaluation method of fusing the comparison matrix model.
The oral cavity affection modeling method of the invention is added with a Bayesian evaluation model and a paired comparison matrix (evaluation algorithm), and can realize the evaluation of oral cavity affection factors at different stages in the remote transmission process of the oral cavity data block chain of a patient. The model construction is carried out by the following method:
firstly, oral disease information in the oral data information of a patient is collected, and the oral disease information is assumed to be recorded asX={X 1,X 2,…,X i …,X n }，X i Expressing the oral cavity disease data information acquired by different nodes of the patient oral cavity data in the block chain structure, recording the random factors influencing the oral cavity data acquisition information of the patient as X, Y and Z, and recording the X, Y and Z oral cavity data acquisition information of the patient not enough to influence the oral cavity data acquisition information of the patient1Patient sex fault log X2Or age X of the patient3The influencing factor of the remote transmission of the patient oral cavity data block chain comprises communication fault data information Z1Or block link point setting Z2Y represents the patient without oral disease, a Bayesian algorithm model is constructed, relative entropy is set in the model, and the expression is as follows:
Figure 102841DEST_PATH_IMAGE011
（1）
in the formula (1), the reaction mixture is, p(x)、q(x)respectively representing different probability values of a block link point data set X influencing the remote transmission of the oral cavity data of the patient, representing the relation between p and q as the relative entropy of factors influencing the remote transmission of the oral cavity data of the patient, and constructing a Bayesian algorithm model to ensure that the leakage probability of the oral cavity data of the patient is as follows:
Figure 687537DEST_PATH_IMAGE012
(2)
in the formula (2), whereinB 1 、B 2 、.........B n For various forms of failure probability occurring during the remote transmission of the patient oral data blockchain,Athe influence factor of the patient oral cavity data set through the Bayesian algorithm model by external information is obtained;
suppose again thatX iThe random variable representing the safety of the patient oral data transmission is recorded asX 1，X 2，…,X n Then, then
Figure 700492DEST_PATH_IMAGE013
To take place of
Figure 396047DEST_PATH_IMAGE014
Under the condition of transmitting fault probability, the probability of the oral cavity of the patient with the highest probability is expressed by the formula:
Figure 810848DEST_PATH_IMAGE015
（3）
in the formula (3), the Bayesian data model is set to different nodes in the block chain topological structure, so that the block chain remote transmission safety analysis of the patient oral cavity data is calculated, the condition probability or the posterior probability in the patient oral cavity data information is calculated, and the evaluation of the maximum probability is output.
In specific application, a data calculation accelerator and an encryption algorithm can be added into the Bayesian data model.
The calculation speed of the Bayesian data model can be improved by adding a data calculation accelerator, for example, the data calculation speed can be improved by compressing data information, or changing data format, or changing data attributes and other different ways. The encryption algorithm can be combined and applied or selectively applied through different methods such as an MD5 algorithm, an SHA1 algorithm, an HMAC algorithm, an AES/DES/3DES algorithm or a DES algorithm, and the data acceleration capability is greatly improved.
The original file or data in plain text is processed according to a certain algorithm to make it become an unreadable segment of code as 'cipher text', so that it can only display original content after inputting corresponding key, and the purpose of protecting data from being stolen and read by illegal person is achieved through such a way.
In step 4, the method for evaluating the algorithm model to realize diagnosis comprises the following steps:
(a) determining the type of the oral disease of the patient, and setting different disease types and data transmission safety indexes, such as general loopholes, larger loopholes or serious loopholes in the oral data transmission safety of the patient.
(b) According to the loopholes with different information transmission grades, different loophole judgment standards are formulated;
(c) various node data information remotely transmitted by the oral cavity data of the patient is used for refining a vulnerability decision standard from A to k through constructing an evaluation algorithm; expressed by the following formula:
Figure 566445DEST_PATH_IMAGE016
（4）
(d) then, each criterion w = (w) in the hierarchical structure is obtained from the equation1，w2，…，wk) The weight vector of (a), as shown in equation (5);
Figure 879746DEST_PATH_IMAGE017
（5）
(e) the consistency is checked according to the final consistency ratio CR, and expressed by formula (6), there are:
Figure 362680DEST_PATH_IMAGE018
（6）
Figure 913878DEST_PATH_IMAGE019
（7）
in the formula (7), w represents the characteristic value of the patient oral cavity data transmission leak event in the matrix A,
Figure 824066DEST_PATH_IMAGE020
represents a vulnerability decision criterion eigenvalue, λmaxAnd when CR is more than or equal to 0.1, the patient oral cavity data transmission security vulnerability data information does not conform to the receiving and judging matrix condition, and no hole leakage exists in the patient oral cavity data transmission process.
By means of the above described evaluation algorithm model, a grey relevance model can also be introduced, called relevance, for a measure of the magnitude of relevance of factors between two systems that vary with time or different objects. In the system development process, if the trend of the two factors is consistent, namely the synchronous change degree is higher, the correlation degree between the two factors is higher, otherwise, the correlation degree is lower, therefore, the grey correlation analysis method is a method for measuring the correlation degree between the factors according to the similarity or difference degree of the development trends between the factors, namely the grey correlation. The correlation degree analysis of the gray system has prominent technical advantages in the analysis of the patient oral cavity data information remote fault diagnosis, and the method can improve the evaluation capability of the hidden danger of the data information in the oral cavity data transmission process. In other embodiments, the TOPSIS method can also be used.
In the above specific application, a comparative analysis, a grouping analysis, a regression analysis, an index analysis, a prediction analysis, and the like may also be introduced.
The comparative analysis is to compare two or more related index data, analyze the change and understand the nature and development rules of things.
The grouping analysis is to divide the data into different parts according to the property and the characteristic of the data and a certain index, and analyze the internal structure and the interrelation of the parts, thereby knowing the development rule of things.
Regression analysis is a widely applied statistical analysis method, and can determine the causal relationship between variables by specifying dependent variables and independent variables, establish a regression model, solve each parameter of the model according to the measured data, evaluate whether the regression model can well fit the measured data, and if so, further predict according to the independent variables.
Index analysis refers to directly using some basic indexes in statistics to perform data analysis, such as mean, mode, median, maximum, minimum, and so on. In selecting which base index to use specifically, it is necessary to consider the orientation of the result.
The predictive analysis is mainly based on the current data, and judges and predicts the future data change trend.
Although specific embodiments of the present invention have been described above, it will be understood by those skilled in the art that these specific embodiments are merely illustrative and that various omissions, substitutions and changes in the form of the detail of the methods and systems described above may be made by those skilled in the art without departing from the spirit and scope of the invention. For example, it is within the scope of the present invention to combine the steps of the above-described methods to perform substantially the same function in substantially the same way to achieve substantially the same result. Accordingly, the scope of the invention is to be limited only by the following claims.

Claims (8)

1. A method for monitoring oral cavity data information capable of realizing remote data interaction and instant analysis is characterized in that: the method comprises the following steps:
step 1, detecting the oral cavity of a patient through an oral cavity detection device, and extracting oral disease information through a probe; the extraction or acquisition of the patient disease data information is realized by manually controlling the data information acquisition, the extraction mode comprises the extraction of gum data information images or the extraction of tooth visual screen image data information, and the extracted oral disease simulation data information is converted into data information;
step 2, transmitting the disease data information of the patient to an intelligent terminal through a wireless communication method, wherein the intelligent terminal is arranged in a data block chain to receive and transmit the disease data information detected in the oral cavity of the patient;
step 3, the retrieved patient disease data are transmitted to other block chain terminal equipment through the block chain nodes so as to realize the analysis and transmission of the patient disease data in the block chain nodes;
and 4, analyzing the disease data of the patient through different block chain nodes, and diagnosing and analyzing the oral disease information through a Bayesian algorithm model.
2. The method for monitoring oral cavity data information capable of realizing remote data interaction and instant analysis according to claim 1, wherein: the oral detection device comprises an MSP430FG4619 processor, a communication module, a data acquisition module, a power supply module, a sensor interface and block chain nodes, wherein the MSP430FG4619 processor is respectively connected with the communication module, the data acquisition module, the power supply module, the sensor interface and the block chain nodes, and the sensor interface and the block chain nodes are in interactive communication with each other.
3. The method for monitoring oral cavity data information capable of realizing remote data interaction and instant analysis according to claim 1, wherein: and data information is transmitted to realize data communication with the intelligent terminal through the embedded board card.
4. The method for monitoring oral cavity data information capable of realizing remote data interaction and instant analysis according to claim 3, wherein: and the embedded board card is also provided with a block chain node.
5. The method for monitoring oral cavity data information capable of realizing remote data interaction and instant analysis according to claim 4, wherein: the block chain link points are provided with an interaction method of a consensus mechanism.
6. The method for monitoring oral cavity data information capable of realizing remote data interaction and instant analysis according to claim 1, wherein: the Bayesian algorithm model is an oral cavity affection factor evaluation method fusing a comparison matrix model.
7. The method for monitoring oral cavity data information capable of realizing remote data interaction and instant analysis according to claim 6, wherein: the working method of the Bayesian algorithm model comprises the following steps:
suppose oral disease information is recorded asX={X 1,X 2,…,X i …,X n }，X i The oral cavity diseased data information obtained by different nodes of the patient oral cavity data in the block chain structure can influence the acquisition information of the patient oral cavity dataThe random factors are recorded as X, Y and Z, and the acquired data information of oral cavity of the patient, which is not sufficiently influenced, comprises diet X of the patient1Patient sex fault log X2Or age X of the patient3The influencing factors of the remote transmission of the patient oral cavity data block chain comprise communication fault data information Z1Or block link point setting Z2Y represents the patient without oral disease, a Bayesian algorithm model is constructed, relative entropy is set in the model, and the expression is as follows:
Figure 335430DEST_PATH_IMAGE001
（1）
in the formula (1), the reaction mixture is,p(x)、q(x)respectively representing different probability values of a block link point data set X influencing the remote transmission of the oral cavity data of the patient, representing the relation between p and q as the relative entropy of factors influencing the remote transmission of the oral cavity data of the patient, and constructing a Bayesian algorithm model to ensure that the leakage probability of the oral cavity data of the patient is as follows:
Figure 314888DEST_PATH_IMAGE002
(2)
in the formula (2), whereinB 1 、B 2 、.........B n For the various forms of failure probability that occur during the remote transmission of patient oral data blockchains,Athe influence factor of the patient oral cavity data set through the Bayesian algorithm model by external information is obtained;
suppose again thatX iThe random variable representing the safety of the data transmission in the oral cavity of the patient is recorded asX 1，X 2，…,X n Then, then
Figure 907674DEST_PATH_IMAGE003
To take place of
Figure 365200DEST_PATH_IMAGE004
In the case of transmission of the probability of failure, the greatest probability of occurrence of the failureThe oral cavity probability is expressed by the formula:
Figure 992622DEST_PATH_IMAGE005
（3）
in the formula (3), the Bayesian data model is set to different nodes in the block chain topological structure, so that the block chain remote transmission safety analysis of the patient oral cavity data is calculated, the condition probability or the posterior probability in the patient oral cavity data information is calculated, and the evaluation of the maximum probability is output.
8. The method for monitoring oral cavity data information capable of realizing remote data interaction and instant analysis according to claim 6, wherein: the method for realizing diagnosis by the estimation model comprises the following steps:
(a) determining the type of oral diseases of a patient, and setting different disease types and data transmission safety indexes;
(b) according to the loopholes with different information transmission grades, different loophole judgment standards are formulated;
(c) various node data information remotely transmitted by the oral cavity data of the patient is used for refining a vulnerability decision standard from A to k through constructing an evaluation algorithm; expressed by the following formula:
Figure 877401DEST_PATH_IMAGE006
（4）
(d) then, each criterion w = (w) in the hierarchical structure is obtained from the equation1，w2，…，wk) The weight vector of (a), as shown in equation (5);
Figure 957484DEST_PATH_IMAGE007
（5）
(e) the consistency is checked according to the final consistency ratio CR, and expressed by formula (6), there are:
Figure 218701DEST_PATH_IMAGE008
（6）
Figure 700629DEST_PATH_IMAGE009
（7）
in the formula (7), w represents the characteristic value of the patient oral cavity data transmission leak event in the matrix A,
Figure 756310DEST_PATH_IMAGE010
characteristic value, lambda, representing a vulnerability decision criterionmaxAnd when CR is more than or equal to 0.1, the patient oral cavity data transmission security vulnerability data information does not conform to the receiving and judging matrix condition, and no hole leakage exists in the patient oral cavity data transmission process.
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