Artificial tooth life cycle management system based on patient individualized information

Abstract

The invention discloses an artificial tooth life cycle management system based on patient individualized information, and relates to the technical field of oral rehabilitation. The artificial tooth life cycle management system comprises an interface state monitoring module, an integrated electrical impedance signal acquisition unit, a state parameter calculation unit and an abnormal mark identification unit; high-precision real-time sensing of the physiological state of a contact interface of the false tooth edge and the gingiva can be achieved, a complex impedance sequence is obtained through an alternating micro-current injection and voltage response synchronous acquisition method, precise modeling of the electrical characteristics of gingival tissue is achieved in combination with the wearing state and time position data, resistance and reactance components can be distinguished, and the accuracy of the gingival tissue electrical characteristics is improved. Therefore, key physiological indexes such as gingival wettability, inflammatory response and an interface adhesion coefficient are accurately calculated, dynamic fluctuation analysis is further performed on the state parameters, biological abnormal events such as interface dryness, adhesion reduction or inflammation aggravation are found in time, automatic marking and data uploading are performed, and an accurate intervention basis is provided for doctors.

Description

Technical Field

[0001] This invention relates to the field of oral restoration technology, specifically to a denture lifecycle management system based on individualized patient information. Background Technology

[0002] With the continuous development of oral prosthetics technology, dentures, as common oral functional replacement devices, are widely used to restore functions such as chewing, speech, and facial support in patients with missing teeth. However, the design and management of traditional dentures mainly rely on the experience and judgment of dentists. They typically lack a systematic monitoring and dynamic evaluation mechanism after installation, making them prone to problems such as denture loosening, marginal inflammation, and fatigue cracking in high-stress areas during long-term use, affecting the patient's experience and oral health. Especially under the combined effects of long-term chewing loads and the biological environment, the local material properties of dentures may undergo irreversible degradation. If this is not identified and intervened in a timely manner, it may lead to premature denture failure.

[0003] Currently, there is a lack of intelligent systems capable of integrating individualized occlusal behavior with bio-interface states for full-lifecycle prediction and management. On the one hand, traditional occlusal designs are mostly based on static mechanical models, failing to accurately reflect the three-dimensional changes in occlusal force during actual chewing. On the other hand, there is a lack of real-time monitoring methods for the bio-response state of the denture-gingival tissue interface, making it difficult to promptly identify potential risks such as gingival inflammation, abnormal moisture, or decreased adhesion. Furthermore, denture replacement and restoration times are mostly based on periodicity or patient complaints, lacking scientific assessment mechanisms based on fatigue indices or usage status, which may lead to delayed restoration or wasted resources. Summary of the Invention

[0004] To address the shortcomings of existing technologies, this invention provides a denture lifecycle management system based on individualized patient information to solve the problems mentioned in the background section.

[0005] To achieve the above objectives, the present invention provides the following technical solution: a denture lifecycle management system based on individualized patient information, comprising:

[0006] The interface status monitoring module, installed at the edge of the denture, includes a wearable bioelectrical impedance sensor unit to collect interfacial electrical impedance parameters at the contact point between the gingiva and the denture in real time, and calculate the gingival moisture index. Inflammatory response markers and interfacial adhesion coefficient It identifies three abnormal situations and generates corresponding abnormal warning instructions if any are identified.

[0007] The three-dimensional occlusal force acquisition module is used to acquire the three-dimensional occlusal force vector of each contact point on each contact surface of the denture during the patient's individualized chewing process. A three-dimensional occlusal force vector map model of the denture was constructed, and high stress concentration contact points were identified and marked.

[0008] The lifespan assessment module, based on joint modeling of the interface state and occlusal data, extracts the cumulative occlusal force of the j-th surface unit for each surface unit in the denture. Inflammatory response markers and interfacial adhesion coefficient Construct the fatigue index of the j-th surface element. To dynamically assess the local material performance degradation trend;

[0009] Preset fatigue threshold ,when This triggers a lifespan warning command, and for each surface unit j, it calculates the cumulative biting force based on the j-th surface unit. Redundancy thickness design is performed using a linear amplification function, and the redundancy thickness increment of the i-th surface unit is calculated. The information was then sent to a doctor, who recommended repair and replacement.

[0010] Preferably, the interface status monitoring module includes an impedance signal acquisition unit, a status parameter calculation unit, and an anomaly marker identification unit;

[0011] The impedance signal acquisition unit is embedded in the inner surface of the denture edge and deploys a multi-channel flexible bioelectrode array. It continuously acquires impedance signals at the contact point between the gingiva and the denture based on a fixed sampling frequency. The impedance measurement adopts a method of synchronous reading of alternating microcurrent injection and voltage response to obtain a complex impedance sequence. The acquisition timestamp t, electrode position coordinates, microcurrent intensity, and denture wearing status are recorded simultaneously.

[0012] The complex impedance of the time series was calculated based on Ohm's law. :

[0013]

[0014] in, This represents a complex impedance signal, measured in ohms, indicating the overall electrical properties of the gingival-prosthetic interface tissue. This represents the complex impedance signal, measured by the attached electrode array at time point t, and is measured in volts. This indicates the applied AC excitation current, measured in amperes, with an amplitude in the microampere range. This represents the real part of the impedance, in Ω, and corresponds to the resistance component, which is affected by the tissue water content. The impedance represents the imaginary part, in Ω, corresponding to the reactance component, which is related to cell structure, capacitance characteristics, and interfacial adhesion state; j represents the imaginary unit, satisfying... ;

[0015] The state parameter calculation unit is used to calculate the state parameter based on the time series complex impedance. Extract physiological characteristic indicators of the interface state, including gingival moisture index. Inflammatory response markers and interfacial adhesion coefficient ;

[0016] The anomaly marker identification unit is used to analyze the calculated gingival moisture index. Inflammatory response markers and interfacial adhesion coefficient Perform real-time fluctuation analysis, identify corresponding abnormal events, and complete automatic tagging and data uploading.

[0017] Preferably, the state parameter estimation unit is used to calculate the state parameter based on the time series complex impedance. Extract interface state physiological characteristic indicators. The state parameter estimation unit includes a moisture analysis subunit, an inflammation response analysis subunit, and a denture adhesion analysis subunit.

[0018] The humidity analysis subunit is used to extract the real part impedance value of the low-frequency impedance signal below 1kHz. Constructing a gingival moisture index ;

[0019]

[0020] in, Indicates the individual calibration coefficient. This represents the real part impedance value in the low-frequency range. This indicates the estimated offset constant. The water content of the tissue significantly affects its low-frequency conductivity. In the low-frequency range, the current mainly propagates through the extracellular fluid. The lower the value, the more moisture there is, and therefore the higher the humidity.

[0021] The inflammatory response analysis subunit is used to extract the real part of the impedance from the electrical impedance signal. and the imaginary part of impedance Calculate the phase angle The variance over a given time window was statistically analyzed and defined as an inflammatory response indicator. :

[0022]

[0023]

[0024] in, This represents a statistical contrast operation. For the selected time evaluation window; Indicates the start time of the time window. This indicates the length of the assessment time window; inflammation-induced changes in tissue structure lead to changes in cell membrane capacitance and increased phase angle fluctuations, hence the use of inflammatory response indicators. Fluctuation is used to estimate the degree of inflammation;

[0025] The denture adhesion analysis subunit is used to statistically analyze the resistance fluctuation rate per unit time, measure the adhesion stability of the tissue contact interface, and construct the interface adhesion coefficient. :

[0026]

[0027] Among them, surface adhesion coefficient The smaller the value, the more stable the interface. This represents the real part of the impedance, in Ω, corresponding to the resistance component. The first derivative of resistance with respect to time is the absolute value of the rate of change of resistance, representing the speed at which resistance changes. Indicates from time arrive The definite integral operation over time; dt represents the length of the evaluation time window; dt represents the small change in the integral variable, and dt represents the small step size along the time axis.

[0028] When dentures are worn stably, The change is slow; if the contact is unstable or the interface adhesion changes repeatedly. The derivative of will fluctuate frequently, leading to Increased size indicates interface instability.

[0029] Preferably, the anomaly marker identification unit includes a first identification unit, a second identification unit, and a third identification unit;

[0030] The first identification unit is used for the previously constructed gingival moisture index. Let the current time be... During the time assessment window Inside, an abnormal humidity level is determined. The specific steps are as follows:

[0031] Calculate the decrease in gingival moisture :

[0032]

[0033] When the following conditions are met: This indicates the gingival moisture level within the time assessment window. If the moisture level drops by more than 20%, it is considered an abnormal drop event, indicating that there may be a risk of cracking at the denture contact points, abnormal saliva distribution, or local dehydration in the oral cavity, triggering an abnormal moisture warning command.

[0034] The second identification unit is used to preset an inflammation threshold. When inflammatory markers And within three consecutive event windows If the trend is increasing, it is determined to be an event of increased inflammatory response, indicating that there is a risk of infection at the denture wearing site, triggering an abnormal inflammation warning signal;

[0035] The third identification unit is used to extract the average value of the interface adhesion coefficient of previous historical windows. and the standard deviation of the adhesion volatility index Based on the established interface adhesion coefficient Make a judgment when the following conditions are met:

[0036] If two consecutive assessment windows occur, it is determined to be a rapid fluctuation event in adhesion, indicating a risk of denture loosening or occlusal interference, triggering an adhesion abnormality warning instruction.

[0037] Preferably, the trajectory record set is obtained in the following way:

[0038] At each sampling time The three-dimensional biting force vector at each contact point is output by the triaxial force solver unit. : ;

[0039] This represents the horizontal biting force at the position of the i-th contact point on the X-axis in the denture coordinate system.

[0040] This represents the horizontal biting force at the Y-axis position of the i-th contact point in the denture coordinate system;

[0041] The principal compressive stress component represents the position of the i-th contact point on the Z-axis in the denture coordinate system;

[0042] And simultaneously associate the spatial coordinates of the contact point. :

[0043] ;

[0044] in, This indicates the X-axis position of the i-th contact point in the denture coordinate system;

[0045] in, This indicates the Y-axis position of the i-th contact point in the denture coordinate system;

[0046] in, This indicates the Z-axis position of the i-th contact point in the denture coordinate system;

[0047] The final recorded data sequence is represented as follows:

[0048] ;

[0049] N represents the total number of samples taken in one chewing cycle; M represents the number of activated contact points in the sensor array.

[0050] Preferably, the three-dimensional bite force acquisition module further includes a high stress concentration identification subunit and a material redundancy design subunit;

[0051] The high-stress accumulation identification subunit is used to detect contact points with skewed stress distribution in the stress-thermal diagram, which are defined as local stress extreme points and their surrounding contact points.

[0052] The criteria for determining the high-stress accumulation contact point are as follows:

[0053] During multiple consecutive chewing cycles, the cumulative biting force at a certain contact point is... satisfy:

[0054] If the contact point is determined to be a localized high-stress concentration contact point, it will be marked and the process will proceed to the pre-reinforcement design stage.

[0055] in, This represents the average cumulative biting force at all contact points. This represents the standard deviation of bite force.

[0056] Preferably, the material redundancy design subunit is used to pre-define a material redundancy layer in the denture model for identified local high-stress concentration contact points. The thickness of this redundancy layer increases proportionally to the local maximum cumulative occlusal force, thereby enhancing the fatigue resistance of the contact point. For identified local high-stress concentration points, these are summarized as a set of surface units in the concentration area, and their corresponding cumulative occlusal force values ​​are obtained. A surface unit refers to a denture model formed by combining several surface units, i.e., j facets. The entire denture model's outer shell is composed of many small triangular or quadrilateral mesh facets. The cumulative occlusal force of the j-th surface unit is calculated by summation. :

[0057]

[0058] in, This indicates that the i-th contact point is at the th contact point. The force value per unit time in a chewing cycle; T represents the total number of chewing cycles recorded; This represents the number of locally high-stress-accumulation contact points identified in the j-th surface unit;

[0059] The cumulative biting force of several j-th surface units Inside, determine the maximum cumulative bite force. :

[0060]

[0061] in, This indicates the total number of surface units.

[0062] Preferably, the life assessment module includes a fatigue index calculation unit and a life warning instruction generation unit;

[0063] The fatigue index calculation unit is used to extract the cumulative biting force of the j-th surface unit for each surface unit j in the denture. Inflammatory response markers and interfacial adhesion coefficient After normalization, the fatigue index of the j-th surface element is constructed. :

[0064]

[0065] in, , and Represent the cumulative biting force of the j-th surface unit after normalization. Inflammatory response markers and interfacial adhesion coefficient The empirical weighting coefficients, with a weight sum of 1; Indicates the length of the life assessment time window.

[0066] Preferably, the lifespan warning command generation unit is used to preset a fatigue threshold. ,when Trigger lifespan warning commands, including:

[0067] Output the corresponding surface element, contact point number, and spatial coordinates;

[0068] It is recommended to perform local surface reinforcement treatment or compensation for redundant structures on the dentures;

[0069] When a lifespan warning command is detected, for each surface unit j, the cumulative biting force of its corresponding j-th surface unit is used. Redundancy thickness design is performed using a linear amplification function, and the redundancy thickness increment of the i-th surface unit is calculated. :

[0070]

[0071] in, The redundancy design factor for pressurized materials is set to 0.3-1.0; This represents the cumulative biting force of the j-th surface unit. , Indicates the maximum cumulative bite force , This represents the wall thickness of the j-th surface element in the denture model, and represents the redundant thickness increment of the i-th surface element. The message was sent to a doctor who recommended repair or replacement.

[0072] This invention provides a denture lifecycle management system based on individualized patient information. It has the following beneficial effects:

[0073] (1) This denture lifecycle management system based on individualized patient information, by setting up an interface state monitoring module, integrating an impedance signal acquisition unit, a state parameter estimation unit and an abnormal marker recognition unit, can achieve high-precision real-time perception of the physiological state of the denture edge and gingival contact interface, effectively solving the problem of lack of dynamic monitoring means of biological interface during the use of traditional dentures; by deploying a multi-channel flexible bioelectrode array on the inner side of the denture edge, and using the method of synchronous acquisition of alternating microcurrent injection and voltage response to obtain complex impedance sequence, combined with wearing status and time position data, accurate modeling of the electrical characteristics of gingival tissue can be achieved, which can distinguish between resistance and reactance components, thereby accurately estimating key physiological indicators such as gingival moisture, inflammatory response and interface adhesion coefficient, and further using the abnormal marker recognition unit to perform dynamic fluctuation analysis on these state parameters, timely detection of biological abnormal events such as interface dryness, decreased adhesion or increased inflammation, and automatic marking and data uploading, providing doctors with accurate intervention basis, significantly improving the biocompatibility, safety and intelligent management capabilities of long-term denture wear.

[0074] (2) This denture lifecycle management system based on individualized patient information, comprising a first identification unit, a second identification unit, and a third identification unit, enables real-time identification and early warning of three key risks: abnormal gingival moisture, increased inflammatory response, and unstable denture interface adhesion. This significantly improves the intelligence level and response timeliness of denture wearing status monitoring. Specifically, the first identification unit can sensitively detect a rapid decrease in moisture by comparing the current moisture index with the mean change within the evaluation window, thereby providing early warning of risks such as dryness or abnormal saliva distribution. The second identification unit sets an inflammatory index threshold and continuously tracks its increasing trend to ensure timely detection of the inflammatory development trend, assisting in determining whether infection may occur at the denture wearing site. The third identification unit adopts... The statistical characteristic judgment method of adhesion coefficient, combined with the mean and standard deviation, avoids false alarms caused by occasional fluctuations. The warning is only triggered when the adhesion fluctuation index is significantly weakened and occurs continuously, ensuring the reliability of the judgment results. This multi-parameter joint judgment mechanism enables the system to cover a variety of complex situations during the wearing process, effectively avoiding the problems of missed detection and false alarms caused by single monitoring dimensions or crude judgment logic, and further improving the safety of denture use and the scientific nature of maintenance. At the same time, the trajectory recording set, based on the spatial position of each occlusal contact point and its three-dimensional occlusal force vector, can accurately describe the stress state and usage conditions of the denture, providing high-resolution data support for subsequent fatigue analysis, life assessment and structural optimization, and realizing the visualization and intelligent management of the entire denture wearing process.

[0075] (3) This denture lifecycle management system based on individual patient information sets up a lifespan warning command generation unit and combines it with a preset fatigue threshold. It can dynamically monitor and intelligently judge the fatigue accumulation state of denture surface units during long-term use. Once the cumulative force value of any surface unit is identified to reach or exceed the fatigue threshold, a lifespan warning command can be triggered, and the contact point number and spatial coordinates of the surface unit can be output in a timely manner to provide doctors with accurate positioning information and avoid blind examination and intervention. In addition, by introducing a linear amplification function to realize the automatic calculation of redundant thickness increment, and considering the proportional relationship between the actual cumulative biting force and the maximum biting force of the model, and combining the original wall thickness value for redundant compensation design, it not only improves the local strengthening efficiency of denture structure, but also provides personalized structural optimization suggestions without interrupting wear and use, effectively extending the lifespan of dentures and reducing the risk of structural damage and functional decline. At the same time, by pushing the calculation results to the doctor's end in an interactive manner, a closed-loop risk response mechanism is formed, which enhances the foresight, scientific nature and timeliness of clinical intervention in denture wearing status management. Attached Figure Description

[0076] Figure 1 This is a schematic diagram of the process of a denture lifecycle management system based on individualized patient information according to the present invention. Detailed Implementation

[0077] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0078] Example 1

[0079] Please see Figure 1 This invention provides a denture lifecycle management system based on individualized patient information, comprising:

[0080] The interface status monitoring module, installed at the edge of the denture, includes a wearable bioelectrical impedance sensor unit to collect interfacial electrical impedance parameters at the contact point between the gingiva and the denture in real time, and calculate the gingival moisture index. Inflammatory response markers and interfacial adhesion coefficient It identifies three abnormal situations and generates corresponding abnormal warning instructions if any are identified.

[0081] The three-dimensional occlusal force acquisition module is used to acquire the three-dimensional occlusal force vector of each contact point on each contact surface of the denture during the patient's individualized chewing process. A three-dimensional occlusal force vector map model of the denture was constructed, and high stress concentration contact points were identified and marked.

[0082] The lifespan assessment module, based on joint modeling of the interface state and occlusal data, extracts the cumulative occlusal force of the j-th surface unit for each surface unit in the denture. Inflammatory response markers and interfacial adhesion coefficient Construct the fatigue index of the j-th surface element. To dynamically assess the local material performance degradation trend;

[0083] Preset fatigue threshold ,when This triggers a lifespan warning command, and for each surface unit j, it calculates the cumulative biting force based on the j-th surface unit. Redundancy thickness design is performed using a linear amplification function, and the redundancy thickness increment of the i-th surface unit is calculated. The information was then sent to a doctor, who recommended repair and replacement.

[0084] In this embodiment, the present invention effectively solves the problem of insufficient lifespan management caused by the reliance on dentist experience and the lack of dynamic monitoring and fatigue assessment mechanisms in traditional denture design. By integrating individualized occlusal force data and denture-gingival interface status information, it achieves real-time perception and accurate identification of the denture's usage status. It can not only dynamically monitor gingival moisture, inflammatory response, and interface adhesion coefficient, but also construct a complete mechanical behavior atlas model based on three-dimensional occlusal force data of multi-cycle chewing processes, identify high stress accumulation areas, and then construct a local fatigue index by combining the force and biological state of each contact surface to dynamically assess the material performance degradation trend. This makes up for the shortcomings of existing technologies that cannot reflect the complex environmental changes during actual wear. In addition, after identifying local fatigue risks, the system can intelligently generate reinforcement suggestions, including design values ​​for redundant thickness increments and early warning information, to assist dentists in timely repair or replacement. This improves the scientific nature of denture design and the level of intelligent post-management from the source, significantly reduces the probability of early denture failure, and extends the service life.

[0085] Example 2

[0086] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the interface status monitoring module includes an impedance signal acquisition unit, a status parameter calculation unit, and an anomaly marker identification unit;

[0087] The impedance signal acquisition unit is embedded in the inner surface of the denture edge and deploys a multi-channel flexible bioelectrode array. It continuously acquires impedance signals at the contact point between the gingiva and the denture based on a fixed sampling frequency. The impedance measurement adopts a method of synchronous reading of alternating microcurrent injection and voltage response to obtain a complex impedance sequence. The acquisition timestamp t, electrode position coordinates, microcurrent intensity, and denture wearing status are recorded simultaneously.

[0088] The complex impedance of the time series was calculated based on Ohm's law. :

[0089]

[0090] in, This represents a complex impedance signal, measured in ohms, indicating the overall electrical properties of the gingival-prosthetic interface tissue. This represents the complex impedance signal, measured by the attached electrode array at time point t, and is measured in volts. This indicates the applied AC excitation current, measured in amperes, with an amplitude in the microampere range. This represents the real part of the impedance, in Ω, and corresponds to the resistance component, which is affected by the tissue water content. The impedance represents the imaginary part, in Ω, corresponding to the reactance component, which is related to cell structure, capacitance characteristics, and interfacial adhesion state; j represents the imaginary unit, satisfying... ;

[0091] The state parameter calculation unit is used to calculate the state parameter based on the time series complex impedance. Extract physiological characteristic indicators of the interface state, including gingival moisture index. Inflammatory response markers and interfacial adhesion coefficient ;

[0092] The anomaly marker identification unit is used to analyze the calculated gingival moisture index. Inflammatory response markers and interfacial adhesion coefficient Perform real-time fluctuation analysis, identify corresponding abnormal events, and complete automatic tagging and data uploading.

[0093] In this embodiment, the present invention, by setting up an interface state monitoring module, integrates an impedance signal acquisition unit, a state parameter estimation unit, and an anomaly marker recognition unit, enabling high-precision real-time perception of the physiological state of the interface between the denture edge and the gingiva. This effectively solves the problem of the lack of dynamic monitoring methods for biological interfaces during the use of traditional dentures. By deploying a multi-channel flexible bioelectrode array on the inner side of the denture edge, and using a method of synchronous acquisition of alternating microcurrent injection and voltage response to obtain complex impedance sequences, combined with wearing status and time position data, accurate modeling of the electrical properties of gingival tissue can be achieved. This allows for the differentiation of resistance and reactance components, thereby accurately estimating key physiological indicators such as gingival moisture, inflammatory response, and interface adhesion coefficient. Furthermore, the anomaly marker recognition unit performs dynamic fluctuation analysis on these state parameters, promptly detecting biological abnormalities such as interface dryness, decreased adhesion, or increased inflammation, and automatically marking and uploading the data. This provides doctors with accurate intervention basis, significantly improving the biocompatibility, safety, and intelligent management capabilities of long-term denture wear.

[0094] Example 3

[0095] This embodiment is an explanation based on Embodiment 2. Please refer to it. Figure 1 Specifically, the state parameter calculation unit is used to calculate the state parameter based on the time series complex impedance. Extract interface state physiological characteristic indicators. The state parameter estimation unit includes a moisture analysis subunit, an inflammation response analysis subunit, and a denture adhesion analysis subunit.

[0096] The humidity analysis subunit is used to extract the real part impedance value of the low-frequency impedance signal below 1kHz. Constructing a gingival moisture index ;

[0097]

[0098] in, Indicates the individual calibration coefficient. This represents the real part impedance value in the low-frequency range. This indicates the estimated offset constant. The water content of the tissue significantly affects its low-frequency conductivity. In the low-frequency range, the current mainly propagates through the extracellular fluid. The lower the value, the more moisture there is, and therefore the higher the humidity.

[0099] The inflammatory response analysis subunit is used to extract the real part of the impedance from the electrical impedance signal. and the imaginary part of impedance Calculate the phase angle The variance over a given time window was statistically analyzed and defined as an inflammatory response indicator. :

[0100]

[0101]

[0102] in, This represents a statistical contrast operation. For the selected time evaluation window; Indicates the start time of the time window. This indicates the length of the assessment time window; inflammation-induced changes in tissue structure lead to changes in cell membrane capacitance and increased phase angle fluctuations, hence the use of inflammatory response indicators. Fluctuation is used to estimate the degree of inflammation;

[0103] The denture adhesion analysis subunit is used to statistically analyze the resistance fluctuation rate per unit time, measure the adhesion stability of the tissue contact interface, and construct the interface adhesion coefficient. :

[0104]

[0105] Among them, surface adhesion coefficient The smaller the value, the more stable the interface. This represents the real part of the impedance, in Ω, corresponding to the resistance component. The first derivative of resistance with respect to time is the absolute value of the rate of change of resistance, representing the speed at which resistance changes. Indicates from time arrive The definite integral operation over time; dt represents the length of the evaluation time window; dt represents the small change in the integral variable, and dt represents the small step size along the time axis.

[0106] When dentures are worn stably, The change is slow; if the contact is unstable or the interface adhesion changes repeatedly. The derivative of will fluctuate frequently, leading to Increased size indicates interface instability.

[0107] In this embodiment, the wettability analysis subunit, the inflammation response analysis subunit, and the denture adhesion analysis subunit independently analyze and construct indicators for water content, tissue inflammation degree, and contact adhesion stability, respectively. The wettability analysis subunit extracts low-frequency real impedance values ​​to construct a gingival wettability index, which can sensitively reflect changes in local tissue water content. The inflammation response analysis subunit calculates the complex impedance phase angle and its fluctuation variance within the evaluation time window to accurately assess changes in cell membrane structural capacitance caused by inflammation, quantifying the degree of inflammation fluctuation. The denture adhesion analysis subunit calculates the resistance fluctuation rate based on the first derivative of resistance to construct an interface adhesion coefficient, used to reflect the contact stability and interface fit during denture wearing in real time. This structural design not only achieves continuous sensing and accurate assessment of the microscopic electrical properties between dentures and biological tissues but also timely identifies risk signs in the early stages of wearing abnormalities, providing doctors with a scientific and objective basis for intervention decisions. This effectively avoids denture loosening, pain, or local lesions caused by interface problems, improving the comfort, safety, and lifespan of denture wearing.

[0108] Example 4

[0109] This embodiment is an explanation based on Embodiment 3. Please refer to it. Figure 1 Specifically, the anomaly marker identification unit includes a first identification unit, a second identification unit, and a third identification unit;

[0110] The first identification unit is used for the previously constructed gingival moisture index. Let the current time be... During the time assessment window Inside, an abnormal humidity level is determined. The specific steps are as follows:

[0111] Calculate the decrease in gingival moisture :

[0112]

[0113] When the following conditions are met: This indicates the gingival moisture level within the time assessment window. If the moisture level drops by more than 20%, it is considered an abnormal drop event, indicating that there may be a risk of cracking at the denture contact points, abnormal saliva distribution, or local dehydration in the oral cavity, triggering an abnormal moisture warning command.

[0114] The second identification unit is used to preset an inflammation threshold. When inflammatory markers And within three consecutive event windows If the trend is increasing, it is determined to be an event of increased inflammatory response, indicating that there is a risk of infection at the denture wearing site, triggering an abnormal inflammation warning signal;

[0115] The third identification unit is used to extract the average value of the interface adhesion coefficient of previous historical windows. and the standard deviation of the adhesion volatility index Based on the established interface adhesion coefficient Make a judgment when the following conditions are met:

[0116] If two consecutive assessment windows occur, it is determined to be a rapid fluctuation event in adhesion, indicating a risk of denture loosening or occlusal interference, triggering an adhesion abnormality warning instruction. This indicates the threshold of being two standard deviations below the mean, if at the current time... The value is less than or equal to If the adhesion fluctuation intensity is significantly reduced (much lower than normal fluctuation), and this situation occurs for at least two consecutive time windows (to avoid occasional false alarms), then it can be judged as an "adhesive fluctuation event," which means there is a risk of denture loosening or poor contact. This is similar to body temperature having an average of 36.5°C and a standard deviation of 0.3°C. If you measure 35.9°C (less than the average minus 2 × 0.3), then it may not be a "normal fluctuation," but rather a "problem."

[0117] The trajectory record set is obtained in the following way:

[0118] At each sampling time The three-dimensional biting force vector at each contact point is output by the triaxial force solver unit. : ;

[0119] This represents the horizontal biting force at the position of the i-th contact point on the X-axis in the denture coordinate system.

[0120] This represents the horizontal biting force at the Y-axis position of the i-th contact point in the denture coordinate system;

[0121] The principal compressive stress component represents the position of the i-th contact point on the Z-axis in the denture coordinate system;

[0122] And simultaneously associate the spatial coordinates of the contact point. :

[0123] ;

[0124] in, This indicates the X-axis position of the i-th contact point in the denture coordinate system;

[0125] in, This indicates the Y-axis position of the i-th contact point in the denture coordinate system;

[0126] in, This indicates the Z-axis position of the i-th contact point in the denture coordinate system;

[0127] The final recorded data sequence is represented as follows:

[0128] ;

[0129] N represents the total number of samples taken in one chewing cycle; M represents the number of activated contact points in the sensor array.

[0130] In this embodiment, the first, second, and third identification units enable real-time identification and early warning of three key risks: abnormal gingival moisture, increased inflammation, and unstable denture adhesion. This significantly improves the intelligence and responsiveness of denture wearing status monitoring. Specifically, the first identification unit can sensitively detect a rapid decrease in moisture by comparing the current moisture index with the mean change within the evaluation window, thus providing early warning of risks such as dryness or abnormal saliva distribution. The second identification unit sets an inflammation index threshold and continuously tracks its increasing trend to ensure timely detection of inflammation development, assisting in determining whether infection may occur at the denture wearing site. The third identification unit uses the statistical characteristics of the adhesion coefficient. The judgment method, combining the average value and standard deviation, avoids false alarms caused by occasional fluctuations. It only triggers an alarm when the adhesion fluctuation index significantly weakens and occurs continuously, ensuring the reliability of the judgment results. This multi-parameter joint judgment mechanism enables the system to cover various complex situations during the wearing process, effectively avoiding the problems of missed detections and false alarms caused by single monitoring dimensions or crude judgment logic, further improving the safety of denture use and the scientific nature of maintenance. At the same time, the trajectory recording set, based on the spatial position of each occlusal contact point and its three-dimensional occlusal force vector, can accurately describe the stress state and usage conditions of the denture, providing high-resolution data support for subsequent fatigue analysis, life assessment and structural optimization, realizing the visualization and intelligent management of the entire denture wearing process.

[0131] Example 5

[0132] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the three-dimensional bite force acquisition module also includes a high stress concentration identification subunit and a material redundancy design subunit;

[0133] The high-stress accumulation identification subunit is used to detect contact points with skewed stress distribution in the stress-thermal diagram, which are defined as local stress extreme points and their surrounding contact points.

[0134] The criteria for determining the high-stress accumulation contact point are as follows:

[0135] During multiple consecutive chewing cycles, the cumulative biting force at a certain contact point is... satisfy:

[0136] If the contact point is determined to be a localized high-stress concentration contact point, it will be marked and the process will proceed to the pre-reinforcement design stage.

[0137] in, This represents the average cumulative biting force at all contact points. This represents the standard deviation of bite force.

[0138] The material redundancy design subunit is used to pre-define a material redundancy layer in the denture model for identified local high-stress concentration contact points. The thickness of this redundancy layer increases proportionally to the local maximum cumulative occlusal force, enhancing the fatigue resistance of the contact point. For identified local high-stress concentration points, these are summarized as a set of surface units in the concentration area, and their corresponding cumulative occlusal force values ​​are obtained. A surface unit refers to a denture model formed by combining several surface units, i.e., j facets. The entire denture model's outer shell is composed of many small triangular or quadrilateral mesh facets. The cumulative occlusal force of the j-th surface unit is calculated by summation. :

[0139]

[0140] in, This indicates that the i-th contact point is at the th contact point. The force value per unit time in a chewing cycle; T represents the total number of chewing cycles recorded; This represents the number of locally high-stress-accumulation contact points identified in the j-th surface unit;

[0141] The cumulative biting force of several j-th surface units Inside, determine the maximum cumulative bite force. :

[0142]

[0143] in, This indicates the total number of surface units.

[0144] In this embodiment, by introducing a high-stress concentration identification subunit and a material redundancy design subunit into the three-dimensional occlusal force acquisition module, it is possible to accurately identify areas of abnormal force concentration in the denture during multi-cycle chewing. Based on the statistical criteria of local occlusal force, local high-stress concentration contact points are identified, and the cumulative force is quantitatively analyzed by combining the surface combination calculation method. On this basis, a material redundancy layer is designed according to the proportional relationship of the local maximum occlusal force to strengthen and reinforce the local fatigue-prone areas, thereby improving the overall structural durability and fatigue life of the denture model, avoiding early damage to the denture caused by local ultimate load, and possessing good clinical adaptability and structural stability.

[0145] Example 6

[0146] This embodiment is an explanation based on Embodiment 1. Please refer to it. Figure 1 Specifically, the life assessment module includes a fatigue index calculation unit and a life warning instruction generation unit;

[0147] The fatigue index calculation unit is used to extract the cumulative biting force of the j-th surface unit for each surface unit j in the denture. Inflammatory response markers and interfacial adhesion coefficient After normalization, the fatigue index of the j-th surface element is constructed. :

[0148]

[0149] in, , and Represent the cumulative biting force of the j-th surface unit after normalization. Inflammatory response markers and interfacial adhesion coefficient The empirical weighting coefficients, with a weight sum of 1; , , ;

[0150] in, This indicates the length of the lifespan assessment time window. It comprehensively considers three key influencing factors for each denture surface unit: cumulative occlusal force, inflammatory response indicators, and interfacial adhesion coefficient. By introducing normalization and weighted fusion mechanisms, indicators of different dimensions can be measured for their fatigue impact on a unified scale. Furthermore, by constructing a fatigue index model within the lifespan assessment time window, it achieves a multi-dimensional dynamic assessment of localized stress fatigue, inflammatory erosion, and material bonding stability in dentures, effectively improving the accuracy and timeliness of lifespan early warning judgments.

[0151] The lifespan warning command generation unit is used to preset the fatigue threshold. ,when Trigger lifespan warning commands, including:

[0152] Output the corresponding surface element, contact point number, and spatial coordinates;

[0153] It is recommended to perform local surface reinforcement treatment or compensation for redundant structures on the dentures;

[0154] When a lifespan warning command is detected, for each surface unit j, the cumulative biting force of its corresponding j-th surface unit is used. Redundancy thickness design is performed using a linear amplification function, and the redundancy thickness increment of the i-th surface unit is calculated. :

[0155]

[0156] in, The redundancy design factor for pressurized materials is set to 0.3-1.0; This represents the cumulative biting force of the j-th surface unit. , Indicates the maximum cumulative bite force , This represents the wall thickness of the j-th surface element in the denture model, and represents the redundant thickness increment of the i-th surface element. The message was sent to a doctor who recommended repair or replacement.

[0157] In this embodiment, a lifespan warning command generation unit is set up and combined with a preset fatigue threshold to dynamically monitor and intelligently judge the fatigue accumulation state of the denture surface units during long-term use. Once the cumulative force value of any surface unit is identified to reach or exceed the fatigue threshold, a lifespan warning command is triggered, and the contact point number and spatial coordinates of the surface unit are output in a timely manner, providing doctors with accurate positioning information and avoiding blind examination and intervention. In addition, by introducing a linear amplification function to realize the automatic calculation of redundant thickness increment, and considering the proportional relationship between the actual cumulative biting force and the maximum biting force of the model, and combining it with the original wall thickness value for redundant compensation design, not only is the local strengthening efficiency of the denture structure improved, but personalized structural optimization suggestions can also be provided without interrupting wearing and use, effectively extending the lifespan of the denture and reducing the risk of structural damage and functional decline. At the same time, by pushing the calculation results to the doctor's end in an interactive manner, a closed-loop risk response mechanism is formed, which enhances the foresight, scientific nature and timeliness of clinical intervention in denture wearing status management.

[0158] The threshold is set to facilitate comparison. The size of the threshold depends on the amount of sample data and the number of bases set by those skilled in the art for each set of sample data; as long as it does not affect the ratio between the parameter and the quantized value, it is acceptable.

[0159] The above formulas are all derived from software simulation using a large amount of data and are selected to be close to the actual values. The coefficients in the formulas are set by those skilled in the art according to the actual situation. The above description is only a preferred embodiment of the present invention, but the protection scope of the present invention is not limited thereto. Any equivalent substitutions or changes made by those skilled in the art within the technical scope disclosed in the present invention, based on the technical solution and inventive concept of the present invention, should be covered within the protection scope of the present invention.

Claims

1. A denture lifecycle management system based on individualized patient information, characterized in that, include: The interface status monitoring module, installed at the edge of the denture, includes a wearable bioelectrical impedance sensor unit to collect interfacial electrical impedance parameters at the contact point between the gingiva and the denture in real time, and calculate the gingival moisture index. Inflammatory response markers and interfacial adhesion coefficient It identifies three abnormal situations and generates corresponding abnormal warning instructions if any are identified. The three-dimensional occlusal force acquisition module is used to acquire the three-dimensional occlusal force vector of each contact point on each contact surface of the denture during the patient's individualized chewing process. A three-dimensional occlusal force vector map model of the denture was constructed, and high stress concentration contact points were identified and marked. The lifespan assessment module, based on joint modeling of the interface state and occlusal data, extracts the cumulative occlusal force of the j-th surface unit for each surface unit in the denture. Inflammatory response markers and interfacial adhesion coefficient Construct the fatigue index of the j-th surface element. To dynamically assess the local material performance degradation trend; Preset fatigue threshold ,when This triggers a lifespan warning command, and for each surface unit j, it calculates the cumulative biting force based on the j-th surface unit. Redundancy thickness design is performed using a linear amplification function, and the redundancy thickness increment of the i-th surface unit is calculated. The information was then sent to a doctor, who recommended repair and replacement.

2. The denture lifecycle management system based on individualized patient information according to claim 1, characterized in that, The interface status monitoring module includes an impedance signal acquisition unit, a status parameter calculation unit, and an anomaly marker identification unit. The impedance signal acquisition unit is embedded in the inner surface of the denture edge and deploys a multi-channel flexible bioelectrode array. It continuously acquires impedance signals at the contact point between the gingiva and the denture based on a fixed sampling frequency. The impedance measurement adopts a method of synchronous reading of alternating microcurrent injection and voltage response to obtain a complex impedance sequence. The acquisition timestamp t, electrode position coordinates, microcurrent intensity, and denture wearing status are recorded simultaneously. The complex impedance of the time series was calculated based on Ohm's law. : in, This represents a complex impedance signal, measured in ohms, indicating the overall electrical properties of the gingival-prosthetic interface tissue. This represents the complex impedance signal, measured by the attached electrode array at time point t, and is measured in volts. This indicates the applied AC excitation current, measured in amperes, with an amplitude in the microampere range. This represents the real part of the impedance, in Ω, and corresponds to the resistance component, which is affected by the tissue water content. This represents the imaginary part of impedance, in Ω, and corresponds to the reactance component, which is related to cell structure, capacitance characteristics, and interfacial adhesion state. j represents the imaginary unit, satisfying... ; The state parameter calculation unit is used to calculate the state parameter based on the time series complex impedance. Extract physiological characteristic indicators of the interface state, including gingival moisture index. Inflammatory response markers and interfacial adhesion coefficient ; The anomaly marker identification unit is used to analyze the calculated gingival moisture index. Inflammatory response markers and interfacial adhesion coefficient Perform real-time fluctuation analysis, identify corresponding abnormal events, and complete automatic tagging and data uploading.

3. The denture lifecycle management system based on individualized patient information according to claim 2, characterized in that, The state parameter calculation unit is used to calculate the state parameter based on the time series complex impedance. Extract interface state physiological characteristic indicators. The state parameter estimation unit includes a moisture analysis subunit, an inflammation response analysis subunit, and a denture adhesion analysis subunit. The humidity analysis subunit is used to extract the real part impedance value of the low-frequency impedance signal below 1kHz. Constructing a gingival moisture index ; in, Indicates the individual calibration coefficient. This represents the real part impedance value in the low-frequency range. This indicates the estimated offset constant. The water content of the tissue significantly affects its low-frequency conductivity. In the low-frequency range, the current mainly propagates through the extracellular fluid. The lower the value, the more moisture there is, and therefore the higher the humidity. The inflammatory response analysis subunit is used to extract the real part of the impedance from the electrical impedance signal. and the imaginary part of impedance Calculate the phase angle The variance over a given time window was statistically analyzed and defined as an inflammatory response indicator. : in, This represents a statistical contrast operation. For the selected time evaluation window; Indicates the start time of the time window. This indicates the length of the assessment time window; inflammation-induced changes in tissue structure lead to changes in cell membrane capacitance and increased phase angle fluctuations, hence the use of inflammatory response indicators. Fluctuation is used to estimate the degree of inflammation; The denture adhesion analysis subunit is used to statistically analyze the resistance fluctuation rate per unit time, measure the adhesion stability of the tissue contact interface, and construct the interface adhesion coefficient. : Among them, surface adhesion coefficient The smaller the value, the more stable the interface. This represents the real part of the impedance, in Ω, corresponding to the resistance component. The first derivative of resistance with respect to time is the absolute value of the rate of change of resistance, representing the speed at which resistance changes. Indicates from time arrive The definite integral operation over time; dt represents the length of the evaluation time window; dt represents the small change in the integral variable, and dt represents the small step size along the time axis. When dentures are worn stably, The change is slow; if the contact is unstable or the interface adhesion changes repeatedly. The derivative of will fluctuate frequently, leading to Increased size indicates interface instability.

4. A denture lifecycle management system based on individualized patient information as described in claim 2, characterized in that, The anomaly marker identification unit includes a first identification unit, a second identification unit, and a third identification unit; The first identification unit is used for the previously constructed gingival moisture index. Let the current time be... During the time assessment window Inside, an abnormal humidity level is determined. The specific steps are as follows: Calculate the decrease in gingival moisture : When the following conditions are met: This indicates the gingival moisture level within the time assessment window. If the moisture level drops by more than 20%, it is considered an abnormal drop event, indicating that there may be a risk of cracking at the denture contact points, abnormal saliva distribution, or local dehydration in the oral cavity, triggering an abnormal moisture warning command. The second identification unit is used to preset an inflammation threshold. When inflammatory markers And within three consecutive event windows If the trend is increasing, it is determined to be an event of increased inflammatory response, indicating that there is a risk of infection at the denture wearing site, triggering an abnormal inflammation warning signal; The third identification unit is used to extract the average value of the interface adhesion coefficient of previous historical windows. and the standard deviation of the adhesion volatility index Based on the established interface adhesion coefficient Make a judgment when the following conditions are met: If two consecutive assessment windows occur, it is determined to be a rapid fluctuation event in adhesion, indicating a risk of denture loosening or occlusal interference, triggering an adhesion abnormality warning instruction.

5. A denture lifecycle management system based on individualized patient information as described in claim 1, characterized in that, The three-dimensional occlusal force acquisition module is located at the main force contact point of the denture, including a distributed pressure sensor array subunit, a triaxial force calculation subunit, an occlusal trajectory recording unit, and an occlusal force vector map generation unit; The distributed pressure sensor array subunit is deployed at multiple contact points on the occlusal surface of the denture to collect the pressure per unit contact area during the chewing process. The triaxial force calculation subunit is used to calculate the bite force vector components of each contact point in the three-dimensional coordinate system based on the raw pressure data of the sensor array. ; This indicates the horizontal biting force along the left-right direction. This represents the horizontal biting force along the front-to-back direction. Indicates the principal compressive stress component along the vertical direction; The bite trajectory recording unit is used to continuously record the force change trajectory of each contact position at different time points during the chewing cycle, forming a trajectory recording set; The biting force vector map generation unit is used to perform temporal overlay and spatial mapping of the collected trajectory record set to construct a three-dimensional biting force vector map model of the denture, which is used for subsequent local fatigue assessment and analysis.

6. A denture lifecycle management system based on individualized patient information as described in claim 5, characterized in that, The trajectory record set is obtained in the following way: At each sampling time The three-dimensional biting force vector at each contact point is output by the triaxial force solver unit. : ; This represents the horizontal biting force at the position of the i-th contact point on the X-axis in the denture coordinate system. This represents the horizontal biting force at the Y-axis position of the i-th contact point in the denture coordinate system; The principal compressive stress component represents the position of the i-th contact point on the Z-axis in the denture coordinate system; And simultaneously associate the spatial coordinates of the contact point. : ； in, This indicates the X-axis position of the i-th contact point in the denture coordinate system; in, This indicates the Y-axis position of the i-th contact point in the denture coordinate system; in, This indicates the Z-axis position of the i-th contact point in the denture coordinate system; The final recorded data sequence is represented as follows: ； N represents the total number of samples taken in one chewing cycle; M represents the number of activated contact points in the sensor array.

7. A denture lifecycle management system based on individualized patient information according to claim 1, characterized in that, The three-dimensional bite force acquisition module also includes a high stress concentration identification subunit and a material redundancy design subunit; The high-stress accumulation identification subunit is used to detect contact points with skewed stress distribution in the stress-thermal diagram, which are defined as local stress extreme points and their surrounding contact points. The criteria for determining the high-stress accumulation contact point are as follows: During multiple consecutive chewing cycles, the cumulative biting force at a certain contact point is... satisfy: If the contact point is determined to be a localized high-stress concentration contact point, it will be marked and the process will proceed to the pre-reinforcement design stage. in, This represents the average cumulative biting force at all contact points. This represents the standard deviation of bite force.

8. A denture lifecycle management system based on individualized patient information according to claim 7, characterized in that, The material redundancy design subunit is used to pre-set a material redundancy layer in the denture model for the identified local high stress concentration contact points. The thickness of the material redundancy layer is increased proportionally to the local maximum cumulative occlusal force to enhance the fatigue resistance of the contact point. For identified local high-stress concentration points, these are summarized and recorded as a set of surface elements in the concentration area, and their corresponding cumulative occlusal force values ​​are obtained. A surface element refers to a denture model formed by combining several surface elements, i.e., j facets. The entire denture model's shell is composed of many small triangular or quadrilateral mesh facets. The cumulative occlusal force of the j-th surface element is calculated by summation. : in, This indicates that the i-th contact point is at the th contact point. The force value per unit time in a chewing cycle; T represents the total number of chewing cycles recorded; This represents the number of locally high-stress-accumulation contact points identified in the j-th surface unit; The cumulative biting force of several j-th surface units Inside, determine the maximum cumulative bite force. : in, This indicates the total number of surface units.

9. A denture lifecycle management system based on individualized patient information as described in claim 8, characterized in that, The life assessment module includes a fatigue index calculation unit and a life warning command generation unit. The fatigue index calculation unit is used to extract the cumulative biting force of the j-th surface unit for each surface unit j in the denture. Inflammatory response markers and interfacial adhesion coefficient After normalization, the fatigue index of the j-th surface element is constructed. : in, , and Represent the cumulative biting force of the j-th surface unit after normalization. Inflammatory response markers and interfacial adhesion coefficient The empirical weighting coefficient, Indicates the length of the life assessment time window.

10. A denture lifecycle management system based on individualized patient information according to claim 9, characterized in that, The lifespan warning command generation unit is used to preset the fatigue threshold. ,when Trigger lifespan warning commands, including: Output the corresponding surface element, contact point number, and spatial coordinates; It is recommended to perform local surface reinforcement treatment or compensation for redundant structures on the dentures; When a lifespan warning command is detected, for each surface unit j, the cumulative biting force of its corresponding j-th surface unit is used. Redundancy thickness design is performed using a linear amplification function, and the redundancy thickness increment of the i-th surface unit is calculated. : in, The redundancy design factor for pressurized materials is set to 0.3-1.0; This represents the cumulative biting force of the j-th surface unit. , Indicates the maximum cumulative bite force , This represents the wall thickness of the j-th surface element in the denture model, and represents the redundant thickness increment of the i-th surface element. The message was sent to a doctor who recommended repair or replacement.

Images