Digital tracing method and system based on electric pressure sensing film

Abstract

The invention discloses a digital tracing method and system based on an electric pressure sensing film, and relates to the technical field of data analysis. An abnormal value composed of a local pressure flow direction consistency disturbance value and a sub-frame decomposition track line intersection density value is constructed; the perturbation abnormal frame which does not change suddenly but deviates from a real track in digital Gott's bow tracing can be accurately recognized, subsequence matching is conducted on the perturbation abnormal frame and a preset track template library, correction is completed after the reasonable position of the perturbation abnormal frame is determined, the problems of jump points, turn-back, breakage and the like caused by unrecognized hidden interference in a traditional method are solved, and the accuracy of perturbation abnormal frame recognition is improved. And excessive correction and structural distortion caused by unified filtering are avoided, so that the definiteness and structural retentivity correction of abnormal trajectory points is realized, and the authenticity and continuity of trajectory data and the controllability and stability of a digital denture repair process are improved.

Description

Technical Field

[0001] This invention relates to the field of data analysis technology, and specifically to a digital recording method and system based on a voltage-sensitive thin film. Background Technology

[0002] Gothic arch tracing is a clinical method for recording the movement trajectory of the mandible during protrusion and lateral movements. Its endpoint, the "Gothic arch apex," is often used to determine the mandibular central relationship in complete denture restorations. In traditional methods, a tracing needle draws lines on a pigmented tracing plate, and the dentist observes and interprets the trajectory morphology and convergence points. However, this method suffers from significant subjective errors and the inability to quantify information. In recent years, with the development of flexible sensors and digital measurement technology, research has introduced a voltage-sensitive film into the Gothic arch tracing system to replace the traditional tracing plate. This film can sense the pressure distribution on a two-dimensional plane in real time and convert the pressure trajectory generated during the tracing head's movement into a visualized digital signal, achieving the digitization, quantification, and visualization of trajectory acquisition. Through the accompanying software algorithm, the pressure trajectory can be automatically extracted and the position of the mandibular movement apex can be identified, thereby assisting in the judgment and recording of the central relationship. This digital tracing method has significant advantages in improving surgical precision, reducing human error, enhancing data archiving, and remote sharing capabilities, and is gradually becoming an important technological direction in the field of prosthodontics.

[0003] However, despite the significant technological advancements of digital recording methods based on voltage-sensing thin films compared to traditional methods, practical applications still face significant technical challenges at the signal level. In voltage-sensing thin-film digital recording, trajectory anomalies often do not appear as obvious abrupt changes, but rather as subtle patterns such as local disturbances, trajectory inversion, directional instability, and inconsistent pressure diffusion, gradually deviating from the true trajectory. These anomalies often cannot be directly identified through single-frame maximum value tracking or velocity mutation judgment. Furthermore, using uniform filtering or global fitting methods can easily lead to miscorrection of normal trajectory segments, thereby disrupting the overall continuity and morphological structure. Therefore, there is an urgent need for a method capable of dynamically identifying local frames with "micro-disturbance anomaly characteristics" in the trajectory, and after accurately locating the anomaly points, implementing a correction mechanism driven by local, limited, and structural consistency based on historical trajectory trends to ensure the local authenticity of the trajectory data and the coherence and unity of the overall structure. Summary of the Invention

[0004] The purpose of this invention is to solve the problems mentioned above and provide a digital recording method and system based on voltage-sensitive thin film.

[0005] In a first aspect of this invention, a digital recording method based on a voltage-sensitive thin film is first proposed, the method comprising:

[0006] S1: Obtain pressure data from multiple consecutive frames and calculate the local pressure flow direction consistency perturbation value to characterize the stability of the pressure flow direction in the main peak region over time.

[0007] S2: Extract the trajectory point set of consecutive frames, construct the subframe decomposed trajectory lines, and calculate the proportion of intersection times between adjacent subframe trajectory lines to obtain the intersection density value of the subframe decomposed trajectory lines, which is used to characterize the degree of spatial interlacing of trajectories in local areas.

[0008] S3: Obtain outliers based on the local pressure flow direction consistency disturbance value and the intersection density value of the subframe decomposed trajectory lines; and determine whether there are trajectory anomalies in the current frame based on the outliers and the preset threshold.

[0009] S4: If the current frame has a trajectory abnormality, then determine the corrected trajectory point of the current frame by combining the preset trajectory template library, and output the corrected trajectory point as the trajectory point of the current frame.

[0010] Optionally, the calculation steps for the local pressure flow direction consistency disturbance value are as follows:

[0011] Based on multiple frames of pressure data continuously acquired by a voltage-sensitive thin-film sensor, a multi-frame pressure image sequence is constructed in chronological order, where each frame image consists of the pressure values ​​of all pixels on the sensing film in a two-dimensional coordinate plane;

[0012] Identify the main peak region of pressure data in each frame of a multi-frame pressure image sequence, and in each frame of consecutive frames... Within the main peak region, each pixel is traversed one by one, and a local neighborhood window centered on the pixel is constructed. The pressure change rate of each point in the window in the horizontal and vertical directions is extracted, that is, the pressure value changes along the horizontal and vertical directions respectively, and the local pressure flow direction vector of the pixel is constructed accordingly.

[0013] Based on the pressure gradient direction vector of the same pixel in two adjacent frames, the angle of change of local pressure flow direction of each pixel between two adjacent frames is calculated based on the vector angle.

[0014] By statistically summing the angle of flow direction change of pixels in the main peak region of each frame, the overall flow direction torsional energy value of the main peak region of the corresponding frame image can be obtained.

[0015] The absolute difference of the overall flow direction torsional energy values ​​of two adjacent frames is used as the numerator, the sum of the overall flow direction torsional energy values ​​of two adjacent frames is used as the denominator, and the result of the numerator divided by the denominator is used as the energy evolution ratio.

[0016] The nonlinear divergence factor is calculated based on three consecutive energy evolution ratios. The formula for calculation is as follows: In the formula, Indicates the first The nonlinear divergence factor of the frame; , , These are the energy evolution ratios of the previous frame, the current frame, and the next frame, respectively.

[0017] Calculate the root mean square of all nonlinear divergence factors to obtain the local pressure flow direction uniformity perturbation value.

[0018] In a voltage-sensitive thin film, the set of trajectory points for consecutive frames is acquired, and the set of trajectory points is divided into multiple sub-frame segments;

[0019] For each pair of adjacent subframes, the total number of their intersection points is calculated using the line segment intersection algorithm;

[0020] For each pair of adjacent subframes, divide the total number of their intersection points by the total number of line segments in the two subframes to obtain the intersection ratio of the corresponding adjacent subframes.

[0021] Calculate the root mean square of all intersection percentages as the intersection density value of the subframe decomposed trajectory lines. Optionally, outlier values ​​are obtained based on the local pressure flow consistency perturbation value and the intersection density value of the subframe decomposed trajectory lines. The step of determining whether there are trajectory anomalies in the current frame based on the outlier values ​​and a preset threshold is as follows:

[0022] The local pressure flow direction consistency perturbation value and the intersection density value of the subframe decomposition trajectory line are normalized. The normalized local pressure flow direction consistency perturbation value and the intersection density value of the subframe decomposition trajectory line are added together to obtain the outlier value.

[0023] Compare the outlier with the preset threshold. If the outlier is less than the preset threshold, the trajectory point of the current frame is output as a valid trajectory point.

[0024] If the abnormal value is not less than the preset threshold, then the current frame is determined to have a trajectory abnormality.

[0025] Optionally, the steps of determining the corrected trajectory points for the current frame by combining the preset trajectory template library and outputting the corrected trajectory points as the trajectory points for the current frame are as follows:

[0026] If there is a trajectory anomaly in the current frame, extract several historical trajectory points from before the current frame to form a historical trajectory point set. Perform subsequence matching between the historical trajectory point set and multiple templates in the preset trajectory template library, calculate the matching error, select the template with the smallest matching error, and determine the corrected trajectory point for the current frame based on the corresponding position of the template. Output the corrected trajectory point as the trajectory point for the current frame.

[0027] In a second aspect of the invention, a digital recording system based on a voltage-force-sensing thin film is provided, the system comprising:

[0028] Pressure flow direction module: acquires pressure data from multiple consecutive frames and calculates the local pressure flow direction consistency perturbation value, which is used to characterize the stability of the pressure flow direction in the main peak region over time.

[0029] Line intersection module: Extracts the trajectory point set of continuous frames, constructs subframe decomposed trajectory lines, and calculates the proportion of intersection times between adjacent subframe trajectory lines to obtain the intersection density value of subframe decomposed trajectory lines, which is used to characterize the degree of spatial interlacing of trajectories in local areas;

[0030] Analysis and comparison module: It obtains outlier values ​​based on the local pressure flow consistency disturbance value and the intersection density value of the subframe decomposed trajectory lines; and determines whether there is trajectory anomaly in the current frame based on the outlier values ​​and preset thresholds.

[0031] Correction and recording module: If the current frame has a trajectory abnormality, the corrected trajectory point of the current frame is determined by combining the preset trajectory template library, and the corrected trajectory point is output as the trajectory point of the current frame.

[0032] Optionally, the pressure flow module includes:

[0033] Sequence Module: Based on multiple frames of pressure data continuously acquired by a voltage-sensitive thin-film sensor, a multi-frame pressure image sequence is constructed in chronological order, where each frame consists of the pressure values ​​of all pixels on the sensing membrane in a two-dimensional coordinate plane;

[0034] Gradient Direction Vector Module: Identifies the main peak region of pressure data in each frame of a multi-frame pressure image sequence, and in each frame of a continuous sequence... Within the main peak region, each pixel is traversed one by one, and a local neighborhood window centered on the pixel is constructed. The pressure change rate of each point in the window in the horizontal and vertical directions is extracted, that is, the pressure value changes along the horizontal and vertical directions respectively, and the local pressure flow direction vector of the pixel is constructed accordingly.

[0035] Local flow direction change angle module: Based on the pressure gradient direction vector of the same pixel in two adjacent frames, the local pressure flow direction change angle of each pixel between two adjacent frames is calculated based on the vector angle.

[0036] Flow direction torsion energy value module: By statistically summing the flow direction change angle of the pixels in the main peak region of each frame, the overall flow direction torsion energy value of the main peak region of the corresponding frame image is obtained;

[0037] Energy Evolution Ratio Module: The absolute difference of the overall flow direction torsional energy values ​​of two adjacent frames is used as the numerator, the sum of the overall flow direction torsional energy values ​​of two adjacent frames is used as the denominator, and the result of the numerator divided by the denominator is used as the energy evolution ratio.

[0038] Divergence Factor Module: Calculates the nonlinear divergence factor based on three consecutive energy evolution ratios. The formula is as follows: In the formula, Indicates the first The nonlinear divergence factor of the frame; , , These are the energy evolution ratios of the previous frame, the current frame, and the next frame, respectively.

[0039] Local pressure flow direction consistency perturbation module: Calculates the root mean square of all nonlinear divergence factors to obtain the local pressure flow direction consistency perturbation value.

[0040] Optionally, the line intersection module includes:

[0041] Subframe module: In the voltage force sensing film, acquire the set of trajectory points for consecutive frames and divide the set of trajectory points into multiple subframes;

[0042] Intersection module: For each pair of adjacent subframe segments, the total number of their intersection points is calculated using the line segment intersection algorithm;

[0043] Intersection ratio module: For each pair of adjacent subframes, divide the total number of their intersection points by the total number of line segments in the two subframes to obtain the intersection ratio of the corresponding adjacent subframes.

[0044] Intersection Density Value Module: Calculates the root mean square of all intersection percentages as the intersection density value of the subframe decomposed trajectory lines.

[0045] Optionally, the analysis and comparison module includes:

[0046] Outlier Calculation Module: Normalizes the local pressure flow direction consistency disturbance value and the intersection density value of the subframe decomposition trajectory line, and adds the normalized local pressure flow direction consistency disturbance value to the intersection density value of the subframe decomposition trajectory line to obtain the outlier value;

[0047] The first comparison module compares outliers with a preset threshold. If the outlier is less than the preset threshold, the current frame trajectory point is output as a valid trajectory point.

[0048] The second comparison module: If the abnormal value is not less than the preset threshold, it is determined that there is a trajectory abnormality in the current frame.

[0049] Optionally, the correction recording module is specifically used as follows:

[0050] If there is a trajectory anomaly in the current frame, extract several historical trajectory points from before the current frame to form a historical trajectory point set. Perform subsequence matching between the historical trajectory point set and multiple templates in the preset trajectory template library, calculate the matching error, select the template with the smallest matching error, and determine the corrected trajectory point for the current frame based on the corresponding position of the template. Output the corrected trajectory point as the trajectory point for the current frame.

[0051] The beneficial effects of this invention are:

[0052] This invention proposes a digital recording method and system based on a voltage-sensing thin film. By constructing anomaly values ​​composed of local pressure flow consistency perturbation values ​​and intersection density values ​​of subframe decomposed trajectory lines, it can effectively identify micro-perturbation anomaly frames that do not show obvious abrupt changes but have deviated from the true trajectory during the digital Gothic arch recording process. Then, by performing subsequence matching with a preset trajectory template library, it can accurately locate the reasonable position of the current frame in the overall trajectory structure and make corrections. This avoids problems such as trajectory jumps, reversals, and breaks caused by the inability to identify latent interference in traditional methods, and also avoids over-correction and structural distortion caused by uniform filtering or fitting processing. Thus, it achieves the limitation and structural preservation correction of anomaly trajectory points, effectively ensuring the authenticity of trajectory data locally and the coherence of the whole, improving the stability of mandibular movement trajectory recognition, the extraction accuracy of central relation vertices, and the controllability and reliability of the digital denture restoration process. Attached Figure Description

[0053] The invention will now be further described with reference to the accompanying drawings.

[0054] Figure 1 This is a flowchart of a digital recording method based on a voltage-sensitive thin film;

[0055] Figure 2 This is a framework diagram of a digital recording system based on a voltage-sensitive thin film. Detailed Implementation

[0056] 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.

[0057] This invention provides a digital recording method based on a voltage-sensitive thin film. See also... Figure 1 , Figure 1 A flowchart illustrating a digital recording method based on a voltage-sensitive thin film, provided as an embodiment of the present invention. The method includes the following steps:

[0058] S1: Obtain pressure data from multiple consecutive frames and calculate the local pressure flow direction consistency perturbation value to characterize the stability of the pressure flow direction in the main peak region over time.

[0059] S2: Extract the trajectory point set of consecutive frames, construct the subframe decomposed trajectory lines, and calculate the proportion of intersection times between adjacent subframe trajectory lines to obtain the intersection density value of the subframe decomposed trajectory lines, which is used to characterize the degree of spatial interlacing of trajectories in local areas.

[0060] S3: Obtain the outlier value based on the local pressure flow direction consistency disturbance value and the intersection density value of the subframe decomposed trajectory lines, and determine whether there is a trajectory anomaly in the current frame based on the outlier value and the preset threshold.

[0061] S4: If the current frame has a trajectory abnormality, then determine the corrected trajectory point of the current frame by combining the preset trajectory template library, and output the corrected trajectory point as the trajectory point of the current frame.

[0062] Based on the digital recording method based on a voltage-sensing thin film provided by the embodiments of the present invention, by constructing anomalies composed of local pressure flow consistency perturbation values ​​and intersection density values ​​of subframe decomposed trajectory lines, it is possible to effectively identify those micro-perturbation anomalies that have deviated from the true trajectory but do not show obvious abrupt changes during the digital Gothic arch recording process. Then, by performing subsequence matching with a preset trajectory template library, the reasonable position of the current frame in the overall trajectory structure is accurately located and corrected. This avoids problems such as trajectory jumps, reversals, and breaks caused by the inability to identify latent interference in traditional methods, and also avoids over-correction and structural distortion caused by uniform filtering or fitting processing. Thus, it achieves the limitation and structural preservation correction of anomaly trajectory points, effectively ensuring the authenticity of trajectory data locally and the coherence of the whole, improving the stability of mandibular movement trajectory recognition, the extraction accuracy of central relation vertices, and the controllability and reliability of the digital denture restoration process.

[0063] In one embodiment, S1: Obtain pressure data from multiple consecutive frames and calculate the local pressure flow direction consistency perturbation value to characterize the stability of the pressure flow direction in the main peak region over time.

[0064] In one implementation, the calculation steps for the local pressure flow direction consistency disturbance value are as follows:

[0065] Based on multiple frames of pressure data continuously acquired by a voltage-sensitive thin-film sensor, a multi-frame pressure image sequence is constructed in chronological order. Each frame consists of the pressure values ​​of all pixels on the sensing film in a two-dimensional coordinate plane. Pressure image sequence: ,in Indicates the first Two-dimensional coordinates of pixels in a frame image Pressure value at the location; , indicating consecutive time frame numbers; These are the two-dimensional pixel coordinates on the voltage-sensitive film; this sequence constitutes a set of two-dimensional pressure distribution maps that change over time, used for subsequent trajectory behavior analysis. Indicates the first Pressure values ​​of pixels in a frame image;

[0066] Identify the main peak region of pressure data in each frame of a multi-frame pressure image sequence. and in each frame of a consecutive frame Within the main peak region, each pixel is traversed sequentially, and a local neighborhood window centered on each pixel is constructed. The pressure change rate of each point in the window in the horizontal and vertical directions is extracted, that is, the pressure value changes along the horizontal and vertical directions are calculated respectively, and the local pressure flow direction vector of the pixel is constructed accordingly to characterize the instantaneous pressure conduction direction of the region; the corresponding steps are: calculate the pressure gradient direction vector of each pixel: In the formula, Indicates the first Pixels in a frame The local pressure flow direction vector; express The rate of change of pressure in the direction, express Rate of change of pressure in the direction; This represents a pixel window surrounding the main peak region, used to capture the pressure structure of the main peak;

[0067] Based on the pressure gradient direction vectors of the same pixels in two adjacent frames, the angle of change of local pressure flow direction of each pixel between two adjacent frames is calculated using the vector angle method. The calculation formula is: In the formula, Indicates the first Frame and the Frame in pixel The angle of change of local flow direction at that location To prevent division by zero, small constants are generally taken as 1. ;

[0068] By statistically summing the flow direction change angles of pixels in the main peak region of each frame, the overall flow direction torsional energy value of the main peak region of the corresponding frame image is obtained; specifically, the flow direction torsional energy in the main peak region of each frame is calculated based on the local flow direction change angle, and the calculation formula is as follows: , Indicates the first Energy for flow reversal within the neighborhood of the main peak of the frame;

[0069] The absolute difference in the overall flow-direction torsional energy values ​​of two adjacent frames is used as the numerator, and the sum of the overall flow-direction torsional energy values ​​of two adjacent frames is used as the denominator. The ratio of the numerator to the denominator is used as the energy evolution ratio; the calculation formula is as follows: , Indicates the first Frame relative to the first The energy evolution ratio of each frame; To prevent division by zero, small constants are generally taken as 1. ;

[0070] The nonlinear divergence factor is calculated based on three consecutive energy evolution ratios. The formula for calculation is as follows: In the formula, Indicates the first The nonlinear divergence factor of the frame; , , These represent the energy evolution ratios of the previous frame, the current frame, and the next frame, respectively.

[0071] Calculate the root mean square of all nonlinear divergence factors to obtain the local pressure flow direction uniformity perturbation value.

[0072] It should be noted that in calculating the local pressure flow consistency perturbation value, each step relies on multi-frame pressure data acquired in real time from the voltage-sensing thin film. Specifically, continuous two-dimensional pressure distribution map data is first acquired through the voltage-sensing thin film. This data is acquired in time frames, with each frame representing the pressure value at various locations on the film surface. The pressure data for each pixel is provided by the thin-film sensor array, forming a continuous frame sequence over time. In each frame, the algorithm automatically identifies the main peak region (automatic identification of the main peak region is a crucial step. To identify the main peak region in each frame, an image processing-based peak detection algorithm is used, specifically through a combination of local maximum algorithm and pressure threshold filtering. First, by calculating the pressure value of each pixel in the pressure matrix of each frame, Gaussian smoothing filtering is used to remove noise and enhance signal smoothness. Then, the local maximum detection algorithm is used to find the maximum pressure value point in each local region in the smoothed pressure image. To ensure that the identified region is the main peak region, a pressure threshold is further set. This threshold is automatically calculated based on the pressure distribution characteristics of all pixels in the current frame, usually a certain percentage of the pressure values ​​in the entire image, such as the top 10% of pressure values. Finally, all pixels exceeding this threshold and being local maxima constitute the main peak region, which is the key region of the required mandibular movement trajectory. This algorithm determines the range of the main peak region automatically without manual intervention and can dynamically adapt to different pressure distributions, thus providing accurate basic data for subsequent flow direction analysis and disturbance calculation.), which is the part with the highest pressure value and is usually associated with the key trajectory points of mandibular movement. For the main peak region of each frame, a local neighborhood window is selected, the size of which is dynamically determined based on the regional characteristics of the pressure distribution. Next, the pressure gradient of each pixel within this window is calculated, yielding its corresponding flow direction vector, representing the direction of pressure change. Based on the pressure gradient vectors at the same location in two adjacent frames, the flow direction change angle is further calculated, reflecting the flow direction disturbance. The flow direction disturbance energy of each pixel is obtained by calculating the sum of the squares of the flow direction change angles, and the stability and disturbance intensity are further reflected by the energy change ratio between frames. Furthermore, the nonlinear divergence factor is calculated using the energy evolution ratio of adjacent frames. Finally, the root mean square of all nonlinear divergence factors is used to obtain the local pressure flow direction consistency disturbance value, which is ultimately used to determine the stability of the pressure flow direction and the presence of abnormal disturbances. Pressure data for each frame is acquired and processed in real time to ensure the accuracy of the data's temporal sequence and spatial location.

[0073] It should be noted that the local pressure flow direction consistency perturbation value is an indicator used to measure the stability and consistency of pressure flow direction during voltage-sensing film recording. It reflects whether there are abnormal or unstable changes in the pressure flow direction of the main peak region in continuous time frames by calculating the degree of change in the pressure flow direction of a local area. Specifically, the local pressure flow direction consistency perturbation value calculates the change of the local pressure gradient direction vector between different time frames. If the flow direction is abnormal or inconsistent, the value will increase. This is because when the local pressure flow direction changes significantly, the distribution of pressure values ​​no longer exhibits a consistent dynamic change pattern, possibly due to multi-point interference, local pressure fluctuations, or trajectory changes that do not conform to the expected stability law. For example, when there are drastic fluctuations in mandibular movement or an incorrect recording direction, the pressure flow direction changes abruptly, thereby increasing the torsional energy and angle of flow direction change, resulting in an increase in the local pressure flow direction consistency perturbation value. A higher local pressure flow direction consistency perturbation value indicates more drastic changes in the flow direction, suggesting poor consistency of the pressure flow direction in the main peak region over time, which usually indicates abnormal behavior or interference during the recording process. Therefore, the larger the local pressure flow consistency disturbance value, the greater the likelihood of trajectory anomalies in the current frame. This is usually due to abrupt changes or inconsistencies in pressure flow direction, reflecting irregularities, nonlinearities, or errors in the mandibular movement trajectory. For example, during recording, if the recording head suddenly vibrates or undergoes an irregular directional change, the flow direction in the main peak region will change rapidly, leading to an increase in the local flow direction change angle and the flow torsional energy, thus increasing the local pressure flow consistency disturbance value. This situation usually indicates anomalies or interference in the recording results, thereby affecting the accuracy and reliability of the trajectory.

[0074] It's important to note that the advantage of calculating local pressure flow consistency perturbation values ​​using the above method lies in its ability to accurately capture minute changes in pressure flow direction during the recording process, especially when there are latent interferences or subtle disturbances in the mandibular movement trajectory. Other traditional methods often struggle to achieve this. Specifically, the calculation method based on the local pressure gradient direction vector can accurately quantify the directionality of pressure changes at each pixel, rather than simply relying on changes in the pressure value itself. This allows for the identification of whether the trajectory flow direction is stable. By calculating the angle and energy evolution ratio of local flow direction changes, the local pressure flow consistency perturbation value can not only capture changes at a single pressure point but also comprehensively consider the persistence and stability of pressure flow direction over time, which is more effective than simply relying on maximum value tracking or traditional velocity mutation detection. Calculating local pressure flow consistency perturbation values ​​using the flow direction gradient method is highly sensitive and can detect minute flow direction deviations, which are often caused by minor movements or slight disturbances, whereas traditional methods typically only focus on more significant changes. Therefore, by accurately assessing the consistency of pressure flow direction, the local pressure flow direction consistency perturbation value can effectively identify micro-perturbation anomalies in the trajectory, avoid erroneous corrections or unnecessary perturbation processing, thereby ensuring the continuity and accuracy of the trajectory, making the digital recording method more reliable and accurate in clinical applications.

[0075] In one embodiment, S2: Extract the set of trajectory points of consecutive frames, construct the subframe decomposed trajectory lines, and calculate the proportion of the number of intersections between adjacent subframe trajectory lines to obtain the intersection density value of the subframe decomposed trajectory lines, which is used to characterize the degree of spatial interlacing of trajectories in local areas.

[0076] In one implementation, the calculation steps for the intersection density value of the subframe decomposition trajectory lines are as follows:

[0077] In a voltage-sensitive thin film, the set of trajectory points for consecutive frames is obtained. Each frame The set of discrete points representing the trajectory of mandibular movement , Indicates the first The set of trajectory points of a frame, containing A discrete trajectory point; each point For the first The mandibular motion trajectory point at frame time; , The two-dimensional coordinates of the trajectory point on the thin-film sensor;

[0078] Set of trajectory points Divided into multiple subframes In the formula, For the first The first frame Sub-frames; Indicates the first The number of trajectory points within a subframe; subframe Connecting adjacent trajectory points and composition;

[0079] For each pair of adjacent subframes and The total number of intersection points is calculated using a line segment intersection algorithm. The formula is as follows: In the formula, Indicates the first Within the subframe A trajectory line segment, connecting points and , As an indicator function, when line segment and The value is 1 when they intersect, and 0 otherwise. Indicates the nth frame. Subframe and the The total number of intersection points in a subframe;

[0080] For each pair of adjacent subframes and Divide the total number of intersection points by the total number of line segments in the two subframes to obtain the intersection ratio of the corresponding adjacent subframes; calculate the ratio of intersecting line segments to the total number of line segments using the following formula: In the formula, Indicates the nth frame. Subframe and the The overlap ratio of subframes This represents the total number of line segments in the two subframes;

[0081] Calculate the root mean square of all intersection percentages and use it as the intersection density value of the subframe decomposed trajectory lines.

[0082] It should be noted that the data involved in the calculation of the intersection density value of the trajectory lines in the above subframe decomposition process is mainly acquired in real time by a voltage-sensitive film deployed in the mandibular movement panel area of ​​the Gothic arch. Specifically, during the user's mandibular movements such as biting, opening, and closing, the voltage-sensitive film continuously collects the pressure change data acting on its surface and converts the corresponding two-dimensional pressure distribution map at each moment into a frame image. By extracting the center line of the high-pressure continuous area in each frame pressure distribution map, the set of mandibular movement trajectory points for that frame can be constructed. To ensure the continuity and spatial resolution of the trajectory, the system usually records trajectory data continuously at a fixed frame rate (e.g., tens of frames per second) and performs standardization processing on the trajectory point set of each frame, including noise filtering, smooth interpolation, and equidistant resampling. Then, the trajectory point sequence of each frame is divided into multiple subframe segments according to a preset time window or trajectory segment length. Each subframe segment contains several adjacent trajectory points. By calculating the connecting line segments of adjacent trajectory points within these subframe segments, the set of trajectory lines can be constructed, providing basic data for subsequent calculations of the number of intersections, the intersection ratio, and the root mean square. Therefore, the entire set of trajectory points and its sub-frame segments are converted in real time by the data stream continuously output by the voltage force sensing film, without the need for additional manual marking, thus ensuring the objectivity and high-frequency accuracy of data acquisition.

[0083] It's important to note that the subframe decomposition trajectory line intersection density value is an indicator used to measure whether there are abnormal spatial intersections in the mandibular movement trajectory within a continuous time period. Essentially, it measures the frequency of intersections between trajectory lines of adjacent subframe segments within a given frame. A higher value indicates more spatial intersections and interweaving of movement trajectories from different time periods within that frame, typically indicating nonlinear, disordered, or repetitive abnormal movements. During normal chewing or biting, the mandibular movement trajectory should have a clear direction and fluidity, with minimal intersections and a continuous trend. However, when situations such as sudden muscle twitching, mistransmission of nerve signals, or pain interference occur, the trajectory may repeatedly swing back, exhibit localized tremors, or abnormal repetition, leading to frequent intersections between lines of different subframe segments and forming a high density of trajectory intersection points. Therefore, a higher subframe decomposition trajectory line intersection density value indicates a more disordered spatial trajectory, stronger behavioral repetition between trajectory segments, and a greater likelihood of non-physiological trajectory deviations or behavioral abnormalities. For example, under normal circumstances, the trajectory lines of consecutive subframe segments A and B should remain smoothly connected and in the same direction. However, under abnormal conditions, multiple lines of segment B may cross segment A in the opposite direction, forming multiple intersection points. This degree of spatial overlap is amplified and captured in this value, thereby effectively identifying abnormal trajectory states. It is especially suitable for early identification of slight trajectory disturbances, and can accurately identify them through structural behavior features without relying on absolute amplitude.

[0084] It should be noted that the greatest advantage of calculating the intersection density value of the trajectory lines in the subframe decomposition method described above is that it does not rely on conventional indicators such as displacement amplitude, velocity change, or frequency characteristics. Instead, it directly captures the spatial complexity of the trajectory, characterizing the nonlinear behavior of the trajectory at the subframe level, thus possessing higher sensitivity and interpretability. This method divides each frame's trajectory point set into multiple subframe segments and constructs line segment connections to form a high-resolution trajectory line network. Based on the actual number of intersection points of line segments in geometric space, it accurately assesses the actual spatial interweaving degree of the trajectory at different time periods. Compared to simple directional fluctuations or velocity abrupt changes, this method better reflects the trajectory. This method is particularly suitable for identifying weak but recurring abnormal signal patterns, such as swinging, overlapping, and turning back in a two-dimensional plane. Furthermore, its computational steps are rigorous and coherent, with the output of each stage serving the trajectory structure analysis of the next stage. It does not introduce any weighting or fuzzy factors, ensuring the physical interpretability and objectivity of the results. Simultaneously, by extracting the global spatial interlacing trend through root mean square extraction, it can effectively suppress the interference of random noise, improving the overall stability and robustness of the judgment. It is suitable for the accurate detection and early warning of trajectory perturbation anomalies in real-world scenarios, and has extremely high practical value and scalability in applications such as clinical mandibular motion analysis and voltage-sensing trajectory monitoring.

[0085] In one embodiment, S3: Obtain an outlier value based on the local pressure flow direction consistency disturbance value and the intersection density value of the subframe decomposed trajectory lines, and determine whether there is a trajectory anomaly in the current frame based on the outlier value and a preset threshold.

[0086] In one implementation, the step of obtaining outliers based on the local pressure flow consistency perturbation value and the intersection density value of the subframe decomposed trajectory lines is as follows:

[0087] The local pressure flow direction consistency perturbation value and the intersection density value of the subframe decomposition trajectory line are normalized. The normalized local pressure flow direction consistency perturbation value and the intersection density value of the subframe decomposition trajectory line are added together to obtain the outlier value.

[0088] It should be noted that the above-mentioned normalization methods for removing dimensions include Min-Max normalization, Z-Score standardization, etc., which will not be elaborated here.

[0089] In one implementation, the step of determining whether there is a trajectory anomaly in the current frame based on the outlier and a preset threshold is as follows:

[0090] Compare the outlier with the preset threshold. If the outlier is less than the preset threshold, the trajectory point of the current frame is output as a valid trajectory point.

[0091] If the abnormal value is not less than the preset threshold, then the current frame is determined to have a trajectory abnormality.

[0092] It should be noted that when the outlier value is less than the threshold, it indicates that the various trajectory structure features in the current frame do not exceed the system's tolerance range for normal fluctuations. Therefore, the trajectory of this frame can be considered to have good continuity, stable structure, and no abnormal behavior. The trajectory points of this frame can be included in subsequent trajectory behavior analysis and model training and retained as valid trajectory points. However, when the outlier value is greater than or equal to the threshold, it indicates that the local flow disturbance or trajectory intersection degree of the current frame has reached the warning level, and there is a sudden abnormal fluctuation, such as swinging, path twisting, excessive overlap, etc. Therefore, this frame is directly judged as having trajectory anomalies and will not enter subsequent processing procedures such as trajectory clustering and classification. For example, if a frame causes severe entanglement of the trajectory path due to user jaw twitching or device mis-sampling, causing the intersection density value of its subframe trajectory lines to jump to 0.87 instantly (far exceeding the system's preset threshold of 0.6), the system will immediately identify it as an abnormal frame and remove it to avoid polluting the overall trajectory structure judgment, thereby ensuring the stability and accuracy of the system output results.

[0093] In one embodiment, S4: If the current frame has a trajectory anomaly, then the corrected trajectory point of the current frame is determined by combining the preset trajectory template library, and the corrected trajectory point is output as the trajectory point of the current frame, including:

[0094] If there is a trajectory anomaly in the current frame, extract several historical trajectory points from before the current frame to form a historical trajectory point set. Perform subsequence matching between the historical trajectory point set and multiple templates in the preset trajectory template library, calculate the matching error, select the template with the smallest matching error, and determine the corrected trajectory point for the current frame based on the corresponding position of the template. Output the corrected trajectory point as the trajectory point for the current frame.

[0095] Specifically, when the current frame is determined to have an abnormal trajectory, to prevent the abnormal trajectory point from interfering with the overall analysis results, the system will activate a trajectory correction mechanism. This mechanism corrects the abnormal frame by tracing back historical trajectory points and matching them with template trajectories. Specifically, the system extracts trajectory points from several consecutive frames preceding the current frame (e.g., the previous 5 or 10 frames) to form a historical trajectory point set. This set reflects the true trajectory evolution trend before the current frame. Then, the system uses this historical trajectory point set as input and performs sub-sequence matching with multiple preset standard motion pattern templates in the trajectory template library. It uses matching algorithms with different alignment ratios, such as Dynamic Time Warping (DTW), to calculate the matching error. The matching error reflects the similarity between the historical trajectory and each template in local structure; the smaller the error, the better the trajectory match. The system selects the template with the smallest error as the standard motion pattern to which the current trajectory most likely belongs, and locates the trajectory point in that template corresponding to the current frame's time position. The template trajectory point at that position is used as the corrected trajectory point for the current frame, effectively replacing the original distorted trajectory points in the abnormal frame. For example, if a user experiences a jerky, erratic trajectory in the current frame due to device loosening, but their trajectory in the previous frames progressed smoothly, the system will use template matching to find that it matches the "smooth progress" template best. The system will then extract the standard trajectory points corresponding to the current frame time from that template and replace them, thereby correcting the continuity of the trajectory and ensuring the accuracy and robustness of subsequent analysis.

[0096] It should be noted that, from a clinical perspective, the traditional Gothic arch can record the graphic representation and vertex position of mandibular movements. It mainly consists of a tracing needle and a tracing plate. By placing a tracing system between the patient's upper and lower dentition, the tracing needle leaves a trajectory on the tracing plate during functional movements of the mandible, such as protrusion, retraction, and lateral movements, thus forming a graphic Gothic arch trajectory diagram. The central vertex of this diagram is usually considered the "central relation point" or "occlusal relation vertex" during mandibular movements, providing a basis for treatments such as prosthetic restoration and occlusal reconstruction. Clinicians can judge the coordination of mandibular movements and the stability of the occlusal relationship by observing the symmetry, trajectory direction, and vertex position of the tracing diagram. However, the traditional Gothic arch can only record the two-dimensional morphology and endpoint vertex position of the mandibular movement trajectory. The novel approach proposed in this paper is based on... The digital Gothic arch tracing system with a voltage-sensitive film has achieved significant functional expansion. It can not only capture the spatial path of the trajectory line in real time, but also simultaneously acquire key parameters such as speed changes during movement, pressure magnitude during contact, and trajectory overlap frequency at the same position. Among them, speed information can reflect the rhythm and smoothness of mandibular movement, pressure magnitude can reveal the strength of occlusal contact or muscle force, and position overlap frequency can help identify whether a certain area is a key node of repetitive movement or a point of instability in control. This collaborative recording of three dynamic parameters allows the functional characteristics of mandibular movement behavior to be presented more accurately and comprehensively, significantly improving the clinical ability to judge functional abnormalities, motor coordination, and individual differences, and providing more valuable dynamic data support for denture design, occlusal adjustment, and postoperative evaluation.

[0097] Based on the same inventive concept, this invention also provides a digital recording system based on a voltage-force-sensing thin film. See also Figure 2 , Figure 2 A framework diagram of a digital recording system based on a voltage-force-sensing thin film provided in an embodiment of the present invention is shown. The system includes:

[0098] Pressure flow direction module: acquires pressure data from multiple consecutive frames and calculates the local pressure flow direction consistency perturbation value, which is used to characterize the stability of the pressure flow direction in the main peak region over time.

[0099] Line intersection module: Extracts the trajectory point set of continuous frames, constructs subframe decomposed trajectory lines, and calculates the proportion of intersection times between adjacent subframe trajectory lines to obtain the intersection density value of subframe decomposed trajectory lines, which is used to characterize the degree of spatial interlacing of trajectories in local areas;

[0100] Analysis and comparison module: It obtains outlier values ​​based on the local pressure flow consistency disturbance value and the intersection density value of the subframe decomposed trajectory lines; and determines whether there is trajectory anomaly in the current frame based on the outlier values ​​and preset thresholds.

[0101] Correction and recording module: If the current frame has a trajectory abnormality, the corrected trajectory point of the current frame is determined by combining the preset trajectory template library, and the corrected trajectory point is output as the trajectory point of the current frame.

[0102] The digital recording system based on a voltage-sensing thin film provided by this invention, through the above-described method, constructs anomalies composed of local pressure flow consistency perturbation values ​​and intersection density values ​​of subframe decomposed trajectory lines. This effectively identifies micro-perturbation anomalies that deviate from the true trajectory during the digital Gothic arch recording process, even if they do not exhibit obvious abrupt changes. Furthermore, by performing subsequence matching with a preset trajectory template library, the system accurately locates and corrects the reasonable position of the current frame within the overall trajectory structure. This avoids problems such as trajectory jumps, reversals, and breaks caused by the inability to identify latent interference in traditional methods, and also avoids over-correction and structural distortion caused by uniform filtering or fitting. Thus, it achieves limiting and structurally preserving correction of anomaly trajectory points, effectively ensuring the local authenticity and overall coherence of trajectory data. This improves the stability of mandibular movement trajectory recognition, the accuracy of central relation vertex extraction, and the controllability and reliability of the digital denture restoration process.

[0103] In one embodiment, the pressure flow module includes:

[0104] Sequence Module: Based on multiple frames of pressure data continuously acquired by a voltage-sensitive thin-film sensor, a multi-frame pressure image sequence is constructed in chronological order, where each frame consists of the pressure values ​​of all pixels on the sensing membrane in a two-dimensional coordinate plane;

[0105] Gradient Direction Vector Module: Identifies the main peak region of pressure data in each frame of a multi-frame pressure image sequence, and in each frame of a continuous sequence... Within the main peak region, each pixel is traversed one by one, and a local neighborhood window centered on the pixel is constructed. The pressure change rate of each point in the window in the horizontal and vertical directions is extracted, that is, the pressure value changes along the horizontal and vertical directions respectively, and the local pressure flow direction vector of the pixel is constructed accordingly.

[0106] Local flow direction change angle module: Based on the pressure gradient direction vector of the same pixel in two adjacent frames, the local pressure flow direction change angle of each pixel between two adjacent frames is calculated based on the vector angle.

[0107] Flow direction torsion energy value module: By statistically summing the flow direction change angle of the pixels in the main peak region of each frame, the overall flow direction torsion energy value of the main peak region of the corresponding frame image is obtained;

[0108] Energy Evolution Ratio Module: The absolute difference of the overall flow direction torsional energy values ​​of two adjacent frames is used as the numerator, the sum of the overall flow direction torsional energy values ​​of two adjacent frames is used as the denominator, and the result of the numerator divided by the denominator is used as the energy evolution ratio.

[0109] Divergence Factor Module: Calculates the nonlinear divergence factor based on three consecutive energy evolution ratios. The formula is as follows: In the formula, Indicates the first The nonlinear divergence factor of the frame; , , These are the energy evolution ratios of the previous frame, the current frame, and the next frame, respectively.

[0110] Local pressure flow direction consistency perturbation module: Calculates the root mean square of all nonlinear divergence factors to obtain the local pressure flow direction consistency perturbation value.

[0111] In one embodiment, the line intersection module includes:

[0112] Subframe module: In the voltage force sensing film, acquire the set of trajectory points for consecutive frames and divide the set of trajectory points into multiple subframes;

[0113] Intersection module: For each pair of adjacent subframe segments, the total number of their intersection points is calculated using the line segment intersection algorithm;

[0114] Intersection ratio module: For each pair of adjacent subframes, divide the total number of their intersection points by the total number of line segments in the two subframes to obtain the intersection ratio of the corresponding adjacent subframes.

[0115] Intersection Density Value Module: Calculates the root mean square of all intersection percentages as the intersection density value of the subframe decomposed trajectory lines.

[0116] In one embodiment, the analysis and comparison module includes:

[0117] Outlier Calculation Module: Normalizes the local pressure flow direction consistency disturbance value and the intersection density value of the subframe decomposition trajectory line, and adds the normalized local pressure flow direction consistency disturbance value to the intersection density value of the subframe decomposition trajectory line to obtain the outlier value;

[0118] The first comparison module compares outliers with a preset threshold. If the outlier is less than the preset threshold, the current frame trajectory point is output as a valid trajectory point.

[0119] The second comparison module: If the abnormal value is not less than the preset threshold, it is determined that there is a trajectory abnormality in the current frame.

[0120] In one embodiment, the correction recording module is specifically used as follows:

[0121] If there is a trajectory anomaly in the current frame, extract several historical trajectory points from before the current frame to form a historical trajectory point set. Perform subsequence matching between the historical trajectory point set and multiple templates in the preset trajectory template library, calculate the matching error, select the template with the smallest matching error, and determine the corrected trajectory point for the current frame based on the corresponding position of the template. Output the corrected trajectory point as the trajectory point for the current frame.

[0122] The foregoing has provided a detailed description of one embodiment of the present invention, but this description is merely a preferred embodiment and should not be construed as limiting the scope of the invention. All equivalent variations and modifications made within the scope of the claims of this invention should still fall within the patent coverage of this invention.

Claims

1. A digital recording method based on a voltage-sensitive thin film, characterized in that, Includes the following steps: Calculate the local pressure flow direction consistency disturbance value by acquiring pressure data from multiple consecutive frames; Extract the trajectory point set of consecutive frames, construct the subframe decomposed trajectory lines, and calculate the proportion of intersection times between adjacent subframe trajectory lines to obtain the intersection density value of the subframe decomposed trajectory lines. Anomalies are obtained by comparing the local pressure flow direction consistency disturbance value with the intersection density value of the subframe decomposed trajectory lines. Anomalies are then used to determine whether there are trajectory anomalies in the current frame based on the anomalies and a preset threshold. If an abnormal trajectory is found in the current frame, the corrected trajectory point for the current frame is determined by combining the preset trajectory template library, and the corrected trajectory point is output as the trajectory point of the current frame.

2. The digital recording method based on a voltage-sensitive thin film according to claim 1, characterized in that, The calculation steps for the local pressure flow direction consistency disturbance value are as follows: Based on multiple frames of pressure data continuously acquired by a voltage-sensitive thin-film sensor, a multi-frame pressure image sequence is constructed in chronological order, where each frame image consists of the pressure values ​​of all pixels on the sensing film in a two-dimensional coordinate plane; Identify the main peak region of pressure data in each frame of a multi-frame pressure image sequence, and in each frame of consecutive frames... Within the main peak region, each pixel is traversed one by one, and a local neighborhood window centered on the pixel is constructed. The pressure change rate of each point in the window in the horizontal and vertical directions is extracted, that is, the pressure value changes along the horizontal and vertical directions respectively, and the local pressure flow direction vector of the pixel is constructed accordingly. Based on the pressure gradient direction vector of the same pixel in two adjacent frames, the angle of change of local pressure flow direction of each pixel between two adjacent frames is calculated based on the vector angle. By statistically summing the angle of flow direction change of pixels in the main peak region of each frame, the overall flow direction torsional energy value of the main peak region of the corresponding frame image can be obtained. The absolute difference of the overall flow direction torsional energy values ​​of two adjacent frames is used as the numerator, the sum of the overall flow direction torsional energy values ​​of two adjacent frames is used as the denominator, and the result of the numerator divided by the denominator is used as the energy evolution ratio. The nonlinear divergence factor is calculated based on three consecutive energy evolution ratios. The formula for calculation is as follows: In the formula, Indicates the first The nonlinear divergence factor of the frame; , , These are the energy evolution ratios of the previous frame, the current frame, and the next frame, respectively. Calculate the root mean square of all nonlinear divergence factors to obtain the local pressure flow direction uniformity perturbation value.

3. The digital recording method based on a voltage-sensitive thin film according to claim 1, characterized in that, The steps for calculating the intersection density value of the subframe decomposed trajectory lines are as follows: In a voltage-sensitive thin film, the set of trajectory points for consecutive frames is acquired, and the set of trajectory points is divided into multiple sub-frame segments; For each pair of adjacent subframes, the total number of their intersection points is calculated using the line segment intersection algorithm; For each pair of adjacent subframes, divide the total number of their intersection points by the total number of line segments in the two subframes to obtain the intersection ratio of the corresponding adjacent subframes. Calculate the root mean square of all intersection percentages and use it as the intersection density value of the subframe decomposed trajectory lines.

4. The digital recording method based on a voltage-sensitive thin film according to claim 1, characterized in that, The steps for determining whether there are trajectory anomalies in the current frame based on the outlier value obtained from the local pressure flow consistency disturbance value and the intersection density value of the subframe decomposed trajectory lines are as follows: The local pressure flow direction consistency perturbation value and the intersection density value of the subframe decomposition trajectory line are normalized. The normalized local pressure flow direction consistency perturbation value and the intersection density value of the subframe decomposition trajectory line are added together to obtain the outlier value. Compare the outlier with the preset threshold. If the outlier is less than the preset threshold, the trajectory point of the current frame is output as a valid trajectory point. If the abnormal value is not less than the preset threshold, then the current frame is determined to have a trajectory abnormality.

5. The digital recording method based on a voltage-force-sensing thin film according to claim 1, characterized in that, The steps for determining the corrected trajectory points for the current frame by combining the preset trajectory template library and outputting the corrected trajectory points as the trajectory points for the current frame are as follows: If there is a trajectory anomaly in the current frame, extract several historical trajectory points from before the current frame to form a historical trajectory point set. Perform subsequence matching between the historical trajectory point set and multiple templates in the preset trajectory template library, calculate the matching error, select the template with the smallest matching error, and determine the corrected trajectory point for the current frame based on the corresponding position of the template. Output the corrected trajectory point as the trajectory point for the current frame.

6. A digital recording system based on a voltage-force-sensing thin film, characterized in that, The system includes: Pressure flow direction module: acquires pressure data from multiple consecutive frames and calculates the local pressure flow direction consistency perturbation value, which is used to characterize the stability of the pressure flow direction in the main peak region over time. Line intersection module: Extracts the trajectory point set of continuous frames, constructs subframe decomposed trajectory lines, and calculates the proportion of intersection times between adjacent subframe trajectory lines to obtain the intersection density value of subframe decomposed trajectory lines, which is used to characterize the degree of spatial interlacing of trajectories in local areas; Analysis and comparison module: Based on the local pressure flow direction consistency disturbance value and the intersection density value of the subframe decomposed trajectory lines, anomaly values ​​are obtained, and the anomaly values ​​and preset thresholds are used to determine whether there is trajectory anomaly in the current frame; Correction and recording module: If the current frame has a trajectory abnormality, the corrected trajectory point of the current frame is determined by combining the preset trajectory template library, and the corrected trajectory point is output as the trajectory point of the current frame.

7. A digital recording system based on a voltage-force-sensing thin film according to claim 6, characterized in that, The pressure flow direction module includes: Sequence Module: Based on multiple frames of pressure data continuously acquired by a voltage-sensitive thin-film sensor, a multi-frame pressure image sequence is constructed in chronological order, where each frame consists of the pressure values ​​of all pixels on the sensing membrane in a two-dimensional coordinate plane; Gradient Direction Vector Module: Identifies the main peak region of pressure data in each frame of a multi-frame pressure image sequence, and in each frame of consecutive frames... Within the main peak region, each pixel is traversed one by one, and a local neighborhood window centered on the pixel is constructed. The pressure change rate of each point in the window in the horizontal and vertical directions is extracted, that is, the pressure value changes along the horizontal and vertical directions respectively, and the local pressure flow direction vector of the pixel is constructed accordingly. Local flow direction change angle module: Based on the pressure gradient direction vector of the same pixel in two adjacent frames, the local pressure flow direction change angle of each pixel between two adjacent frames is calculated based on the vector angle. Flow direction torsion energy value module: By statistically summing the flow direction change angle of the pixels in the main peak region of each frame, the overall flow direction torsion energy value of the main peak region of the corresponding frame image is obtained; Energy Evolution Ratio Module: The absolute difference of the overall flow direction torsional energy values ​​of two adjacent frames is used as the numerator, the sum of the overall flow direction torsional energy values ​​of two adjacent frames is used as the denominator, and the result of the numerator divided by the denominator is used as the energy evolution ratio. Divergence Factor Module: Calculates the nonlinear divergence factor based on three consecutive energy evolution ratios. The formula is as follows: In the formula, Indicates the first The nonlinear divergence factor of the frame; , , These are the energy evolution ratios of the previous frame, the current frame, and the next frame, respectively. Local pressure flow direction consistency perturbation module: Calculates the root mean square of all nonlinear divergence factors to obtain the local pressure flow direction consistency perturbation value.

8. A digital recording system based on a voltage-force-sensing thin film according to claim 6, characterized in that, The line intersection module includes: Subframe module: In the voltage force sensing film, acquire the set of trajectory points for consecutive frames and divide the set of trajectory points into multiple subframes; Intersection module: For each pair of adjacent subframe segments, the total number of their intersection points is calculated using the line segment intersection algorithm; Intersection ratio module: For each pair of adjacent subframes, divide the total number of their intersection points by the total number of line segments in the two subframes to obtain the intersection ratio of the corresponding adjacent subframes. Intersection Density Value Module: Calculates the root mean square of all intersection percentages as the intersection density value of the subframe decomposed trajectory lines.

9. A digital recording system based on a voltage-force-sensing thin film according to claim 6, characterized in that, The analysis and comparison module includes: Outlier Calculation Module: Normalizes the local pressure flow direction consistency disturbance value and the intersection density value of the subframe decomposition trajectory line, and adds the normalized local pressure flow direction consistency disturbance value to the intersection density value of the subframe decomposition trajectory line to obtain the outlier value; The first comparison module compares outliers with a preset threshold. If the outlier is less than the preset threshold, the current frame trajectory point is output as a valid trajectory point. The second comparison module: If the abnormal value is not less than the preset threshold, it is determined that there is a trajectory abnormality in the current frame.

10. A digital recording system based on a voltage-force-sensing thin film according to claim 6, characterized in that, The specific application of the correction recording module is as follows: If there is a trajectory anomaly in the current frame, extract several historical trajectory points from before the current frame to form a historical trajectory point set. Perform subsequence matching between the historical trajectory point set and multiple templates in the preset trajectory template library, calculate the matching error, select the template with the smallest matching error, and determine the corrected trajectory point for the current frame based on the corresponding position of the template. Output the corrected trajectory point as the trajectory point for the current frame.

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