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CN113066567B - Medical treatment registration system that sees a doctor based on block chain - Google Patents

Medical treatment registration system that sees a doctor based on block chain Download PDF

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CN113066567B
CN113066567B CN202110382094.3A CN202110382094A CN113066567B CN 113066567 B CN113066567 B CN 113066567B CN 202110382094 A CN202110382094 A CN 202110382094A CN 113066567 B CN113066567 B CN 113066567B
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叶月玲
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Wuhan Topyourself Informtion Technoligy Development Co ltd
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Abstract

The invention discloses a block chain-based medical treatment registration system, and belongs to the technical field of medical registration. The medical graphic display system comprises a medical graphic display module, a micro expression recognition module, a pain grade classification module, a recommended registration module, a fee clearing module, an intelligent positioning module, a screen display module and a block chain recording module, wherein the medical graphic display module, the micro expression recognition module, the pain grade classification module, the recommended registration module and the fee clearing module are sequentially connected; the output end of the fee clearing module is connected with the input ends of the intelligent positioning module and the block chain recording module; the output end of the intelligent positioning module is connected with the output end of the screen display module; the output end of the block chain recording module is connected with the input ends of the pain grade classification module and the expense clearing module.

Description

Medical treatment registration system that sees a doctor based on block chain
Technical Field
The invention relates to the technical field of medical registration, in particular to a block chain-based medical treatment registration system.
Background
With the continuous development of modern science and technology, network appointment registration becomes the mainstream direction of people in the era of medical treatment registration, the appointment registration shortens the treatment process, the time of patients is saved, and the network appointment registration is convenient for the people to see a doctor.
Firstly, a large number of patients cannot accurately express the problems of the patients during registration, so that registration departments are wrong, doctors are difficult to see, and time of the two parties is wasted; secondly, patients have unclear knowledge about the severity of their disease conditions, pursue 'expert numbers' under the condition that the disease conditions are not serious or rare, and waste medical resources; thirdly, the patient cannot see a doctor in time after registration, and the time of the doctor is wasted; fourthly, in the existing registration system, the picture is uploaded to a doctor for diagnosis, the format of the picture is not clear, and the action is not changed, so that the doctor is difficult to accurately judge; fifthly, the registered data has real information of the patient, is easy to lose and leak and cannot ensure privacy; sixthly, when the patient arrives at the hospital for a doctor, the patient needs to take out the mobile phone again to enter the system for inquiring registration information, and the patient is very inconvenient due to various pains.
The block chain is used as a database with a data hash verification function, wherein blocks, namely data blocks, are combined into a chain structure according to time sequence, and the reliability of the database is maintained collectively in a distributed accounting mode by using a cryptographic algorithm. Therefore, in view of the problems of data privacy and storage, a blockchain-based medical attendance registration system is proposed in the present invention to solve the above problems.
Disclosure of Invention
The invention aims to provide a medical treatment registration system based on a block chain, which is used for solving the problems in the background technology.
In order to solve the technical problems, the invention provides the following technical scheme: a block chain-based medical treatment registration system comprises a medical graphic representation module, a micro-expression recognition module, a pain grade classification module, a recommended registration module, a fee payment module, an intelligent positioning module, a screen display module and a block chain recording module;
the medical graphic display module is used for guiding the patient to carry out self-checking and recording a video for system analysis; the micro expression recognition module is used for capturing micro expression changes of the patient in the self-checking process; the pain grade classification module is used for deducing the pain grade of the patient according to the facial expression change of the patient; the recommending registration module is used for recommending patients to register according to the results obtained by the medical graphic module, the micro-expression recognition module and the pain grade classification module and by integrating the actual conditions of doctors in the hospital; the fee clearing module is used for paying and refunding the registered fee; the intelligent positioning module is used for carrying out accurate positioning and confirming whether a patient arrives at a hospital or not; the screen display module is used for displaying the registration information on a mobile phone screen; the block chain recording module is used for recording various behavior data of the patient during registration and recording the disappointment behavior of the patient;
the output end of the medical graphic representation module is connected with the input end of the micro-expression recognition module; the output end of the micro-expression recognition module is connected with the input end of the pain grade classification module; the output end of the pain grade classification module is connected with the input end of the recommended registration module; the output end of the recommended registration module is connected with the input end of the expense settlement module; the output end of the fee clearing module is connected with the input ends of the intelligent positioning module and the block chain recording module; the output end of the intelligent positioning module is connected with the output end of the screen display module; the output end of the block chain recording module is connected with the input ends of the pain grade classification module and the expense clearing module.
According to the technical scheme, the method is characterized in that: the medical illustration module comprises the following units:
the detection unit is used for detecting whether the whole body of the patient is within the range of the camera;
the figure unit is used for setting a figure for pressing a body part and guiding a patient to carry out self-checking;
in the figure unit, the whole body part is pressed or touched, and the patient only needs to press or touch the whole body part according to the instruction;
the voice unit is used for carrying out voice reminding;
the voice prompt comprises the following conditions:
the whole body of the patient is not in the range of the camera, the pressed part of the patient is not in line with the diagram, and the like;
the video recording unit is used for recording videos in the self-checking process;
the output end of the detection unit is connected with the input end of the voice unit; the output end of the graphic unit is connected with the input end of the voice unit; the output end of the video recording unit is connected with the input end of the micro expression recognition module.
According to the technical scheme, the micro expression recognition module comprises the following units:
the micro-expression recognition unit is used for collecting micro-expression changes of the face of the human face;
an eyebrow detecting unit for detecting a variation range of eyebrows, thereby determining a pain level score;
a mouth corner detection unit for detecting a mouth opening amplitude, thereby determining a pain level score;
the face muscle line detection unit is used for determining a pain grade score according to the twitch degree of the face lines;
the output end of the micro expression recognition unit is connected with the input ends of the eyebrow detection unit, the mouth corner detection unit and the face muscle line detection unit; the output ends of the eyebrow detecting unit, the mouth corner detecting unit and the face muscle line detecting unit are connected with the pain grade classifying module.
According to the technical scheme, the pain grade score is calculated by the following specific steps:
s4-1, in an eyebrow detection unit, acquiring the position of the eyebrow of a patient in an initial state, and performing tangent processing on the eyebrow in the up-down direction, wherein the highest tangent point is marked as A, and the lowest tangent point is marked as B;
s4-2, collecting the position of eyebrow of patient in each step of self-checking, making tangent treatment in up-down direction on eyebrow, and recording the highest tangent point as A i The lowest tangent point is marked as B i
S4-3, according to the formula:
Figure GDF0000017937810000051
wherein, X 1 Scoring an eyebrow detection unit pain level; l is 1 Is a proportionality coefficient of 1;
calculating to obtain an eyebrow detection unit pain grade score;
in the process, the frown condition of the eyebrow is formed when people feel pain, the pain condition of the human body is judged by using the maximum height difference between the upper part and the lower part of the eyebrow, the result is more accurate, and the proportionality coefficient 1 can be set by self;
s4-4, in the mouth corner detection unit, the mouth is in a closed state in the initial state, the mouth opening amplitude of the patient in each step of self-checking is collected, the area of the opening is recorded and recorded as S i
S4-5, according to the formula:
Figure GDF0000017937810000052
wherein, X 2 Scoring the pain level detected by the mouth corner detection unit; l is 2 A proportionality coefficient of 2;
calculating a pain grade score detected by the mouth corner detection unit;
in the process, when a user feels pain, the mouth can be opened to send sound to relieve the pain, the pain of the patient can be judged according to the mouth opening area, and the proportionality coefficient 2 can be set automatically;
s4-6, in the face muscle line detection unit, the face muscle lines are in a normal state in an initial state, and the twitch degree of the face muscle lines of the patient in each step of self-checking is collected, wherein the twitch degree is the change amplitude of the face muscle lines;
s4-7, extracting each part of lines according to the data collected in S4-6, drawing a plane sketch of the lines of the muscles of the face of the patient according to the pain face plane sketch in the historical data, and ensuring that the sizes of the lines are the same as those of the pain face plane sketch in the historical data;
s4-8, establishing a coordinate system by taking the central point of the plane sketch as the origin, and carrying out comparison on the plane sketch of the muscle line of the face of the current patient mentioned in S4-7 and the painful face plane in the historical dataThe sketch selects N key points and records the coordinate condition, wherein the coordinates of the N key points of the plane sketch of the muscle line of the face of the current patient are recorded as a set M { (a) 1 ,b 1 )、(a 2 ,b 2 )、……、 (a n ,b n ) N key point coordinates of the painful facial plane sketch in history are recorded as set M 2 ={(c 1 ,d 1 )、(c 2 ,d 2 )、……、(c n ,d n )};
S4-9, according to the formula:
Figure GDF0000017937810000061
wherein X 3 Scoring the pain level detected by the facial muscle line detection unit; l is 3 A proportionality coefficient of 3;
calculating to obtain a pain grade score of the facial muscle line detection unit;
in the step, because the lines of the face are changed due to the pain, a plane sketch is drawn by using a projection mode by using the change, points with obvious lines are selected as key points, the plane sketch with the pain in historical data is selected for comparison of similar distances, so that the pain grade of the current patient is obtained, and the proportionality coefficient 3 can be set automatically;
according to the above technical solution, the pain level classification module includes the following units:
the data receiving unit is used for receiving the storage information transmitted by the block chain recording module and providing the storage information to the patient checking unit;
the patient checking unit is used for checking whether the patient is a first patient or a repeated patient, the first patient is a patient who is registered for the first time in the hospital, and the repeated patient is a patient who is registered for two times or more in the hospital;
a pain scoring unit for calculating a final pain score of the patient in a state of each self-examination step;
in a first patient, according to the pain level score of the eyebrow detection unit, the pain level score detected by the mouth corner detection unit and the pain level score of the facial muscle line detection unit obtained in the micro-expression recognition module, an initial system weight is prepared, and according to a formula:
X general assembly =w 1 X 1 +w 2 X 2 +w 3 X 3
Wherein, X General assembly Patient self-test final pain score at each step, w 1 、w 2 、w 3 Respectively corresponding to the system scoring weights of the eyebrow detection unit, the mouth corner detection unit and the face muscle line detection unit;
in repeated patients, the system initial weight is not prepared, and the weight is adjusted according to the patient medical record prescribed by the doctor in the previous diagnosis, and the adjustment mode is as follows:
facial expression reaction capacities including invalid, dull, normal and better, which are diagnosed by doctors, exist in the patient medical records; the weights respectively corresponding to the eyebrow detection unit, the mouth corner detection unit and the face muscle line detection unit are w 10 、w 11 、w 1 、w 12 ;w 20 、w 21 、w 2 、w 22 ; w 30 、w 31 、w 3 、w 32
Thus in a repeat patient, according to the formula:
X general assembly =w i X 1 +w j X 2 +w k X 3
Wherein, w i 、w j 、w k Respectively corresponding to each unit weight adjusted according to the diagnosis of a doctor;
in this step, considering that different patients have different facial expressions, various diseases exist due to the particularity of the patients, some patients may have dull facial expressions, such as some elderly patients or patients with encephalopathy, different weights are set, and the doctor subjective judgment opinions are adopted, so that different patients do not need to analyze, and the system burden is reduced as much as possible, and the result is accurate.
A pain grade unit for classifying the pain grade of the part according to the final pain score of the patient self-checking in each step state;
the pain rating units are classified as follows:
setting a scoring threshold to X max 、X min
If X General assembly Greater than X max This is indicative of a very painful area;
if X General assembly Less than X min Representing no pain at this site;
if X General assembly In the interval [ X min ,X max ]Inner, representing pain at this site;
the output end of the data receiving unit is connected with the input end of the patient checking unit; the output end of the patient test unit is connected with the input end of the pain scoring unit; the output end of the pain scoring unit is connected with the input end of the pain grade unit.
According to the technical scheme, the recommending registration module comprises the following units:
the department recommending unit is used for determining which department the department should be registered in according to the pain grades of all parts transmitted by the pain grade classifying module, namely, establishing a registered department according to the parts with pain or very pain;
the doctor recommending unit is used for recommending registered doctors;
the recommended doctor-registering mode is as follows:
for very painful patients, specialist category doctors were recommended; for general patients, a general physician is recommended;
preferentially recommending doctors with a small number of registered numbers on the day according to the registration date;
the output end of the department recommending unit is connected with the input end of the doctor recommending unit.
According to the technical scheme, the fee clearing module comprises the following units:
the data unit is used for transmitting data with the block chain recording platform;
the payment unit is used for registering and paying;
the fee refunding unit is used for refunding fees, and the refunding modes comprise the following two modes:
the patient cancels the registration one day before the registration day, and the registration fee paid by the patient is returned in full amount;
the patient pays a guarantee fund due to credit behavior, and the guarantee fund is returned in full amount after the treatment is finished;
the fee clearing module is connected with a payment platform;
the payment platform comprises a payment treasure, a WeChat, a bank card and the like;
the output end of the payment unit is connected with the input end of the data unit; the output end of the data unit is connected with the input end of the fee refunding unit.
According to the above technical solution, the intelligent positioning module includes the following units:
the date confirmation unit is used for reading the registration date after the registration is successful, determining whether the current day is the registration date or not, and reminding the current day by using a mobile phone on the registration date;
the address positioning unit is used for carrying out address positioning on the registered hospital after the registration is successful;
the distance verification unit is used for measuring and calculating the distance between the patient and the hospital after the registration is successful and the date confirmation unit confirms that the current day is the registration date;
the output end of the date confirmation unit is connected with the input ends of the address positioning unit and the distance verification unit; and the output end of the address positioning unit is connected with the input end of the distance verification unit.
According to the above technical solution, the screen display module includes the following units:
the reading unit is used for reading the related information transmitted by the intelligent positioning module;
the starting unit is used for starting the registration software, reading the registration information and displaying the registration information on a screen of the mobile phone;
the starting steps of the starting unit are as follows:
s9-1, determining whether the current day is a registration day according to the information condition in the intelligent positioning module read by the reading unit, and if so, entering the step S9-2; if not, ending;
s9-2, according to the distance between the patient and the hospital read by the reading unit, if the distance is smaller than a threshold value Y, the starting unit starts registration software, departments and doctors in the registration information are directly displayed on a mobile phone screen, and the patient is prevented from entering the registration software again to inquire;
by using the mode, the condition that the patient needs to enter the system to inquire registration information again in a hospital can be avoided, time is wasted, and unnecessary troubles are brought to the patient;
the output end of the reading unit is connected with the input end of the starting unit.
According to the above technical solution, the block chain recording module includes the following units:
the block chain registration recording unit is used for recording the registration condition of the patient, and after the registration of the user is successful, the registration information and the treatment information are written into the block chain registration recording unit for storage;
the appointment losing behavior recording unit is used for recording and storing the behavior that the patient is not available for treatment on time after registration;
the feedback unit is used for making corresponding feedback on the pain grade classification module and the expense settlement module according to the registration records of the block chain registration recording unit and the settlement behavior records in the settlement behavior recording unit, namely whether the patient needs to adjust the pain grading weight and whether the patient needs to pay a deposit or not;
and the output ends of the block chain registration recording unit and the loss behavior recording unit are connected with the input end of the feedback unit.
Compared with the prior art, the invention has the following beneficial effects:
1. according to the invention, an appointment registration mode is adopted, so that the medical efficiency is improved, and the real reaction of a patient can be perceived better from a micro-expression by using the modes of eyebrow detection, mouth corner detection and face muscle line detection, so that the clinical judgment of a doctor is facilitated, and the overall judgment result is more accurate;
2. by adopting a home appointment mode, the outgoing of a patient can be effectively reduced, the pain is avoided, the load of the flow of people in a hospital is reduced, the diagnosis pressure of a doctor is reduced, and the hospital diagnosis efficiency is improved;
3. the pain grade score is used for recommending departments and doctors, so that the patient cannot select a wrong department, and meanwhile, adaptive measures are taken according to the degree of pain, medical resources are saved, the medical efficiency is improved, and more critical patients are rescued;
4. the block chain is used for recording and storing the registration information, so that on one hand, the effectiveness and privacy of data are ensured, on the other hand, the data are not tampered, and the warning is given to the patient who is registered for many times but does not see a doctor; meanwhile, according to the case information provided for the patient by the doctor, more accurate illness state control is provided for the patient who registers for many times, more accurate pain scores are provided for the patients with facial expressions problems, and the diagnosis of the doctor is facilitated;
5. utilize intelligent location, distance to detect and arrive under the condition of hospital after confirming that patient's registration is successful, automatic display registration information and administrative or technical offices have avoided the patient to need log in the registration system once more and have inquired, occupy system resource, and most patients are uncomfortable or inconvenient simultaneously, and inquiry many times may cause uncomfortable and waste time.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention.
In the drawings:
FIG. 1 is a schematic diagram of a block chain-based medical attendance registration system according to the present invention;
FIG. 2 is a schematic diagram of the pain level score calculation steps of a blockchain-based medical encounter registration system of the present invention;
fig. 3 is a flow chart of a medical treatment registration system based on a blockchain according to the present invention.
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.
Referring to fig. 1-3, the present invention provides the following technical solutions: a medical treatment registration system based on a block chain comprises a medical graphic display module, a micro-expression recognition module, a pain grade classification module, a recommended registration module, a fee payment module, an intelligent positioning module, a screen display module and a block chain recording module;
the medical graphic display module is used for guiding the patient to carry out self-checking and recording a video for system analysis; the micro expression recognition module is used for capturing micro expression changes of the patient in the self-checking process; the pain grade classification module is used for deducing the pain grade of the patient according to the facial expression change of the patient; the recommending registration module is used for recommending patients to register according to the results obtained by the medical graphic module, the micro-expression recognition module and the pain grade classification module and by integrating the actual conditions of doctors in the hospital; the fee clearing module is used for paying and refunding the registered fee; the intelligent positioning module is used for carrying out accurate positioning and confirming whether a patient arrives at a hospital or not; the screen display module is used for displaying the registration information on a mobile phone screen; the block chain recording module is used for recording various behavior data of the patient during registration and recording the loss behavior of the patient;
the output end of the medical graphic representation module is connected with the input end of the micro-expression recognition module; the output end of the micro-expression recognition module is connected with the input end of the pain grade classification module; the output end of the pain grade classification module is connected with the input end of the recommended registration module; the output end of the recommended registration module is connected with the input end of the expense settlement module; the output end of the fee paying module is connected with the input ends of the intelligent positioning module and the block chain recording module; the output end of the intelligent positioning module is connected with the output end of the screen display module; the output end of the block chain recording module is connected with the input ends of the pain grade classification module and the expense clearing module.
The medical illustration module comprises the following units:
the detection unit is used for detecting whether the whole body of the patient is within the range of the camera;
the figure unit is used for setting a figure of the body pressing part and guiding the patient to carry out self-checking;
the voice unit is used for carrying out voice reminding;
the video recording unit is used for recording videos in the self-checking process;
the output end of the detection unit is connected with the input end of the voice unit; the output end of the graphic unit is connected with the input end of the voice unit; the output end of the video recording unit is connected with the input end of the micro expression recognition module.
The micro expression recognition module comprises the following units:
the micro-expression recognition unit is used for collecting micro-expression changes of the face of the human face;
an eyebrow detecting unit for detecting a variation range of eyebrows, thereby determining a pain level score;
a mouth corner detection unit for detecting a mouth opening amplitude, thereby determining a pain level score;
a facial muscle line detection unit for determining a pain level score according to the degree of twitch of facial lines;
the output end of the micro expression recognition unit is connected with the input ends of the eyebrow detection unit, the mouth corner detection unit and the face muscle line detection unit; the output ends of the eyebrow detection unit, the mouth corner detection unit and the face muscle line detection unit are connected with the pain grade classification module.
The pain grade score is calculated by the following specific steps:
s4-1, in an eyebrow detection unit, acquiring the position of the eyebrow of a patient in an initial state, and performing tangent processing on the eyebrow in the up-down direction, wherein the highest tangent point is marked as A, and the lowest tangent point is marked as B;
s4-2, collecting the eyebrow position of the patient in each self-checking step, and cutting the eyebrow vertically, with the highest cutting point marked as A i The lowest tangent point is marked as B i
S4-3, according to the formula:
Figure GDF0000017937810000151
wherein, X 1 Scoring an eyebrow detection unit pain level; l is 1 Is a proportionality coefficient of 1;
calculating to obtain an eyebrow detection unit pain grade score;
s4-4, in the mouth corner detection unit, the mouth is in a closed state in the initial state, the mouth opening amplitude of the patient in each step of self-checking is collected, the area of the opening is recorded and recorded as S i
S4-5, according to the formula:
Figure GDF0000017937810000161
wherein, X 2 Scoring the pain level detected by the mouth corner detection unit; l is 2 A proportionality coefficient of 2;
calculating a pain grade score detected by the mouth corner detection unit;
s4-6, in the face muscle line detection unit, the face muscle lines are in a normal state in an initial state, and the twitch degree of the face muscle lines of the patient in each step of self-checking is collected, wherein the twitch degree is the change amplitude of the face muscle lines;
s4-7, extracting each part of lines according to the data collected in S4-6, drawing a plane sketch of the lines of the muscles of the face of the patient according to the pain face plane sketch in the historical data, and ensuring that the sizes of the lines are the same as those of the pain face plane sketch in the historical data;
s4-8, establishing a coordinate system by taking the central point of the plane sketch as an origin, selecting N key points for the plane sketch of the muscle line of the face of the current patient mentioned in S4-7 and the painful face plane sketch in the historical data, and recording the coordinate condition, wherein the coordinates of the N key points of the plane sketch of the muscle line of the face of the current patient are recorded as a set M { (a) 1 ,b 1 )、(a 2 ,b 2 )、……、 (a n ,b n ) N key point coordinates of the painful facial plane sketch in history are recorded as set M 2 ={(c 1 ,d 1 )、(c 2 ,d 2 )、……、(c n ,d n )};
S4-9, according to the formula:
Figure GDF0000017937810000171
wherein, X 3 Scoring the pain level detected by the facial muscle line detection unit; l is 3 A proportionality coefficient of 3;
calculating to obtain a pain grade score of the facial muscle line detection unit;
the pain level classification module comprises the following elements:
the data receiving unit is used for receiving the storage information transmitted by the block chain recording module and providing the storage information to the patient checking unit;
the patient checking unit is used for checking whether the patient is a first patient or a repeated patient, the first patient is a patient who is registered for the first time in the hospital, and the repeated patient is a patient who is registered for two times or more in the hospital;
a pain scoring unit for calculating a final pain score of the patient in each step of the self-examination;
in a first patient, according to the eyebrow detection unit pain level score, the mouth corner detection unit pain level score and the face muscle line detection unit pain level score obtained in the micro expression recognition module, an initial system weight is prepared, and according to a formula:
X general assembly =w 1 X 1 +w 2 X 2 +w 3 X 3
Wherein, X General (1) Patient self-test final pain score at each step, w 1 、w 2 、w 3 Respectively corresponding to the system scoring weights of the eyebrow detection unit, the mouth corner detection unit and the face muscle line detection unit;
in repeated patients, the system initial weight is not prepared, and the weight is adjusted according to the patient medical record prescribed by the doctor in the previous diagnosis in the following way:
facial expression reaction capacities including invalid, dull, normal and better, which are diagnosed by doctors, exist in the patient medical records; the weights of the eyebrow detection unit, the mouth corner detection unit and the face muscle line detection unit are w 10 、w 11 、w 1 、w 12 ;w 20 、w 21 、w 2 、w 22 ; w 30 、w 31 、w 3 、w 32
Thus in a repetitive patient, according to the formula:
X general assembly =w i X 1 +w j X 2 +w k X 3
Wherein, w i 、w j 、w k Respectively corresponding to each unit weight adjusted according to the diagnosis of a doctor;
the pain grade unit is used for classifying the pain grade of the part according to the final pain score of the patient in each step of self-examination;
the pain rating units are classified as follows:
setting a scoring threshold to X max 、X min
If X General assembly Greater than X max This is indicative of a very painful area;
if X General assembly Less than X min Representing no pain at this site;
if X General assembly In the interval [ X min ,X max ]Inner, representing pain at this site;
the output end of the data receiving unit is connected with the input end of the patient checking unit; the output end of the patient test unit is connected with the input end of the pain scoring unit; the output end of the pain scoring unit is connected with the input end of the pain grade unit.
The recommendation registration module comprises the following units:
the department recommending unit is used for determining which department the department should be registered in according to the pain grades of all parts transmitted by the pain grade classifying module, namely, establishing a registered department according to the parts with pain or very pain;
the doctor recommending unit is used for recommending registered doctors;
the recommended registered doctor mode is as follows:
for very painful patients, specialist category doctors were recommended; for general patients, a general physician is recommended;
preferentially recommending doctors with a small number of registered numbers on the day according to the registration date;
the output end of the department recommending unit is connected with the input end of the doctor recommending unit.
The fee clearing module comprises the following units:
the data unit is used for transmitting data with the block chain recording platform;
the payment unit is used for registering and paying;
the fee refunding unit is used for refunding fees, and the refunding modes comprise the following two modes:
the patient cancels the registration one day before the registration day, and the registration fee paid by the patient is returned in full amount;
the patient pays the deposit due to the credit behavior, and the deposit is returned in full amount after the visit is finished;
the fee clearing module is connected with a payment platform;
the output end of the payment unit is connected with the input end of the data unit; the output end of the data unit is connected with the input end of the refund unit.
The intelligent positioning module comprises the following units:
the date confirmation unit is used for reading the registration date after the registration is successful, determining whether the current day is the registration date or not, and reminding the current day by using a mobile phone;
the address positioning unit is used for carrying out address positioning on the registered hospital after the registration is successful;
the distance verification unit is used for measuring and calculating the distance between the patient and the hospital after the registration is successful and the date confirmation unit confirms that the current day is the registration date;
the output end of the date confirmation unit is connected with the input ends of the address positioning unit and the distance verification unit; and the output end of the address positioning unit is connected with the input end of the distance verification unit.
The screen display module includes the following units:
the reading unit is used for reading the related information transmitted by the intelligent positioning module;
the starting unit is used for starting the registration software, reading the registration information and displaying the registration information on a screen of the mobile phone;
the starting steps of the starting unit are as follows:
s9-1, determining whether the current day is a registration day according to the information condition in the intelligent positioning module read by the reading unit, and if so, entering the step S9-2; if not, ending;
s9-2, according to the distance between the patient and the hospital read by the reading unit, if the distance is smaller than a threshold value Y, the starting unit starts registration software, departments and doctors in the registration information are directly displayed on a mobile phone screen, and the condition that the patient needs to enter the registration software again for inquiring is avoided;
the output end of the reading unit is connected with the input end of the starting unit.
The block chain recording module comprises the following units:
the block chain registration recording unit is used for recording the registration condition of the patient, and after the user successfully registers, the registration information and the doctor seeing information are written into the block chain registration recording unit for storage;
the appointment losing behavior recording unit is used for recording and storing the behavior that the patient is not available for treatment on time after registration;
the feedback unit is used for making corresponding feedback on the pain grade classification module and the expense clearing module according to the registration record of the block chain registration recording unit and the loss behavior record in the loss behavior recording unit, namely whether the patient needs to adjust the pain grading weight and whether the registration needs to pay the deposit;
and the output ends of the block chain registration recording unit and the loss behavior recording unit are connected with the input end of the feedback unit.
In the embodiment, a patient J is a patient who is repeatedly registered, after the patient J logs in a registered mobile phone terminal, the patient J is prompted by voice to perform touch pressing on each part according to graphic information, and a video is recorded and transmitted to a micro-expression recognition module;
the micro expression recognition module collects the eyebrow position of a patient J in an initial state in an eyebrow detection unit, and performs tangent processing on the eyebrow in the up-down direction, wherein the highest tangent point is marked as A, and the lowest tangent point is marked as B;
collecting the eyebrow position of patient J in each self-checking step, making tangent treatment on the eyebrow in up-down direction, and recording the highest tangent point as A i The lowest tangent point is marked as B i
According to the formula:
Figure GDF0000017937810000221
calculating to obtain the pain grade score X of the eyebrow detection unit 1
In the mouth corner detection unit, the mouth is in a closed state in an initial state, the mouth opening amplitude of the patient J in each step of self-checking is collected, the area of the opening is recorded and is recorded as S i
According to the formula:
Figure GDF0000017937810000222
calculating the pain grade score X detected by the mouth corner detection unit 2
In the face muscle line detection unit, the face muscle lines are in a normal state in an initial state, and the twitch degree of the face muscle lines of the patient J in each step of self-checking state is acquired, wherein the twitch degree is the change amplitude of the face muscle lines;
extracting each part of lines, and drawing a plane sketch of the lines of the facial muscles of the current patient according to the pain facial plane sketch in the historical data to ensure that the sizes of the lines are the same as those of the pain facial plane sketch in the historical data;
establishing a coordinate system by taking a central point of the plane sketch as an origin, selecting N key points, and recording the coordinate condition, wherein the coordinates of the N key points of the plane sketch of the J face muscle line of the current patient are recorded as a set M { (a) 1 ,b 1 )、(a 2 ,b 2 )、……、(a n ,b n ) N key point coordinates of the painful facial plane sketch in history are recorded as set M 2 ={(c 1 ,d 1 )、(c 2 , d 2 )、……、(c n ,d n )};
According to the formula:
Figure GDF0000017937810000231
calculating to obtain pain grade score X of facial muscle line detection unit 3
After inquiry, the repeated patient J is identified as a normal state in the micro-expression, but suffers from cervical spondylosis;
according to the formula:
X general assembly =w 1 X 1 +w 2 X 2 +w 3 X 3
Calculating to obtain each total score of each part of the patient J after being pressed;
setting a scoring threshold to X max 、X min
The total score of J shoulder region of the patient was found to exceed X max The total score of cervical vertebra is in the interval [ X ] min ,X max ]In the interior, no other part exceeds X min (ii) a Therefore, the shoulder pain and the cervical vertebra pain are judged;
according to the fact that the shoulder is very painful, the cervical vertebra is painful, and the cervical spondylosis is caused, the fact that the cervical vertebra is registered in the spinal surgery is determined, and a specialist doctor is recommended;
calling the data of the block chain recording module, and finding that the condition of no registration and no treatment exists, so that a guarantee deposit is not needed to be paid;
after the registration is successful, the registration information is 'spine surgery, Liu doctor, 302 rd building'; the inquiry hospital is 'the first people hospital in the city'; 3 months and 23 afternoons;
patient J has arrived "city first person hospital" in the afternoon of 23 days in 3 months, and reading unit reads that the distance between patient J and "city first person hospital" is less than the distance threshold value, therefore the start unit sends information "spinal surgery, Liu doctor, 3 rd building 302 room" to the cell-phone screen on, therefore patient J need not bow for a long time, gets into the system and goes the inquiry, has reduced painful sense.
After the doctor visits, the doctor stores the relevant information of the doctor to the block chain recording module for later data use.
The working principle of the invention is as follows: the invention utilizes the medical graphic display module to display a graphic to guide the patient to carry out self-check, and records a video for analysis; capturing the micro-expression change of the patient in the self-checking process by using a micro-expression recognition module so as to determine the pain of the patient; using a pain grade classification module to infer the pain grade of the patient according to the facial expression change of the patient; the recommended registration module is used for recommending patients to register according to the results obtained by the medical graphic module, the micro-expression recognition module and the pain grade classification module and by integrating the actual conditions of doctors in hospitals; the registered fee is paid and refunded by using the fee clearing module, and the fee clearing module is communicated with the block chain recording module; the intelligent positioning module is used for carrying out accurate positioning, and whether the patient arrives at the hospital on the registration day after successful registration is confirmed; displaying the registration information on a mobile phone screen by using a screen display module; and recording various behavior data of the patient during registration by using the block chain recording module, recording the loss behavior of the patient, and making corresponding feedback.
It should be noted that, in this document, relational terms such as first and second, and the like are used solely to distinguish one entity or action from another entity or action without necessarily requiring or implying any actual such relationship or order between such entities or actions. Also, the terms "comprises," "comprising," or any other variation thereof, are intended to cover a non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements does not include only those elements but may include other elements not expressly listed or inherent to such process, method, article, or apparatus.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.

Claims (1)

1. The utility model provides a medical treatment registration system of seeing a doctor based on blockchain which characterized in that: the system comprises a medical graphic representation module, a micro-expression recognition module, a pain grade classification module, a recommended registration module, a fee payment module, an intelligent positioning module, a screen display module and a block chain recording module;
the medical graphic display module is used for guiding the patient to carry out self-checking and recording a video for system analysis; the micro expression recognition module is used for capturing micro expression changes of the patient in the self-checking process; the pain grade classification module is used for deducing the pain grade of the patient according to the facial expression change of the patient; the recommending registration module is used for recommending patients to register according to the results obtained by the medical graphic module, the micro-expression recognition module and the pain grade classification module and by integrating the actual conditions of doctors in the hospital; the fee clearing module is used for paying and refunding the registered fee; the intelligent positioning module is used for carrying out accurate positioning and confirming whether a patient arrives at a hospital or not; the screen display module is used for displaying the registration information on a mobile phone screen; the block chain recording module is used for recording various behavior data of the patient during registration and recording the loss behavior of the patient;
the output end of the medical graphic representation module is connected with the input end of the micro-expression recognition module; the output end of the micro-expression recognition module is connected with the input end of the pain grade classification module; the output end of the pain grade classification module is connected with the input end of the recommended registration module; the output end of the recommended registration module is connected with the input end of the expense settlement module; the output end of the fee clearing module is connected with the input ends of the intelligent positioning module and the block chain recording module; the output end of the intelligent positioning module is connected with the output end of the screen display module; the output end of the block chain recording module is connected with the input ends of the pain grade classification module and the expense clearing module;
the medical illustration module comprises the following units:
the detection unit is used for detecting whether the whole body of the patient is within the range of the camera;
the figure unit is used for setting a figure of the body pressing part and guiding the patient to carry out self-checking;
the voice unit is used for carrying out voice reminding;
the video recording unit is used for recording videos in the self-checking process;
the output end of the detection unit is connected with the input end of the voice unit; the output end of the graphic display unit is connected with the input end of the voice unit; the output end of the video recording unit is connected with the input end of the micro expression recognition module;
the micro expression recognition module comprises the following units:
the micro-expression recognition unit is used for collecting micro-expression changes of the face of the human face;
an eyebrow detecting unit for detecting a variation range of eyebrows, thereby determining a pain level score;
a mouth corner detection unit for detecting a mouth opening amplitude, thereby determining a pain level score;
a facial muscle line detection unit for determining a pain level score according to the degree of twitch of facial lines;
the output end of the micro expression recognition unit is connected with the input ends of the eyebrow detection unit, the mouth corner detection unit and the face muscle line detection unit; the output ends of the eyebrow detecting unit, the mouth corner detecting unit and the face muscle line detecting unit are connected with the pain grade classifying module;
the pain grade score is calculated by the following specific steps:
s4-1, in an eyebrow detection unit, acquiring the position of the eyebrow of a patient in an initial state, and performing tangent processing on the eyebrow in the up-down direction, wherein the highest tangent point is marked as A, and the lowest tangent point is marked as B;
s4-2, collecting the eyebrow position of the patient in each self-checking step, and cutting the eyebrow vertically, with the highest cutting point marked as A i The lowest tangent point is marked as B i
S4-3, according to the formula:
Figure FDF0000017937800000031
wherein, X 1 Scoring an eyebrow detection unit pain level; l is a radical of an alcohol 1 Is a proportionality coefficient of 1;
calculating to obtain an eyebrow detection unit pain grade score;
s4-4, in the mouth corner detection unit, the mouth is in a closed state in the initial state, the mouth opening amplitude of the patient in each step of self-checking is collected, and the opening is recordedArea of (d), denoted as S i
S4-5, according to the formula:
Figure FDF0000017937800000032
wherein, X 2 Scoring the pain level detected by the mouth corner detection unit; l is 2 A proportionality coefficient of 2;
calculating a pain grade score detected by the mouth corner detection unit;
s4-6, in the face muscle line detection unit, the face muscle lines are in a normal state in an initial state, and the twitch degree of the face muscle lines of the patient in each step of self-checking is collected, wherein the twitch degree is the change amplitude of the face muscle lines;
s4-7, extracting each part of lines according to the data collected in S4-6, drawing a plane sketch of the lines of the muscles of the face of the patient according to the pain face plane sketch in the historical data, and ensuring that the sizes of the lines are the same as those of the pain face plane sketch in the historical data;
s4-8, establishing a coordinate system by taking the central point of the plane sketch as an origin, selecting N key points for the plane sketch of the muscle line of the face of the current patient mentioned in S4-7 and the painful face plane sketch in the historical data, and recording the coordinate condition, wherein the coordinates of the N key points of the plane sketch of the muscle line of the face of the current patient are recorded as a set M { (a) 1 ,b 1 )、(a 2 ,b 2 )、……、(a n ,b n ) N key point coordinates of the painful facial plane sketch in history are recorded as set M 2 ={(c 1 ,d 1 )、(c 2 ,d 2 )、……、(c n ,d n )};
S4-9, according to the formula:
Figure FDF0000017937800000041
wherein X 3 Scoring the pain level detected by the facial muscle line detection unit; l is 3 A proportionality coefficient of 3;
calculating to obtain a pain grade score of the facial muscle line detection unit;
the pain rating classification module comprises the following elements:
the data receiving unit is used for receiving the storage information transmitted by the block chain recording module and providing the storage information to the patient checking unit;
the patient checking unit is used for checking whether the patient is a first patient or a repeated patient, the first patient is a patient who is registered for the first time in the hospital, and the repeated patient is a patient who is registered for two times or more in the hospital;
a pain scoring unit for calculating a final pain score of the patient in a state of each self-examination step;
in a first patient, according to the eyebrow detection unit pain level score, the mouth corner detection unit pain level score and the face muscle line detection unit pain level score obtained in the micro expression recognition module, an initial system weight is prepared, and according to a formula:
X general assembly =w 1 X 1 +w 2 X 2 +w 3 X 3
Wherein, X General assembly Patient self-test final pain score at each step, w 1 、w 2 、w 3 Respectively corresponding to the system scoring weights of the eyebrow detection unit, the mouth corner detection unit and the face muscle line detection unit;
in repeated patients, the system initial weight is not prepared, and the weight is adjusted according to the patient medical record prescribed by the doctor in the previous diagnosis, and the adjustment mode is as follows:
facial expression reaction capacities including invalid, dull, normal and better, which are diagnosed by doctors, exist in the patient medical records; the weights respectively corresponding to the eyebrow detection unit, the mouth corner detection unit and the face muscle line detection unit are w 10 、w 11 、w 1 、w 12 ;w 20 、w 21 、w 2 、w 22 ;w 30 、w 31 、w 3 、w 32
Thus in a repeat patient, according to the formula:
X general assembly =w i X 1 +w j X 2 +w k X 3
Wherein, w i 、w j 、w k Respectively corresponding to each unit weight adjusted according to the diagnosis of a doctor;
the pain grade unit is used for classifying the pain grade of the part according to the final pain score of the patient in each step of self-examination;
the pain rating units are classified as follows:
setting a scoring threshold to X max 、X min
If X General assembly Greater than X max This is indicative of a very painful area;
if X General assembly Less than X min Representing no pain at this site;
if X General assembly In the interval [ X min ,X max ]Inner, representing pain at this site;
the output end of the data receiving unit is connected with the input end of the patient checking unit; the output end of the patient test unit is connected with the input end of the pain scoring unit; the output end of the pain scoring unit is connected with the input end of the pain grade unit;
the recommendation registration module comprises the following units:
the department recommending unit is used for determining which department the department should be registered in according to the pain grades of all parts transmitted by the pain grade classifying module, namely, establishing a registered department according to the parts with pain or very pain;
the doctor recommending unit is used for recommending registered doctors;
the recommended registered doctor mode is as follows:
for very painful patients, specialist category doctors were recommended; for general patients, a general physician is recommended;
preferentially recommending doctors with a small number of registered numbers on the day according to the registration date;
the output end of the department recommending unit is connected with the input end of the doctor recommending unit;
the fee clearing module comprises the following units:
the data unit is used for transmitting data with the block chain recording platform;
the payment unit is used for registering and paying;
the fee refunding unit is used for refunding fees, and the fee refunding modes comprise the following two modes:
the patient cancels the registration one day before the registration day, and the registration fee paid by the patient is returned in full amount;
the patient pays the deposit due to the credit behavior, and the deposit is returned in full amount after the visit is finished;
the fee clearing module is connected with a payment platform;
the output end of the payment unit is connected with the input end of the data unit; the output end of the data unit is connected with the input end of the fee refunding unit;
the intelligent positioning module comprises the following units:
the date confirmation unit is used for reading the registration date after the registration is successful, determining whether the current day is the registration date or not, and reminding the current day by using a mobile phone on the registration date;
the address positioning unit is used for positioning the address of the registration hospital after the registration is successful;
the distance verification unit is used for measuring and calculating the distance between the patient and the hospital after the registration is successful and the date confirmation unit confirms that the current day is the registration date;
the output end of the date confirmation unit is connected with the input ends of the address positioning unit and the distance verification unit; the output end of the address positioning unit is connected with the input end of the distance verification unit;
the screen display module includes the following units:
the reading unit is used for reading the related information transmitted by the intelligent positioning module;
the starting unit is used for starting the registration software, reading the registration information and displaying the registration information on a screen of the mobile phone;
the starting steps of the starting unit are as follows:
s9-1, determining whether the current day is a registration day according to the information condition in the intelligent positioning module read by the reading unit, and if so, entering the step S9-2; if not, ending;
s9-2, according to the distance between the patient and the hospital read by the reading unit, if the distance is smaller than a threshold value Y, the starting unit starts registration software, departments and doctors in the registration information are directly displayed on a mobile phone screen, and the patient is prevented from entering the registration software again to inquire;
the output end of the reading unit is connected with the input end of the starting unit;
the block chain recording module comprises the following units:
the block chain registration recording unit is used for recording the registration condition of the patient, and after the user successfully registers, the registration information and the doctor seeing information are written into the block chain registration recording unit for storage;
the appointment behavior recording unit is used for recording and storing the behavior that the patient does not see a doctor on time after registration;
the feedback unit is used for making corresponding feedback on the pain grade classification module and the expense clearing module according to the registration record of the block chain registration recording unit and the loss behavior record in the loss behavior recording unit, namely whether the patient needs to adjust the pain grading weight and whether the registration needs to pay the deposit;
and the output ends of the block chain registration recording unit and the loss behavior recording unit are connected with the input end of the feedback unit.
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Address after: Room 01 and 02, 5th Floor, Building 3, Guoce Technology Headquarters Space, No. 38 Tangxun North Road, Donghu New Technology Development Zone, Wuhan City, Hubei Province 430000

Patentee after: Wuhan Topyourself Informtion Technoligy Development Co.,Ltd.

Country or region after: China

Address before: Room 01 and 02, 5th Floor, Building 3, Guoce Technology Headquarters Space, No. 38 Tangxun North Road, Donghu New Technology Development Zone, Wuhan City, Hubei Province 430000

Patentee before: Wuhan Synchronous Remote Information Technology Development Co.,Ltd.

Country or region before: China