CN113921132A - Postoperative guiding method and system for orthopedic surgery - Google Patents
Postoperative guiding method and system for orthopedic surgery Download PDFInfo
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Abstract
The invention provides a postoperative guidance method and a postoperative guidance system for orthopedic surgery, wherein the method comprises the following steps: obtaining basic information of a first user, wherein the basic information comprises bone information of the first user; obtaining surgical information of a first user; constructing a bone grade and operation grade evaluation database based on the big data; inputting the basic information and the operation information into a bone grade and operation grade evaluation database to obtain a first bone grade and a first operation grade; obtaining a first fracture position through operation information to construct a first recovery scheme data set; and performing scheme screening on the first recovery scheme data set through the first bone quality grade and the first operation grade to obtain a first postoperative guidance scheme for postoperative guidance. The technical problem of poor stability caused by high requirements on professional level of medical staff due to the fact that a postoperative recovery scheme is obtained mainly depending on experience of the medical staff in the prior art is solved.
Description
Technical Field
The invention relates to the technical field of artificial intelligence correlation, in particular to a postoperative guidance method and a postoperative guidance system for orthopedic surgery.
Background
The postoperative guidance and training of orthopedic patients are helpful for accelerating postoperative recovery speed of the patients and reducing the repeated probability of the disease, so that an effective and reasonable postoperative recovery scheme has an important effect on rehabilitation of the orthopedic patients.
The existing orthopedic postoperative recovery scheme mainly adopts a general scheme that medical workers rely on experience to combine with the illness state of patients to obtain recovery, and the mode has high requirements on the professional level of the medical workers, and careless mistakes can be made by artificial judgment, so that certain risks exist.
However, in the process of implementing the technical solution of the invention in the embodiments of the present application, the inventors of the present application find that the above-mentioned technology has at least the following technical problems:
in the prior art, the postoperative recovery scheme is obtained mainly depending on the experience of medical workers, so that the requirement on the professional level of the medical workers is high, and the technical problem of poor stability exists.
Disclosure of Invention
The embodiment of the application provides a postoperative guidance method and a postoperative guidance system for orthopedic surgery, and solves the technical problem that in the prior art, the requirement on the professional level of medical staff is high due to the fact that a postoperative recovery scheme is obtained mainly by relying on the experience of the medical staff, and the stability is weak. Grading the bone information of the patient by analyzing the bone information of the patient such as bone density and the like to obtain a bone grade; grading the operation information of the patient to obtain an operation grade; the bone grade and operation grade evaluation database is obtained by storing the multiple groups of bone grades and the corresponding multiple groups of operation grades in a simultaneous manner, and is used for evaluating the bone grade and the operation grade of a subsequent patient according to the bone condition and the operation condition; reading the surgical fracture position information of the patient, generating a plurality of groups of recovery scheme data sets based on the fracture position information, and screening the plurality of groups of recovery scheme data sets based on the bone grade and the surgical grade to obtain a surgical guidance scheme meeting the physical requirements of the patient. The recovery scheme is automatically generated through an intelligent system, medical personnel do not need to be relied on, the application range is wider, and the technical effect of improving the generation stability of the postoperative recovery scheme is achieved.
In view of the above problems, the embodiments of the present application provide a method and a system for guiding an orthopedic operation after surgery.
In a first aspect, the present embodiments provide a method for guiding an orthopedic operation after a surgery, wherein the method is applied to a system for guiding after the surgery, and the method includes: obtaining basic information of a first user, wherein the basic information comprises bone information of the first user; obtaining surgical information of the first user, wherein the surgical information comprises surgical information of the first user performing an orthopedic surgery; constructing a bone grade and operation grade evaluation database based on the big data; inputting the basic information and the operation information into the bone quality grade and operation grade evaluation database to obtain a first bone quality grade and a first operation grade of the first user; obtaining a first fracture location of the first user from the surgical information; constructing a postoperative recovery scheme according to the first fracture position to obtain a first recovery scheme data set; and performing scheme screening and post-scheme adjustment on the first recovery scheme data set through the first bone quality grade and the first operation grade to obtain a first post-operation guidance scheme, and performing post-operation guidance of the first user through the first post-operation guidance scheme.
In another aspect, an embodiment of the present application provides a post-operative guidance system for an orthopedic operation, wherein the system includes: a first obtaining unit, configured to obtain basic information of a first user, where the basic information includes bone information of the first user; a second obtaining unit, configured to obtain surgical information of the first user, where the surgical information includes surgical information of the first user performing an orthopedic surgery; a first construction unit for constructing a bone grade and surgery grade assessment database based on big data; a first processing unit for inputting the basic information and the surgical information into the bone grade and surgical grade assessment database, obtaining a first bone grade and a first surgical grade of the first user; a third obtaining unit for obtaining a first fracture position of the first user through the surgical information; the second processing unit is used for constructing a postoperative recovery scheme according to the first fracture position to obtain a first recovery scheme data set; a first execution unit, configured to perform scheme post-screening adjustment on the first recovery scheme data set through the first bone quality grade and the first surgical grade to obtain a first post-operative guidance scheme, and perform post-operative guidance of the first user through the first post-operative guidance scheme.
In a third aspect, an embodiment of the present application provides a post-operative guidance system for bone surgery, including a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the steps of the method according to any one of the first aspect when executing the program.
One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages:
obtaining basic information of a first user, wherein the basic information comprises bone information of the first user; obtaining surgical information of the first user, wherein the surgical information comprises surgical information of the first user performing an orthopedic surgery; constructing a bone grade and operation grade evaluation database based on the big data; inputting the basic information and the operation information into the bone quality grade and operation grade evaluation database to obtain a first bone quality grade and a first operation grade of the first user; obtaining a first fracture location of the first user from the surgical information; constructing a postoperative recovery scheme according to the first fracture position to obtain a first recovery scheme data set; performing scheme screening and adjustment on the first recovery scheme data set according to the first bone quality grade and the first operation grade to obtain a first postoperative guidance scheme, performing a technical scheme of postoperative guidance of the first user according to the first postoperative guidance scheme, and grading bone information of the patient by analyzing the bone information of the patient, such as bone density, to obtain a bone quality grade; grading the operation information of the patient to obtain an operation grade; the bone grade and operation grade evaluation database is obtained by storing the multiple groups of bone grades and the corresponding multiple groups of operation grades in a simultaneous manner, and is used for evaluating the bone grade and the operation grade of a subsequent patient according to the bone condition and the operation condition; reading the surgical fracture position information of the patient, generating a plurality of groups of recovery scheme data sets based on the fracture position information, and screening the plurality of groups of recovery scheme data sets based on the bone grade and the surgical grade to obtain a surgical guidance scheme meeting the physical requirements of the patient. The recovery scheme is automatically generated through an intelligent system, medical personnel do not need to be relied on, the application range is wider, and the technical effect of improving the generation stability of the postoperative recovery scheme is achieved.
The foregoing description is only an overview of the technical solutions of the present application, and the present application can be implemented according to the content of the description in order to make the technical means of the present application more clearly understood, and the following detailed description of the present application is given in order to make the above and other objects, features, and advantages of the present application more clearly understandable.
Drawings
FIG. 1 is a schematic flow chart of a method for guiding bone surgery after surgery according to an embodiment of the present application;
FIG. 2 is a schematic flow chart illustrating a post-operative guidance program updating method for orthopedic surgery according to an embodiment of the present application;
FIG. 3 is a schematic structural diagram of a post-operative guidance system for orthopedic surgery according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an exemplary electronic device according to an embodiment of the present application.
Description of reference numerals: the device comprises a first obtaining unit 11, a second obtaining unit 12, a first constructing unit 13, a first processing unit 14, a third obtaining unit 15, a second processing unit 16, a first executing unit 17, an electronic device 300, a memory 301, a processor 302, a communication interface 303 and a bus architecture 304.
Detailed Description
The embodiment of the application provides a postoperative guidance method and a postoperative guidance system for orthopedic surgery, and solves the technical problem that in the prior art, the requirement on the professional level of medical staff is high due to the fact that a postoperative recovery scheme is obtained mainly by relying on the experience of the medical staff, and the stability is weak. Grading the bone information of the patient by analyzing the bone information of the patient such as bone density and the like to obtain a bone grade; grading the operation information of the patient to obtain an operation grade; the bone grade and operation grade evaluation database is obtained by storing the multiple groups of bone grades and the corresponding multiple groups of operation grades in a simultaneous manner, and is used for evaluating the bone grade and the operation grade of a subsequent patient according to the bone condition and the operation condition; reading the surgical fracture position information of the patient, generating a plurality of groups of recovery scheme data sets based on the fracture position information, and screening the plurality of groups of recovery scheme data sets based on the bone grade and the surgical grade to obtain a surgical guidance scheme meeting the physical requirements of the patient. The recovery scheme is automatically generated through an intelligent system, medical personnel do not need to be relied on, the application range is wider, and the technical effect of improving the generation stability of the postoperative recovery scheme is achieved.
Summary of the application
The postoperative guidance and training of orthopedic patients are helpful for accelerating postoperative recovery speed of the patients and reducing the repeated probability of the disease, so that an effective and reasonable postoperative recovery scheme has an important effect on rehabilitation of the orthopedic patients. The existing orthopedic postoperative recovery scheme mainly adopts a general scheme that medical staff are dependent on experience and the illness state of a patient is recovered, the requirement on the professional level of the medical staff is high, careless mistakes can be made by manual judgment, and certain risks exist.
In view of the above technical problems, the technical solution provided by the present application has the following general idea:
the embodiment of the application provides a postoperative guidance method for orthopedic surgery, wherein the method is applied to a postoperative guidance system, and the method comprises the following steps: obtaining basic information of a first user, wherein the basic information comprises bone information of the first user; obtaining surgical information of the first user, wherein the surgical information comprises surgical information of the first user performing an orthopedic surgery; constructing a bone grade and operation grade evaluation database based on the big data; inputting the basic information and the operation information into the bone quality grade and operation grade evaluation database to obtain a first bone quality grade and a first operation grade of the first user; obtaining a first fracture location of the first user from the surgical information; constructing a postoperative recovery scheme according to the first fracture position to obtain a first recovery scheme data set; and performing scheme screening and post-scheme adjustment on the first recovery scheme data set through the first bone quality grade and the first operation grade to obtain a first post-operation guidance scheme, and performing post-operation guidance of the first user through the first post-operation guidance scheme.
Having thus described the general principles of the present application, various non-limiting embodiments thereof will now be described in detail with reference to the accompanying drawings.
Example one
As shown in fig. 1, the present application provides a method for guiding an orthopedic operation after operation, wherein the method is applied to a system for guiding after operation, and the method comprises:
s100: obtaining basic information of a first user, wherein the basic information comprises bone information of the first user;
specifically, the first user is an orthopedic post-operative patient served by a post-operative guidance system, including but not limited to: common debridement and suture, general limb fracture reduction plaster fixation, common fracture, hand and foot tendon repair, complicated hand trauma operation treatment, arthroscopic surgery, spine surgery, joint replacement surgery and other orthopedic surgery patients; the basic information of the first user is a data set characterizing the patient operation and the basic body information after the operation, including but not limited to: patient medical record information, patient operation information, patient bone density information, patient bone composition and proportion information, patient complication information, patient recovery condition information and other data sets. Further, the bone information of the first user is data which is obtained by extracting patient bone density information from the basic information and comprehensively analyzing the patient bone component composition and proportion information and represents the bone quality of the patient. Through right the sclerotin information of first user carries out the analysis, can match the higher postoperative recovery scheme of individuation degree for first user in the later step, establish the basis for the accuracy of intelligent generation postoperative recovery scheme, reached the technological effect that improves the feasibility of automatic generation postoperative recovery scheme.
S200: obtaining surgical information of the first user, wherein the surgical information comprises surgical information of the first user performing an orthopedic surgery;
specifically, the surgical information of the first user is the current orthopedic surgical information of the first user obtained by extracting the patient surgical information from the basic information, and includes but is not limited to: surgical information such as surgical location, surgical type, preoperative diagnostic conditions, preoperative plan, etc. Through operation information can be to postoperative patient's health and operation grade aassessment, the more comprehensive analysis of operation patient health condition of being convenient for, and then the postoperative recovery scheme that generates to agree with patient health condition has improved the intelligent system's of automatic generation orthopedics postoperative recovery scheme the feasibility of falling to the ground.
S300: constructing a bone grade and operation grade evaluation database based on the big data;
further, based on the inputting the basic information and the surgical information into the bone quality grade and surgical grade assessment database, obtaining a first bone quality grade and a first surgical grade of the first user, wherein the step S300 further includes:
s310: collecting bone density information of a user, and taking the bone density information as a first influence factor;
s320: collecting bone tissue component information of a user, and taking the bone tissue component information as a second influence factor;
s330: and constructing the bone grade and operation grade evaluation database according to the proportion distribution of the first influencing factor and the second influencing factor.
Specifically, the bone grade and operation grade evaluation database is a cloud database which is constructed based on big data and used for representing the bone grade and the operation grade of a patient, the cloud database is a novel method for sharing an infrastructure and is developed under the big background of cloud computing, the storage capacity of the database is greatly enhanced, repeated configuration of personnel, hardware and software is eliminated, and software and hardware are more easily upgraded. The construction method is not limited by the following examples:
bone grade construction: the physical conditions and the surgical conditions of various orthopedic patients in multiple hospitals are called through the interconnected consultation platform, and the bone density, the bone component composition and the proportion information representing the bone of the patient can be obtained on the basis of the basic information of the body of the patient, so that the bone of the patient is divided into different grades, exemplarily: the first influencing factor bone density is g/cm3The method mainly comprises the steps of distinguishing according to a bone density T value, wherein when the T value is larger than or equal to-1, the bone density of a patient is in a normal interval and is set as 0 grade, when the T value is smaller than-1 and larger than or equal to-2.5, the bone density is reduced and is set as 1 grade, when the T value is smaller than-2.5, osteoporosis is set as 3 grade, wherein the higher the grade is, the lower the bone quality is, and a softer mode is needed for recovery exercise of a corresponding postoperative recovery scheme; further, the bone components of the second influencing factor are classified mainly according to the ratio of organic matter, mainly bone collagen fiber bundles, mucopolysaccharidic protein and the like, which serve as a scaffold for bone and impart elasticity and toughness to the bone. The inorganic substance is mainly alkaline calcium phosphate, so that the bone is hard and stiff. When the ratio of organic substance to inorganic substance is 3:7, the most suitable is the toughness and hardness of bone, and when the ratio of organic substance to inorganic substance is [2.8:7.2,3.2:6.8 ]]When the ratio of organic matter to inorganic matter is in the range of [2:8,2.8:7.2 ] or (3.2:6.8,5: 5)]When the ratio of organic matter to inorganic matter is in the range of [0:10,2:8 ] or (5:5,10: 0)]And when the first user is in a state of 3 grades, adding the grades of the bone density and the grades of the bone components to obtain the grade representing the bone quality of the first user.
And (3) constructing the grade of the orthopedic operation: level 1: the operation is the common debridement and suture in clinic, the reduction and plaster fixation of the four limbs fracture, the bone traction operation of the fracture and the removal of tenosynovitis; and 2, stage: repairing tendon of hand and foot, internal fixation for fracture cutting and reduction, internal fixation and extraction, scraping osteomyelitis sinus, cutting and draining, etc.; and 3, level: complicated limb fracture and intra-articular fracture are cut, restored and internally fixed, complicated hand trauma is treated by operation, arthroscopic surgery and the like; 4, level: spinal surgery and joint replacement surgery.
The data of a plurality of groups of patients are collected through the interconnected cloud consultation platform to construct orthopedic data with wide coverage, then the bone grade and operation grade assessment database is constructed according to the bone grade construction rule and the orthopedic operation grade, and the bone grade and operation grade assessment database is stored in the cloud, so that the data can be conveniently called by a plurality of hospitals, the periodical update is preset, and the real-time performance of the content of the database is ensured.
S400: inputting the basic information and the operation information into the bone quality grade and operation grade evaluation database to obtain a first bone quality grade and a first operation grade of the first user;
specifically, the basic information and the operation information of the first user are read and input into the bone grade and operation grade evaluation database, and the bone grade of the first user can be quickly classified according to the bone information in the basic information and the bone surgery performed by the first user can be classified according to the constructed mature database. And further generating the quantified first bone quality grade and the quantified first surgical grade, wherein the quantified first bone quality grade and the quantified first surgical grade can be used for accurately representing the postoperative condition of the first user, and an information feedback basis is provided for further generating a postoperative recovery scheme more suitable for the first user.
S500: obtaining a first fracture location of the first user from the surgical information;
s600: constructing a postoperative recovery scheme according to the first fracture position to obtain a first recovery scheme data set;
specifically, the first fracture site is surgical site information extracted from the surgical information of the first user, and generally, a medical staff at an expert level provides a recovery plan data set for a patient according to the surgical site information and the condition of the patient, including but not limited to: the fixed time of the gypsum, the type of recovery exercise after the gypsum is removed, the duration corresponding to each type of recovery exercise, the diet strategy and other data; the first recovery plan data set is plan information for assisting postoperative rehabilitation of the patient and is output based on inference of an expert system, wherein, the expert system is an artificial intelligence computer program or a group of artificial intelligence computer programs which can solve complex problems in certain specific fields by applying a large amount of expert knowledge and reasoning methods, the expert system is composed of an inference engine, a knowledge base, a database, an interactive interface and knowledge acquisition respectively, wherein the first fracture site is provided with known data, thereby enabling an expert system to output information based on the constructed rules with logical rationality, therefore, the first recovery scheme data set is obtained, the effect of high conformity with the recovery scheme provided by expert medical personnel is achieved, the information which is predicted and inferred based on the expert system has accuracy and logicality, and accurate results are provided for the subsequent judgment.
S700: and performing scheme screening and post-scheme adjustment on the first recovery scheme data set through the first bone quality grade and the first operation grade to obtain a first post-operation guidance scheme, and performing post-operation guidance of the first user through the first post-operation guidance scheme.
Specifically, the first recovery plan data set represents all postoperative recovery plan data for similar surgery at the first surgical site, the first postoperative guidance plan is information obtained by performing screening adjustment on the first recovery plan data set through the first bone quality grade and the first surgical grade, and the screening mainly relates to type screening of postoperative rehabilitation training, which is exemplified by: if the first bone quality grade of the first user is higher, it indicates that the bone quality of the first user is poor, a relatively small and softer means is needed for recovery, and if the first surgery grade is higher, the plaster fixation time is needed to be increased, and the like. Furthermore, the model is preferably intelligently screened through scheme screening, the scheme screening model is an artificial intelligent model based on neural network training, the models are trained through multiple groups of bone levels, operation levels and corresponding postoperative recovery scheme data, after convergence is achieved, the obtained intelligent model can generate the first postoperative guidance scheme which is more suitable for the first user, and the technical effect of automatically generating the more accurate orthopedic operation guidance scheme is achieved.
Further, the method further includes step S800:
s810: obtaining a user data set, wherein the user data set comprises encrypted recovery data of users under a recovery scheme, and the user data set comprises a unique decryption key of each user;
s820: obtaining a first model training instruction, identifying the user data set through the scheme screening model according to the first model training instruction, and decrypting data through a unique decryption key in the user data set to obtain first decrypted data;
s830: training the scheme screening model through the first decrypted data to obtain a first training result of the scheme screening model;
s840: judging whether the first training result meets a first training result threshold value;
s850: and when the first training result meets the first training result threshold value, inputting the first bone quality grade and the first operation grade into the scheme screening model to obtain the first postoperative guide scheme.
Specifically, the user data set is postoperative recovery data and recovery scheme data of a plurality of orthopedic patients at the same surgical position, which are extracted from big data, the recovered scheme data and the recovered data are correspondingly stored in a list form, the recovered scheme data and the recovered data of each user are encrypted, each encryption result uniquely corresponds to each unique decryption key, and the unique decryption key set is independently stored in an offline manner, so that the key set stored on the line is prevented from being hijacked. When the scheme screening model needs to be trained, the scheme screening model is in communication connection with a database which independently stores the unique decryption key set in an off-line mode, all the unique decryption keys are read, the user data set is decrypted, the first decryption data are obtained after decryption, multiple groups of data are used, and each group of data comprises: when the scheme screening model reaches convergence, stopping training, and testing the output accuracy of the model by using a data set with the same part as the training data, wherein the proportion of the testing data to the training data is preferably 2:8, obtaining the first training result; the first training result threshold is the accuracy which is required to be achieved by preset model output and can be set according to practical application scenes, when the first training result meets the first training result threshold, the output accuracy of the scheme screening model is required, and the first bone quality grade and the first operation grade can be input into the scheme screening model to obtain the first post-operation guidance scheme after screening. Furthermore, the encryption process, the decryption process, the training process and the testing process of the user data are all processed in a non-visual mode through the scheme screening model, so that the safety of the privacy data of the user is guaranteed, and the safety of the system is improved.
Further, the post-operation guidance system is in communication connection with the first image capturing device, and the method further includes step S900:
s910: obtaining a first stage of rehabilitation according to the first post-operative guidance protocol;
s920: carrying out image acquisition time node distribution according to the first rehabilitation stage to obtain a first acquisition time node distribution result;
s930: acquiring, by the first image acquisition device, an image rehabilitation action based on the first acquisition time node distribution result to obtain a first image set;
s940: performing motion matching degree analysis through the first image set and the first post-operative guidance scheme to obtain a first analysis result;
s950: and obtaining a first correction scheme according to the first analysis result, and performing postoperative guidance on the first user through the first correction scheme.
Specifically, the first rehabilitation stage is a preset postoperative rehabilitation time for the first user according to the first postoperative guidance scheme, and a specific rehabilitation stage may be different according to different orthopedic surgeries, which is exemplified by: if the wrist is fractured, plaster is used for fixation, the first rehabilitation stage is preferably preset for 2 weeks, and the rehabilitation condition is observed; the second rehabilitation stage is 3-4 weeks, and whether the plaster can be removed or not is observed; the third rehabilitation stage is observed in weeks 5-7, the rehabilitation status is observed and the rehabilitation exercise scheme is provided, and the fourth rehabilitation stage is continuously observed in weeks 7-9. When the first rehabilitation stage is analyzed in the system, the first rehabilitation stage is set as the first rehabilitation stage, and after the first rehabilitation stage is analyzed, the second rehabilitation stage is updated to the first rehabilitation stage until the first user stops updating when rehabilitation is performed. Further, the first collection time node distribution result is that when the first user starts rehabilitation training, the image collection device deployed for evaluating the recovery condition of the first user, the time node of image collection by the image collection device is the same as the time node of rehabilitation training of the first user recommended by the first postoperative guidance scheme; the first image set is an image set acquired by an image acquisition device based on the first acquisition time node distribution result; further, performing training motion feature extraction of the first user on the first image set, preferably using a training motion feature extractor based on convolutional neural network training, comparing the extracted training motion feature of the first user with a standard motion provided by the first post-operative guidance plan, and storing difference information, including but not limited to: obtaining the first analysis result through information such as difference angles, difference distances and the like; furthermore, a first correction scheme for the training action of the first user is generated through the first analysis result of the characterization difference information, and the first user is guided, so that the technical effect of ensuring the stability of the first user in the recovery process is achieved.
Further, based on the motion matching degree analysis performed by the first image set and the first post-operative guidance plan, obtaining a first analysis result, step S940 further includes:
s941: collecting the biased habits of the first user according to the first image set and the first postoperative guidance scheme to obtain a first biased habit collection result;
s942: acquiring a time node identifier in the first image set, and acquiring a first deviation trend change curve according to the time node identifier and the first deviation habit acquisition result;
s943: and obtaining a first deviation reminding node, and carrying out postoperative guidance reminding on the first user according to the first deviation trend change curve and the first deviation reminding node.
Specifically, the deviation habit of the first user is habitual deviation angle, deviation distance and other information of the first user during rehabilitation training, and the deviation habits of the same group of rehabilitation training at the same time node are collected to obtain a first deviation habit collection result; the first deviation habit acquisition results under a plurality of time nodes are stored according to time sequence, information such as deviation angles and deviation distances according to time changes is obtained, a curve is drawn to obtain a first deviation trend change curve, the action deviation condition of the rehabilitation training of the first user can be represented through the first deviation trend change curve, and the first deviation habit acquisition results can be timely reminded when abnormal deviation trends occur. The following are exemplary: if the first user rehabilitation training action is not deviated, but the movement deviation at the symmetrical position is too large, the symmetrical movement is inconsistent, and an ideal recovery effect cannot be achieved. The first deviation trend change curve can remind the user when the first user rehabilitation training action meets the requirement but the accumulated deviation trend appears, so that the applicability of the postoperative recovery scheme is improved.
Further, the method S900 further includes step S960:
s961: obtaining feedback information of the first user, wherein the feedback information is feedback information of the first user in a postoperative recovery action process, and the feedback information is provided with a feedback time identifier;
s962: analyzing the actual adaptation degree of the user according to the feedback information and the first analysis result to obtain a first adaptation degree analysis result;
s963: and correcting the first postoperative guidance scheme of the first user according to the first fitness analysis result.
Specifically, the feedback information of the first user is feedback information of the first user performing rehabilitation training using the first postoperative guidance plan, including but not limited to: patient complaint information, the recovery condition of the joint range of motion of the patient, and the like; further, the feedback information of the first user under each time node and the time nodes are correspondingly stored, and sequencing is performed according to the time sequence to obtain a feedback information set of the first user changing along with the time; the feedback information can determine the adaptation degree of the patient to the current postoperative guidance scheme, namely: whether a certain action amplitude of rehabilitation training is too large, the actual recovery effect of the first user and the like; and then, by combining the first analysis result representing the degree of difference of the rehabilitation training action of the first user, whether the occurrence factor of the degree of difference is an error caused by subjective factors such as pain of the first user or objective factors of joint limitation of the first user is obtained, so that the rehabilitation training action caused by the first postoperative guidance scheme of the first user not conforming to the objective factors of the first user is optimized, and the postoperative rehabilitation guidance scheme more suitable for the first user is obtained. The method comprises the steps of avoiding the damage to the first user caused by the forced correction of errors caused by objective factors of joint limitation of the first user, dynamically optimizing a first postoperative guidance scheme of the first user based on real-time monitoring recovery state information, and guaranteeing the body state of the first user in the recovery process.
Further, as shown in fig. 2, the method step S960 further includes:
s964: obtaining a periodic evaluation result of the first user according to the first fitness analysis result and the first analysis result;
s965: performing periodic recovery grading according to the periodic evaluation result to obtain a first grading result;
s966: and adjusting a subsequent postoperative guidance scheme according to the first grading result.
Specifically, the periodic evaluation result of the first user is a plurality of analyzed first postoperative guidance plans corresponding to a plurality of rehabilitation stages of the first user, the periodic evaluation result and the rehabilitation stage of the first user correspond to each other, the periodic evaluation result of the first user is stored according to a time sequence according to a time node corresponding to the rehabilitation stage, a plurality of groups of postoperative guidance plans-rehabilitation stage information along with the time sequence are obtained and recorded as the first grading result, and the first grading result includes a rehabilitation stage corresponding to the postoperative guidance plan needing to be corrected and a rehabilitation stage corresponding to the postoperative guidance plan not needing to be corrected; further, when the recovery stage corresponding to the postoperative guidance scheme needing to be corrected is before the recovery stage time sequence corresponding to the postoperative guidance scheme needing not to be corrected, the postoperative guidance scheme needing not to be corrected is adopted, and the postoperative guidance scheme in the period before the time sequence is adopted immediately after the postoperative guidance scheme needing to be corrected is adopted. By means of the postoperative guidance scheme after synchronous correction in the later rehabilitation stage, the stable state of postoperative recovery of the first user is guaranteed, and the landing possibility of the postoperative guidance system is improved.
In summary, the method and system for guiding the bone surgery provided by the embodiment of the present application after the surgery have the following technical effects:
1. the embodiment of the application provides a postoperative guidance method and a postoperative guidance system for orthopedic surgery, and solves the technical problem that in the prior art, the requirement on the professional level of medical staff is high due to the fact that a postoperative recovery scheme is obtained mainly by relying on the experience of the medical staff, and the stability is weak. Grading the bone information of the patient by analyzing the bone information of the patient such as bone density and the like to obtain a bone grade; grading the operation information of the patient to obtain an operation grade; the bone grade and operation grade evaluation database is obtained by storing the multiple groups of bone grades and the corresponding multiple groups of operation grades in a simultaneous manner, and is used for evaluating the bone grade and the operation grade of a subsequent patient according to the bone condition and the operation condition; reading the surgical fracture position information of the patient, generating a plurality of groups of recovery scheme data sets based on the fracture position information, and screening the plurality of groups of recovery scheme data sets based on the bone grade and the surgical grade to obtain a surgical guidance scheme meeting the physical requirements of the patient. The recovery scheme is automatically generated through an intelligent system, medical personnel do not need to be relied on, the application range is wider, and the technical effect of improving the generation stability of the postoperative recovery scheme is achieved.
Example two
Based on the same inventive concept as the method for guiding the bone surgery after the surgery in the previous embodiment, as shown in fig. 3, the present application provides a system for guiding the bone surgery after the surgery, wherein the system comprises:
a first obtaining unit 11, where the first obtaining unit 11 is configured to obtain basic information of a first user, where the basic information includes bone information of the first user;
a second obtaining unit 12, configured to obtain surgical information of the first user, where the surgical information includes surgical information of the first user performing an orthopedic surgery;
a first construction unit 13, the first construction unit 13 is used for constructing a bone grade and operation grade evaluation database based on big data;
a first processing unit 14, wherein the first processing unit 14 is configured to input the basic information and the surgical information into the bone quality grade and surgical grade assessment database, and obtain a first bone quality grade and a first surgical grade of the first user;
a third obtaining unit 15, wherein the third obtaining unit 15 is used for obtaining the first fracture position of the first user through the operation information;
a second processing unit 16, said second processing unit 16 being configured to perform a post-operative recovery plan construction according to said first fracture position, obtaining a first recovery plan data set;
a first executing unit 17, wherein the first executing unit 17 is configured to perform scheme screening and post-scheme adjustment on the first recovery scheme data set through the first bone quality level and the first surgical level to obtain a first post-operative guidance scheme, and perform post-operative guidance of the first user through the first post-operative guidance scheme.
Further, the system further comprises:
a fourth obtaining unit, configured to obtain a user data set, where the user data set includes recovery data of encrypted users under a recovery scheme, and the user data set includes a unique decryption key of each user;
a fifth obtaining unit, configured to obtain a first model training instruction, identify the user data set through the scheme screening model according to the first model training instruction, and perform data decryption through a unique decryption key in the user data set to obtain first decryption data;
a sixth obtaining unit, configured to perform training of the scheme screening model through the first decrypted data, and obtain a first training result of the scheme screening model;
a first judging unit, configured to judge whether the first training result satisfies a first training result threshold;
a third processing unit, configured to, when the first training result satisfies the first training result threshold, input the first bone quality grade and the first surgical grade into the plan screening model to obtain the first postoperative guidance plan.
Further, the system further comprises:
a seventh obtaining unit for obtaining a first rehabilitation stage according to the first postoperative guidance schedule;
an eighth obtaining unit, configured to perform image acquisition time node distribution according to the first rehabilitation stage, and obtain a first acquisition time node distribution result;
a ninth obtaining unit, configured to perform, by the first image acquisition device, image rehabilitation action acquisition based on the first acquisition time node distribution result, to obtain a first image set;
a tenth obtaining unit, configured to perform motion matching degree analysis through the first image set and the first post-operative guidance plan, to obtain a first analysis result;
a second execution unit, configured to obtain a first correction scheme according to the first analysis result, and perform post-operation guidance on the first user through the first correction scheme.
Further, the system further comprises:
an eleventh obtaining unit, configured to perform biased habit acquisition of the first user according to the first image set and the first postoperative guidance scheme, and obtain a first biased habit acquisition result;
a twelfth obtaining unit, configured to obtain a time node identifier in the first image set, and obtain a first deviation trend change curve according to the time node identifier and the first deviation habit acquisition result;
a thirteenth obtaining unit, configured to obtain a first deviation reminding node, and perform postoperative guidance reminding of the first user according to the first deviation trend change curve and the first deviation reminding node.
Further, the system further comprises:
a fourteenth obtaining unit, configured to obtain feedback information of the first user, where the feedback information is feedback information of the first user during a postoperative recovery action, and the feedback information has a feedback time identifier;
a fifteenth obtaining unit, configured to perform user actual adaptation degree analysis according to the feedback information and the first analysis result, so as to obtain a first adaptation degree analysis result;
a third execution unit, configured to correct the first post-operative guidance scenario of the first user according to the first fitness analysis result.
Further, the system further comprises:
the first setting unit is used for acquiring bone density information of a user and taking the bone density information as a first influence factor;
the first acquisition unit is used for acquiring bone tissue component information of a user and taking the bone tissue component information as a second influence factor;
a second construction unit for constructing the bone grade and operation grade evaluation database according to the ratio distribution of the first influence factor and the second influence factor.
Further, the system further comprises:
a sixteenth obtaining unit, configured to obtain a periodic evaluation result of the first user according to the first fitness analysis result and the first analysis result;
a seventeenth obtaining unit, configured to perform periodic recovery binning according to the periodic evaluation result to obtain a first binning result;
a fourth execution unit, configured to perform adjustment of a subsequent postoperative guidance schedule according to the first classification result.
Exemplary electronic device
The electronic device of the embodiment of the present application is described below with reference to figure 4,
based on the same inventive concept as the postoperative guidance method of the orthopedic operation in the foregoing embodiments, the present application embodiment further provides a postoperative guidance system of the orthopedic operation, including: a processor coupled to a memory for storing a program that, when executed by the processor, causes a system to perform the method of any of the first aspects
The electronic device 300 includes: processor 302, communication interface 303, memory 301. Optionally, the electronic device 300 may also include a bus architecture 304. Wherein, the communication interface 303, the processor 302 and the memory 301 may be connected to each other through a bus architecture 304; the bus architecture 304 may be a Peripheral Component Interconnect (PCI) bus, an Extended Industry Standard Architecture (EISA) bus, or the like. The bus architecture 304 may be divided into an address bus, a data bus, a control bus, and the like. For ease of illustration, only one thick line is shown in FIG. 4, but this does not indicate only one bus or one type of bus.
The communication interface 303 is a system using any transceiver or the like, and is used for communicating with other devices or communication networks, such as ethernet, Radio Access Network (RAN), Wireless Local Area Network (WLAN), wired access network, and the like.
The memory 301 may be a ROM or other type of static storage device that can store static information and instructions, a RAM or other type of dynamic storage device that can store information and instructions, an electrically erasable Programmable read-only memory (EEPROM), a compact disc read-only memory (compact disc)
read-only memory, CD-ROM) or other optical disk storage, optical disk storage (including compact disk, laser disk, optical disk, digital versatile disk, blu-ray disk, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer, but is not limited to such. The memory may be self-contained and coupled to the processor through a bus architecture 304. The memory may also be integral to the processor.
The memory 301 is used for storing computer-executable instructions for executing the present application, and is controlled by the processor 302 to execute. The processor 302 is used for executing the computer-executable instructions stored in the memory 301, so as to implement the method for guiding the bone surgery after the surgery provided by the above-mentioned embodiment of the present application.
Optionally, the computer-executable instructions in the embodiments of the present application may also be referred to as application program codes, which are not specifically limited in the embodiments of the present application.
The embodiment of the application provides a postoperative guidance method and a postoperative guidance system for orthopedic surgery, and solves the technical problem that in the prior art, the requirement on the professional level of medical staff is high due to the fact that a postoperative recovery scheme is obtained mainly by relying on the experience of the medical staff, and the stability is weak. Grading the bone information of the patient by analyzing the bone information of the patient such as bone density and the like to obtain a bone grade; grading the operation information of the patient to obtain an operation grade; the bone grade and operation grade evaluation database is obtained by storing the multiple groups of bone grades and the corresponding multiple groups of operation grades in a simultaneous manner, and is used for evaluating the bone grade and the operation grade of a subsequent patient according to the bone condition and the operation condition; reading the surgical fracture position information of the patient, generating a plurality of groups of recovery scheme data sets based on the fracture position information, and screening the plurality of groups of recovery scheme data sets based on the bone grade and the surgical grade to obtain a surgical guidance scheme meeting the physical requirements of the patient. The recovery scheme is automatically generated through an intelligent system, medical personnel do not need to be relied on, the application range is wider, and the technical effect of improving the generation stability of the postoperative recovery scheme is achieved.
Those of ordinary skill in the art will understand that: the various numbers of the first, second, etc. mentioned in this application are only used for the convenience of description and are not used to limit the scope of the embodiments of this application, nor to indicate the order of precedence. "and/or" describes the association relationship of the associated objects, meaning that there may be three relationships, e.g., a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. The character "/" generally indicates that the former and latter associated objects are in an "or" relationship. "at least one" means one or more. At least two means two or more. "at least one," "any," or similar expressions refer to any combination of these items, including any combination of singular or plural items. For example, at least one (one ) of a, b, or c, may represent: a, b, c, a-b, a-c, b-c, or a-b-c, wherein a, b, c may be single or multiple.
In the above embodiments, the implementation may be wholly or partially realized by software, hardware, firmware, or any combination thereof. When implemented in software, may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions. When loaded and executed on a computer, cause the processes or functions described in accordance with the embodiments of the application to occur, in whole or in part. The computer may be a general purpose computer, a special purpose computer, a network of computers, or other programmable system. The computer finger
The instructions may be stored in a computer readable storage medium or transmitted from one computer readable storage medium to another computer readable storage medium, for example, where the computer instructions may be transmitted from one website site, computer, server, or data center to another website site, computer, server, or data center by wire (e.g., coaxial cable, fiber optic, Digital Subscriber Line (DSL)) or wirelessly (e.g., infrared, wireless, microwave, etc.). The computer-readable storage medium can be any available medium that can be accessed by a computer or a data storage device including one or more available media integrated servers, data centers, and the like. The usable medium may be a magnetic medium (e.g., floppy Disk, hard Disk, magnetic tape), an optical medium (e.g., DVD), or a semiconductor medium (e.g., Solid State Disk (SSD)), among others.
The various illustrative logical units and circuits described in this application may be implemented or operated upon by general purpose processors, digital signal processors, Application Specific Integrated Circuits (ASICs), Field Programmable Gate Arrays (FPGAs) or other programmable logic systems, discrete gate or transistor logic, discrete hardware components, or any combination thereof. A general-purpose processor may be a microprocessor, but in the alternative, the processor may be any conventional processor, controller, microcontroller, or state machine. A processor may also be implemented as a combination of computing systems, e.g., a digital signal processor and a microprocessor, a plurality of microprocessors, one or more microprocessors in conjunction with a digital signal processor core, or any other similar configuration.
The steps of a method or algorithm described in the embodiments herein may be embodied directly in hardware, in a software element executed by a processor, or in a combination of the two. The software cells may be stored in RAM memory, flash memory, ROM memory, EPROM memory, EEPROM memory, registers, hard disk, a removable disk, a CD-ROM, or any other form of storage medium known in the art. For example, a storage medium may be coupled to the processor such the processor can read information from, and write information to, the storage medium. In the alternative, the storage medium may be integral to the processor. The processor and the storage medium may reside in an ASIC, which may be disposed in a terminal. In the alternative, the processor and the storage medium may reside in different components within the terminal. These computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions specified in the flowchart flow or flows and/or block diagram block or blocks.
Although the present application has been described in conjunction with specific features and embodiments thereof, it will be evident that various modifications and combinations can be made thereto without departing from the spirit and scope of the application. Accordingly, the specification and figures are merely exemplary of the present application as defined in the appended claims and are intended to cover any and all modifications, variations, combinations, or equivalents within the scope of the present application. It will be apparent to those skilled in the art that various changes and modifications may be made in the present application without departing from the scope of the application. Thus, if such modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is intended to include such modifications and variations.
Claims (9)
1. A post-operative guidance method for orthopedic surgery, wherein the method is applied to a post-operative guidance system, the method comprising:
obtaining basic information of a first user, wherein the basic information comprises bone information of the first user;
obtaining surgical information of the first user, wherein the surgical information comprises surgical information of the first user performing an orthopedic surgery;
constructing a bone grade and operation grade evaluation database based on the big data;
inputting the basic information and the operation information into the bone quality grade and operation grade evaluation database to obtain a first bone quality grade and a first operation grade of the first user;
obtaining a first fracture location of the first user from the surgical information;
constructing a postoperative recovery scheme according to the first fracture position to obtain a first recovery scheme data set;
and performing scheme screening and post-scheme adjustment on the first recovery scheme data set through the first bone quality grade and the first operation grade to obtain a first post-operation guidance scheme, and performing post-operation guidance of the first user through the first post-operation guidance scheme.
2. The method of claim 1, wherein the method further comprises:
obtaining a user data set, wherein the user data set comprises encrypted recovery data of users under a recovery scheme, and the user data set comprises a unique decryption key of each user;
obtaining a first model training instruction, identifying the user data set through the scheme screening model according to the first model training instruction, and decrypting data through a unique decryption key in the user data set to obtain first decrypted data;
training the scheme screening model through the first decrypted data to obtain a first training result of the scheme screening model;
judging whether the first training result meets a first training result threshold value;
and when the first training result meets the first training result threshold value, inputting the first bone quality grade and the first operation grade into the scheme screening model to obtain the first postoperative guide scheme.
3. The method of claim 1, wherein the post-operative guidance system is communicatively coupled to a first image acquisition device, the method further comprising:
obtaining a first stage of rehabilitation according to the first post-operative guidance protocol;
carrying out image acquisition time node distribution according to the first rehabilitation stage to obtain a first acquisition time node distribution result;
acquiring, by the first image acquisition device, an image rehabilitation action based on the first acquisition time node distribution result to obtain a first image set;
performing motion matching degree analysis through the first image set and the first post-operative guidance scheme to obtain a first analysis result;
and obtaining a first correction scheme according to the first analysis result, and performing postoperative guidance on the first user through the first correction scheme.
4. The method of claim 3, wherein the performing an action matching analysis by the first set of images and the first post-operative guidance protocol to obtain a first analysis result further comprises:
collecting the biased habits of the first user according to the first image set and the first postoperative guidance scheme to obtain a first biased habit collection result;
acquiring a time node identifier in the first image set, and acquiring a first deviation trend change curve according to the time node identifier and the first deviation habit acquisition result;
and obtaining a first deviation reminding node, and carrying out postoperative guidance reminding on the first user according to the first deviation trend change curve and the first deviation reminding node.
5. The method of claim 4, wherein the method further comprises:
obtaining feedback information of the first user, wherein the feedback information is feedback information of the first user in a postoperative recovery action process, and the feedback information is provided with a feedback time identifier;
analyzing the actual adaptation degree of the user according to the feedback information and the first analysis result to obtain a first adaptation degree analysis result;
and correcting the first postoperative guidance scheme of the first user according to the first fitness analysis result.
6. The method of claim 1, wherein said entering said basic information and said surgical information into said bone grade and surgical grade assessment database, obtaining a first bone grade and a first surgical grade for said first user, further comprises:
collecting bone density information of a user, and taking the bone density information as a first influence factor;
collecting bone tissue component information of a user, and taking the bone tissue component information as a second influence factor;
and constructing the bone grade and operation grade evaluation database according to the proportion distribution of the first influencing factor and the second influencing factor.
7. The method of claim 5, wherein the method further comprises:
obtaining a periodic evaluation result of the first user according to the first fitness analysis result and the first analysis result;
performing periodic recovery grading according to the periodic evaluation result to obtain a first grading result;
and adjusting a subsequent postoperative guidance scheme according to the first grading result.
8. A postoperative guidance system for orthopedic surgery, wherein the system comprises:
a first obtaining unit, configured to obtain basic information of a first user, where the basic information includes bone information of the first user;
a second obtaining unit, configured to obtain surgical information of the first user, where the surgical information includes surgical information of the first user performing an orthopedic surgery;
a first construction unit for constructing a bone grade and surgery grade assessment database based on big data;
a first processing unit for inputting the basic information and the surgical information into the bone grade and surgical grade assessment database, obtaining a first bone grade and a first surgical grade of the first user;
a third obtaining unit for obtaining a first fracture position of the first user through the surgical information;
the second processing unit is used for constructing a postoperative recovery scheme according to the first fracture position to obtain a first recovery scheme data set;
a first execution unit, configured to perform scheme post-screening adjustment on the first recovery scheme data set through the first bone quality grade and the first surgical grade to obtain a first post-operative guidance scheme, and perform post-operative guidance of the first user through the first post-operative guidance scheme.
9. A postoperative guidance system for orthopedic surgery, comprising: a processor coupled with a memory for storing a program that, when executed by the processor, causes a system to perform the method of any of claims 1 to 7.
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116864133A (en) * | 2023-09-05 | 2023-10-10 | 中国医学科学院北京协和医院 | Personalized orthopedics rehabilitation plan recommendation system |
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| Publication number | Priority date | Publication date | Assignee | Title |
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| CN116864133A (en) * | 2023-09-05 | 2023-10-10 | 中国医学科学院北京协和医院 | Personalized orthopedics rehabilitation plan recommendation system |
| CN116864133B (en) * | 2023-09-05 | 2023-11-24 | 中国医学科学院北京协和医院 | Personalized orthopedics rehabilitation plan recommendation system |
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