Multi-dimensional signal mapping for precise control of plasma surgical electrodes and systems

Abstract

The embodiment of the application discloses a kind of multi-dimensional signal mapping's plasma surgical electrode precision control method and system, method includes: obtaining the multi-dimensional signal in the working process of plasma surgical electrode;Multi-dimensional signal is reconstructed to phase space, and the state vector sequence of the state of electrode work is obtained;State vector sequence is constructed based on joint recurrence graph;Joint recurrence graph is analyzed by joint recurrence quantization, and joint recurrence quantization index for representing the cooperative dynamics characteristics of multi-dimensional signal is extracted, and joint recurrence quantization index at least includes joint determinacy, joint laminar flow, joint recurrence rate and joint entropy;According to the corresponding relationship between joint recurrence quantization index and plasma energy output stability, control parameter of plasma generator is generated according to preset mapping rule, and the energy output of plasma surgical electrode is adjusted in real time according to control parameter.The application significantly improves control precision, reduces thermal damage and improves surgical safety.

Description

Technical Field

[0001] This application relates to the field of medical device technology, and in particular to a method and system for precise control of plasma surgical electrodes. Background Technology

[0002] Plasma surgical electrodes (such as low-temperature plasma blades) are widely used in minimally invasive surgeries in the ear, nose and throat, spine, joints, and urology fields. Their working principle is to use radio frequency energy to form a thin layer of plasma in a saline medium to cut, ablate, and stop bleeding in tissues, while maintaining a low temperature to reduce thermal damage to surrounding tissues.

[0003] Existing plasma surgery systems typically employ impedance feedback control, which monitors changes in tissue impedance and automatically reduces power or switches modes when the impedance rises to a certain threshold. This control method relies primarily on a single signal or simple multi-signal threshold judgment, and has the following shortcomings: insufficient exploration of the synergistic dynamic characteristics of multidimensional signals (impedance, voltage, current, temperature, etc.), failing to effectively capture the nonlinear coupling and synchronization behavior between signals; control strategies are mostly post-event threshold triggering, lacking the ability to predict plasma layer instability in the early stages, easily leading to excessive tissue carbonization or thermal diffusion; poor adaptability to individual differences among different patients and tissue types, resulting in insufficient control robustness.

[0004] Therefore, there is an urgent need for a new method that can comprehensively utilize the synergistic dynamic characteristics of multidimensional signals to achieve predictive and precise control. Summary of the Invention

[0005] This application provides a method and system for precise control of plasma surgical electrodes, enabling early sensing and preventive adjustment of plasma layer stability, thereby significantly improving control accuracy, reducing thermal damage, and enhancing surgical safety.

[0006] This application provides the following solution:

[0007] According to a first aspect, a method for precise control of a plasma surgical electrode based on multidimensional signal mapping is provided. The method includes: acquiring multidimensional signals during the operation of the plasma surgical electrode, wherein the multidimensional signals include at least two of impedance, voltage, current, and temperature; reconstructing the phase space of the multidimensional signals to obtain a state vector sequence characterizing the electrode's operating state; constructing a joint recursive graph based on the state vector sequence, wherein the element values ​​of the joint recursive graph depend on whether the state vectors at two different times are simultaneously close within a preset neighborhood radius; and performing joint recursive quantization analysis on the joint recursive graph to extract a joint recursive quantization index characterizing the cooperative dynamics of the multidimensional signals. It includes at least joint determinism, joint laminar flowability, joint recursion rate, and joint entropy; based on the correspondence between the joint recursion quantification index and the stability of plasma energy output, control parameters of the plasma generator are generated according to a preset mapping rule, and the energy output of the plasma surgical electrode is adjusted in real time according to the control parameters. The control parameters include at least one of output power, pulse frequency, and duty cycle. The preset mapping rule includes: reducing the output power when both joint determinism and joint laminar flowability decrease relative to the historical stable interval; and switching to a control mode that limits the rate of change of energy output when the joint recursion rate is higher than the upper quantile threshold of the statistical distribution within the corresponding time window and the joint entropy is lower than the lower entropy threshold.

[0008] According to one achievable method in the embodiments of this application, the phase space reconstruction includes: normalizing the multidimensional signal and constructing a state vector sequence using a delayed coordinate embedding method, with an embedding dimension of 3 to 10, and the delay parameter being determined according to the mutual information minimum criterion or the false nearest neighbor criterion.

[0009] According to one achievable method in the embodiments of this application, the preset neighborhood radius is adaptively adjusted based on the average distance, standard deviation, or combination thereof of the state vector sequence within the current time window.

[0010] According to one achievable method in the embodiments of this application, the historical stable interval is established by multidimensional signals in the initial stage of surgery or the offline calibration stage, and is switched according to changes in tissue type during surgery or updated online by means of a sliding time window.

[0011] According to one achievable method in an embodiment of this application, the control mode for limiting the rate of change of energy output includes: limiting the rate of change of at least one control parameter of the plasma generator to within a preset upper limit value, wherein the upper limit value is dynamically determined based on the degree of deviation of the current joint recursion rate and joint entropy from the corresponding reference value.

[0012] According to one achievable method in the embodiments of this application, the joint recursive quantization index further includes a joint trap time, which is used to characterize the average duration of multidimensional signals entering the laminar flow state in tandem; the preset mapping rule further includes: when the joint trap time is extended by more than a preset proportion relative to the initial calibration value of the surgery, the pulse frequency is gradually increased to actively break the excessive laminar flow state.

[0013] According to one achievable method in an embodiment of this application, after generating the control parameters, the method further includes: performing time-domain smoothing on the control parameters, wherein the time-domain smoothing includes performing a weighted average or a first-order low-pass filter on the control parameters in adjacent control cycles; during the smoothing process, setting a limiting constraint on the change amplitude of the control parameters so that the change amount of the control parameters in adjacent control cycles does not exceed a preset change threshold.

[0014] According to a second aspect, a precision control system for a plasma surgical electrode based on multidimensional signal mapping is provided. The system includes: a multidimensional signal acquisition unit configured to acquire multidimensional signals during the operation of the plasma surgical electrode, wherein the multidimensional signals include at least two of impedance, voltage, current, and temperature; a phase space reconstruction unit configured to perform phase space reconstruction on the multidimensional signals to obtain a state vector sequence characterizing the electrode's operating state; a joint recursion graph construction unit configured to construct a joint recursion graph based on the state vector sequence, wherein the element values ​​of the joint recursion graph depend on whether the state vectors at two different times are simultaneously close within a preset neighborhood radius; and a joint recursive quantization analysis unit configured to perform joint recursive quantization analysis on the joint recursion graph to extract characteristics representing the cooperative dynamics of the multidimensional signals. The joint recursive quantization index includes at least joint determinism, joint laminar flowability, joint recursion rate, and joint entropy. The electrode energy output adjustment unit is configured to generate control parameters for the plasma generator according to a preset mapping rule based on the correspondence between the joint recursive quantization index and the stability of the plasma energy output, and to adjust the energy output of the plasma surgical electrode in real time according to the control parameters. The control parameters include at least one of output power, pulse frequency, and duty cycle. The preset mapping rule includes: reducing the output power when both joint determinism and joint laminar flowability decrease relative to the historical stable interval; and switching to a control mode that limits the rate of change of energy output when the joint recursion rate is higher than the upper quantile threshold of the statistical distribution within the corresponding time window and the joint entropy is lower than the lower entropy threshold.

[0015] According to a third aspect, a computer-readable storage medium is provided having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described in any one of the first aspects above.

[0016] According to a fourth aspect, an electronic device is provided, comprising: one or more processors; and a memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method described in any one of the first aspects.

[0017] According to the specific embodiments provided in this application, the following technical effects are disclosed:

[0018] This application introduces joint recursion graphs and joint recursive quantization analysis to reconstruct the phase space and characterize the co-dynamics of multidimensional signals during the operation of plasma surgical electrodes. It extracts indices such as joint determinism, joint laminarity, joint recursion rate, and joint entropy, achieving precise capture of the overall synchronization, regularity, laminar-turbulent transition, and complexity changes of multidimensional signals. Based on the correspondence between these indices and the stability of plasma energy output, a pre-defined mapping rule combining multiple indices is designed: when both joint determinism and joint laminarity decrease simultaneously, the output power is reduced promptly to prevent plasma layer instability; when the joint recursion rate is too high and the joint entropy is too low, a conservative mode limiting the rate of energy change is switched to avoid excessive tissue carbonization. This method significantly improves the early prediction capability and control robustness of plasma layer dynamics, is more sensitive and timely than traditional single impedance threshold feedback, effectively reduces thermal damage volume, sharpens ablation boundaries, and improves surgical precision and safety, making it particularly suitable for minimally invasive surgical scenarios sensitive to thermal damage.

[0019] Of course, any product implementing this application does not necessarily need to achieve all of the advantages described above at the same time. Attached Figure Description

[0020] To more clearly illustrate the technical solutions in the embodiments of this application or the prior art, the drawings used in the embodiments 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.

[0021] Figure 1 A flowchart of a method for precise control of a plasma surgical electrode using multidimensional signal mapping, provided in an embodiment of this application;

[0022] Figure 2 A structural block diagram of the plasma surgical electrode precision control system with multidimensional signal mapping provided in the embodiments of this application;

[0023] Figure 3 A schematic block diagram of an electronic device provided in an embodiment of this application. Detailed Implementation

[0024] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of this application, and not all embodiments. All other embodiments obtained by those skilled in the art based on the embodiments of this application are within the scope of protection of this application.

[0025] The terminology used in the embodiments of this invention is for the purpose of describing particular embodiments only and is not intended to limit the invention. The singular forms “a,” “the,” and “the” as used in the embodiments of this invention and the appended claims are also intended to include the plural forms unless the context clearly indicates otherwise.

[0026] It should be understood that the term "and / or" used in this article is merely a description of the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A existing alone, A and B existing simultaneously, and B existing alone. Additionally, the character " / " in this article generally indicates that the preceding and following related objects have an "or" relationship.

[0027] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0028] Figure 1 A flowchart illustrating the precise control method for a plasma surgical electrode using multidimensional signal mapping, as provided in this application embodiment. Figure 1 As shown, the method may include the following steps:

[0029] Step 101: Acquire multidimensional signals during the operation of the plasma surgical electrode, wherein the multidimensional signals include at least two of impedance, voltage, current and temperature.

[0030] Step 102: Perform phase space reconstruction on the multidimensional signal to obtain a state vector sequence characterizing the working state of the electrode.

[0031] Step 103: Construct a joint recursive graph based on the state vector sequence. The element values ​​of the joint recursive graph depend on whether the state vectors at two different times are simultaneously close within a preset neighborhood radius.

[0032] Step 104: Perform joint recursive quantization analysis on the joint recursive graph to extract joint recursive quantization indices for characterizing the cooperative dynamics of multidimensional signals. The joint recursive quantization indices include joint determinism, joint laminarity, joint recursion rate, and joint entropy.

[0033] Step 105: Based on the correspondence between the joint recursive quantization index and the stability of plasma energy output, generate control parameters for the plasma generator according to a preset mapping rule, and adjust the energy output of the plasma surgical electrode in real time. The control parameters include at least one of output power, pulse frequency, and duty cycle. The preset mapping rule includes: reducing the output power when the joint determinism and joint laminarity decrease simultaneously relative to the historical stable interval; and switching to a control mode that limits the rate of change of energy output when the joint recursion rate is higher than the upper quantile threshold of the statistical distribution within the corresponding time window and the joint entropy is lower than the lower entropy threshold.

[0034] As can be seen from the above process, this application, by introducing joint recursion graphs and joint recursive quantification analysis, performs phase space reconstruction and co-dynamic characterization of multidimensional signals during the operation of plasma surgical electrodes, extracting indicators such as joint determinism, joint laminarity, joint recursion rate, and joint entropy. This achieves precise capture of the overall synchronization, regularity, laminar-turbulent transition, and complexity changes of multidimensional signals. Based on the correspondence between these indicators and the stability of plasma energy output, a preset mapping rule for multi-indicator combinations is designed: when joint determinism and joint laminarity decrease simultaneously, the output power is reduced in a timely manner to prevent plasma layer instability; when the joint recursion rate is too high and the joint entropy is too low, a conservative mode that limits the rate of energy change is switched to avoid excessive tissue carbonization. This method significantly improves the early prediction capability and control robustness of plasma layer dynamics, is more sensitive and timely than traditional single impedance threshold feedback, can effectively reduce thermal damage volume, sharpen ablation boundaries, and improve surgical precision and safety, and is particularly suitable for minimally invasive surgical scenarios sensitive to thermal damage.

[0035] The following describes in detail each step of the above process and the effects that can be further produced, with reference to the embodiments. First, step 101, namely "acquiring multidimensional signals during the operation of the plasma surgical electrode, wherein the multidimensional signals include at least two of impedance, voltage, current and temperature", will be described in detail with reference to the embodiments.

[0036] This application acquires multidimensional signals generated by the plasma surgical electrode during surgery in real time. These signals directly reflect the physical state and energy transfer during the interaction between the electrode and tissue, forming the basis for subsequent precise control. Specific sources of the multidimensional signals include parameters such as impedance, voltage, current, and temperature; at least two of these parameters must be acquired to ensure a comprehensive characterization of the dynamic behavior of the plasma layer from multiple dimensions.

[0037] Impedance signals are typically obtained by measuring the resistance of the tissue to the radiofrequency current at both ends of the electrode. The impedance increases significantly when the tissue is ablated or dried, making it the most commonly used indicator reflecting changes in tissue state. Voltage and current signals correspond to the instantaneous voltage applied to the electrode by the radiofrequency generator and the actual current flowing through the tissue, respectively. Together, they determine the instantaneous power level and can sensitively capture fluctuations during the formation and maintenance of the plasma layer. Temperature signals are acquired either by integrating them near the electrode or through infrared thermography, directly indicating the thermal state of the tissue surface or plasma layer, thus preventing damage to surrounding tissues caused by excessive heat accumulation.

[0038] The requirement to acquire at least two types of signals stems from the fact that a single signal often reflects only one aspect of the system's state, while multidimensional signals provide richer, more comprehensive information. For example, relying solely on impedance may overlook the independent rise in temperature, while combining voltage and current can detect power distribution anomalies earlier. By simultaneously acquiring multiple signals, this invention lays a solid data foundation for subsequent phase space reconstruction and joint recursive analysis, thereby enabling a more comprehensive and in-depth understanding and control of the dynamics of plasma surgery procedures.

[0039] The following describes in detail step 102, namely "reconstructing the phase space of the multidimensional signal to obtain a state vector sequence characterizing the working state of the electrode," with reference to the embodiments.

[0040] Phase space reconstruction is based on Takens' embedding theorem. Its fundamental principle is to extend the observed values ​​of a multidimensional signal into multiple dimensions using time-delay coordinates, forming a series of state vectors. Each state vector is composed of the values ​​of the same signal at different delay times or the concurrent values ​​of other signal channels, thus reproducing the geometric structure of the system trajectory in a high-dimensional space. As time progresses, the continuously sampled state vectors are sequentially connected to form a state vector sequence. This state vector sequence is the core output of the phase space reconstruction step in this invention. It is a sequence formed by transforming the original multidimensional signal into a series of ordered vectors in a high-dimensional phase space, with each vector representing the complete working state of the plasma surgical electrode at a specific moment. This sequence depicts a continuous trajectory in phase space, and the geometry and evolution of the trajectory reflect the intrinsic dynamic processes of plasma layer formation, stable maintenance, and potential instability. This reconstruction can reveal seemingly random signal fluctuations as deterministic low-dimensional attractors, characterizing the dynamic evolution process of plasma layer formation, maintenance, and instability.

[0041] As an implementable approach, the phase space reconstruction of this application includes: normalizing the multidimensional signal and constructing a state vector sequence using a delayed coordinate embedding method, with an embedding dimension of 3 to 10, and the delay parameter being determined according to the mutual information minimum criterion or the false nearest neighbor criterion.

[0042] Specifically, normalization of multidimensional signals is a necessary preprocessing step. Because signals such as impedance, voltage, current, and temperature vary greatly in dimensions and amplitude range, directly using them for phase space reconstruction can easily lead to certain dimensions dominating distance calculations and masking the contributions of other signals. Normalization typically employs zero mean and unit variance methods, or maps to a uniform interval, ensuring a relatively balanced contribution of each signal channel to the state vector distance, thereby improving the accuracy and reliability of joint recursive analysis.

[0043] Subsequently, constructing a state vector sequence using a delayed coordinate embedding method is the core approach for phase space reconstruction. This method does not require knowledge of all system variables; it only utilizes the observed multidimensional signals to expand the dimensions through delayed replication. Specifically, each state vector is composed of the values ​​of multiple signals at the current moment and several delayed moments, forming a high-dimensional vector sequence. This embedding method can effectively reproduce the topological structure of the attractors in the original system, providing a geometric basis for subsequently determining the proximity relationships between state vectors.

[0044] The embedding dimension is limited to a range of 3 to 10, determined based on the complexity of actual plasma surgical signals. Too low a dimension fails to fully expand the attractor, leading to spurious crossovers; too high a dimension increases computational burden and introduces redundant noise. Practice shows that an embedding dimension of 3 to 10 is sufficient to capture the main characteristics of plasma layer dynamics while maintaining the feasibility of real-time computation.

[0045] The delay parameter is determined using either the minimum mutual information criterion or the false nearest neighbor criterion. The minimum mutual information criterion calculates the mutual information between the signal and its delayed version, selecting the delay corresponding to the first minimum value as the optimal parameter to ensure statistical independence between embedded coordinates. The false nearest neighbor criterion, on the other hand, verifies the delay selection by observing the decrease in the proportion of false neighbors in the trajectory as the embedding dimension increases. The arbitrary selection or combination of these two criteria allows the delay parameter to adapt to the signal characteristics under different surgical scenarios, further improving the quality and robustness of phase space reconstruction.

[0046] In the operation of plasma surgical electrodes, multidimensional signals often exhibit strong nonlinear and non-stationary characteristics. Traditional time-domain or frequency-domain analysis is insufficient to fully describe the complex coupling relationships between signals, while phase space reconstruction provides a unified geometric framework, enabling the state vector sequence to intuitively reflect the overall dynamic behavior of the interaction between the electrode and tissue. For example, when the plasma layer is stable, the state vector trajectory tends to be a regular finite region; when the tissue begins to carbonize or dry, the trajectory may show an expanding or chaotic trend.

[0047] The following describes in detail step 103, namely, "constructing a joint recursive graph based on the state vector sequence, wherein the element values ​​of the joint recursive graph depend on whether the state vectors at two different times are simultaneously close within a preset neighborhood radius", with reference to the embodiments.

[0048] Joint Recurrence Quantification Analysis (JRQA) is an advanced nonlinear time series analysis method based on Joint Recurrence Plot (JRP) to study the cooperative dynamics among multiple variables (multidimensional signals).

[0049] A joint recursive graph is essentially a square matrix, with rows and columns corresponding to different time points in the state vector sequence. Each element in the matrix indicates whether the state vectors at two specific times are "recursive," i.e., whether they are sufficiently close. If the state vectors at two times are simultaneously close within a preset neighborhood radius, the element has a value of 1, indicating that the system states at these two times are highly similar; otherwise, it has a value of 0, indicating that the states are significantly different. This binary matrix forms a black-and-white dot matrix, where dense black dots represent regions in phase space where the system repeatedly returns to similar states.

[0050] When constructing a joint recursive graph, a preset neighborhood radius is a key threshold for determining whether two state vectors are "simultaneously close." The criterion for "simultaneous closeness" is that the state vector components of all signal channels must collectively satisfy a distance threshold condition. Specifically, for two state vectors... and If their Euclidean distance in high-dimensional phase space is less than a preset neighborhood radius, and this proximity relationship holds true for every signal channel, then they are considered to be simultaneously close. This requirement ensures that the joint recurrence graph not only captures the recurrence patterns of individual signals, but also emphasizes the synchronization and coupling consistency between multi-dimensional signal channels, which is impossible to achieve with traditional single-signal recurrence analysis.

[0051] As an implementable approach, this application pre-sets the neighborhood radius to be adaptively adjusted based on the average distance, standard deviation, or combination thereof of the state vector sequence within the current time window.

[0052] Specifically, the average distance between all pairwise state vectors within a time window can be calculated as a benchmark for the overall dispersion of the signal; simultaneously, the standard deviation is calculated to reflect the dispersion of signal fluctuations. Adjustment strategies can involve taking a multiple of the average distance, or combining it with a weighted combination of standard deviations. For example, the radius can be equal to the average distance plus k times the standard deviation, where k is an empirical coefficient. This combination automatically adapts to changes in signal scale: when the signal amplitude is large and fluctuations are severe, the radius increases accordingly to maintain a reasonable recursion density; when the signal tends to stabilize and fluctuations decrease, the radius decreases accordingly to improve sensitivity to subtle changes.

[0053] In the application of plasma surgical electrodes, the construction of a joint recurrence graph can intuitively reflect the stability of the plasma layer. When the plasma layer is maintained normally, a distinct diagonal structure and blocky recurrence regions appear in the graph, indicating that the system state repeatedly cycles around the stable attractor over time. When tissue dries or carbonizes, the recurrence points may become sparse or broken, indicating a shift in the dynamic mode from laminar to turbulent flow. Through this characteristic, the joint recurrence graph provides a geometric basis for subsequent quantitative analysis, enabling the control system to sensitively perceive the overall coordinated changes in multidimensional signals, thereby achieving earlier and more precise energy output regulation.

[0054] The following describes in detail step 104, namely, "performing joint recursive quantization analysis on the joint recursive graph and extracting joint recursive quantization indices to characterize the cooperative dynamics of multidimensional signals, wherein the joint recursive quantization indices include joint determinism, joint laminarity, joint recursion rate, and joint entropy," with reference to an embodiment.

[0055] Joint recursive quantization analysis starts with the structural characteristics of the joint recursion graph, focusing primarily on the distribution patterns of diagonals, vertical lines, and overall recursion points. The joint recursion rate is the most fundamental indicator; it calculates the proportion of recursion points to the entire matrix, directly reflecting the frequency and intensity of multidimensional signal channels repeatedly returning to similar states in phase space. A high joint recursion rate indicates that the system as a whole is in a highly synchronized and stable cooperative dynamic, while a low value may predict instability or decoupling trends in the plasma layer.

[0056] Joint determinism focuses on diagonal structures, statistically analyzing the proportion of diagonal segments exceeding a certain threshold in the total length of all recursive points. This metric quantifies the regularity and predictability of multidimensional signal coordination patterns. Long, continuous diagonals correspond to a system maintaining similar dynamic evolution paths over a period of time; in plasma surgery, this typically indicates stable plasma layer maintenance. Short diagonals or breaks suggest transient interruptions in signal coupling, potentially related to tissue drying or energy fluctuations.

[0057] Joint laminarity focuses on the vertical and horizontal line structures, calculating the average length or proportion of these line segments to characterize the transition state between laminar and turbulent flows in conjunction with multidimensional signals. High joint laminarity indicates that the system remains in a similar state in phase space for a long time, i.e., the plasma layer exhibits stable laminar characteristics; when this index decreases, it indicates that the system begins to transition to turbulence or instability, which may foreshadow an increased risk of thermal damage.

[0058] Joint entropy is calculated based on the probability distribution of the diagonal length, measuring the complexity and diversity of multidimensional signal cooperative patterns. High joint entropy corresponds to rich and unpredictable signal cooperative behavior, indicating that the plasma layer is in dynamic equilibrium; low joint entropy indicates that the patterns tend to be singular and ordered, often associated with over-synchronization or carbonization states.

[0059] By extracting these joint recursive quantization indices, this invention achieves a comprehensive quantitative characterization of the cooperative dynamics of multidimensional signals. Compared to traditional single-signal analysis, these indices can more sensitively capture the implicit coupling and overall evolution laws between signal channels, providing a solid scientific foundation for designing predictive control rules.

[0060] Preferably, the joint recursive quantization index of this application further includes a joint trap time, which characterizes the average duration of multidimensional signals co-entering the laminar flow state. The joint trap time is essentially the average length of all vertical or horizontal line segments in the joint recursive graph. These line segments represent the system remaining near similar state vectors at multiple consecutive moments in phase space, meaning that the multidimensional signal channels collectively exhibit highly consistent laminar flow behavior. In calculation, all vertical or horizontal lines with lengths exceeding a certain minimum threshold are first identified, and then their average value is calculated to obtain the joint trap time. This index reflects how long the plasma layer can maintain a stable state without significant disturbances or transitions; a larger value indicates a more persistent laminar flow state and a more stable system.

[0061] The following describes in detail step 105, namely, "Based on the correspondence between the joint recursive quantization index and the stability of plasma energy output, generate control parameters for the plasma generator according to a preset mapping rule, and adjust the energy output of the plasma surgical electrode in real time. The control parameters include at least one of output power, pulse frequency, and duty cycle. The preset mapping rule includes: reducing output power when joint determinism and joint laminarity decrease simultaneously relative to the historical stable interval; and switching to a control mode that limits the rate of change of energy output when the joint recursion rate is higher than the upper quantile threshold of the statistical distribution within the corresponding time window and the joint entropy is lower than the lower entropy threshold."

[0062] There is a clear physical correspondence between joint recursive quantification indices and plasma energy output stability: joint determinism reflects the regularity and predictability of multidimensional signal coordination patterns, with high values ​​indicating that the plasma layer maintains a stable trajectory; joint laminarity characterizes the tendency of signal channels to remain in similar states for extended periods, with high values ​​corresponding to a laminar stability phase; joint recursion rate measures the overall degree of synchronization, with high values ​​indicating a high degree of system consistency; and joint entropy reflects the complexity of the coordination patterns, with high values ​​indicating dynamic equilibrium and low values ​​suggesting a single pattern or excessive synchronization. Changes in the combination of these indices can sensitively predict the transition of the plasma layer from stability to instability. For example, excessively high synchronization and decreased complexity often correspond to the risk of tissue drying or carbonization, while a simultaneous decrease in regularity and laminarity predicts a transition from laminar to turbulent flow.

[0063] The preset mapping rules are an engineering design based on the above correspondence, encompassing control strategies for at least two typical scenarios. The first rule addresses situations where both joint determinism and joint laminarity decrease relative to the historical stable range. In this case, laminar flow interruption or regular decay occurs, indicating that the plasma layer is about to become unstable. To prevent the spread of thermal damage, the system immediately reduces its output power, typically by 15% to 30%, to quickly restore a stable state. This preventative power reduction mechanism intervenes earlier than traditional post-event threshold responses, significantly reducing thermal diffusion.

[0064] The historical stable interval can be established using multidimensional signals from the initial surgical phase or the offline calibration phase, and can be switched during the surgery based on changes in tissue type or updated online via a sliding time window. Specifically, the historical stable interval refers to a set of reference ranges defined during the surgery to determine whether the current joint recursive quantitative indicators deviate from the normal state. It can be established in two ways: the first is real-time acquisition during the initial surgical phase, i.e., in the first few minutes after the surgery begins and the electrode has just contacted the target tissue and entered a stable ablation state, continuously acquiring multidimensional signals and calculating the statistical distribution of the joint recursive quantitative indicators, for example, taking the mean plus or minus the standard deviation as the upper and lower limits to form the initial stable interval; the second is the offline calibration phase, i.e., using in vitro models or animal experimental data of the same or similar tissues to pre-calculate the standard interval before the surgery, and directly loading it at the start of the surgery. This dual establishment method takes into account both real-time performance and versatility.

[0065] The second rule addresses situations where the joint recursion rate exceeds the upper quantile threshold of the statistical distribution within the corresponding time window and the joint entropy is below the lower entropy threshold. In this case, the multidimensional signals enter a state of over-synchronization and low complexity, often corresponding to excessively dry tissue surfaces and insufficient plasma generation. To prevent further deterioration leading to a decrease in carbonization or ablation efficiency, the system switches to a control mode that limits the rate of change in energy output. In this mode, the adjustment speed of power, pulse frequency, or duty cycle is strictly limited to prevent abrupt impacts on the tissue, while allowing for slow recovery to ensure gradual changes in energy output.

[0066] Specifically, the control mode for limiting the rate of change of energy output in this application includes limiting the rate of change of at least one control parameter of the plasma generator to within a preset upper limit value, wherein the upper limit value is dynamically determined based on the degree of deviation of the current joint recursion rate and joint entropy from the corresponding reference value.

[0067] In this control mode, the system strictly limits the rate of change of at least one control parameter of the plasma generator (such as output power, pulse frequency, or duty cycle) to a preset upper limit. For example, if the current output power is 50 watts, the power adjustment in the next cycle will be limited to a rate of no more than 5 watts per second. This rate-limiting design prevents rapid power spikes or drops caused by drastic fluctuations in a single parameter, thereby avoiding shock-induced thermal damage to tissue or instantaneous collapse of the plasma layer.

[0068] The key innovation of this feature lies in the dynamic determination of the upper limit. It is not a fixed constant, but rather calculated in real-time based on the deviation of the current joint recursion rate and joint entropy from the corresponding baseline values. The baseline values ​​are typically derived from historical stable intervals or the statistical mean of the initial calibration phase during surgery. When the joint recursion rate is significantly higher than the baseline value and the joint entropy is lower, it indicates that the multidimensional signals have entered a state of over-synchronization and low complexity, meaning the tissue may be on the verge of drying or carbonization. In this case, the greater the deviation, the smaller the upper limit value; for example, the upper limit of the rate of change is dynamically reduced from the normal 10 watts / second to 2 watts / second. This adaptive adjustment mechanism makes the control mode more conservative when the risk is higher, ensuring that energy output changes slowly enough to allow the system time to recover stability through subsequent feedback.

[0069] By dynamically limiting the rate of change, this mode achieves preventative protection: in traditional control methods, power may jump instantaneously due to a single threshold trigger, leading to localized overheating; this feature, however, uses the deviation of a joint recursive quantification index as the triggering and adjustment basis, making the rate limiting rule more intelligent and targeted. At the same time, this mode does not completely disable adjustments, but allows for gradual changes, balancing surgical efficiency and safety, making it particularly suitable for surgical scenarios involving heat-sensitive tissues (such as those near nerves and blood vessels).

[0070] The control parameters generated by the above mapping rules include at least one of output power, pulse frequency, and duty cycle, and are applied to the plasma generator in real time to achieve dynamic adjustment of energy output. The innovation of this feature lies in transforming complex nonlinear dynamic indicators into operable control rules, realizing a closed-loop control that combines predictive, preventative, and conservative approaches. This far exceeds the limitations of traditional single impedance feedback, ultimately improving the precision, safety, and adaptability to different tissue types in plasma surgery.

[0071] As an implementable approach, the preset mapping rule of this application also includes: when the combined trap time is extended by more than a preset ratio relative to the initial calibration value of the surgery, the pulse frequency is gradually increased to actively break the excessive laminar flow state.

[0072] The combined trapping time characterizes the average duration of multidimensional signals co-entering the laminar flow state, reflecting the ability of the plasma layer to maintain a similar state in phase space for an extended period. During the initial calibration phase of the procedure, a baseline value is typically calculated using data from several minutes of stable ablation, for example, an average laminar flow duration of 0.5 seconds. If the combined trapping time during the procedure extends by more than a predetermined percentage, such as 150% or 200%, i.e., the duration significantly increases to more than 1 second, it indicates that the multidimensional signal channels are collectively in an overly stable laminar flow mode. In this case, the plasma layer may be too "calm," lacking necessary micro-perturbations, leading to excessive tissue surface drying and insufficient plasma generation, thereby reducing the cutting or ablation rate and even affecting the surgical outcome.

[0073] To address this situation, this feature introduces an active adjustment mechanism: the system gradually increases the pulse frequency, for example, starting from the reference frequency and increasing it by 5% to 10% per control cycle until the combined trap time returns to the normal range. This gradual increase avoids tissue shock caused by abrupt changes, while introducing moderate perturbation by increasing the pulse frequency disrupts the continuity of excessive laminar flow, promoting the recovery of multidimensional signals from a single stable mode to dynamic equilibrium. The increased pulse frequency enhances the reionization capability of the plasma layer, helping the tissue surface to regenerate sufficient plasma, thereby restoring the normal ablation rate.

[0074] Preferably, after generating the control parameters, the method further includes: performing time-domain smoothing on the control parameters, wherein the time-domain smoothing includes performing a weighted average or a first-order low-pass filter on the control parameters in adjacent control cycles; during the smoothing process, a limiting constraint is set on the change amplitude of the control parameters so that the change amount of the control parameters in adjacent control cycles does not exceed a preset change threshold.

[0075] Time-domain smoothing is the core operation of this feature, mainly achieved through two methods: First, weighted averaging, which involves summing the control parameters generated in the current control cycle and the previous few cycles with weights, where recent parameters have higher weights and distant parameters have lower weights, resulting in a smoothed output value; second, using a first-order low-pass filter, which treats the control parameters as signals and removes high-frequency abrupt changes using a low-pass filter (such as an equivalent RC filter with a suitable cutoff frequency), while preserving the low-frequency stable trend. Both methods can effectively suppress instantaneous jumps in control parameters, making the energy output exhibit a continuous and gradual change characteristic, avoiding the thermal shock to tissues caused by sudden increases or decreases in power or pulse frequency.

[0076] During the smoothing process, a limiting constraint is introduced to further enhance safety. Specifically, preset threshold values ​​are set for the changes in control parameters between two adjacent control cycles, such as power changes not exceeding 10 watts, pulse frequency changes not exceeding 20 Hz, or duty cycle changes not exceeding 5%. If the parameter changes calculated during smoothing exceed these thresholds, the changes are forcibly truncated to the upper or lower limit of the threshold to ensure that the adjustment range remains within a safe range. This limiting mechanism is similar to rate saturation protection in engineering control, preventing drastic fluctuations caused by extreme conditions (such as noise interference or brief signal anomalies).

[0077] The innovation of this embodiment lies in combining temporal smoothing with amplitude limiting constraints to form a dual protection mechanism: smoothing eliminates high-frequency noise and abrupt changes, while amplitude limiting forces a restriction on the rate of change in amplitude, thereby maximizing the protection of sensitive tissues without sacrificing response speed. This post-processing step is particularly important in plasma surgery scenarios because tissues are extremely sensitive to energy changes; any abrupt change can trigger local overheating or plasma layer collapse. Through this embodiment, the control parameters achieve a highly smooth transition from initial calculation to actual application, ultimately enabling precise, stable, and safe adjustment of energy output, significantly reducing the risk of surgical complications.

[0078] The methods provided in this application can be applied to various scenarios, including but not limited to: First, in otolaryngological surgeries, such as endoscopic low-temperature plasma ablation for chronic sinusitis, this method precisely controls energy output by real-time monitoring of multidimensional signal synergistic dynamics, avoiding excessive thermal damage to the nasal mucosa and nerve structures, and reducing postoperative bleeding and scar formation. Second, in spinal surgery for intervertebral disc nucleolysis, this method can detect early signs of tissue drying or carbonization, dynamically adjust pulse frequency and power, maintain a stable plasma layer, improve ablation efficiency, reduce the risk of nerve root thermal damage, and significantly improve postoperative pain relief. Third, in arthroscopic cartilage repair surgery, this method, combined with predictive control using recursive quantitative indicators, achieves precise ablation and hemostasis of articular cartilage, reduces heat diffusion within the joint cavity, and ensures better postoperative joint function recovery.

[0079] The foregoing has described specific embodiments of this specification. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in a different order than that shown in the embodiments and may still achieve the desired result. Furthermore, the processes depicted in the drawings do not necessarily require the specific or sequential order shown to achieve the desired result. In some embodiments, multitasking and parallel processing are possible or may be advantageous.

[0080] According to another embodiment, a multidimensional signal mapping plasma surgical electrode precision control system is provided. Figure 2 A schematic block diagram of a multidimensional signal mapping plasma surgical electrode precision control system according to one embodiment is shown. Figure 2 As shown, the system 200 includes:

[0081] The multidimensional signal acquisition unit 201 is configured to acquire multidimensional signals during the operation of the plasma surgical electrode, wherein the multidimensional signals include at least two of impedance, voltage, current and temperature.

[0082] The phase space reconstruction unit 202 is configured to perform phase space reconstruction on the multidimensional signal to obtain a state vector sequence characterizing the working state of the electrode.

[0083] The joint recursive graph construction unit 203 is configured to construct a joint recursive graph based on the state vector sequence, wherein the element values ​​of the joint recursive graph depend on whether the state vectors at two different times are simultaneously close within a preset neighborhood radius.

[0084] The joint recursive quantization analysis unit 204 is configured to perform joint recursive quantization analysis on the joint recursive graph and extract joint recursive quantization indices for characterizing the cooperative dynamics of multidimensional signals. The joint recursive quantization indices include at least joint determinism, joint laminarity, joint recursion rate, and joint entropy.

[0085] The electrode energy output adjustment unit 205 is configured to generate control parameters for the plasma generator according to a preset mapping rule based on the correspondence between the joint recursive quantization index and the stability of the plasma energy output, and to adjust the energy output of the plasma surgical electrode in real time according to the control parameters. The control parameters include at least one of output power, pulse frequency, and duty cycle. The preset mapping rule includes: reducing the output power when the joint determinism and joint laminarity decrease simultaneously relative to the historical stable interval; and switching to a control mode that limits the rate of change of energy output when the joint recursion rate is higher than the upper quantile threshold of the statistical distribution within the corresponding time window and the joint entropy is lower than the lower entropy threshold.

[0086] As an implementable approach, the phase space reconstruction unit 202 can be configured such that phase space reconstruction includes: normalizing the multidimensional signal and constructing a state vector sequence using a delayed coordinate embedding method, with an embedding dimension of 3 to 10, and the delay parameter being determined according to the mutual information minimum criterion or the false nearest neighbor criterion.

[0087] As an feasible approach, the preset neighborhood radius of the joint recursive graph construction unit 203 is adaptively adjusted based on the average distance, standard deviation, or combination thereof of the state vector sequence within the current time window.

[0088] As an feasible approach, the historical stable range of the electrode energy output adjustment unit 205 is established through multidimensional signals during the initial stage of surgery or the offline calibration stage, and is switched according to changes in tissue type during surgery or updated online through a sliding time window.

[0089] As one feasible approach, the control mode of limiting the rate of change of energy output of the electrode energy output regulating unit 205 includes limiting the rate of change of at least one control parameter of the plasma generator to within a preset upper limit value, which is dynamically determined based on the degree of deviation of the current joint recursion rate and joint entropy from the corresponding reference value.

[0090] As an implementable approach, the joint recursive quantization index of the joint recursive quantization analysis unit 204 also includes a joint trap time, which is used to characterize the average duration of multidimensional signals entering the laminar flow state in tandem; the preset mapping rule of the electrode energy output adjustment unit 205 also includes: when the joint trap time is extended by more than a preset ratio relative to the initial calibration value of the surgery, the pulse frequency is gradually increased to actively break the excessive laminar flow state.

[0091] As an implementable approach, after generating the control parameters, the electrode energy output adjustment unit 205 can also be configured to: perform time-domain smoothing on the control parameters, wherein the time-domain smoothing includes weighted averaging or first-order low-pass filtering on the control parameters in adjacent control cycles; and during the smoothing process, setting a limiting constraint on the change amplitude of the control parameters so that the change amount of the control parameters in adjacent control cycles does not exceed a preset change threshold.

[0092] The various embodiments in this specification are described in a progressive manner. Similar or identical parts between embodiments can be referred to mutually. Each embodiment focuses on its differences from other embodiments. In particular, the system embodiments are basically similar to the method embodiments, so the description is relatively simple; relevant parts can be referred to the descriptions in the method embodiments. The system embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. Components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without creative effort.

[0093] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, data stored, data displayed, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties. Furthermore, the collection, use and processing of the relevant data must comply with the relevant laws, regulations and standards of the relevant countries and regions, and corresponding operation entry points are provided for users to choose to authorize or refuse.

[0094] In addition, embodiments of this application also provide a computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the steps of the method described in any of the foregoing method embodiments.

[0095] And an electronic device comprising: one or more processors; and a memory associated with the one or more processors, the memory being used to store program instructions that, when read and executed by the one or more processors, perform the steps of the method described in any of the foregoing method embodiments.

[0096] This application also provides a computer program product, including a computer program that, when executed by a processor, implements the steps of the method described in any of the foregoing method embodiments.

[0097] in, Figure 3 The architecture of an electronic device is illustrated, which may include a processor 310, a video display adapter 311, a disk drive 312, an input / output interface 313, a network interface 314, and a memory 320. The processor 310, video display adapter 311, disk drive 312, input / output interface 313, network interface 314, and memory 320 can communicate with each other via a communication bus 330.

[0098] The processor 310 can be implemented using a general-purpose CPU, microprocessor, application-specific integrated circuit (ASIC), or one or more integrated circuits to execute relevant programs in order to implement the technical solution provided in this application.

[0099] The memory 320 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 320 can store the operating system 321 for controlling the operation of the electronic device 300, and the basic input / output system (BIOS) 322 for controlling the low-level operations of the electronic device 300. Additionally, it can store a web browser 323, a data storage management system 324, and a multi-dimensional signal mapping plasma surgical electrode precision control system 325, etc. The aforementioned multi-dimensional signal mapping plasma surgical electrode precision control system 325 can be the application program that specifically implements the aforementioned steps in this embodiment. In summary, when implementing the technical solution provided in this application through software or firmware, the relevant program code is stored in the memory 320 and executed by the processor 310.

[0100] Input / output interface 313 is used to connect input / output modules to realize information input and output. Input / output modules can be configured as components in the device (not shown in the figure) or externally connected to the device to provide corresponding functions. Input devices may include keyboards, mice, touch screens, microphones, various sensors, etc., and output devices may include displays, speakers, vibrators, indicator lights, etc.

[0101] Network interface 314 is used to connect a communication module (not shown in the figure) to enable communication between this device and other devices. The communication module can communicate via wired means (such as USB, Ethernet cable, etc.) or wireless means (such as mobile network, WIFI, Bluetooth, etc.).

[0102] Bus 330 includes a pathway for transmitting information between various components of the device, such as processor 310, video display adapter 311, disk drive 312, input / output interface 313, network interface 314, and memory 320.

[0103] It should be noted that although the above-described device only shows the processor 310, video display adapter 311, disk drive 312, input / output interface 313, network interface 314, memory 320, bus 330, etc., in specific implementations, the device may also include other components necessary for normal operation. Furthermore, those skilled in the art will understand that the above-described device may only include the components necessary for implementing the solution of this application, and does not necessarily include all the components shown in the figures.

[0104] As can be seen from the above description of the embodiments, those skilled in the art can clearly understand that this application can be implemented by means of software plus necessary general-purpose hardware platforms. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, can be embodied in the form of a computer program product. This computer program product can be stored in a storage medium, such as ROM / RAM, magnetic disk, optical disk, etc., and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute the methods described in various embodiments or some parts of the embodiments of this application.

[0105] The technical solutions provided in this application have been described in detail above. Specific examples have been used to illustrate the principles and implementation methods of this application. The descriptions of the above embodiments are only for the purpose of helping to understand the methods and core ideas of this application. Furthermore, those skilled in the art will recognize that, based on the ideas of this application, there will be changes in the specific implementation methods and application scope. Therefore, the content of this specification should not be construed as a limitation of this application.

Claims

1. A precision control system for a multi-dimensional signal mapping plasma surgical electrode, characterized in that, The system includes: A multidimensional signal acquisition unit is configured to acquire multidimensional signals during the operation of a plasma surgical electrode, wherein the multidimensional signals include at least two of impedance, voltage, current and temperature; A phase space reconstruction unit is configured to perform phase space reconstruction on the multidimensional signal to obtain a state vector sequence characterizing the working state of the electrode. The joint recursive graph construction unit is configured to construct a joint recursive graph based on the state vector sequence, wherein the element values ​​of the joint recursive graph depend on whether the state vectors at two different times are simultaneously close within a preset neighborhood radius; The joint recursive quantization analysis unit is configured to perform joint recursive quantization analysis on the joint recursive graph and extract joint recursive quantization indices to characterize the cooperative dynamics of multidimensional signals. The joint recursive quantization indices include joint determinism, joint laminarity, joint recursion rate, joint entropy, and joint trap time. The joint trap time is used to characterize the average duration of multidimensional signals cooperatively entering the laminar state. The electrode energy output adjustment unit is configured to generate control parameters for the plasma generator according to a preset mapping rule based on the correspondence between the joint recursive quantization index and the stability of the plasma energy output, and to adjust the energy output of the plasma surgical electrode in real time according to the control parameters. The control parameters include at least one of output power, pulse frequency, and duty cycle. The preset mapping rule includes: reducing the output power when the joint determinism and joint laminar flow decrease simultaneously relative to the historical stable interval; switching to a control mode that limits the rate of change of energy output when the joint recursion rate is higher than the upper quantile threshold of the statistical distribution within the corresponding time window and the joint entropy is lower than the lower entropy threshold; and gradually increasing the pulse frequency to actively break the excessive laminar flow state when the joint trap time is extended by more than a preset proportion relative to the initial calibration value of the surgery.

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