Disclosure of Invention
The invention aims to provide a medical auxiliary device based on a virtual reality technology and a control system thereof.A virtual reality equipment module establishes a virtual basic database, establishes a patient emergency data set in the virtual basic database, matches a patient emergency value of a patient to be treated in an auxiliary way with the patient emergency data set in the virtual basic database to obtain an interval preset data set of the virtual basic database and the patient to be treated in the auxiliary way, matches a treatment matching value of the patient in the interval preset data set with the patient to be treated in the auxiliary way to obtain an optimal virtual human model for auxiliary treatment, and is beneficial to the accurate treatment of the patient by calling a treatment scheme of the virtual human model.
The purpose of the invention can be realized by the following technical scheme:
the medical auxiliary control system based on the virtual reality technology comprises a data acquisition module, a virtual reality equipment module and a data analysis module;
the virtual reality device module is accessed to the cloud end, acquires body characteristic information stored by the cloud end to generate a corresponding virtual character model and a virtual basic database, and visualizes the virtual character model through the virtual reality device and the virtual basic database;
the data acquisition module is used for acquiring the body characteristic information of the patient and transmitting the body characteristic information of the patient to the data analysis module;
the data analysis module is used for receiving the body characteristic information acquired by the data acquisition module in real time for the patient, comparing the body characteristic information of the patient with the body characteristic information stored in the virtual basic database, and calling the virtual human model parameters to perform medical assistance on the patient according to the comparison result.
As a further scheme of the invention: the data acquisition module is also used for transmitting the acquired physical characteristic information of the patient to the cloud end and storing the information.
As a further scheme of the invention: the cloud end stores the body characteristic information of different patients;
including but not limited to the sex, age, height, weight and region of the patient.
As a further scheme of the invention: the physical characteristic information comprises medical histories corresponding to the patients, different patients are classified according to the medical histories, and virtual human models with different medical histories are built.
As a further scheme of the invention: the data acquisition module acquires body characteristic information of a patient, including pathological degree, a pathological diagnosis report and identity information of the patient;
obtaining the pathological degree of the patient according to the pathological diagnosis report of the patient and the diagnosis report of the main doctor, and marking the pathological degree of the patient as Di;
the identity information comprises the illness time of the patient, the age of the patient and the patient area, the illness time of the patient is marked as Ti, and the illness age of the patient is marked as Ni;
assigning weights to the pathological degree, the disease time and the disease age of the patient, wherein the pathological degree of the patient is marked as q1, the disease time of the patient is marked as q2, and the disease time of the patient is marked as q3, wherein q1+ q2+ q3=1;
the patient emergency value Mi of the patient is calculated by the formula Mi = Di xq 1+ Ti xq 2+ Ni xq 3, and the data acquisition module transmits Mi to the data analysis module.
As a further scheme of the invention: the data analysis module receives the patient emergency value Mi, compares the patient emergency value Mi with the virtual basic database in the virtual reality device module, and specifically comprises the following steps:
s1: calculating the patient emergency value in the virtual basic database according to the stored patient emergency value to obtain a patient emergency value data set Ei in the virtual basic database;
s2: the data analysis module carries out error correction on the emergency value Mi of the patient to obtain Mi1 and Mi2, wherein Mi1= Mi-My, mi2= Mi + My, and My is a preset error correction threshold;
s3: and comparing the patient emergency value data set Ei of the virtual basic database with the corrected patient emergency value Mi to obtain an interval preset data set of the patient emergency value data set Ei positioned at two endpoints of Mi1 and Mi2, namely Eiy belongs to [ Mi1, mi2].
As a further scheme of the invention: the data analysis module obtains the number of virtual character models of the interval preset data set Eiy through calculation, and the processing steps of the number of the virtual character models of the interval preset data set Eiy are as follows:
the method comprises the following steps: acquiring the identity information of a corresponding patient in an interval provisioned data set Eiy, and marking the patient as Wj, j =1, 8230, n;
step two: the number of times that the patient did not participate in the adjuvant therapy in the preset data set in the set interval is recorded as M1 Wj (ii) a The total number of patient participation in adjuvant therapy was recorded as M2 Wj (ii) a Set patient age as N Wj ;
Step three: and recording the illness time of the patient as T according to the illness time of the patient stored in the virtual basic database Wj ;
Step four: by the formula
Obtaining treatment matching value MX of virtual human model and patient in interval pre-prepared data set
Wj ;
Wherein f1, f2, f3, f4 and f5 are all preset proportionality coefficients; WQ Wj The number of times that the patient needs adjuvant therapy without adjuvant therapy;
the data analysis module pre-allocates the treatment matching value MX in the interval data set Wj Sequentially arranging according to the sequence from big to small, selecting treatment matching value MX in interval pre-prepared data set Wj The largest patient builds a virtual character model.
As a further scheme of the invention: data analysis module calls treatment matching value MX Wj The maximum virtual character model is stored in the auxiliary treatment scheme at the cloud end, so that medical assistance is performed on the patient through the virtual character model.
As a further scheme of the invention: the virtual reality equipment further comprises a login unit, and the login unit is used for registering and logging in by a patient or a doctor.
The invention has the beneficial effects that:
(1) The virtual reality equipment module establishes a virtual basic database, establishes a patient emergency data set in the virtual basic database, matches a patient emergency value of a patient to be assisted and treated with the patient emergency data set in the virtual basic database to obtain an interval pre-prepared data set of the virtual basic database and the patient to be assisted and treated, matches the patient in the interval pre-prepared data set with a treatment matching value of the patient to be assisted and treated to obtain an optimal virtual human model for assisted treatment, and is helpful for accurate treatment of the patient by calling a treatment scheme of the virtual human model;
based on a virtual reality technology, the disease time of a patient in a virtual basic database is closer to the disease time of the patient to be treated in an auxiliary way through the matching processing of big data; the more times that the patient does not participate in the adjuvant therapy (the patient has good therapeutic effect and does not need multiple adjuvant therapies) in the virtual basic database; the closer the age of the patient in the virtual basic database is to the age of the patient to be assisted and treated, the larger the obtained treatment matching value is, the higher the coincidence rate of the scheme of the patient in the virtual basic database and the patient to be assisted and treated is, and the treatment effect of the patient is improved.
Detailed Description
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, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Example 1
Referring to fig. 1, the present invention relates to a medical auxiliary device based on virtual reality technology and a control system thereof, including a data acquisition module, a virtual reality device module, and a data analysis module;
the virtual reality equipment module is accessed to cloud storage, generates a corresponding virtual character model and a virtual basic database according to the body characteristic information acquired by the cloud storage, simultaneously stores the acquired body characteristic information, and visualizes the virtual character model through virtual reality equipment and the virtual basic database;
the data acquisition module is used for acquiring the body characteristic information of the patient and transmitting the body characteristic information of the patient to the data analysis module and the cloud end for storage;
the data analysis module is used for receiving the body characteristic information acquired by the data acquisition module in real time for the patient, comparing the body characteristic information of the patient with the body characteristic information stored in the virtual basic database, and calling the virtual human model parameters to perform corresponding medical assistance on the patient according to the comparison result.
The cloud end stores body characteristic information of different patients;
different patients include, but are not limited to, the patient's sex, age, height, weight, and region;
the physical characteristic information comprises medical histories corresponding to the patients, different patients are classified according to the medical histories, and virtual character models with different medical histories are built.
In a particular embodiment, patients with the same medical history can be classified according to different parameters, including but not limited to, the congenital or acquired type of disease, the age of the patient, and the region of the patient.
In this embodiment, taking medical assistance for a stroke patient as an example, specifically, the data acquisition module acquires physical characteristic information of the patient, where the physical characteristic information includes a pathological degree, a pathological diagnosis report, and identity information of the patient;
wherein, the parameters of the pathological diagnosis report include but are not limited to blood sugar and blood fat index, total leukocyte index, eosinophil index and electroencephalogram of the patient;
obtaining the pathological degree of the patient according to the pathological diagnosis report of the patient and the diagnosis report of the main doctor, and marking the pathological degree of the patient as Di;
the identity information comprises the illness time of the patient, the age of the patient and the patient area, the illness time of the patient is marked as Ti, and the illness age of the patient is marked as Ni;
assigning weights to the pathological degree, the disease time and the disease age of the patient, wherein the pathological degree of the patient is marked as q1, the disease time of the patient is marked as q2, and the disease time of the patient is marked as q3, wherein q1+ q2+ q3=1;
the patient emergency value Mi of the patient is obtained through calculation of the formula Mi = Di xq 1+ Ti xq 2+ Ni xq 3, and the data acquisition module transmits Mi to the data analysis module.
The data analysis module receives the patient emergency value Mi, compares the patient emergency value Mi with the virtual basic database in the virtual reality device module, and specifically comprises the following steps:
the method comprises the following steps: calculating the patient emergency value in the virtual basic database according to the stored patient emergency value to obtain a patient emergency value data set Ei in the virtual basic database;
step two: the data analysis module corrects errors of the emergency value Mi of the patient to obtain Mi1 and Mi2, wherein Mi1= Mi-My, mi2= Mi + My, and My is a preset error correction threshold;
step three: and comparing the patient emergency value data set Ei of the virtual basic database with the corrected patient emergency value Mi to obtain an interval preset data set of the patient emergency value data set Ei positioned at two endpoints of Mi1 and Mi2, namely Eiy belongs to [ Mi1, mi2].
The data analysis module obtains the number of virtual character models of the interval preset data set Eiy through calculation, and the processing steps of the number of the virtual character models of the interval preset data set Eiy are as follows:
the method comprises the following steps: acquiring the identity information of a corresponding patient in an interval provisioned data set Eiy, and marking the patient as Wj, j =1, 8230, n;
step two: the number of times that the patient did not participate in the adjuvant therapy in the preset data set in the set interval is recorded as M1 Wj (ii) a The total number of patients taking part in the adjuvant therapy was recorded as M2 Wj (ii) a Set patient age as N Wj ;
Step three: and recording the illness time of the patient as T according to the illness time of the patient stored in the virtual basic database Wj ;
Step four: by the formula
Obtaining treatment matching value MX of virtual human model and patient in interval pre-prepared data set
Wj ;
Wherein f1, f2, f3, f4 and f5 are all preset proportionality coefficients; WQ Wj The number of times that the patient needs adjuvant therapy without adjuvant therapy;
the disease time of the patient in the virtual basic database is closer to the disease time of the patient to be treated in an auxiliary way, and the larger the treatment matching value is, the higher the coincidence rate of the scheme of the patient in the virtual basic database and the patient to be treated in the auxiliary way is;
the more times that the patient does not participate in the auxiliary treatment (the treatment effect of the patient is good, and the auxiliary treatment is not needed for multiple times) in the virtual basic database, the larger the treatment matching value is, the higher the coincidence rate of the scheme of the patient in the virtual basic database and the patient to be subjected to the auxiliary treatment is;
the more the total times of the patients participating in the auxiliary treatment in the virtual basic database are, the smaller the treatment matching value is, the lower the coincidence rate of the scheme of the patients in the virtual basic database and the patients to be treated in the auxiliary treatment is;
the closer the age of the patient in the virtual basic database is to the age of the patient to be assisted and treated, the larger the treatment matching value is, the higher the coincidence rate of the scheme of the patient in the virtual basic database and the patient to be assisted and treated is;
step five: the data analysis module pre-allocates the treatment matching value MX in the interval data set Wj Sequentially arranging according to the order of big to small, preferentially selecting the treatment matching value MX in the interval pre-prepared data set Wj Constructing a virtual character model for the largest patient;
step six: the data analysis module calls an auxiliary treatment scheme stored in the cloud end by the virtual character model, the called treatment scheme is transmitted to the virtual reality equipment by the data analysis module and displayed by the virtual reality equipment, and therefore medical assistance of a patient to be treated with auxiliary treatment is achieved.
The pathological degree Di of the patient is obtained by taking the detection value of the number of eosinophils of the patient in the detection process as an example, and the specific analysis method comprises the following steps:
s1: the method comprises the steps of taking preset time t1 as a detection unit, enabling the time interval between two adjacent detection units t1 to be not more than preset time t2, carrying out continuous multiple detection on eosinophils of a patient within the time t1, enabling the time intervals between two adjacent detections to be the same, and obtaining information G1, G2, G
Calculating to obtain a standard deviation value S1 of the group of data, wherein Gp is an average value of G1, G2, and Gf, and deleting when S1 is greater than or equal to a preset value SDividing the maximum value and/or the minimum value in the group of data, calculating the standard difference value S1 of the group of data again until the S1 is smaller than the preset value S, and calculating to obtain the average value Fp1 of the residual data in the group of data;
s2: presetting the value of acidophilic cells in a healthy human body as K1, and calculating to obtain
Wherein, the larger the Di value is, the higher the pathological degree grade of the patient is, and the worse the health condition of the patient is;
the above pathological degree Di includes, but is not limited to, eosinophils.
In a specific embodiment, the virtual reality device further comprises a login unit, wherein the login unit is used for submitting registration information for registration through the intelligent terminal and sending the registration information which is successfully registered into the virtual reality device; marking the user successfully registered as a registered user; the registration information comprises the name, the mobile phone number, the identification number and the detection hospital name of the registered user;
the login unit further comprises an online acquisition unit, the online acquisition unit is used for acquiring login time and login area of a registered user for logging in the virtual reality device and storing login information of the user, and the online acquisition unit comprises the following specific steps:
the method comprises the following steps: a registered user (a patient or a doctor) accesses the virtual reality equipment through a computer terminal or a mobile terminal, inputs a private key of a password pair through the computer terminal or the mobile terminal and generates a calling instruction;
step two: and the computer terminal or the mobile terminal sends the calling instruction to the virtual reality equipment, and the virtual reality equipment receives the calling instruction and then acquires the private key of the registered user and matches the private key with the public key of the key pair to realize calling of the virtual character model treatment scheme.
Furthermore, in this embodiment, an encryption module is further arranged for logging in or out of the virtual reality device, the encryption module generates a key pair, and calling of the virtual character model treatment scheme in the virtual basic database can be realized only after decryption by a registered user, so that the privacy of a virtual reality device patient is ensured.
Example 2
The medical auxiliary device based on the virtual reality technology comprises a data acquisition module, a virtual reality equipment module and a data analysis module;
the data acquisition module is electrically connected with the virtual reality equipment module, and the virtual reality equipment module is electrically connected with the data analysis module;
the virtual reality equipment module generates a corresponding virtual character model and a virtual basic database through the body characteristic information stored in the cloud;
the data acquisition module is used for acquiring physical characteristic information of a patient;
the data analysis module is used for receiving the body characteristic information acquired by the data acquisition module in real time for the patient, comparing the body characteristic information of the patient with the body characteristic information stored in the virtual basic database, and calling the parameters of the virtual human model to perform medical assistance on the patient.
While one embodiment of the present invention has been described in detail, the description is only a preferred embodiment of the present invention and should not be taken as limiting the scope of the invention. All equivalent changes and modifications made within the scope of the present invention shall fall within the scope of the present invention.