640 results about "Postoperative recovery" patented technology

The invention discloses a method for predicting abnormal indexes after thoracic surgery, and relates to the technical field of medical treatment, and the main scheme is as follows: obtaining historical data related to thoracic surgery and preoperative examination, basic information, intraoperative and postoperative recovery data of a patient, and respectively calculating a preoperative comprehensive value, a basic information evaluation value, an intraoperative risk index and a postoperative recovery index; further obtaining a predicted postoperative infection index and a predicted cardiopulmonary function index; calculating a postoperative infection index threshold value and a cardiopulmonary function index threshold value according to the historical data; by comparing a prediction index with a threshold value, triggering corresponding early warning and formulating postoperative management and intervention strategies of different levels, the postoperative rehabilitation quality and safety of a thoracic surgery patient are improved, a comprehensive method is provided for postoperative management of the thoracic surgery patient, risks can be found in time, targeted measures can be taken, and the postoperative rehabilitation safety of the thoracic surgery patient is improved. The operation success rate and the patient life quality are improved.

The invention discloses a postoperative physical sign monitoring system based on medical information processing. The postoperative physical sign monitoring system comprises a data acquisition module, a physical sign feature extraction module, a postoperative physical sign evaluation model establishment module and a postoperative physical sign monitoring module. The invention belongs to the field of medical information processing, and particularly relates to a postoperative physical sign monitoring system based on medical information processing. Quantifying the total change trend of the heart rate fluctuation in the monitoring time; the quantitative basis is provided for the postoperative recovery process by integrating the blood pressure and heart rate changes; the sign monitoring effect is improved; focusing on dynamic adjustment through a time weight function, a recovery stage weight and an environment correction factor in a postoperative key time period; deviation weights are introduced for fluctuations of heart rates and blood pressures, loss coefficients are dynamically adjusted, segmented loss functions are designed according to physical sign values, conditions of different risk intervals are processed respectively, and the method adapts to uncertainty of individual differences and physical sign fluctuations of postoperative patients; and thus, the accuracy of post-operation sign monitoring is improved.

The invention relates to an orthopedic postoperative drainage liquid infection risk identification method. Drainage liquid is regarded as system output jointly driven by postoperative local immune regulation and wound recovery; capturing a nonlinear time sequence curve; first-order derived trend modeling is carried out; abrupt change after the change rate is stable is analyzed; establishing a postoperative recovery normal path framework, and forming a standard recovery trend library by using drainage fluid dynamic parameters of non-infected cases; comparing the Euclidean offset degree and directional change between the drainage parameter behavior vector of the current patient and the standard trajectory; the change is converted into a visual recovery offset map, and infection prediction data is measured from a multi-day trend angle; constructing and identifying local abnormal signal aggregation; forming a framework of infection event transition to obtain clinical infection nodes of qualitative change caused by quantitative change; according to the method, early-stage accurate recognition can be realized, the intervention opportunity can be obviously advanced, single threshold misjudgment is avoided, the recognition accuracy and specificity are improved, the model adaptability is improved, and the recognition interpretability is enhanced.

The invention discloses a temporal lobe epilepsy resection operation curative effect evaluation system based on brain image fusion features. According to the system, pre-operation and post-operation multi-mode brain image data including T1 weighted images, diffusion tensor imaging (DTI) and functional magnetic resonance imaging (fMRI) are collected and preprocessed, and a post-operation recovery model is generated through a recurrent neural network (RNN), a long-short-term memory network (LSTM) and other multi-time-sequence analysis methods. And the personalized curative effect evaluation module is combined with clinical characteristic data of the patient. And the report generation and visualization module generates an easy-to-understand report from the evaluation data through a visualization technology for medical teams to check and make decisions. Through multi-modal data fusion and an advanced algorithm model, the accuracy and reliability of curative effect evaluation are improved, the brain structure and function changes of the patient are comprehensively reflected, the clinical application prospect is wide, and the postoperative life quality of the patient is remarkably improved.

The invention relates to the technical field of maxillofacial deformity treatment, and discloses a maxillofacial deformity orthognathic post-operation follow-up visit system and method, the system comprises an image analysis model and a follow-up visit evaluation model, the image analysis model carries out multi-dimensional feature fusion processing on post-operation initial data, and the data comprises three-dimensional bone seam, occlusion function, soft tissue distribution and other feature data; and the follow-up assessment model performs dynamic interference suppression processing on the real-time physiological data stream and then inputs the feature generation layer to simulate a recovery track so as to generate a follow-up assessment instruction. The feature generation layer comprises an image preprocessing module and a dynamic feature generation module, and the dynamic feature generation module is obtained through combined training of multi-type historical postoperative data and real-time physiological parameters and comprises a feature analysis layer, a feature correction layer and an instruction triggering layer. According to the method, the system is applied, and multi-dimensional and intelligent follow-up assessment of postoperative recovery is achieved. According to the method, the accuracy and the real-time performance of follow-up visit are improved, and effective support is provided for postoperative recovery monitoring and intervention.

The invention discloses a tumor postoperative treatment staged planning method based on artificial intelligence. The method comprises the following steps: S1, constructing a multi-modal medical data set; s2, performing standardization processing on the acquired multi-modal medical data set to form a standardized data set which can be used for feature extraction; s3, generating a unified patient feature vector; s4, according to the characteristics of tumor postoperative treatment, dividing the whole treatment process into a postoperative immediate recovery stage, a postoperative recovery middle stage and a long-term follow-up visit stage, and defining a corresponding optimization target for each stage; s5, based on the patient feature vector and the optimization target of each stage, generating an initial treatment plan by using a deep ant colony algorithm; and S6, outputting a staged treatment scheme. According to the method, the professional and technical thresholds required by traditional modeling are reduced, and the universality and convenience of three-dimensional modeling are improved.

The invention relates to an anesthesia depth evaluation method, system and device and a storage medium. The method comprises the steps that first electroencephalogram information of a patient before anesthetic is applied and second electroencephalogram information of the patient after anesthetic is applied are obtained; determining a standard deviation unit for converting the intensity of the second electroencephalogram information into the intensity of the first electroencephalogram information, wherein the standard deviation unit represents the relationship between the first electroencephalogram information and the current change rate of the second electroencephalogram information relative to the average intensity of the first electroencephalogram information; determining target electroencephalogram information based on the standard deviation unit; determining category information of the anesthetic applied to the patient; based on the category information and the target electroencephalogram information, the anesthesia depth of the patient is determined. According to the method, the difference of different anesthetic drugs in physiological characteristics in the anesthesia state can be considered, and the judgment of the anesthesia depth of the patient is more accurate by removing the individual difference of the patient, so that the operation smoothness and the postoperative recovery effect are ensured.

The invention relates to the technical field of medical instruments, and discloses an angle-adjustable artificial hip joint prosthesis structure which comprises a thighbone connecting assembly, an acetabulum connecting assembly and a movable part movably connected between the thighbone connecting assembly and the acetabulum connecting assembly. The thighbone connecting assembly comprises a first connecting unit fixedly connected with the movable part, a thighbone stem detachably connected to the lower end of the first connecting unit, and a connecting screw fixedly connected to the upper end of the thighbone stem and in threaded connection with the first connecting unit. The acetabulum connecting assembly comprises a second connecting unit fixedly connected with the movable part and an acetabulum fixedly connected to the second connecting unit. Stable rotating connection is achieved through the double-shaft moving part, and a traditional easily-abraded spherical surface structure is replaced; the locking assembly is matched to realize personalized angle adjustment and locking; the femoral stem can be detached and replaced, and adaptability is improved; the surface composite coating promotes osseointegration and improves biocompatibility, the overall structure stability is high, adaptability is high, and postoperative recovery is fast.

The invention relates to the technical field of clinical nursing, in particular to a clinical nursing system for interventional operations, which can accurately identify and predict potential complications by performing deep neural network analysis in combination with preoperative medical history, intraoperative real-time physiological data and operation types. It is ensured that a nursing scheme can be finely adjusted based on individual differences of patients, complex physiological data can be processed through a deep neural network, key physiological data are recognized from the complex physiological data, the scheme is dynamically adjusted in the nursing process through a long-short-term memory network, and the nursing accuracy is improved. The change trend of data in the operation is deeply mined, the fluctuation of physiological indexes is tracked, the abnormity is timely identified, the potential risk is predicted, the nursing decision and the physiological state of the patient can be synchronously updated, the working efficiency of nursing personnel is optimized, and the postoperative recovery effect and comfort of the patient are improved.

The invention discloses an integrated management system and method for postoperative care of orthopedic patients, and relates to the technical field of medical treatment. Comprising a bone mineral density dynamic monitoring value, six-dimensional mechanical parameters of a joint movement track, emotion spectrum characteristics in voice interaction, microenvironment temperature and humidity changes collected by wearable equipment and skin surface pressure distribution; inputting the recovery data into a multi-modal decision-making model based on orthopedic biomechanics improvement, and generating a nursing scheme including a skeleton stress safety interval, a virtual rehabilitation scene dynamic parameter and an interdisciplinary intervention priority; the scheme parameters are dynamically optimized through a layered reinforcement learning framework special for the orthopedics department, and the deformation logic of the 3D printing brace and the correction strategy of the nursing robot are synchronously controlled; based on the postoperative complication space-time prediction map, a multidisciplinary collaborative response instruction strictly matched with the rehabilitation stage of the patient is triggered.

The invention relates to the technical field of medical information, in particular to a diabetic postoperative recovery condition prediction method, device and equipment, and the method comprises the steps: collecting historical specificity data and historical recovery condition data of historical diabetic patients; training the deep neural network model to obtain a recovery condition prediction model; acquiring target specific data of the target diabetic patient; standardized specific data is obtained; performing feature extraction on the standardized specific data to obtain respective feature data of the standardized specific data; fusing the respective feature data of the standardized specific data to form a comprehensive feature vector; on the basis of the comprehensive feature vector and a recovery condition prediction model, the complication occurrence probability and the predicted recovery time of the target diabetic patient are determined, features are extracted from specific data of the diabetic patient, and the features are fused, so that the complication occurrence probability and the predicted recovery time of the diabetic patient are predicted. And the prediction accuracy is improved.

Disclosed is an adjustable chair for use during post-surgical recovery, including a seat with an opening adapted to reduce or eliminate pressure on the buttocks and hips when a user is seated.

The invention relates to the technical field of health risk assessment, in particular to a neurosurgery risk prediction method and system based on big data analysis, and the method comprises the steps: obtaining the neural signal intensity of a brain region in preoperative functional image data of a patient, analyzing the balance degree of neural signal transmission, and analyzing the balance of oxygen metabolism distribution according to the nerve conduction rate. And preoperative nerve state information is formed. According to the method, by accurately extracting the preoperative neural activity signals and analyzing the signal transmission delay, the fluctuation amplitude and the oxygen metabolism balance, the accuracy of individual neural function state evaluation is improved. In the postoperative recovery stage, the abnormal region is dynamically recognized in combination with the neural signal change trend, and the metabolism matching capacity is evaluated, so that the recovery mode is more refined. Neural network connection adjustment capability analysis enhances signal transmission stability evaluation, and abnormal region identification accuracy is improved by combining time deviation and oxygen metabolism recovery consistency.

The invention discloses an anorectal postoperative rehabilitation intelligent supervision method and system based on multiple modes, and belongs to the technical field of intelligent supervision. A temperature, humidity, air quality and other multi-mode sensor group is arranged in each anorectal postoperative rehabilitation management inpatient area, the body temperature, heart rate and wound surface images of a patient are synchronously collected, and the wound surface area and seepage color are extracted through image processing; the method comprises the following steps: by taking a time node as a unit, adding a time label to an environment and patient basic data set, constructing a multi-modal comprehensive data set in a unified format, calculating an environment comprehensive index and a physiological comprehensive index, fusing the environment comprehensive index and the physiological comprehensive index to calculate a postoperative rehabilitation risk value, setting a threshold interval to generate low, medium and high three-level risk labels, and the patient risk label set is pushed to the doctor end in real time, a dynamic supervision system is constructed, the anomaly recognition rate and the clinical response speed are improved, the complication occurrence rate is reduced, the rehabilitation period is shortened, and reliable data support is provided for nursing quality improvement and evidence-based medical research.

The invention discloses soft tissue high-frequency welding equipment, and belongs to the technical field of surgical operating instruments, the soft tissue high-frequency welding equipment comprises an electrocoagulation pen main body, the electrocoagulation pen main body is connected with an insulating rod, the insulating rod is further provided with a conduction pipeline parallel to a cutter head part, and a temperature sensing unit comprises a hinting structure and a telescopic action structure. The electric resection temperature of the knife head part can be sensed in real time through the action structure in the temperature sensing unit, and when the knife head part is overheated, the action structure can be converted into an extension state from an initial retraction state and triggers the indicating structure to protrude out of the surface of the electrocoagulation pen main body, so that a doctor is reminded to cool the knife head part in time; therefore, in the electric resection operation process of the hypertrophy tonsil and adenoid body of the child, the situation that the scalpel head part is overheated in the long-time continuous state of the operation and burns the tissue of the affected part of the child is effectively avoided, the safety of the soft tissue resection operation of the child is improved, and postoperative recovery and healing of the operative part of the child are facilitated.

The invention relates to the technical field of medical care, in particular to a digestive endoscopy postoperative intelligent nursing system based on deep learning. The system comprises an endoscopic postoperative data acquisition and processing module, an endoscopic postoperative feature analysis module, an endoscopic postoperative recovery risk assessment module and a postoperative recovery risk intelligent nursing module, and can acquire physiological data of a patient after a digestive endoscopic surgery and digestive tract state image data after the endoscopic surgery; the long and short time memory network is used for obtaining the long and short time sequence characteristics of the physiological indexes after the endoscopic surgery, the convolutional neural network is used for identifying and obtaining the healing abnormal lesion characteristics after the endoscopic surgery, the characteristics are input into the preset deep neural network model for characteristic fusion, and postoperative recovery risk assessment calculation and postoperative intelligent nursing analysis are carried out. And generating digestive endoscopy postoperative patient recovery nursing suggestions so as to execute corresponding digestive endoscopy postoperative risk recovery nursing operation. According to the invention, postoperative data of the patient can be accurately analyzed, so that nursing decision-making work can be intelligently guided.

The invention discloses a thoracic surgery patient postoperative remote monitoring method and system based on the Internet of Things, and relates to the technical field of medical rehabilitation monitoring. Feature index extraction is carried out by taking body position pressure and respiration collaborative response as a two-factor dynamic evaluation basis, so that high-sensitivity judgment on a thoracic cavity load state is formed; after the abnormal state is recognized, body position adjustment is carried out, acoustic feedback analysis is linked, secondary evaluation after body position adjustment is achieved, intervention effectiveness of body position adjustment is ensured, personalized adjustment suggestions are automatically generated, the whole process of'perception-recognition-execution 'of remote monitoring is opened, the intelligent level and response real-time performance of postoperative recovery management are improved, and the postoperative recovery management efficiency is improved. According to the overall scheme, health risks caused by position misjudgment, intervention lag and monitoring blind areas in a traditional system are effectively avoided.

An embodiment of the present invention discloses an electrocoagulation surgical instrument, which uses a pulling portion and a first operating arm to form a first electrical path, and uses a sheath portion and a second operating arm to form a second electrical path, so as to apply a coagulation current to biological tissue. Thus, on the one hand, the electrocoagulation surgical instrument is configured as a detachable electrocoagulation component and a drive component, which fully utilizes the multiple incisions of laparoscopic surgery, so that the electrocoagulation component and the rod can be respectively inserted into the cavity from different incisions, reducing the size of the wound corresponding to the rod and improving the patient's postoperative recovery speed. On the other hand, during the assembly process of the electrocoagulation component and the drive component, the pulling portion can pull the electrocoagulation component and the drive component toward each other to facilitate the assembly of the two. At the same time, the pulling portion can further pull the first operating arm and the second operating arm closer to each other, so as to realize the electrocoagulation operation of the first operating arm and the second operating arm on the biological tissue, thereby simplifying the surgical operation.

The utility model provides a limb incubator, and belongs to the technical field of medical instruments. Comprising a box body, a front end cover plate is clamped to the front end of the box body, a rear end cover plate is clamped to the rear end of the box body, an observation cover is fixedly connected to the middle of the box body, a bottom plate is fixedly connected to the bottom of the box body, a bracket is arranged on the top of the bottom plate, and a heating pad is laid on the top of the bracket. The heating pad is arranged, the heating pad conducts contact heating on an affected limb, compared with a radiation heating method of a baking lamp and an ultraviolet lamp, the contact heating can better guarantee the temperature stability, the influence of the room temperature on the affected limb is small, the affected limb is lifted through the bracket, blood circulation is promoted, and postoperative recovery is facilitated; when an affected limb moves on the bracket or collides with the bracket, the bracket can buffer the affected limb, the comfort of a patient is improved, meanwhile, the bracket can deform to drive the height of the bracket to change, the function of adjusting the height of the bracket is achieved, and the comfort of the patient is further improved.

The invention relates to the technical field of intelligent medical treatment, in particular to a urinary surgery postoperative risk layering intelligent nursing management system which comprises the steps of preprocessing dynamic sign flow data of a patient to obtain regular sign time sequence data; and separating a core vital sign track, a wound exudation quantitative sequence and an autonomous perception discomfort record through modal analysis. The feature calculation module compares the vital sign trajectory with a standard recovery trajectory library to generate a sign bias spectrum, analyzes the exudation sequence to obtain a wound humidity distribution vector, and calculates a time attenuation factor of the pain event according to the discomfort record. And the space construction and layering module combines the features to construct a multi-dimensional risk base space, and identifies boundary coordinates of high-risk, medium-risk and low-risk risk clusters through clustering. And the strategy generation module divides risk levels and allocates corresponding monitoring and intervention measures according to the risk levels. According to the system, dynamic and multi-dimensional quantitative evaluation of the postoperative recovery state and objective automatic layering of risks are achieved.

The invention relates to an AI image navigation method, device and equipment for prostatic hyperplasia minimally invasive surgery and a medium thereof. The method comprises the following steps: acquiring a prostate three-dimensional image and an intraoperative real-time image sequence, and fusing the three-dimensional image after preliminary filtering to obtain an optimized and enhanced image; based on the enhanced image and the preoperative three-dimensional image, a three-dimensional offset vector is obtained through a multi-modal registration algorithm combined with an anatomical structure reference, and optimized prostate three-dimensional attitude data is generated in combination with anatomical constraints; combining the attitude data and the three-dimensional image, determining boundary area distribution characteristics, calculating a risk assessment value, mapping a risk level, and generating a path correction instruction to obtain an instrument navigation path if the risk level exceeds a threshold value; and based on the navigation path, constructing a clinical recovery model in combination with the anatomical structure, generating postoperative recovery index simulation data, and performing adjustment and verification until preset requirements are met to obtain a final operation execution scheme. According to the method, precision and individuation of surgical navigation are achieved, and comprehensive technical support is provided for precise implementation of minimally invasive surgery.

The invention discloses a thoracic surgery postoperative drainage monitoring data processing method and a thoracic surgery postoperative drainage monitoring data processing system. The method comprises the following steps: synchronously acquiring thoracic respiration dynamic characteristics of a patient and fluid dynamic characteristics of a thoracic closed drainage system through a data acquisition module; the central processing server establishes a time sequence mapping relationship between the two, performs feature fusion analysis, and calculates to obtain a thoracic cavity-pipeline coupling efficiency index; performing logic judgment on the postoperative recovery state of the patient on the basis of the index, and identifying a chest-pipeline fluid transmission state including breathing work limitation, drainage channel blockage and pleural cavity air leakage; and dynamically generating a grading equipment response strategy including adjusting training intensity and triggering pipeline maintenance early warning or analgesia intervention according to an identification result. According to the method, accurate recognition and closed-loop management of postoperative complications are achieved by quantitatively evaluating the linkage relation between respiration driving and drainage response.

The invention discloses a chest surgery postoperative complication early warning system. The chest surgery postoperative complication early warning system comprises a data acquisition layer, a data transmission layer, a data processing and storage layer, an analysis and early warning layer and a user interface and feedback layer. The data acquisition layer is used for acquiring vital signs of a patient, laboratory inspection, image data and information manually input by medical staff; the data transmission layer transmits the collected data to the data processing and storage layer in real time; the data processing and storage layer preprocesses, stores and manages the collected data; the analysis and early warning layer analyzes the data through a predefined rule and a machine learning model, calculates a risk score in real time, and triggers early warning; and the user interface and feedback layer provides a graphical operation interface, mobile terminal pushing and alarm feedback. According to the invention, the change of the condition of the patient after the thoracic surgery can be accurately monitored in real time, the risk of complication can be early warned in time, decision support is provided for medical personnel, and the postoperative recovery effect of the patient is improved.

The utility model relates to a thyroid postoperative recovery protection device which comprises a postoperative protection block, a connecting assembly is fixedly installed on the surface of the postoperative protection block, a supporting mechanism is fixedly installed in the postoperative protection block, and an auxiliary mechanism is fixedly installed on the surface of the postoperative protection block. The connecting assembly comprises a first connecting belt, the first connecting belt is fixedly installed on one side of the postoperative protection block, and a hook-and-loop fastener rough surface is installed on the surface of the first connecting belt. According to the thyroid postoperative recovery protection device, by arranging a spring and a postoperative protection plate, the postoperative protection plate can be attached to the postoperative part of a person, a first connecting belt and a second connecting belt can be connected through adhesion between a hook-and-loop fastener hook face and a hook-and-loop fastener loop face, and a postoperative protection block is fixed; the jaw of a person is supported through the supporting pad, hurt to a wound due to head lowering is prevented, and the height of the supporting pad can be adjusted according to the length of the neck of a patient.

The plugging drainage device comprises an outer sleeve, a flushing pipe, an inner suction pipe and an umbrella-shaped plugging mechanism, a plurality of first through holes are formed in the front end of the outer sleeve, the inner suction pipe is arranged in the outer sleeve, a plurality of second through holes are formed in the front end of the inner suction pipe, and the umbrella-shaped plugging mechanism is arranged in the inner suction pipe. The umbrella-shaped plugging mechanism is arranged at the front end of the outer sleeve and can be retracted into the outer sleeve. The device is provided with the plugging mechanism, the fistula can be plugged during flushing, intestinal juice loss is effectively avoided, postoperative recovery of a patient is facilitated, the umbrella-shaped structure is adopted for plugging, compared with bag plugging, the umbrella fabric of the umbrella-shaped structure can be tightly attached to the wound surface, obstruction is effectively avoided, and the application safety of the device is further improved.

The utility model provides an integrated stent-type artificial blood vessel which comprises an artificial blood vessel part comprising an artificial blood vessel main branch used for being arranged corresponding to an ascending aorta of a human body; the covered stent comprises a covered stent trunk and a left subclavian artery branch arranged beside the covered stent trunk and communicated with the covered stent trunk; the bendable connecting tube section is arranged between the artificial blood vessel part and the covered stent, the bendable connecting tube section comprises a main tube section and a side short tubular joint which is arranged on the side of the main tube section and communicated with the main tube section, and in the main blood flow direction of the artificial blood vessel, the near end of the main tube section is connected with the main branch of the artificial blood vessel; the far end of the main pipe section is connected with the near end of the artificial blood vessel main branch, and the axial height of the side short pipe-shaped connector is smaller than that of the left subclavian artery branch. The number of branch arteries needing to be dissociated in an operation is reduced, then dissociation anastomosis time is saved, circulation stopping time is shortened, protection on brain tissue is enhanced, and postoperative rehabilitation of a patient is facilitated.

The invention relates to the technical field of high polymer materials, in particular to biological glue applied to fixation of an esophageal hiatus hernia patch. The biological glue comprises 40 to 60 wt% of fibrinogen, 30 to 50 wt% of a polyethylene glycol polymer, 2 to 8 wt% of an amino-containing small molecule compound, 0.2 to 0.8 wt% of a growth factor and 1 to 3 wt% of glutaraldehyde. The biological glue provided by the embodiment of the invention has excellent mechanical properties and good histocompatibility, and can realize a better patch fixing effect in a hiatus hernia operation, so that postoperative recovery of a patient is guaranteed.

The invention relates to the technical field of sports medicine auxiliary diagnosis, in particular to a rotator cuff tearing recovery evaluation method and system. By combining multiple groups of indexes and image group feature data, the rotator cuff tearing recovery process can be effectively evaluated, score data reflecting the current rotator cuff repair postoperative development state can be obtained, and the postoperative recovery degree and potential risks are more visually determined through the score data. Therefore, automatic evaluation and prediction of the repair process are realized.

The invention discloses a cardiac surgery sternum dilator for preventing rib fracture, which comprises a first distraction arm, a guide plate, a second distraction arm, a distraction plate, a pressure gauge, a brake component and a controller, and is characterized in that the first distraction arm is fixed at one end of the guide plate; the second distraction arm is arranged on the guide plate and can move along the guide plate; guide grooves are formed in the opposite sides of the first distraction arm and the second distraction arm, a distraction plate is inserted into each guide groove, and the distraction plates can move in the length direction and the height direction relative to the guide grooves; the first distraction arm and the second distraction arm are each provided with a pressure gauge in a sliding mode, and the detection ends of the pressure gauges can abut against the corresponding distraction plates. And the brake component is arranged on the second distraction arm. Therefore, the sternum distraction pressure can be detected, braking is carried out when the pressure is too large, and therefore the situation of side injury of rib fracture caused by the too large distraction pressure is avoided, and the discomfort of a patient in the postoperative recovery process is reduced.

The invention discloses an anterior cruciate ligament reconstruction postoperative intelligent evaluation system based on artificial intelligence. The system comprises a data acquisition module used for collecting clinical information and MRI image data of a patient; the ligament graft maturity evaluation module is used for automatically measuring and calculating the maturity of the anterior cruciate ligament graft; the tendon-bone interface healing evaluation module is used for automatically measuring bone tunnel diameter changes and tunnel surrounding edema changes. Accurate evaluation and personalized suggestions are provided for postoperative recovery of anterior cruciate ligament reconstruction patients.