Postoperative curative effect monitoring system for maxillofacial surgery

Abstract

The invention discloses a maxillofacial surgery postoperative curative effect monitoring system, which relates to the technical field of medical diagnosis and comprises a data collection module, a transmission module, a data processing module, an interaction module and a recovery suggestion module, the data collection module comprises a face collection unit, an occlusion unit and a voice unit, the data collection module is used for being regularly worn by a postoperative patient, the face collection unit scans the maxillofacial surface of the patient, the occlusion unit is used for the patient to occlude and collect occlusion data, and the voice unit is used for collecting sound of the patient; uploading the collected data to a transmission module; and the transmission module uploads the acquired data to the interaction module based on the Internet of Things mode. According to the method, abnormal fluctuation or potential problems in the recovery process are found in time through data uploaded regularly, rehabilitation training plans and diet suggestions are customized for patients, or review time is adjusted for personalized treatment schemes, and the pertinence and effectiveness of treatment are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of medical diagnosis, and particularly to a postoperative efficacy monitoring system for maxillofacial surgery. Background Art

[0002] Maxillofacial surgery is a discipline mainly focusing on surgical treatment, and its main content is to study the prevention and treatment of diseases of oral organs, facial soft tissues, maxillofacial bones, temporomandibular joints, salivary glands, and certain diseases in the neck. In the field of maxillofacial surgery, various surgeries aim to repair and improve the structure and function of the patient's oral and maxillofacial region, covering complex surgical operations such as reduction and fixation of mandibular fractures, resection and reconstruction of oral and maxillofacial tumors, temporomandibular joint surgeries, and orthodontic correction of dentomaxillofacial deformities. Traditional postoperative efficacy evaluation in maxillofacial surgery mainly relies on doctors' clinical experience and regular outpatient reviews. When conducting reviews, doctors visually observe the recovery of the patient's facial appearance, such as symmetry and scar conditions, and use oral examination tools to check functional indicators such as occlusion relationship and mouth opening degree. However, this evaluation method has obvious deficiencies. First, doctors' subjective judgments are easily affected by factors such as personal experience and observation angles, making it difficult to achieve precise quantitative evaluation, and the evaluation results of different doctors for the same patient may vary. Second, the review interval is relatively long, and it is impossible to promptly capture subtle changes and potential problems that occur in the early postoperative period, thus affecting the patient's final rehabilitation effect. In response to this, we propose a postoperative efficacy monitoring system for maxillofacial surgery. Summary of the Invention

[0003] To solve the above technical problems and provide a postoperative efficacy monitoring system for maxillofacial surgery, this technical solution solves the problem of being unable to capture the changes and potential problems that occur after surgery.

[0004] To achieve the above object, the technical solution adopted by the present invention is: a postoperative efficacy monitoring system for maxillofacial surgery, including: a data collection module, a transmission module, a data processing module, an interaction module, and a recovery suggestion module;

[0005] The data collection module includes a facial acquisition unit, a bite unit, and a voice unit. The data collection module is used for postoperative patients to wear regularly. The facial acquisition unit scans the patient's maxillofacial region, the bite unit is used for the patient to bite and collect bite data, and the voice unit is used to collect the patient's voice; the collected data is uploaded into the transmission module;

[0006] The transmission module uploads the acquired data based on the Internet of Things method and uploads it into the interaction module;

[0007] The data processing module analyzes the acquired data to analyze the patient's maxillofacial recovery, maxillofacial occlusion, and maxillofacial muscle movement;

[0008] The interaction module is used to provide an interaction page for doctors to view the data analyzed by the data processing module and judge the recovery effect of the patient's maxillofacial region after surgery;

[0009] The recovery suggestion module is used to give intelligent reply suggestions based on big data for the current patient's reply situation.

[0010] Preferably, the facial acquisition unit includes a scanner. Using three-dimensional scanning technology, the patient wears it regularly for monitoring, scans the patient's maxillofacial region, scans and obtains the surface morphology data of the patient's maxillofacial region from multiple angles. The data includes the facial bone contour and soft tissue distribution, constructs the three-dimensional digital transformation of the patient's maxillofacial region after surgery, and uploads the data; the occlusion unit provides an occlusion platform, and the patient occludes according to the instructions, and measures the bite force data of the patient during the occlusion process through a pressure sensor and a displacement sensor; the voice unit includes an audio acquisition device, collects the voice signal when the patient speaks, and acquires the frequency, amplitude, and timbre information of the sound when the patient speaks; the collected data is centrally collected and uploaded.

[0011] Preferably, the transmission module uses the Internet of Things method for transmission, preprocesses the collected data, constructs the data into a data set after preprocessing, and transmits and saves it.

[0012] Preferably, through the comparison of models in different periods, the data processing module observes the subtle changes in the maxillofacial shape during the recovery process, including the healing condition of the fracture site, the degree of soft tissue swelling subsidence, and the morphological stability of the surgical repair area; sets the size measurement value of the key anatomical structure of the patient's surgical treatment of the maxillofacial region as Lh, and the size measurement value collected before treatment as Lq, and calculates the maxillofacial shape size recovery rate. The calculation formula is:

[0013]

[0014] Where R is the maxillofacial shape size recovery rate. If the R value is close to 100%, it indicates good surface recovery, and if it deviates greatly, it indicates poor surface recovery.

[0015] Preferably, the maxillofacial occlusion condition analysis measures the bite force at different tooth positions. Let the bite force at the i-th tooth position be F i , the total number of teeth is m, and calculates the average value of the bite force. The calculation formula is:

[0016]

[0017] Where is the average value of the bite force, and calculates the discrete degree value of the bite force. The calculation formula is:

[0018]

[0019] Where SD is the calculated value of the degree of dispersion. The smaller the degree of dispersion of occlusion, the more uniform the distribution of occlusal force, indicating that the patient's recovery status is good. If the degree of dispersion is larger, it means that the distribution of occlusal force is more uneven, indicating that the patient's recovery status is poor.

[0020] Preferably, regarding the movement of the maxillofacial muscles, it is assumed that there are k muscles involved in the maxillofacial muscles, and the starting contraction time during the movement is t i , and the ideal contraction time for each muscle is T i . Calculate the time deviation value of each muscle. The calculation formula is:

[0021] A = |t i - T i |

[0022] Where A is the time deviation value of each muscle. Calculate the average time deviation of the calculation results. The calculation formula is:

[0023]

[0024] Where B represents the average time deviation. The smaller the average time deviation, the better the coordination of the synergistic movement between the muscles, and the more normal the maxillofacial muscle movement function.

[0025] Preferably, the interaction module performs data visualization processing through line charts and tables. For data that changes over time, including the recovery process of the patient's maxillofacial muscle strength and the change in occlusal pressure, a line chart is used. With time as the horizontal axis and the corresponding measurement index as the vertical axis, the recovery trend can be seen, and it can be visually shown through the line chart how the occlusal force gradually increases or there are abnormal fluctuations.

[0026] Preferably, during the process of the doctor in the interaction module viewing the data, important data points and chart areas are annotated, and text descriptions are added to record their observations and preliminary judgments, providing a direct comparison tool for the patient's pre-operative and post-operative data, and enabling one-key switching to view the pre-operative and post-operative maxillofacial models and data charts.

[0027] Preferably, the recovery suggestion module obtains the patient's recovery data based on the Internet, including multi-dimensional characteristic data such as age, gender, surgical type, pre-operative health status, and surgical complexity, and details the recovery process of each patient to form a complete patient recovery case library, and extracts the characteristics of the data in the case library.

[0028] Preferably, for the obtained case library, an analysis is carried out, and combined with diet suggestions, rehabilitation suggestions, and reexamination suggestions, personalized suggestions are recommended for the current patient to help the patient recover quickly.

[0029] Compared with the prior art, the beneficial effects of the present invention are as follows:

[0030] The present invention collects data through multiple units, enabling a comprehensive understanding of the recovery of the patient's maxillofacial region from different perspectives. The data collection module requires the patient to wear the device regularly for data acquisition, which enables doctors to conduct long-term and continuous tracking of the patient's recovery process. Through the regularly uploaded data, doctors can view the dynamic changes in the patient's recovery status in the interaction module, timely detect abnormal fluctuations or potential problems during the recovery process, customize rehabilitation training plans, diet suggestions or adjust the review time for personalized treatment plans for the patient, improve the pertinence and effectiveness of treatment, achieve precise quantitative evaluation, and be able to capture subtle changes and potential problems that occur in the early postoperative period in a timely manner. BRIEF DESCRIPTION OF THE DRAWINGS

[0031] Figure 1 It is a framework diagram of the monitoring system of the present invention. DETAILED DESCRIPTION OF THE INVENTION

[0032] The following description is used to disclose the present invention so that those skilled in the art can implement the present invention. The preferred embodiments in the following description are only examples, and those skilled in the art can think of other obvious variations.

[0033] Referring to Figure 1 As shown, the postoperative efficacy monitoring system for maxillofacial surgery includes: a data collection module, a transmission module, a data processing module, an interaction module and a recovery suggestion module;

[0034] The data collection module includes a facial acquisition unit, a bite unit and a voice unit. The data collection module is used for postoperative patients to wear regularly. The facial acquisition unit scans the patient's maxillofacial region, the bite unit is used for the patient to bite and collect bite data, and the voice unit is used to collect the patient's voice; the collected data is uploaded into the transmission module.

[0035] The transmission module uploads the acquired data based on the Internet of Things method and uploads it into the interaction module.

[0036] The data processing module analyzes the acquired data to analyze the recovery of the patient's maxillofacial region, the maxillofacial bite condition and the maxillofacial muscle movement condition.

[0037] The interaction module is used to provide an interaction page for doctors to view the data analyzed by the data processing module and judge the recovery effect after the patient's maxillofacial surgery.

[0038] The recovery suggestion module is used to give intelligent reply suggestions based on big data for the current patient's recovery situation.

[0039] The data collection module of this application collects data from multiple perspectives, enabling comprehensive monitoring of all aspects of the patient's maxillofacial restoration. The scanning of the facial acquisition unit can accurately capture the subtle changes in maxillofacial morphology. The bite unit collects bite data, which can reflect the recovery of the patient's daily chewing function. The voice unit collects vocalization data, which can indirectly reflect the movement state of the maxillofacial muscles. This comprehensive monitoring helps to detect any potential restoration problems in a timely manner and provides a more precise restoration plan for the patient;

[0040] The analysis of multi-dimensional data by the data processing module provides doctors with comprehensive and accurate patient information. Doctors no longer rely solely on subjective observation and limited examinations to judge the restoration situation. Instead, through detailed data analysis, specific numerical indicators of maxillofacial restoration, quantified data on bite conditions, and dynamic analysis of maxillofacial muscle movement, more accurate diagnoses can be made;

[0041] The large amount of patient data collected by the entire system is a valuable asset for the medical system. This data can be used to establish a more complete maxillofacial restoration database, providing data support for subsequent medical research, improvement of medical equipment, and optimization of treatment plans.

[0042] The facial acquisition unit includes a scanner that uses three-dimensional scanning technology. The patient wears it regularly for monitoring and scans the patient's maxillofacial region. Surface morphology data of the patient's maxillofacial region is obtained from multiple angles. The data includes the facial bone contour and soft tissue distribution, and a three-dimensional digital model of the patient's postoperative maxillofacial region is constructed and the data is uploaded; The bite unit provides a bite platform. The patient bites according to the instructions, and the bite force data of the patient during the biting process is measured through pressure sensors and displacement sensors; The voice unit includes audio acquisition equipment that collects the voice signals of the patient when speaking. When the patient speaks, the frequency, amplitude, and timbre information of the sound are collected; The collected data is centrally collected and uploaded.

[0043] The three-dimensional scanning technology of this application can obtain the surface morphology data of the patient's maxillofacial region from multiple angles, including the facial bone contour and soft tissue distribution. This is crucial for monitoring maxillofacial restoration because it can accurately capture whether the healing position of the postoperative maxillofacial bone is correct, whether there is displacement, and the recovery state of the soft tissue, such as whether the swelling has subsided and the skin fit. The three-dimensional digital model constructed through regular scanning is like establishing a dynamic restoration file for the patient. Doctors can intuitively see the changes in maxillofacial morphology over time, which helps to detect potential restoration problems in a timely manner, such as nonunion and soft tissue contracture. Collecting and uploading facial scans, bite data, and voice data together provides doctors with a comprehensive data set for diagnosis. These data from different dimensions complement each other, enabling doctors to have a more comprehensive understanding of the patient's maxillofacial restoration status.

[0044] The transmission module uses the Internet of Things (IoT) method for transmission. It preprocesses the collected data, constructs the data into a dataset after preprocessing, and then transmits and saves the data.

[0045] This application uses the IoT method for transmission, which is efficient and real-time. The IoT can use various network access technologies to quickly upload data to a specified server or cloud platform.

[0046] The data processing module observes the subtle changes in the maxillofacial shape during the recovery process through the comparison of models at different times, including the healing condition of the fracture site, the degree of soft tissue swelling subsidence, and the morphological stability of the surgical repair area. Set the measured dimension value of the key maxillofacial anatomical structures collected after the patient's surgical treatment as Lh, and the measured dimension value collected before treatment as Lq. Calculate the maxillofacial shape dimension recovery rate, and the calculation formula is:

[0047]

[0048] where R is the maxillofacial shape dimension recovery rate. If the R value is close to 100%, it indicates good recovery; if it deviates greatly, it indicates poor recovery.

[0049] This application calculates the maxillofacial shape dimension recovery rate (R), which provides a quantitative index for the recovery situation. Doctors can more intuitively judge the recovery degree based on this index, rather than relying solely on subjective observation. This quantitative evaluation method makes the comparison of the recovery situations between different patients or at different stages of the same patient more scientific and accurate.

[0050] Analysis of maxillofacial occlusion measures the biting force at different tooth positions. Let the biting force at the i-th tooth position be Fi i , and the total number of teeth be m. Calculate the average value of the biting force, and the calculation formula is:

[0051]

[0052] where is the average value of the biting force. Calculate the value of the dispersion degree of the biting force, and the calculation formula is:

[0053]

[0054] where SD is the calculated value of the dispersion degree. The smaller the dispersion degree of the occlusion, the more uniform the distribution of the biting force, indicating that the patient's recovery state is good. If the dispersion degree is larger, it indicates that the distribution of the biting force is more uneven, indicating that the patient's recovery state is poor.

[0055] By calculating the average value of the biting force, this application can comprehensively understand the magnitude of the patient's biting force, which is an important reference index for evaluating the recovery degree of the patient's occlusal function. After maxillofacial surgery, the normal recovery of the biting force is an important manifestation of good functional recovery. If the average value of the biting force is within the normal range, it indicates that the patient has a good recovery in terms of the overall occlusal force; if the average value is too low, it may suggest that the occlusal function has not been fully restored, and there are problems such as insufficient muscle strength or unsatisfactory tooth occlusion relationship, which helps doctors promptly detect potential occlusal function disorders.

[0056] Regarding the movement of the maxillofacial muscles, assume that there are k muscles involved in the maxillofacial muscles, and the starting contraction time during the movement is t i , and the ideal contraction time for each muscle is T i . Calculate the time deviation value of each muscle. The calculation formula is:

[0057] A = |t i - T i |

[0058] Where A is the time deviation value of each muscle. Calculate the average time deviation of the calculation results. The calculation formula is:

[0059]

[0060] Where B represents the average time deviation. The smaller the average time deviation, the better the coordination of the synergistic movement between the muscles, and the more normal the maxillofacial muscle movement function.

[0061] The interaction module performs data visualization processing through line charts and tables. For data that changes over time, including the recovery process of the patient's maxillofacial muscle strength and the change in occlusal pressure, a line chart is used. With time as the horizontal axis and the corresponding measurement index as the vertical axis, the recovery trend can be seen, and it can visually show how the biting force gradually increases or shows abnormal fluctuations through the line chart.

[0062] This application uses line charts to display data that changes over time, such as the recovery process of maxillofacial muscle strength and the change in occlusal pressure, which can transform abstract data into intuitive lines. Doctors can clearly see whether the recovery trend is rising, falling, or remaining stable at a glance. This visual presentation method allows doctors to quickly grasp the overall dynamics of the patient's recovery and easily observe whether the maxillofacial muscle strength continues to increase in the weeks or months after the operation, or stagnates or even decreases at a certain time point.

[0063] During the process of doctors viewing the data, the interaction module annotates important data points and chart areas, adds text descriptions, records their observations and preliminary judgments, provides a direct comparison tool for the patient's pre-operative and post-operative data, and can switch with one key to view the pre-operative and post-operative maxillofacial models and data charts.

[0064] In this application, doctors can annotate important data points and chart areas and add written explanations, enabling them to record in a timely manner the inspirations, questions, or key findings that occur instantly when viewing the data. These annotations become important clues for subsequent in-depth analysis.

[0065] The recovery suggestion module obtains patients' recovery data based on the Internet, including multi-dimensional characteristic data such as age, gender, type of surgery, pre-operative health status, and complexity of the surgery, and details the recovery process of each patient to form a complete patient recovery case database, and extracts the characteristics of the data in the case database.

[0066] Extracting characteristic data from a large number of patient recovery case databases in this application helps to uncover the general laws and correlations hidden among numerous cases. By analyzing a large amount of data, it may be found that patients with a specific type of surgery combined with a specific pre-operative health status have specific time patterns and common problems in maxillofacial occlusion recovery. These laws can provide a favorable reference basis for doctors to formulate recovery suggestions, making their decisions more scientific and reasonable. When faced with new patients, they can anticipate possible recovery problems in advance based on the discovered laws and give preventive suggestions, improving the overall medical quality.

[0067] For the obtained case database, analysis is carried out, and personalized suggestion recommendations are given to the current patient in combination with diet suggestions, rehabilitation suggestions, and reexamination suggestions to help the patient recover quickly.

[0068] The above shows and describes the basic principles, main features, and advantages of the present invention. Those skilled in the art of this industry should understand that the present invention is not limited by the above embodiments. What is described in the above embodiments and the specification is only the principle of the present invention. Without departing from the spirit and scope of the present invention, the present invention will have various changes and improvements, and these changes and improvements all fall within the scope of the present invention claimed.

Claims

1. Maxillofacial surgery postoperative efficacy monitoring system, characterized in that, Including: A data collection module, a transmission module, a data processing module, an interaction module, and a recovery suggestion module; The data collection module includes a facial acquisition unit, a biting unit, and a voice unit. The data collection module is used for postoperative patients to wear regularly. The facial acquisition unit scans the patient's maxillofacial region. The biting unit is used for the patient to bite and collect biting data. The voice unit is used to collect the patient's voice. The collected data is uploaded to the transmission module; The transmission module uploads the acquired data based on the Internet of Things method to the interaction module; The data processing module analyzes the acquired data to analyze the patient's maxillofacial recovery situation, maxillofacial biting situation, and maxillofacial muscle movement situation; The interaction module is used to provide an interaction page for doctors to view the data analyzed by the data processing module and judge the recovery effect after the patient's maxillofacial surgery; The recovery suggestion module is used to give intelligent recovery suggestions based on big data for the current patient's recovery situation.

2. The maxillofacial surgery postoperative efficacy monitoring system according to claim 1, wherein The facial acquisition unit includes a scanner. Using three-dimensional scanning technology, the patient wears it regularly for monitoring, scans the patient's maxillofacial region, scans and obtains the surface morphology data of the patient's maxillofacial region from multiple angles. The data includes the facial bone contour and soft tissue distribution, constructs a three-dimensional digital model of the patient's postoperative maxillofacial region, and uploads the data; The biting unit provides a biting platform. The patient bites according to the instructions, and the biting force data of the patient during the biting process is measured by a pressure sensor and a displacement sensor; The voice unit includes an audio acquisition device, collects the voice signal when the patient speaks, and collects the frequency, amplitude, and timbre information of the sound when the patient speaks; The collected data is centrally collected and uploaded.

3. The maxillofacial surgery postoperative efficacy monitoring system according to claim 1, wherein The transmission module uses the Internet of Things method for transmission, preprocesses the collected data, constructs the data into a data set after preprocessing, and performs transmission and storage.

4. The maxillofacial surgery postoperative efficacy monitoring system according to claim 1, characterized in that The data processing module observes the subtle changes in the maxillofacial shape during the recovery process through the comparison of models in different periods, including the healing condition of the fracture site, the degree of soft tissue swelling subsidence, and the morphological stability of the surgical repair area; Set the size measurement value of the key anatomical structure of the patient's maxillofacial region collected during the operation as Lh, and the size measurement value collected before the treatment as Lq, and calculate the maxillofacial shape size recovery rate. The calculation formula is: Where R is the maxillofacial shape size recovery rate. If the R value is close to 100%, it indicates good surface recovery. If it deviates greatly, it indicates poor surface recovery.

5. The maxillofacial surgery postoperative efficacy monitoring system according to claim 1, characterized in that, Analysis of maxillofacial occlusion situation measures the bite force at different tooth positions. Let the bite force at the i-th tooth position be F i , and the total number of teeth be m. Calculate the average value of the bite force. The calculation formula is: Among them is the average value of the biting force, and the dispersion value of the biting force is calculated. The calculation formula is as follows: Where SD is the calculated value of the degree of dispersion. The smaller the degree of dispersion of the bite, the more uniform the bite force distribution, indicating that the patient's recovery state is good. If the degree of dispersion is larger, it indicates that the bite force distribution is more uneven, indicating that the patient's recovery state is poor.

6. The maxillofacial surgery postoperative efficacy monitoring system according to claim 1, characterized in that, The movement of the maxillofacial muscles Suppose there are k muscles involved in the maxillofacial muscles, and the starting contraction time during the movement is t i while the ideal contraction time for each muscle is T i , calculate the time deviation value of each muscle. The calculation formula is as follows: A = |t i -T i | Where A is the time deviation value of each muscle, and the average time deviation of the calculated result is obtained. The calculation formula is: Where B represents the average time deviation. The smaller the average time deviation, the better the coordination of the synergistic movement between the muscles, and the more normal the maxillofacial muscle movement function.

7. The maxillofacial surgery postoperative efficacy monitoring system according to claim 1, wherein, The interaction module performs data visualization processing through line charts and tables. For data that changes over time, including the recovery process of the patient's maxillofacial muscle strength and the change in bite pressure, a line chart is used with time as the horizontal axis and the corresponding measurement indicators as the vertical axis to observe the recovery trend and visually show how the bite force gradually increases or exhibits abnormal fluctuations through the line chart.

8. The maxillofacial surgery postoperative efficacy monitoring system according to claim 1, characterized in that During the process of doctors in the interaction module viewing data, they annotate important data points and chart areas, add text explanations, record their observations and preliminary judgments, provide a direct comparison tool for the patient's pre-operative and post-operative data, and can switch with one key to view the pre-operative and post-operative maxillofacial models and data charts.

9. The maxillofacial surgery postoperative efficacy monitoring system according to claim 1, characterized in that, The recovery suggestion module obtains the patient's recovery data based on the Internet, including multi-dimensional characteristic data such as age, gender, surgical type, pre-operative health status, and surgical complexity, and details the recovery process of each patient to form a complete patient recovery case library, and extracts the characteristics of the data in the case library.

10. The maxillofacial surgery postoperative efficacy monitoring system according to claim 9, characterized in that, For the obtained case library, it is analyzed, and combined with diet suggestions, rehabilitation suggestions, and reexamination suggestions, personalized suggestions are recommended for the current patient to help the patient recover quickly.

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