An intraoperative acetabular inner wall three-dimensional shape infrared verification device and detection method

Abstract

The application discloses an intraoperative acetabular inner wall three-dimensional form infrared verification device and a detection method, relates to the technical field of hip joint replacement detection, and comprises the following steps: S1, collecting a no-load baseline before use; S2, probe positioning and self-checking; S3, four batches of infrared reflection sampling; S4, filtering and baseline calibration; S5, channel-by-channel difference and uploading; S6, point cloud surface reconstruction; S7, deviation curvature analysis; S8, tolerance eligibility determination; S9, result output and selection. The application adopts a snapshot sampling scheme of four batches of synchronous light emission, through the time sequence design of synchronous lighting of all three-layer same serial number light emitting devices in the same batch and rapid switching between batches, full array sampling can be completed in milliseconds, position deviation and detection artifacts caused by micro-motion of intraoperative handheld operation can be effectively avoided, and therefore, the consistency of the sampling position is ensured.

Description

Technical Field

[0001] This invention relates to the field of hip replacement testing technology, and in particular to an infrared verification device and testing method for the three-dimensional morphology of the acetabular wall during surgery. Background Technology

[0002] Total hip arthroplasty is a technically mature joint reconstruction surgery in the field of orthopedics. As a standard treatment for end-stage hip joint diseases, it is mainly suitable for conditions such as avascular necrosis of the femoral head, severe osteoarthritis of the hip, rheumatoid arthritis, and displaced femoral neck fractures in the elderly, which cause severe hip pain, limited mobility, and functional impairment. The surgery involves surgically removing the damaged acetabulum and diseased tissue of the femoral head and implanting an artificial acetabular component, femoral stem, and femoral head prosthesis made of biocompatible materials such as metal and ultra-high molecular weight polyethylene. This replaces the original physiological structure and mechanical function of the diseased joint, effectively eliminating joint pain, restoring hip joint mobility and weight-bearing walking ability of the lower limbs, and significantly improving the patient's quality of life.

[0003] However, in current total hip replacement surgery, the quality of acetabular resurfacing directly determines the precision of prosthesis fit, initial stability, and long-term clinical outcomes. Clinically, the acetabular lining is required to have an ideal concentric spherical shell shape with continuous curvature, smooth transition, and minimal overall deviation. Currently, intraoperative assessment relies primarily on the surgeon's visual observation and experience, lacking objective and quantitative verification methods. Conventional optical detection devices suffer from slow sampling speeds, susceptibility to artifacts caused by hand movements, and unreasonable light source layouts. Interlayer crosstalk and stray light interference from reflections within the same layer are difficult to suppress, hindering high-precision three-dimensional surface reconstruction. Furthermore, the lack of standardized elimination mechanisms for inherent weak interferences in the optical path results in insufficient detection stability and consistency, failing to meet the demands for accurate, rapid, and reliable intraoperative detection.

[0004] In the existing technology, there are also corresponding solutions for three-dimensional measurement and positioning of the acetabulum.

[0005] Chinese invention patent CN121639776A discloses a method, device, terminal, and storage medium for automatic measurement of acetabular three-dimensional orientation based on deep learning. This method detects the acetabular three-dimensional orientation by identifying and locating three-dimensional acetabular edge points, converting this information into two-dimensional key point identification of a slice image of the acetabular region, and then reconstructing the acetabular structure using these two-dimensional key points. This application improves the accuracy of traditional acetabular orientation measurement methods, reduces the operational difficulty of measurement, and decreases the labor costs associated with measurement. It helps doctors obtain the patient's acetabular orientation more accurately and provides guidance for the planning of the acetabular cup prosthesis in total hip arthroplasty, enabling doctors to more conveniently utilize acetabular orientation for surgical planning and provide better medical services to patients.

[0006] However, while the aforementioned existing patents can focus on the identification and measurement of the three-dimensional orientation of the acetabulum, the existing technologies mostly rely on key point identification and three-dimensional reconstruction of two-dimensional slice images. This is an image-based offline measurement, which cannot solve the core problems of optimizing sampling efficiency, suppressing hand micro-movement artifacts, and eliminating interlayer crosstalk and reflected stray light in intraoperative optical detection scenarios. It also cannot meet the requirements of real-time, high-precision, and high-stability intraoperative acetabular surface quality detection, and it is difficult to provide immediate quantitative feedback and accuracy guidance for intraoperative grinding operations. Summary of the Invention

[0007] The purpose of this application is to provide an infrared verification device and detection method for the three-dimensional morphology of the acetabular wall during surgery, in order to solve the problem that existing total hip replacement surgeries mainly rely on doctors' visual observation of the acetabulum and subjective judgment based on experience, lacking objective quantitative verification methods.

[0008] This invention includes a probe module, an embedded lower-level machine, a communication module, and a upper-level machine. The probe employs three layers of light sources with different infrared bands: an upper layer of 810nm, a middle layer of 940nm, and a lower layer of 850nm. Each layer has three groups of working units evenly distributed in a 120° circle, and each working unit contains four infrared light-emitting devices. The light-emitting devices with the same sequence number between layers are arranged in a circumferentially staggered and equidistant manner, forming a three-dimensional equilateral triangular optical path structure. The device adopts a four-batch synchronous light emission mode, in which all light-emitting devices with the same sequence number in the three layers of the same batch are lit synchronously, and four batches complete the instantaneous sampling of the entire area, achieving an equivalent optical snapshot and avoiding detection position shift caused by hand-held micro-movements. Physical isolation between layers is achieved through band differentiation, direct and reflected stray light is suppressed through 120° circumferential distribution and three-dimensional triangular geometry, and weak fixed reflection interference is eliminated through empty baseline subtraction. These three mechanisms ensure detection stability. The method constructs a three-dimensional point cloud of the acetabular inner wall based on multi-channel instantaneous sampling data, and completes surface reconstruction, sphericity fitting, curvature continuity analysis, radial deviation calculation, and local defect identification. It determines whether the inner wall morphology meets the prosthesis placement requirements based on the tolerance range corresponding to different diameters, and outputs suggestions for suitable prosthesis models. It features strong anti-interference ability, fast sampling speed, and structural stability and reliability, enabling objective, standardized, and quantitative verification of the acetabular inner wall morphology during surgery.

[0009] An intraoperative infrared verification device for the three-dimensional morphology of the acetabular wall includes a probe module, an embedded lower-level computer, a communication module, and an upper-level computer. The probe module further includes an upper infrared light source, a middle infrared light source at the bottom of the upper infrared light source, and a lower infrared light source at the bottom of the middle infrared light source. Each of the upper, middle, and lower infrared light sources is divided into three equal parts. Each part is configured as a working unit. A first measuring device, a second measuring device, a third measuring device, and a fourth measuring device are sequentially fixedly connected to the surface of each working unit. This three-layered infrared light source structure, with its three equally divided working units and four sets of measuring devices per unit, forms a circumferentially uniformly distributed, longitudinally hierarchically distinct multi-point infrared sampling array, ensuring spatial coverage and point density for acetabular wall detection.

[0010] As a further improvement of the present invention, the first, second, third, and fourth measuring devices fixedly connected to the upper infrared light source are all in the 810nm infrared band, the first, second, third, and fourth measuring devices fixedly connected to the middle infrared light source are all in the 940nm infrared band, and the first, second, third, and fourth measuring devices fixedly connected to the lower infrared light source are all in the 850nm infrared band. The upper, middle, and lower infrared light sources are physically isolated through band differences and narrowband filter structures, and do not interfere with each other. Each working unit of the upper, middle, and lower infrared light sources is arranged at an equal angle of 120° along the circumference. The three infrared light sources employ differentiated infrared bands and are combined with narrowband filters to achieve physical isolation between layers and prevent crosstalk. Combined with the circumferential arrangement of each working unit at a uniform 120° angle, interlayer light interference is suppressed and the sampling points are evenly distributed, improving the stability of the detection signal and the spatial coverage balance.

[0011] As a further improvement of the present invention, the first, second, third, and fourth measuring devices on the surfaces of the upper, middle, and lower infrared light sources are arranged in a circumferentially staggered manner. The distance between the first, second, third, and fourth measuring devices fixed to the middle infrared light source and the two adjacent light-emitting devices with the same serial number of the upper infrared light source is equal. The distance between the first, second, third, and fourth measuring devices fixed to the lower infrared light source and the two adjacent light-emitting devices with the same serial number of the middle infrared light source is also equal. The first, second, third, and fourth measuring devices fixed to the upper, middle, and lower infrared light sources constitute a three-dimensional equilateral triangular optical path structure. The probe module adopts a four-batch synchronous light emission mode, in which all light-emitting devices with the same serial number of the upper, middle, and lower infrared light sources in the same batch are lit synchronously. The four batches complete the full array instantaneous sampling to form an optical snapshot to avoid positional offset errors caused by handheld micro-motion. The light-emitting devices arranged with interlayer circumferential misalignment and equal spacing will form a three-dimensional equilateral triangular optical path structure. Combined with the full array instantaneous snapshot sampling mode of synchronous lighting of four batches of devices with the same serial number, the spatial distribution density and uniformity of the sampling points are improved, which can effectively avoid position offset errors caused by hand-held micro-motion.

[0012] As a further improvement of the present invention, the embedded lower-level computer eliminates the inherent weak fixed reflection interference of the optical path through idle baseline acquisition and real-time difference calculation. The upper-level computer realizes three-dimensional surface reconstruction of the acetabular inner wall, sphericity evaluation, curvature continuity analysis, radial deviation detection, and qualification judgment based on the sampled data. After the upper-level computer makes the judgment, it will output the appropriate prosthesis model. The radial deviation detection calculates the radial deviation of each measuring point by fitting the sphere with the least squares method. The deviation value of the radial deviation detection is mapped to the color level range to generate a radial deviation heat map. The curvature continuity analysis estimates the normal vector of each measuring point through principal component analysis. The normal vector is calculated by fitting the principal curvature k1 and k2 with the local quadratic surface. The Gaussian curvature K is obtained through the principal curvature k1 and k2. The specific formula of K is: K=k1×k2. The curvature value of K is mapped to the color level range to generate a curvature distribution map. When the curvature difference between adjacent measuring points in the curvature distribution map exceeds the threshold, it is marked as a local defect. The lower-level computer eliminates inherent fixed reflection interference in the optical path through idle baseline acquisition and real-time difference calculation to ensure the accuracy of the sampling signal. The upper-level computer can simultaneously realize three-dimensional surface reconstruction of the acetabular inner wall, sphericity evaluation, and dual-dimensional quantitative analysis and visualization of radial deviation and curvature continuity. At the same time, it automatically marks local defects and outputs the appropriate prosthesis model, providing a comprehensive and accurate quantitative verification basis for the intraoperative acetabular inner wall morphology.

[0013] As a further improvement of the present invention, the 120° uniform angle arrangement ensures that the reflection interference generated during synchronous illumination in the same layer is isotropically and uniformly distributed. The upper computer's built-in standard concentric spherical shell reference library and its correspondence with diameter and tolerance allow for a relatively wider tolerance range for large-diameter acetabular joints, while smaller-diameter acetabular joints are subject to stricter tolerance control. The 120° uniform angle arrangement ensures that the reflection interference generated during synchronous illumination in the same layer is isotropically and uniformly distributed. Simultaneously, the upper computer's built-in standard concentric spherical shell reference library and the adoption of a differential tolerance control strategy based on diameter grading enable adaptation to different acetabular sizes, making qualification judgment and prosthesis selection more scientific and reasonable.

[0014] A method for intraoperative infrared detection of the three-dimensional morphology of the acetabular wall, specifically including the following steps:

[0015] S1, Pre-emptive baseline acquisition: When the probe module is not placed in the acetabulum, place it in the matching low-reflection baseline calibration cover, and perform a complete four-batch empty sampling in the order of the first measuring device, the second measuring device, the third measuring device and the fourth measuring device, respectively to obtain and temporarily store the empty baseline of each of the 36 infrared transceiver channels.

[0016] S2, Probe Positioning and Self-Test: After placing the probe module into the polished acetabulum to complete the coarse positioning, the lower computer collects the reflected signal intensity of each channel by lighting the light-emitting device, verifies the signal validity and calculates the relative deviation of the signals of the three 120° working units to determine whether the probe position meets the formal testing requirements.

[0017] S3, Four-batch infrared reflection sampling: After the host computer issues the detection start command, the slave computer triggers four groups of light-emitting devices of different wavelengths to light up synchronously in sequence, and the corresponding ADC channels sample synchronously in parallel. The switching interval is set between batches, and the whole process completes full sampling in milliseconds to achieve an equivalent optical snapshot.

[0018] S4, Filtering and Baseline Calibration: The lower-level computer performs mean filtering on the raw voltage sampling data of each channel, then subtracts the pre-stored no-load baseline data, and calculates the effective optical signal value;

[0019] S5, Channel-by-Channel Differentiation and Upload: The lower-level computer encapsulates the effective optical signal data with the corresponding light source layer number, working unit number, emission sequence number and acquisition timestamp in a structured manner, and uploads it to the upper-level computer through the communication module;

[0020] S6, Point Cloud Surface Reconstruction: After the host computer parses the data packet, it solves the ranging distance of each light-emitting point based on the infrared diffuse reflection ranging principle, calculates the spatial coordinates of all ranging points and forms a three-dimensional point cloud, and then uses the greedy projection triangulation algorithm to construct a triangular mesh surface model.

[0021] S7, Deviation Curvature Analysis: Fit an ideal sphere to the reconstructed surface and generate a radial deviation heatmap. At the same time, solve the principal curvature and Gaussian curvature of each ranging point to generate a curvature distribution map. Based on the curvature continuity threshold, determine and mark local defect areas.

[0022] S8, Tolerance compliance judgment: The host computer calls the standard concentric spherical shell reference library and the correspondence between diameter and tolerance. By comparing the extreme value of the radial deviation of the measuring point with the upper and lower limits of the corresponding model's tolerance, it determines whether the acetabular inner wall morphology is qualified.

[0023] S9, Results Output and Selection: Outputs the acetabular inner wall morphology qualification conclusion, radial deviation heat map, curvature distribution map, global radial deviation statistical results, and provides the best fit acetabular prosthesis model recommendation.

[0024] As a further improvement of the present invention, in step S1, coarse positioning is performed with the annular limiting mark on the outer wall of the probe module being flush with the edge of the acetabular orifice as a depth reference. The light-emitting device is illuminated in a low-power mode. The presence of a channel with signal saturation or below the noise threshold is determined by the intensity of the reflected signal. If a channel is found to be present, the probe position is indicated for repositioning. When all channel signals are within the effective range, the reflected signal intensity distribution of three sets of 120° working units is recorded. The reflected signal intensity distribution is used to calculate the relative deviation, which is set as Δ. The formula for calculating Δ is as follows:

[0025] Δ=[max(S1,S2,S3)-min(S1,S2,S3)] / max(S1,S2,S3)×100%;

[0026] Wherein, S1, S2, and S3 are the reflected signal intensity values ​​collected by the three working units, respectively. max(S1,S2,S3) is the maximum value among the three signal intensities, and min(S1,S2,S3) is the minimum value among the three signal intensities. When Δ≤30%, the probe position is considered acceptable, and formal testing begins; when Δ>30%, a prompt indicating excessive signal deviation and requesting probe re-insertion is issued. Using the annular limit mark on the probe's outer wall as a depth reference, rapid coarse positioning is achieved. Combined with low-power light emission signal validity verification and quantitative judgment of the relative deviation of the signals from the three 120° working units, insertion states with excessive positional deviations can be quickly screened out before formal testing, ensuring the reliability of subsequent test data.

[0027] As a further improvement of the present invention, in steps S2-S3, the lower-level machine enters a four-batch synchronous light emission process. In the light emission process, the timing controller generates four sets of synchronous trigger pulses in the order of the first measuring device, the second measuring device, the third measuring device, and the fourth measuring device. The rising edge of each set of pulses simultaneously drives all light-emitting devices with the same sequence number in the upper-layer infrared light source, the middle-layer infrared light source, and the lower-layer infrared light source to light up instantaneously. The light emission window width of the light emission process is set to... All relevant ADC channels within the light-emitting window are sampled synchronously in parallel, and the sampling frequency of the parallel sampling is set to... Each of the ADC channels acquires Original voltage data The The number of sampling points per channel per batch, the For the i-th original voltage sample value, the light source in this batch is immediately turned off after the sampling is completed. The total sampling time for the four-batch synchronous emission process is... The The specific formula is:

[0028] ;

[0029] Among them, the The interval between batch switching, the The timescale is much smaller than that of handheld micro-motion, thus achieving an equivalent optical snapshot. After sampling, the lower-level computer collects data for each channel. Original voltage data The mean-filtered voltage value is set as follows: The The calculation formula is as follows:

[0030] ;

[0031] Then, the baseline data stored in the idle state is retrieved. The effective optical signal value is obtained. The system employs a timing-controlled mechanism that simultaneously illuminates four batches of identically numbered light-emitting devices and uses a parallel sampling mechanism with an ADC. This allows for full-array sampling within a timescale smaller than that of a handheld micro-motion device, achieving an equivalent optical snapshot to eliminate positional offset errors. Combined with mean filtering and idle baseline difference calculation, it can acquire high signal-to-noise ratio effective optical signal data while ensuring extremely high detection efficiency.

[0032] As a further improvement of the present invention, in steps S5-S7, the host computer performs three-dimensional point cloud construction and surface reconstruction. Specifically, the three-dimensional point cloud construction and surface reconstruction involves setting the spatial position of the i-th light-emitting device as... The The direction vector of the beam's central axis is The The effective optical signal intensity measured by the corresponding receiving device is Based on the principle of infrared diffuse reflection ranging Wherein, K is the receiving system constant, P0 is the emission power, and η(λ) is the receiving efficiency of the corresponding band. For distance, by the stated The distance can be solved by inverse formula. Based on the known position of the light-emitting device and direction vector The equivalent ranging point coordinates corresponding to the light-emitting device are obtained, and the equivalent ranging point coordinates are set as follows: The The formula is as follows: ;

[0033] N light-emitting devices across the entire region independently perform the above calculations to obtain N ranging points, forming a three-dimensional point cloud set P={Q1,Q2,…,Q...} N A greedy projection triangulation algorithm based on Delaunay triangulation is used to construct a triangular mesh surface model. The reconstructed triangular mesh surface S is fitted to an ideal sphere using the least squares method. The coordinates of the center point of the ideal sphere are O(x0, y0, z0), and the radius of the ideal sphere is R. The radial deviation of the ranging point is calculated, and the radial deviation is set as follows: The The formula is as follows:

[0034] ;

[0035] Among them, the , and Given the spatial coordinates of the i-th ranging point in the 3D point cloud, the radial deviation value is mapped to a color gradation interval to generate a radial deviation heatmap. A local quadratic surface model is established for each ranging point. The principal curvatures k1 and k2 are solved using the eigenvalues ​​of the Weingarten mapping matrix. The curvature value of k is mapped to a color gradation interval to generate a curvature distribution map. When adjacent ranging points exist... When it is determined that the curvature discontinuity marker in the region has a local defect, wherein the The Gaussian curvature value at my i-th ranging point, the stated The Gaussian curvature value of the preceding ranging point adjacent to the i-th ranging point, the Let be the average curvature at the i-th ranging point, the The average curvature value of the preceding ranging point adjacent to the i-th ranging point, the The Gaussian curvature continuity threshold, the The average curvature continuity threshold is used; the relationship between diameter and tolerance is determined by the following condition: if the maximum absolute value of radial deviation at all measuring points does not exceed the upper tolerance limit corresponding to the k-th model, and the minimum absolute value of radial deviation at all measuring points is not lower than the lower tolerance limit corresponding to that model, then the acetabular inner wall morphology is deemed acceptable; the specific formula for this determination is as follows:

[0036] ;

[0037] Wherein, k is the model number of the standard acetabular prosthesis, and the The upper limit of the tolerance corresponding to the k-th type of acetabular prosthesis, the This represents the lower tolerance limit for the k-th type of acetabular prosthesis. A three-dimensional point cloud is constructed using infrared diffuse reflection ranging, and a triangular mesh surface is reconstructed. Combined with radial deviation quantification analysis and curvature continuity detection, this method can not only visualize global shape deviations and accurately mark local defects, but also objectively determine conformity based on the tolerance standards of the corresponding prosthesis model, achieving comprehensive quantitative verification of the acetabular inner wall morphology.

[0038] The advantages of this invention are:

[0039] 1. A snapshot-style sampling scheme employing four batches of simultaneous illumination is used. Through the simultaneous lighting of all identically numbered light-emitting devices across three layers within the same batch and rapid switching between batches, full-array sampling can be completed in milliseconds. This effectively avoids positional shifts and detection artifacts caused by micro-movements during intraoperative hand operation, thus ensuring the consistency of the sampling position. Compared to existing point-by-point scanning and layer-by-layer sequential illumination optical detection schemes, this approach retains the advantages of multi-layer, multi-source, high-density sampling while compressing the total sampling time to less than the time required for micro-movements of the human hand. Stable sampling can be achieved without additional fixed supports or vision modules, simplifying the intraoperative procedure and controlling the standard deviation of repeated measurements.

[0040] 2. A three-layer differentiated infrared band optical path layout, with each layer consisting of three 120° equally divided working units and circumferentially staggered light-emitting devices between layers, achieves physical isolation between layers through band differences combined with narrowband filtering. The 120° circumferential distribution ensures isotropic and uniform distribution of stray light reflected from the same layer, suppressing direct crosstalk between layers and interference from stray light reflected from the same layer, thus improving the purity of the sampled signal. This three-dimensional equilateral triangular optical path structure, without increasing the total number of light-emitting devices, forms a multi-view spatial ranging point distribution, improving the spatial coverage density of the 3D point cloud and the geometric accuracy of surface reconstruction.

[0041] 3. By calculating the difference between the pre-stored empty baseline and the real-time value, combined with a signal processing mechanism of mean filtering within a single window, the inherent weak fixed reflection interference of the optical path can be eliminated and random noise suppressed, improving the signal-to-noise ratio of the effective optical signal and ensuring the accuracy of ranging calculation. Simultaneously, the calibration step is moved forward to the pre-stored baseline recall, eliminating the need for additional calibration procedures during the procedure and allowing direct initiation of detection. Furthermore, the mean filtering is completed within a single emission window, without occupying additional sampling time, achieving deep suppression of fixed interference.

[0042] 4. A two-dimensional quality evaluation system combining radial deviation heatmap and curvature continuity analysis was constructed. The overall sphericity was evaluated by calculating the global radial deviation through least squares spherical fitting. At the same time, local defects were identified by determining the continuity threshold of Gaussian curvature and average curvature. The system can simultaneously complete the evaluation of the overall shape tolerance of the acetabular inner wall and the location of local defects.

[0043] 5. Using a standard concentric spherical shell reference library, a differentiated tolerance matching rule is adopted, which relaxes the tolerance range for large-diameter acetabulums and tightens the tolerance control for small-diameter acetabulums. Based on the reconstruction results, the corresponding prosthesis model is matched and its passability is determined, thus adapting to the testing needs of different acetabular sizes. This also prevents the problem of insufficient prosthesis fit and poor stability caused by excessively loose tolerances in small-diameter acetabulums, while avoiding unnecessary repeated grinding caused by excessively tight tolerances in large-diameter acetabulums. Attached Figure Description

[0044] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0045] Figure 1 This is a flowchart of the steps of the present invention.

[0046] Figure 2 This is a three-dimensional structural diagram of the detector light source part of the present invention.

[0047] Figure 3 This is a schematic diagram of the geometric relationship between the two levels of triangles in this invention.

[0048] In the diagram: 100, upper infrared light source; 200, middle infrared light source; 300, lower infrared light source; 400, first measuring device; 500, second measuring device; 600, third measuring device; 700, fourth measuring device. Detailed Implementation

[0049] 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.

[0050] Example 1, taking a standard acetabular model measurement as an example, describes an infrared verification device and detection method for the three-dimensional morphology of the acetabular wall during surgery. This example uses a standard acetabular model with a diameter of 46mm as the detection object to verify the measurement accuracy and repeatability of the infrared verification device for the three-dimensional morphology of the acetabular wall during surgery. The verification device includes a probe module, an embedded lower computer, a communication module, and an upper computer. The probe module includes an upper infrared light source 100, a middle infrared light source 200, and a lower infrared light source 300. The middle infrared light source 200 is set at the bottom of the upper infrared light source 100, and the lower infrared light source 300 is set at the bottom of the middle infrared light source 200. The upper infrared light source 100, the middle infrared light source 200, and the lower infrared light source 300 are equally divided into three parts, each part being a working unit. The surface of each working unit is sequentially fixedly connected to a first measuring device 400, a second measuring device 500, a third measuring device 600, and a fourth measuring device 700.

[0051] The upper infrared light source 100 is equipped with four measuring devices: the first measuring device 400, the second measuring device 500, the third measuring device 600, and the fourth measuring device 700, all operating in the 810nm infrared band. The middle infrared light source 200 corresponds to a light-emitting device operating in the 940nm infrared band, and the lower infrared light source 300 corresponds to a light-emitting device operating in the 850nm infrared band. The three light sources are physically isolated through band differences and narrow-band filtering structures, preventing interference between them. The three working units of each layer are arranged at equal angles of 120° around the circumference, and the reflection interference generated when emitting light synchronously in the same layer is isotropically and uniformly distributed. The light-emitting devices on the surfaces of the three light sources are arranged circumferentially staggered. The distance between each light-emitting device of the middle infrared light source 200 and the two adjacent light-emitting devices of the same number in the upper infrared light source 100 is equal, and the distance between each light-emitting device of the lower infrared light source 300 and the two adjacent light-emitting devices of the middle infrared light source 200 is equal, forming a three-dimensional equilateral triangular optical path structure.

[0052] The specific testing steps are as follows:

[0053] S1, Pre-emptive baseline acquisition: When the probe module is not placed in the acetabulum, place it in the matching low-reflection baseline calibration cover, and perform a complete four-batch empty sampling in the order of the first measuring device 400, the second measuring device 500, the third measuring device 600 and the fourth measuring device 700, respectively to obtain and temporarily store the empty baseline of each of the 36 infrared transceiver channels.

[0054] Table 1. Timing diagram of baseline acquisition before use and formal testing

[0055] Before using the no-load baseline Nine 400 simultaneous send and receive terminals Nine 500 simultaneous send and receive signals Nine 600 simultaneous send and receive signals Nine 700 simultaneous send and receive terminals Formal reflection detection Nine 400 simultaneous send and receive terminals Nine 500 simultaneous send and receive signals Nine 600 simultaneous send and receive signals Nine 700 simultaneous send and receive terminals

[0056] S2, Probe Positioning and Self-Check: Place the probe module into the acetabular fossa of the standard acetabular model, using the annular limit mark on the outer wall of the probe and the edge of the model opening as the depth reference to complete coarse positioning. The lower-level computer controls all light-emitting devices to light up in low-power mode, collects the reflected signal intensity of each channel, verifies the signal validity, and after confirming that there are no channels with signal saturation or below the noise threshold, records the reflected signal intensity S1, S2, and S3 of three sets of 120° working units, and calculates the signal relative deviation Δ. The calculation formula is: Δ=[max(S1,S2,S3)-min(S1,S2,S3)] / max(S1,S2,S3)×100%. In this embodiment, Δ=8%, which meets the judgment condition of Δ≤30%. The lower-level computer's green light indicates that the position is qualified, and the formal testing process begins.

[0057] S3, Four-Batch Infrared Reflection Sampling: After the host computer issues the detection start command, the timing controller of the slave computer generates four sets of synchronous trigger pulses in the order of the first measuring device 400, the second measuring device 500, the third measuring device 600, and the fourth measuring device 700. A four-batch synchronous light emission mode is adopted, where all light-emitting devices with the same sequence number in the upper infrared light source 100, the middle infrared light source 200, and the lower infrared light source 300 within the same batch are simultaneously lit. (Set the light emission window width.) =1ms, inter-batch switching interval =0.5ms, total sampling time =5.5ms, which is much shorter than the time scale of handheld micro-motion, achieving an equivalent optical snapshot and avoiding positional offset errors caused by handheld micro-motion. All relevant ADC channels within the emission window are sampled synchronously and in parallel, with a sampling frequency of... =10kHz, number of sampling points per channel per batch =10 raw voltage data The corresponding light source should be turned off immediately after each batch of sampling is completed.

[0058] S4, Filtering and Baseline Calibration: After sampling, the lower-level computer performs mean filtering on the 10 raw voltage data V_raw(i) collected from each channel to obtain the filtered voltage values: Then, the pre-stored idle state baseline data is retrieved. By eliminating the inherent weak fixed reflection interference of the optical path through idle baseline acquisition and real-time difference calculation, the effective optical signal value is calculated. .

[0059] S5, Channel-by-Channel Differentiation and Upload: The lower-level computer encapsulates all valid optical signal data from all channels with the corresponding light source layer number, working unit number, emission sequence number, and acquisition timestamp in a structured manner, and uploads it to the upper-level computer through the communication module.

[0060] S6, Point Cloud Surface Reconstruction: After the host computer parses the data packet, it is based on the principle of infrared diffuse reflection ranging. (Where K is the receiving system constant, P0 is the transmitted power, and η(λ) is the receiving efficiency of the corresponding band.) (For the distance measurement) Inverse solution, the distance d_i of each light-emitting point is solved; let the spatial position of the i-th light-emitting device be... If the direction vector of the beam's central axis is n_i, then the corresponding equivalent ranging point coordinates are... After independent calculation of all light-emitting devices in the entire region, a three-dimensional point cloud set P={Q1,Q2,…, A greedy projection triangulation algorithm based on Delaunay triangulation is used to construct a triangular mesh surface model. .

[0061] S7, Deviation Curvature Analysis: The reconstructed triangular mesh surface is fitted to an ideal sphere using the least squares method to obtain the coordinates of the center of the ideal sphere O(x0, y0, z0) and the radius R; the radial deviation of each ranging point is calculated: ,in , and The spatial coordinates of the i-th ranging point are given. The deviation value is mapped to a color gradation interval to generate a radial deviation heatmap. Simultaneously, a local quadratic surface model is established for each ranging point. The normal vector of each ranging point is estimated through principal component analysis. The principal curvatures k1 and k2 are solved using the eigenvalues ​​of the Weingarten mapping matrix. The Gaussian curvature K = k1 × k2 is calculated, and the curvature values ​​are mapped to a color gradation interval to generate a curvature distribution map. In this embodiment, the curvature difference between adjacent ranging points is lower than a preset threshold. and No local defect markers.

[0062] S8, Tolerance Acceptance Judgment: The host computer calls the built-in standard concentric spherical shell reference library and the correspondence between diameter and tolerance to match the corresponding tolerance range for a 46mm diameter acetabulum. Judgment criteria are as follows: ,in This represents the upper limit of the tolerance for the corresponding model. This represents the lower limit of the tolerance for the corresponding model. The radial deviation at each measuring point in this embodiment... All within ±0.2mm, the deviation between the fitted ball center and the standard ball center of the model is less than 0.1mm, meeting the tolerance requirements of the 46mm model, and the acetabular inner wall morphology is deemed qualified.

[0063] S9, Results Output and Selection: The host computer outputs the conclusion that the acetabular inner wall morphology is qualified, the statistical results of the radial deviation in the whole domain, the radial deviation heat map and the curvature distribution map, and gives the best fit acetabular prosthesis model as 46mm.

[0064] The same standard model was measured 10 times following the above procedure. The standard deviation of the measurement results was less than 0.05 mm, indicating that the device has good repeatability.

[0065] Example 2, taking the simulated intraoperative acetabular morphology inspection as an example, describes an infrared verification device and detection method for the three-dimensional morphology of the intraoperative acetabular inner wall. In this example, a simulated defective acetabular model prepared by 3D printing is used as the detection object. The model has a local depression with a depth of 0.8 mm in the anterior upper quadrant of the acetabular inner wall to simulate intraoperative acetabular grinding defects and verify the device's ability to identify local defects. The probe module of the calibration device includes an upper infrared light source 100, a middle infrared light source 200, and a lower infrared light source 300. Each layer of light source is divided into three working units arranged at 120° intervals. Each working unit is equipped with a first measuring device 400, a second measuring device 500, a third measuring device 600, and a fourth measuring device 700. The upper infrared light source 100 is in the 810nm band, the middle infrared light source 200 is in the 940nm band, and the lower infrared light source 300 is in the 850nm band. The three layers of light sources are physically isolated through a narrow-band filter structure to prevent interference. The light-emitting devices of each layer are arranged in a circumferentially staggered manner, forming a three-dimensional equilateral triangular optical path structure. A four-batch synchronous light emission mode is used to achieve optical snapshot sampling.

[0066] The specific testing steps are as follows:

[0067] S1, Pre-emptive baseline acquisition: When the probe module is not placed in the acetabulum, place it in the matching low-reflection baseline calibration cover, and perform a complete four-batch empty sampling in the order of the first measuring device 400, the second measuring device 500, the third measuring device 600 and the fourth measuring device 700, respectively to obtain and temporarily store the empty baseline of each of the 36 infrared transceiver channels.

[0068] S2, Probe Positioning and Self-Test: Place the probe module into the acetabular fossa of the defective acetabular model, aligning the annular limiting mark on the outer wall of the probe with the edge of the model opening to complete coarse positioning. The lower-level computer illuminates each light-emitting device in low-power mode, collecting the reflected signal intensity of three sets of 120° working units. After verification, all channel signals are within the effective range, with no saturation or below the noise threshold. The relative signal deviation Δ is calculated to be 12%, meeting the criterion of Δ≤30%, thus passing the self-test and proceeding to formal sampling.

[0069] S3, Four-Batch Infrared Reflection Sampling: After receiving the start command from the host computer, the timing controller sequentially triggers the synchronous emission of four batches of measuring devices: the first measuring device 400, the second measuring device 500, the third measuring device 600, and the fourth measuring device 700. Within each batch, the corresponding numbered light-emitting devices of the upper-layer infrared light source 100, the middle-layer infrared light source 200, and the lower-layer infrared light source 300 are instantaneously and synchronously illuminated. (Set the emission window width) =1ms, sampling frequency =10kHz, single channel, single batch sampling of 10 raw data points, batch switching interval =0.5ms, total sampling time =5.5ms, completing instantaneous sampling of the entire array in milliseconds, equivalent to an optical snapshot, eliminating position offset errors caused by micro-motion during operation.

[0070] S4, Filtering and Baseline Calibration: The lower-level computer performs mean filtering on the raw sampled data of each channel to obtain... Then deduct the pre-stored idle baseline data. By eliminating fixed reflection interference in the optical path through interpolation, the effective optical signal value is obtained. .

[0071] S5, Channel-by-Channel Differential and Upload: The lower-level computer encapsulates the effective optical signal along with the corresponding light source layer number, working unit number, emission sequence number, and timestamp in a structured manner, and then transmits it to the upper-level computer via the communication module.

[0072] S6, Point Cloud Surface Reconstruction: The host computer uses the infrared diffuse reflection ranging principle to inversely solve the ranging distance corresponding to each light-emitting device. Combined with the spatial position of the light-emitting device With direction vector The coordinates of all distance measurement points were calculated. A three-dimensional point cloud set is formed; a greedy projection triangulation algorithm is used to construct a triangular mesh surface model of the acetabular inner wall.

[0073] S7, Deviation Curvature Analysis: The host computer uses the least squares method to fit an ideal sphere to the reconstructed surface and calculates the radial deviation at each ranging point. A radial deviation heatmap was generated, showing a distinct high-deviation red area in the upper front quadrant, indicating the maximum radial deviation. =0.82mm. Simultaneously, the principal curvature and Gaussian curvature of each ranging point were calculated. The principal curvatures k1 and k2 were obtained through local quadratic surface fitting, and the Gaussian curvature K = k1 × k2 was calculated, generating a curvature distribution map. Detection revealed that adjacent ranging points in the upper front quadrant concave region satisfy... If the curvature continuity exceeds the threshold, the system automatically marks the area as a local depression defect.

[0074] S8, Tolerance Acceptance Judgment: The host computer calls the standard concentric spherical shell reference library to match the upper tolerance limit corresponding to a 46mm diameter acetabulum. =0.5mm, lower tolerance limit =-0.5mm. Upon comparison, the maximum radial deviation of this model, 0.82mm, exceeds the upper tolerance limit and does not meet the requirements. Based on the criteria for determination, the morphology of the acetabular inner wall is deemed unqualified.

[0075] S9, Results Output and Selection: The host computer outputs a non-compliance conclusion, and simultaneously displays the radial deviation heat map, curvature distribution map and defect mark location, indicating that the upper quadrant area needs to be re-polished, and the prosthesis model is not recommended at this time.

[0076] Example 3, taking the adaptability verification of acetabula with different diameters as an example, describes an infrared verification device and detection method for the three-dimensional morphology of the acetabular inner wall during surgery. In this example, four standard acetabular models with diameters of 42mm, 48mm, 52mm, and 56mm were selected as the detection objects to verify the device's adaptability and tolerance matching capability for acetabula with different diameters. The probe module of the verification device adopts a three-layer infrared light source structure. The upper infrared light source 100, the middle infrared light source 200, and the lower infrared light source 300 correspond to the 810nm, 940nm, and 850nm wavelength bands, respectively. Each layer is divided into three working units with equal 120° included angles. Each working unit is equipped with a first measuring device 400, a second measuring device 500, a third measuring device 600, and a fourth measuring device 700. The circumferentially staggered light-emitting devices of each layer form a three-dimensional equilateral triangular light path, and snapshot sampling is achieved through four batches of synchronous light emission. The host computer has a built-in standard concentric spherical shell reference library, which follows the matching rule of relatively relaxed tolerance range for large-diameter acetabula and stricter tolerance control for small-diameter acetabula.

[0077] The following testing process will be performed sequentially for each model specification:

[0078] S1, Pre-emptive baseline acquisition: When the probe module is not placed in the acetabulum, place it in the matching low-reflection baseline calibration cover, and perform a complete four-batch empty sampling in the order of the first measuring device 400, the second measuring device 500, the third measuring device 600 and the fourth measuring device 700, respectively to obtain and temporarily store the empty baseline of each of the 36 infrared transceiver channels.

[0079] S2, Probe Positioning and Self-Test: Place the probe module into the acetabular model of the corresponding diameter, and complete the coarse positioning by aligning the annular limit mark with the edge of the opening. The lower-level machine illuminates the light-emitting device at low power to complete the signal verification. Testing showed that the relative deviations Δ of the three working unit signals for the four models (42mm, 48mm, 52mm, and 56mm) were 6%, 10%, 15%, and 9%, respectively, all meeting the acceptable threshold of Δ≤30%, and all self-tests passed.

[0080] S3, Four-batch infrared reflection sampling: The lower-level machine performs sampling in a four-batch synchronous emission mode, with an emission window T_w=1ms and a sampling frequency of... =10kHz, number of sampling points per channel per batch =10, batch interval =0.5ms, total sampling time =5.5ms, completing full sampling in milliseconds, achieving an equivalent optical snapshot.

[0081] S4, Filtering and Baseline Calibration: The lower-level computer performs mean filtering on the raw sampled data, removes the idle baseline data, eliminates fixed reflection interference in the optical path, and obtains the effective optical signal value of each channel.

[0082] S5, Channel-by-Channel Differential and Upload: The lower-level computer encapsulates the valid signal and corresponding parameters in a structured manner and uploads them to the upper-level computer.

[0083] S6, Point Cloud Surface Reconstruction: The host computer uses the principle of infrared diffuse reflection ranging to solve the spatial coordinates of each ranging point, constructs a three-dimensional point cloud, and then uses a greedy projection triangulation algorithm to generate the triangular mesh surface of the acetabular inner wall of each model.

[0084] S7, Curvature Analysis: For each model's reconstructed surface, the least squares method was used to fit an ideal sphere. The calculated fitted sphere diameters for the 42mm, 48mm, 52mm, and 56mm models were 42.1mm, 47.9mm, 52.2mm, and 55.8mm, respectively, with deviations from the standard diameter all less than 0.3mm. Radial deviation heatmaps for each model were generated, and the measured maximum radial deviations were 0.18mm, 0.22mm, 0.25mm, and 0.30mm, respectively. Curvature analysis was performed simultaneously. The curvature difference between adjacent measurement points across the entire domain for all four models was below the continuity threshold, and no local defect markers were found.

[0085] S8, Tolerance Acceptance Judgment: The host computer retrieves the standard concentric spherical shell reference library and matches differentiated tolerance ranges for different diameter models according to the correspondence between diameter and tolerance: the 42mm small diameter model adopts stricter tolerance control, while the 56mm large diameter model has a relatively relaxed tolerance range. After comparison, the extreme values ​​of radial deviation for all four models fall within the corresponding model's upper and lower tolerance limits, thus meeting the requirements. All of the criteria were used to determine that the morphology was qualified.

[0086] S9, Results Output and Selection: The host computer outputs qualified inspection reports, radial deviation statistics and curvature analysis diagrams for four diameter models respectively, and recommends the corresponding suitable prosthesis models as 42mm, 48mm, 52mm and 56mm.

[0087] Experimental results show that this device can be adapted to acetabular testing scenarios with different diameters, and has good testing accuracy and adaptability for acetabular models in the range of 42mm to 56mm.

[0088] Finally, it should be noted that the above are merely preferred embodiments of the present invention and are not intended to limit the present invention. Although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art can still modify the technical solutions described in the foregoing embodiments or make equivalent substitutions for some of the technical features. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of the present invention should be included within the protection scope of the present invention.

Claims

1. An infrared verification device for the three-dimensional morphology of the acetabular wall during surgery, comprising a probe module, an embedded lower-level computer, a communication module, and an upper-level computer, characterized in that, The probe module also includes an upper infrared light source (100), a middle infrared light source (200) is provided at the bottom of the upper infrared light source (100), and a lower infrared light source (300) is provided at the bottom of the middle infrared light source (200). The upper infrared light source (100), the middle infrared light source (200) and the lower infrared light source (300) are all divided into three equal parts. Each of the upper infrared light source (100), the middle infrared light source (200) and the lower infrared light source (300) is set as a working unit. The surface of each working unit is sequentially fixedly connected to a first measuring device (400), a second measuring device (500), a third measuring device (600) and a fourth measuring device (700).

2. The intraoperative acetabular wall three-dimensional morphology infrared verification device as described in claim 1, characterized in that: The upper infrared light source (100) is fixedly connected to a first measuring device (400), a second measuring device (500), a third measuring device (600), and a fourth measuring device (700), all of which are in the 810nm infrared band. The middle infrared light source (200) is fixedly connected to a first measuring device (400), a second measuring device (500), a third measuring device (600), and a fourth measuring device (700), all of which are in the 940nm infrared band. The lower infrared light source (300) is fixedly connected to a first measuring device (400), a second measuring device (500), a third measuring device (600), a fourth measuring device (700), and a fifth measuring device (700), all of which are in the 940nm infrared band. The measuring device (600) and the fourth measuring device (700) are both 850nm infrared band. The upper infrared light source (100), the middle infrared light source (200) and the lower infrared light source (300) are physically isolated by band difference and narrow band filter structure. The upper infrared light source (100), the middle infrared light source (200) and the lower infrared light source (300) do not interfere with each other. Each working unit of the upper infrared light source (100), the middle infrared light source (200) and the lower infrared light source (300) is arranged at an equal angle of 120° along the circumference.

3. The intraoperative acetabular wall three-dimensional morphology infrared verification device as described in claim 1, characterized in that: The first measuring device (400), second measuring device (500), third measuring device (600), and fourth measuring device (700) on the surfaces of the upper infrared light source (100), middle infrared light source (200), and lower infrared light source (300) are arranged circumferentially staggered. The distance between the first measuring device (400), second measuring device (500), third measuring device (600), and fourth measuring device (700) fixed on the middle infrared light source (200) and the two adjacent light-emitting devices with the same serial number on the upper infrared light source (100) is equal. The distance between the first measuring device (400), second measuring device (500), third measuring device (600), and fourth measuring device (700) fixed on the lower infrared light source (300) is equal. The spacing between two light-emitting devices with the same serial number adjacent to the middle infrared light source (200) is equal. The first measuring device (400), the second measuring device (500), the third measuring device (600) and the fourth measuring device (700) fixed by the upper infrared light source (100), the middle infrared light source (200) and the lower infrared light source (300) form a three-dimensional equilateral triangular optical path structure. The probe module adopts a four-batch synchronous light emission mode. All light-emitting devices with the same serial number of the upper infrared light source (100), the middle infrared light source (200) and the lower infrared light source (300) in the same batch are lit synchronously. The four batches complete the full array instantaneous sampling to form an optical snapshot to avoid position offset errors caused by hand micro-motion.

4. The intraoperative acetabular wall three-dimensional morphology infrared verification device as described in claim 1, characterized in that: The embedded lower-level computer eliminates inherent weak fixed reflection interference in the optical path through idle baseline acquisition and real-time difference calculation. The upper-level computer realizes three-dimensional surface reconstruction of the acetabular inner wall, sphericity evaluation, curvature continuity analysis, radial deviation detection, and qualification determination based on the sampled data. After the upper-level computer makes the determination, it will output the appropriate prosthesis model. The radial deviation detection calculates the radial deviation of each measuring point by fitting a sphere using the least squares method. The deviation value of the radial deviation detection is mapped to a color gradation range to generate a radial deviation heatmap. The curvature continuity analysis estimates the normal vector of each measuring point through principal component analysis. The normal vector is calculated by fitting a local quadratic surface to obtain the principal curvatures k1 and k2. The Gaussian curvature K is obtained through the principal curvatures k1 and k2. The specific formula of K is: K = k1 × k2. The curvature value of K is mapped to a color gradation range to generate a curvature distribution map. When the curvature difference between adjacent measuring points in the curvature distribution map exceeds a threshold, it is marked as a local defect.

5. The intraoperative acetabular wall three-dimensional morphology infrared verification device as described in claim 2, characterized in that: The 120° uniform angle arrangement ensures that the reflection interference generated during synchronous light emission in the same layer is isotropically and uniformly distributed. The host computer has a built-in standard concentric spherical shell reference library with a correspondence between diameter and tolerance. The tolerance range of large-diameter acetabulum is relatively relaxed, while small-diameter acetabulum adopts stricter tolerance control.

6. A detection method using the verification device as described in any one of claims 1 to 5, characterized in that, Specifically, the steps include the following: S1, using the pre-emptive baseline acquisition: when the probe module is not placed in the acetabulum, place it in the matching low-reflection baseline calibration cover, and perform a complete four-batch empty sampling in the order of the first measuring device (400), the second measuring device (500), the third measuring device (600) and the fourth measuring device (700), respectively to obtain and temporarily store the current empty baseline of each of the 36 infrared transceiver channels; S2, Probe Positioning and Self-Test: After placing the probe module into the polished acetabulum to complete the coarse positioning, the lower computer collects the reflected signal intensity of each channel by lighting the light-emitting device, verifies the signal validity and calculates the relative deviation of the signals of the three 120° working units to determine whether the probe position meets the formal testing requirements. S3, Four-batch infrared reflection sampling: After the host computer issues the detection start command, the slave computer triggers four groups of light-emitting devices of different wavelengths to light up synchronously in sequence, and the corresponding ADC channels sample synchronously in parallel. The switching interval is set between batches, and the whole process completes full sampling in milliseconds to achieve an equivalent optical snapshot. S4, Filtering and Baseline Calibration: The lower-level computer performs mean filtering on the raw voltage sampling data of each channel, then subtracts the pre-stored no-load baseline data, and calculates the effective optical signal value; S5, Channel-by-Channel Differentiation and Upload: The lower-level computer encapsulates the effective optical signal data with the corresponding light source layer number, working unit number, emission sequence number and acquisition timestamp in a structured manner, and uploads it to the upper-level computer through the communication module; S6, Point Cloud Surface Reconstruction: After the host computer parses the data packet, it solves the ranging distance of each light-emitting point based on the infrared diffuse reflection ranging principle, calculates the spatial coordinates of all ranging points and forms a three-dimensional point cloud, and then uses the greedy projection triangulation algorithm to construct a triangular mesh surface model. S7, Deviation Curvature Analysis: Fit an ideal sphere to the reconstructed surface and generate a radial deviation heatmap. At the same time, solve the principal curvature and Gaussian curvature of each ranging point to generate a curvature distribution map. Based on the curvature continuity threshold, determine and mark local defect areas. S8, Tolerance compliance judgment: The host computer calls the standard concentric spherical shell reference library and the correspondence between diameter and tolerance. By comparing the extreme value of the radial deviation of the measuring point with the upper and lower limits of the corresponding model's tolerance, it determines whether the acetabular inner wall morphology is qualified. S9, Results Output and Selection: Outputs the acetabular inner wall morphology qualification conclusion, radial deviation heat map, curvature distribution map, global radial deviation statistical results, and provides the best fit acetabular prosthesis model recommendation.

7. The method for intraoperative infrared detection of three-dimensional morphology of the acetabular wall as described in claim 6, characterized in that: In step S1, coarse positioning is performed with the annular limiting mark on the outer wall of the probe module aligned with the edge of the acetabular orifice as a depth reference. The light-emitting device is illuminated in low-power mode. The intensity of the reflected signal is used to determine whether there is a channel with signal saturation or below the noise threshold. If a channel is found to be present, the probe position is indicated for repositioning. When all channel signals are within the effective range, the reflected signal intensity distribution of three sets of 120° working units is recorded. The reflected signal intensity distribution is used to calculate the relative deviation, which is set as Δ. The formula for calculating Δ is as follows: Δ=[max(S1,S2,S3-min(S1,S2,S3] / max(S1,S2,S3)×100%; Wherein, S1, S2, and S3 are the reflected signal intensity values ​​collected by the three working units, max(S1,S2,S3) is the maximum value among the three signal intensities S1, S2, and S3, and min(S1,S2,S3) is the minimum value among the three signal intensities S1, S2, and S3. When Δ≤30%, the probe position is considered acceptable and formal testing begins; when Δ>30%, a prompt is issued that the signal deviation is too large and the probe should be repositioned.

8. The method for intraoperative infrared detection of three-dimensional morphology of the acetabular wall as described in claim 6, characterized in that: In steps S2-S3, the lower-level machine enters a four-batch synchronous light emission process. In this process, the timing controller generates four sets of synchronous trigger pulses in the order of the first measuring device (400), the second measuring device (500), the third measuring device (600), and the fourth measuring device (700). The rising edge of each set of pulses simultaneously drives all light-emitting devices with the same sequence number in the upper-layer infrared light source (100), the middle-layer infrared light source (200), and the lower-layer infrared light source (300) to illuminate instantaneously. The light emission window width of this process is set to... All relevant ADC channels within the light-emitting window are sampled synchronously in parallel, and the sampling frequency of the parallel sampling is set to... Each of the ADC channels acquires Original voltage data The The number of sampling points per channel per batch, the For the i-th original voltage sample value, the light source in this batch is immediately turned off after the sampling is completed. The total sampling time for the four-batch synchronous emission process is... The The specific formula is: ； Among them, the The interval between batch switching, the The timescale is much smaller than that of handheld micro-motion, thus achieving an equivalent optical snapshot. After sampling, the lower-level computer collects data for each channel. Original voltage data The mean-filtered voltage value is set as follows: The The calculation formula is as follows: ； Then, the baseline data stored in the idle state is retrieved. The effective optical signal value is obtained. .

9. The method for intraoperative infrared detection of three-dimensional morphology of the acetabular wall as described in claim 6, characterized in that: In steps S5-S7, the host computer performs 3D point cloud construction and surface reconstruction. Specifically, the 3D point cloud construction and surface reconstruction involves setting the spatial position of the i-th light-emitting device as... The The direction vector of the beam's central axis is The The effective optical signal intensity measured by the corresponding receiving device is Based on the principle of infrared diffuse reflection ranging Wherein, K is the receiving system constant, P0 is the emission power, and η(λ) is the receiving efficiency of the corresponding band. For distance, by the stated The distance can be solved by inverse formula. Based on the known position of the light-emitting device and direction vector The equivalent ranging point coordinates corresponding to the light-emitting device are obtained, and the equivalent ranging point coordinates are set as follows: The The formula is as follows: ; N light-emitting devices across the entire region independently perform the above calculations to obtain N ranging points, forming a three-dimensional point cloud set P={Q1,Q2,…, A greedy projection triangulation algorithm based on Delaunay triangulation is used to construct a triangular mesh surface model. The reconstructed triangular mesh surface S is fitted to an ideal sphere using the least squares method. The coordinates of the center point of the ideal sphere are O(x0, y0, z0), and the radius of the ideal sphere is R. The radial deviation of the ranging point is calculated, and the radial deviation is set as follows: The The formula is as follows: ； Among them, the , and Given the spatial coordinates of the i-th ranging point in the 3D point cloud, the radial deviation value is mapped to a color gradation interval to generate a radial deviation heatmap. A local quadratic surface model is established for each ranging point. The principal curvatures k1 and k2 are solved using the eigenvalues ​​of the Weingarten mapping matrix. The curvature value of k is mapped to a color gradation interval to generate a curvature distribution map. When adjacent ranging points exist... When it is determined that the curvature discontinuity marker in the region has a local defect, wherein the The Gaussian curvature value at my i-th ranging point, the stated The Gaussian curvature value of the preceding ranging point adjacent to the i-th ranging point, the Let be the average curvature at the i-th ranging point, the The average curvature value of the preceding ranging point adjacent to the i-th ranging point, the The Gaussian curvature continuity threshold, the The average curvature continuity threshold is used; the relationship between diameter and tolerance is determined by the following condition: if the maximum absolute value of radial deviation at all measuring points does not exceed the upper tolerance limit corresponding to the k-th model, and the minimum absolute value of radial deviation at all measuring points is not lower than the lower tolerance limit corresponding to that model, then the acetabular inner wall morphology is deemed acceptable; the specific formula for this determination is as follows: ； Wherein, k is the model number of the standard acetabular prosthesis, and the The upper limit of the tolerance corresponding to the k-th type of acetabular prosthesis, the This represents the lower tolerance limit for the k-th type of acetabular prosthesis.

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