A real-time detection method and system for abnormal electrical signals in a PCR amplification process

Abstract

The present application relates to the technical field of biological detection, and particularly relates to a real-time detection method and system for abnormal electrical signals in a PCR amplification process, wherein the method comprises: at the end of the annealing stage of PCR amplification, applying an alternating current impedance excitation to a detection electrode in a reaction system to obtain a time-varying voltage response sequence; taking the excitation signal as a phase reference, analyzing the phase lag of the time-varying voltage response sequence to obtain a phase angle dispersion coefficient sequence; performing trend analysis on the phase angle dispersion coefficient sequence to obtain a dispersion trend slope parameter; taking a preset electrode fouling early warning boundary as a reference, determining the slope parameter to obtain an interface inhibition state diagnosis identifier; according to the diagnosis identifier, adaptively remapping a next round of heat cycle cooling rate to generate a corrected cooling rate instruction; after the instruction takes effect, re-collecting the phase angle dispersion coefficient sequence and performing reverse checking to obtain an electrode interface activity recovery confirmation identifier.

Description

Technical Field

[0001] This invention relates to the field of biological detection technology. In particular, it relates to a method and system for real-time detection of abnormal electrical signals during PCR amplification. Background Technology

[0002] PCR, as a key technology for nucleic acid amplification and detection, is widely used in the field of biological detection. In-situ monitoring technology based on electrical sensing acquires electrical signals such as impedance and phase of the reaction system through detection electrodes, reflecting changes in the interface state during amplification. PCR thermal cycling includes three steps: denaturation, annealing, and extension. The annealing stage is crucial for primer binding to the single-stranded DNA template, and the end of the annealing stage represents a stable window near the end of this step, with a balanced interface state and minimal signal interference. The heating and cooling rates of PCR thermal cycling directly affect the stability of the electrode interface microenvironment. Current electrical signal analysis methods mostly use macroscopic amplitude and mean values, and PCR equipment often uses fixed operating parameters, lacking precise signal acquisition for the end of the annealing stage and adaptive control methods based on the interface electrical state. This makes it difficult to ensure electrode detection stability and reliable operation of the amplification process.

[0003] Existing PCR electrical monitoring methods mostly employ global or multi-stage averaging signal analysis, focusing only on macroscopic parameters such as impedance amplitude and overall phase mean. They lack quantitative analysis of fine-grained characteristics such as the phase angle dispersion and inter-cycle decay trends within the time window at the end of the annealing stage. For example, when early reagent adsorption or slight salting-out occurs at the electrode, the phase angle dispersion has already shifted continuously, but traditional mean-based indicators cannot capture such weak abnormal trends, making it impossible to identify the inhibition state of the electrode interface early and with high sensitivity. Furthermore, traditional PCR thermal cycling equipment operates at a fixed cooling rate and has not established a closed-loop control mechanism based on abnormal electrical signals at the electrode interface. For instance, when the electrode interface experiences abnormal electrical signals due to accelerated macromolecular deposition and double-layer structure disorder caused by rapid cooling, the system cannot adaptively remap the cooling rate based on abnormal characteristic parameters such as the dispersion trend slope, nor can it reverse-check the recovery effect of the regulated electrode interface activity. It is difficult to suppress interface contamination and restore detection stability from a control perspective. Summary of the Invention

[0004] This invention provides a method and system for real-time detection of abnormal electrical signals during PCR amplification, addressing the technical problems of inaccurate identification of weak anomalies at the PCR electrode interface and the inability to adaptively control thermal cycling parameters. The aim is to achieve real-time detection of abnormal electrical signals, suppress electrode interface contamination, and ensure detection stability. In a first aspect, a method for real-time detection of abnormal electrical signals includes: S1. At the end of the annealing stage of the PCR amplification process, the detection electrode in the PCR reaction system is excited by AC impedance to obtain the time-varying voltage response sequence of the detection electrode. S2. Using the AC impedance excitation signal applied to the detection electrode as a phase reference, perform phase lag analysis on the time-varying voltage response sequence to obtain the phase angle dispersion coefficient sequence of the PCR reaction system. S3. Perform trend analysis on the phase angle diffusion coefficient sequence to obtain the diffusion trend slope parameter of the PCR reaction system; S4. Using the preset electrode contamination warning boundary as the judgment criterion, the diffusion trend slope parameter of the PCR reaction system is critically judged to obtain the interface inhibition state diagnostic identifier of the PCR reaction system. S5. Based on the interface inhibition state diagnostic identifier, the cooling rate parameter of the next thermal cycle of the PCR amplification process is adaptively decelerated and remapped, and the mapping result is encoded as the corrected cooling rate instruction of the PCR reaction system. S6. During the PCR amplification process after the modified cooling rate command takes effect, the phase angle diffusion coefficient sequence that has been re-acquired is checked against the reverse trend to obtain the electrode interface activity recovery confirmation mark of the PCR reaction system.

[0005] Preferably, at the end of the annealing stage of the PCR amplification process, the detection electrode in the PCR reaction system is subjected to AC impedance excitation to obtain the time-varying voltage response sequence of the detection electrode, including: During the thermal cycling of the PCR amplification process, the real-time temperature value of the PCR reaction system is captured in real time. Based on the real-time temperature value, the annealing stage of the PCR reaction system is identified to obtain the excitation application window identifier of the PCR reaction system. Based on the excitation application window identifier, a constant amplitude swept AC current sequence is injected into the detection electrode in the PCR reaction system to obtain the current perturbation excitation signal of the detection electrode; Under the action of the current disturbance excitation signal, the potential difference of the voltage across the detection electrode is analyzed to obtain the original voltage response waveform of the detection electrode; The original voltage response waveform is bandpass filtered to reconstruct the time-varying voltage response sequence of the detection electrode.

[0006] Preferably, using the AC impedance excitation signal applied to the detection electrode as a phase reference, phase hysteresis analysis is performed on the time-varying voltage response sequence to obtain the phase angle dispersion coefficient sequence of the PCR reaction system, including: Using the AC impedance excitation signal applied to the detection electrode as a phase reference, the time-varying voltage response sequence is coherently demodulated and separated to obtain the in-phase voltage component and the quadrature voltage component of the PCR reaction system. The in-phase voltage component and the quadrature voltage component are orthogonally phase fitted to obtain the impedance phase angle point sequence of the PCR reaction system; The phase angle deviation distribution of the PCR reaction system is obtained by differentially comparing the impedance phase angle point-by-point sequence with the preset resistive phase reference value. The phase angle deviation distribution is discretely calculated to obtain the phase angle dispersion coefficient sequence of the PCR reaction system.

[0007] Preferably, trend analysis is performed on the phase angle diffusion coefficient sequence to obtain the diffusion trend slope parameter of the PCR reaction system, including: The annealing interval is truncated from the phase angle dispersion coefficient sequence to obtain the annealing-specific fluctuation subsequence of the phase angle dispersion coefficient sequence; Based on the annealing-specific wave subsequence, the phase angle dispersion coefficient sequence is subjected to inter-cycle difference extraction to obtain the cyclic decay difference component of the phase angle dispersion coefficient sequence; Based on the cyclic decay difference component, the phase angle diffusion coefficient sequence is subjected to multi-cyclic window recursive aggregation to obtain the cumulative decay window mean of the phase angle diffusion coefficient sequence. Based on the cumulative attenuation window mean, gradient fitting is performed on the phase angle diffusion coefficient sequence to obtain the diffusion trend slope parameter of the PCR reaction system.

[0008] Preferably, based on the cumulative attenuation window mean, gradient fitting is performed on the phase angle diffusion coefficient sequence to obtain the diffusion trend slope parameter of the PCR reaction system, including: The mean of the cumulative decay window is mapped to time-series point coordinates to obtain a scattered numerical coordinate group of the mean of the cumulative decay window. Based on the scattered numerical coordinate set, the straight line element direction of the cumulative decay window mean is optimized to obtain the optimal penetration trend trajectory of the cumulative decay window mean. The attenuation direction of the optimal penetration trend trajectory is measured to obtain the diffusion trend slope parameter of the PCR reaction system.

[0009] Preferably, using a preset electrode contamination warning boundary as a criterion, the diffusion trend slope parameter of the PCR reaction system is critically determined to obtain a diagnostic indicator of the interface inhibition state of the PCR reaction system, including: Based on the preset electrode contamination warning boundary, the deviation tolerance of the diffusion trend slope parameter is compared to obtain the boundary exceedance quantification value of the diffusion trend slope parameter. Based on the quantified value of the boundary exceedance, the diffusion trend slope parameter is classified and analyzed for suppression hierarchy to obtain the transient interface suppression level code of the PCR reaction system. The transient interface inhibition level code is cumulatively analyzed to obtain the interface inhibition state diagnostic identifier of the PCR reaction system.

[0010] Preferably, based on the interface inhibition state diagnostic identifier, the cooling rate parameter of the next thermal cycle in the PCR amplification process is adaptively degraded and remapped, and the mapping result is encoded as a corrected cooling rate instruction for the PCR reaction system, including: The urgency scale of the interface inhibition state diagnostic identifier is applied to obtain the inhibition urgency level code of the interface inhibition state diagnostic identifier; Based on a preset cooling rate compensation mapping table, a mapping inversion is performed on the suppression urgency level code to obtain the reduction correction ratio coefficient of the cooling rate parameter. Based on the aforementioned reduction correction ratio, the cooling rate parameter of the next thermal cycle in the PCR amplification process is compensated for the reduction, thereby obtaining the intervention-state cooling rate calibration value of the PCR amplification process. The calibration value of the intervention-state cooling rate is compiled into instructions to obtain the corrected cooling rate instructions for the PCR reaction system.

[0011] Preferably, based on a preset cooling rate compensation mapping table, a mapping inversion is performed on the suppression urgency level code to obtain the reduction correction ratio coefficient of the cooling rate parameter, including: Discretize the suppression urgency level code to obtain adjacent discrete node pairs that match the level code in the preset cooling rate compensation mapping table; Based on the adjacent discrete node pairs, linear interpolation is performed to obtain the continuous domain correction reference value of the cooling rate parameter. By applying convergence limiting constraints to the continuous domain correction reference value, the reduction correction ratio coefficient of the cooling rate parameter is obtained.

[0012] Preferably, during the PCR amplification process after the corrected cooling rate command takes effect, the re-acquired phase angle diffusion coefficient sequence is subjected to reverse trend verification to obtain a confirmation indicator of electrode interface activity recovery in the PCR reaction system, including: After the modified cooling rate command takes effect, the phase angle diffusion coefficient sequence during the PCR amplification process is collected to obtain the time-series distribution results of the coefficients during the PCR amplification process; Based on the standard phase angle diffusion baseline of the PCR reaction system, the time-series distribution results of the coefficients are baseline normalized to obtain the calibrated time-series data of the PCR reaction system. Based on the calibrated time series data, reverse feature analysis was performed on the phase angle dispersion coefficient sequence to obtain the trend change characteristics of the PCR reaction system. The trend change characteristics are evaluated for feature adaptation to obtain the activity recovery parameters of the PCR reaction system. Based on the activity recovery degree parameter, the inhibition recovery status of the electrode interface of the PCR reaction system is determined to obtain the activity recovery confirmation identifier of the electrode interface of the PCR reaction system.

[0013] In a second aspect, a real-time detection system for abnormal electrical signals includes: a processor and a memory, wherein the memory stores computer program instructions, and when the computer program instructions are executed by the processor, the real-time detection method for abnormal electrical signals described in any one of the claims is implemented.

[0014] 1. By applying swept-frequency AC current excitation to the detection electrode within a fixed time window at the end of the annealing stage of PCR amplification and acquiring time-varying voltage response sequences, the impedance phase angle point-by-point sequence is fitted after coherent demodulation to separate in-phase and quadrature components. This sequence is then compared with the resistive phase reference value to obtain the phase angle deviation distribution and calculate its dispersion, forming a phase angle dispersion coefficient sequence. Further, annealing-specific fluctuation subsequences are extracted, adjacent cycle decay difference components are extracted, and multi-window sliding aggregation is performed. Finally, the optimal penetration trajectory is fitted using scattered coordinates, and the slope is measured to obtain the dispersion trend slope parameter. This method refines the analytical granularity of the electrode interface electrical response from the macroscopic amplitude mean to the phase angle dispersion at the end of annealing and its inter-cycle decay trend. It can capture weak phase dispersion shifts caused by early reagent adsorption and slight salting out, achieving early high-sensitivity identification of the electrode interface inhibition state and solving the problem of traditional mean-based indicators being insensitive to weak abnormal trends.

[0015] 2. Based on the deviation tolerance comparison between the diffusion trend slope parameter and the electrode fouling early warning boundary, a quantitative value of the boundary exceedance degree is generated. After hierarchical classification and multi-cycle cumulative situation analysis, an interface inhibition state diagnostic identifier is obtained. Then, by linear interpolating the inhibition urgency level code in the cooling rate compensation mapping table, the reduction correction ratio coefficient is solved. The cooling rate parameter for the next thermal cycle is adaptively remapped and encoded as a corrected cooling rate command. After the command takes effect, the phase angle diffusion coefficient sequence is re-acquired. After standard phase angle diffusion baseline normalization and inverse feature analysis, the activity recovery degree parameter is evaluated and compared with a threshold to generate an electrode interface activity recovery confirmation identifier. This closed-loop control mechanism can dynamically adjust the cooling rate according to the degree of diffusion trend slope anomaly, slowing down the rate of macromolecular deposition and double-layer disturbance, and inversely verifying the interface activity recovery effect from time-series data. This achieves active inhibition of electrode fouling and control-level assurance of detection stability, overcoming the deficiency of traditional fixed cooling rates in responding to electrical anomaly signals.

[0016] The above and other objects, advantages and features of the present invention will become more apparent to those skilled in the art from the following detailed description of specific embodiments of the invention in conjunction with the accompanying drawings. Attached Figure Description

[0017] The following sections will describe some specific embodiments of the invention in detail by way of example and not limitation, with reference to the accompanying drawings. The same reference numerals in the drawings denote the same or similar parts or portions. Those skilled in the art should understand that these drawings are not necessarily drawn to scale. In the drawings: Figure 1 This is a schematic flowchart of a method for real-time detection of abnormal electrical signals during PCR amplification according to an embodiment of the present invention. Figure 2 This is a schematic diagram of a real-time detection system for abnormal electrical signals during PCR amplification according to an embodiment of the present invention. Detailed Implementation

[0018] The following reference Figure 1This invention describes a method and system for real-time detection of abnormal electrical signals during PCR amplification. In the description of this invention, it should be understood that the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Therefore, a feature defined with "first" or "second" may explicitly or implicitly include at least one of that feature, that is, include one or more of that feature. In the description of this invention, "multiple" means at least two, such as two, three, etc., unless otherwise explicitly specified. When a feature "includes or contains" one or more of the features it encompasses, unless otherwise specifically stated, this indicates that other features are not excluded and may be further included.

[0019] In the description of this embodiment, the terms "one embodiment," "some embodiments," "illustrative embodiment," "example," "specific example," or "some examples," etc., refer to specific features, structures, materials, or characteristics described in connection with that embodiment or example, which are included in at least one embodiment or example of this invention. In this specification, the illustrative expressions of the above terms do not necessarily refer to the same embodiment or example. Furthermore, the specific features, structures, materials, or characteristics described may be combined in any suitable manner in one or more embodiments or examples.

[0020] This embodiment provides a real-time detection method for abnormal electrical signals during PCR amplification. This method can achieve real-time and accurate detection of abnormal electrical signals at the electrode interface and adaptive control of the thermal cycling cooling rate without interfering with the normal PCR amplification reaction, effectively suppressing electrode interface contamination and ensuring the stability of electrical detection.

[0021] Please see Figure 1 , Figure 1 This is a schematic flowchart of a method for real-time detection of abnormal electrical signals during PCR amplification according to an embodiment of the present invention. The method generally includes: S1. At the end of the annealing stage of the PCR amplification process, the detection electrode in the PCR reaction system is excited by AC impedance to obtain the time-varying voltage response sequence of the detection electrode. S2. Using the AC impedance excitation signal applied to the detection electrode as a phase reference, perform phase lag analysis on the time-varying voltage response sequence to obtain the phase angle dispersion coefficient sequence of the PCR reaction system. S3. Perform trend analysis on the phase angle diffusion coefficient sequence to obtain the diffusion trend slope parameter of the PCR reaction system; S4. Using the preset electrode contamination warning boundary as the judgment criterion, the diffusion trend slope parameter of the PCR reaction system is critically judged to obtain the interface inhibition state diagnostic identifier of the PCR reaction system. S5. Based on the interface inhibition state diagnostic identifier, the cooling rate parameter of the next thermal cycle of the PCR amplification process is adaptively decelerated and remapped, and the mapping result is encoded as the corrected cooling rate instruction of the PCR reaction system. S6. During the PCR amplification process after the modified cooling rate command takes effect, the phase angle diffusion coefficient sequence that has been re-acquired is checked against the reverse trend to obtain the electrode interface activity recovery confirmation mark of the PCR reaction system.

[0022] In step S1 above, the real-time temperature value of the reaction system during the PCR amplification thermal cycle is acquired; the real-time temperature value is compared with the temperature range corresponding to the annealing stage one by one; when the real-time temperature value falls into the annealing stage temperature range and continues until a fixed duration node before the end of the annealing stage, it is determined to be the end of the annealing stage and an excitation application window identifier is generated; according to the indication of the excitation application window identifier, a sweep frequency AC current with a constant amplitude is continuously injected into the detection electrode inside the PCR reaction system; the sweep frequency AC current acts on the detection electrode to form a current perturbation excitation signal; the potential signal at both ends of the detection electrode is acquired in real time and the potential difference between the two ends is calculated; the calculated potential difference values ​​are arranged in the order of acquisition time to form the original voltage response waveform. The original voltage response waveform is bandpass filtered to retain the effective signal part of the waveform that matches the frequency of the AC impedance excitation signal; the filtered effective signal is rearranged and combined in the order of acquisition time to form the time-varying voltage response sequence of the detection electrode; the time-varying voltage response sequence is a set of voltage values ​​of the detection electrode changing with time under AC impedance excitation, which can completely reflect the electrical response state of the interface between the electrode and the reaction system.

[0023] In step S2 above, the phase of the AC impedance excitation signal is used as a fixed reference. The time-varying voltage response sequence is coherently demodulated, decomposing the voltage signal in the sequence into an in-phase voltage component with the same phase as the excitation signal and a quadrature voltage component perpendicular to the excitation signal. The in-phase and quadrature voltage components are synchronously fitted, and the impedance phase angle corresponding to the voltage signal is calculated point-by-point during the fitting process, forming a point-by-point sequence of impedance phase angles. The difference between each phase angle value in the point-by-point sequence of impedance phase angles and the preset resistive phase reference value is calculated to obtain the phase angle deviation value at each point. All phase angles are then... The deviation values ​​are arranged in time sequence to form a phase angle deviation distribution. The dispersion of all values ​​in the phase angle deviation distribution is calculated. The calculation process is to take the difference between each deviation value and the average value of the deviation distribution, take the square, sum all the square values ​​and divide by the total number of values ​​in the deviation distribution. Finally, take the square root of the result to obtain the dispersion value. The dispersion values ​​corresponding to each time point are arranged in the acquisition order to form the phase angle dispersion coefficient sequence of the PCR reaction system. The phase angle dispersion coefficient sequence is a set of time-series values ​​that reflect the degree of deviation of the impedance phase angle of the reaction system from the reference, and can reflect the discrete fluctuation state of the electrical signal at the electrode interface.

[0024] In step S3 above, the numerical portion corresponding only to the annealing stage is extracted from the phase angle dispersion coefficient sequence to form an annealing-specific fluctuation subsequence of the phase angle dispersion coefficient sequence; the point-by-point difference of the annealing-specific fluctuation subsequence of adjacent thermal cycles is calculated to extract the change values ​​of the sequence between different cycles, forming the cyclic attenuation difference component of the phase angle dispersion coefficient sequence; taking a fixed number of continuous thermal cycles as a calculation window, the cyclic attenuation difference component is accumulated window by window and the average value is calculated to obtain the cumulative attenuation window mean of the phase angle dispersion coefficient sequence; the cumulative attenuation window mean is then calculated according to the corresponding thermal cycle. The serial numbers are mapped to scattered coordinates in a Cartesian coordinate system. A straight line is fitted to all the scattered coordinates to find the straight line trajectory that passes through most of the scattered points with the smallest fitting error. This trajectory is considered the optimal penetration trend trajectory for the cumulative attenuation window mean. Along the direction of numerical change of the optimal penetration trend trajectory, the ratio of the vertical numerical change to the horizontal cycle number change is calculated. This ratio is the diffusion trend slope parameter of the PCR reaction system. The diffusion trend slope parameter is a quantitative value reflecting the rate of change of the phase angle diffusion coefficient sequence with the advancement of thermal cycling, and can directly reflect the changing trend of the inhibition state at the electrode interface.

[0025] In step S4 above, the difference between the diffusion trend slope parameter and the preset electrode fouling warning boundary value is calculated and the absolute value is taken. The boundary exceedance quantification value is equal to the diffusion trend slope parameter minus the absolute value of the electrode fouling warning boundary. According to the magnitude of the boundary exceedance quantification value, it is divided into preset three-level threshold intervals: quantification value less than the first threshold is mild inhibition, quantification value greater than or equal to the first threshold and less than the second threshold is moderate inhibition, and quantification value greater than or equal to the second threshold is severe inhibition. The corresponding results are encoded as digital codes 0 / 1 / 2 / 3 to form transient interface inhibition level codes. The transient interface inhibition level codes of N thermal cycles are continuously collected. If the level code remains unchanged or increases in each cycle, it is determined that the inhibition is continuous or aggravated, and a corresponding diagnostic label is generated. If the level code decreases in each cycle, it is determined that the inhibition is relieved, and a relief label is generated. If all are normal codes, a normal label is generated, that is, the corresponding interface inhibition state diagnostic label is obtained. The interface inhibition state diagnostic label is used to clarify whether there is fouling and the degree of inhibition at the electrode interface, and can directly indicate the operating status of the electrode interface of the reaction system.

[0026] In step S5 above, based on the degree of inhibition corresponding to the interface inhibition state diagnostic identifier, the identifier is classified into urgency levels to form an inhibition urgency level code for the interface inhibition state diagnostic identifier; in the preset cooling rate compensation mapping table, the two discrete node values ​​closest to the inhibition urgency level code are retrieved; linear calculation is performed on the two adjacent discrete node values, the calculation process is to multiply the difference between the level code and the previous node by the difference between the two node values, then divide by the level difference between the next node and the previous node, and finally add the value of the previous node to obtain the continuous domain correction reference value of the cooling rate parameter; the continuous domain correction reference value is restricted to the preset maximum and minimum correction value range to form the reduction amplitude correction ratio coefficient of the cooling rate parameter; the original cooling rate parameter is multiplied by the reduction amplitude correction ratio coefficient to obtain the intervention state cooling rate calibration value for the next thermal cycle of the PCR amplification process; the intervention state cooling rate calibration value is encapsulated into a control instruction with a check bit according to the device communication protocol, for example, the calibration value is 1.2℃ / s, according to ASCII The code is "TEMP:COOL:1.2:OK". The device directly parses and executes it to form a corrected cooling rate instruction for the PCR reaction system. The corrected cooling rate instruction is an execution instruction used to control the PCR device to adjust the cooling speed, which can accurately match the inhibition state of the electrode interface to adjust the operating parameters.

[0027] In step S6 above, after the cooling rate correction command takes effect, the phase angle diffusion coefficient sequence during the PCR amplification process is re-acquired and generated according to the aforementioned acquisition and analysis steps, forming a coefficient time-series distribution result; each value in the coefficient time-series distribution result is divided by the corresponding value of the standard phase angle diffusion baseline to complete the baseline normalization process, obtaining the calibrated time-series data of the PCR reaction system; the calibrated time-series data is subjected to inverse trend analysis using the time-series difference method and least squares linear regression; the inverse trend analysis of the calibrated time-series data is performed to analyze the direction and magnitude of change of the data compared with before the correction command took effect, obtaining the trend change characteristics of the PCR reaction system, and the calculation formula for the activity recovery degree parameter is: ; in These are the measured characteristic values. The standard feature value is used as the standard feature value. The trend change feature result is matched one by one with the standard feature of electrode interface activity recovery, and the matching degree value is calculated to form the activity recovery degree parameter. When the activity recovery degree parameter reaches the preset recovery threshold, it is determined that the electrode interface inhibition state is relieved, and an electrode interface activity recovery confirmation mark of the PCR reaction system is generated. The electrode interface activity recovery confirmation mark is used to confirm that the electrical activity of the electrode interface has returned to normal, and can confirm the execution effect of the modified cooling rate command.

[0028] The beneficial effects are as follows: It accurately targets the application of excitation at the end of annealing and eliminates interference, fully acquiring the true electrical response data of the electrode interface, ensuring the completeness and accuracy of the detection data; it generates a dispersion coefficient sequence through phase demodulation, fitting, and dispersion calculation, accurately quantifying the discrete state of the electrical signal at the electrode interface; it improves signal analysis accuracy, obtaining trend slope parameters through subsequence truncation, difference calculation, and trajectory fitting, clearly quantifying the rate of change of the electrode interface state, accurately characterizing abnormal trends; it generates diagnostic labels through boundary comparison, hierarchical division, and situational assessment, accurately identifying the degree of electrode interface contamination and inhibition, achieving real-time anomaly detection; it generates corrective cooling commands through scaling, interpolation, and command encoding, adaptively matching cooling parameters to achieve precise control of operating parameters; and it generates recovery labels through re-analysis, normalization, and threshold determination, verifying the parameter correction effect in real time and accurately confirming the activity recovery state of the electrode interface.

[0029] In step S1 above, at the end of the annealing stage of the PCR amplification process, the detection electrode in the PCR reaction system is subjected to AC impedance excitation to obtain the time-varying voltage response sequence of the detection electrode, including the following steps: Step S101: During the thermal cycling of the PCR amplification process, the real-time temperature value of the PCR reaction system is captured in real time. Based on the real-time temperature value, the annealing stage of the PCR reaction system is identified to obtain the excitation application window identifier of the PCR reaction system. Step S102: Based on the excitation application window identifier, a constant amplitude swept AC current sequence is injected into the detection electrode in the PCR reaction system to obtain the current perturbation excitation signal of the detection electrode; Step S103: Under the action of the current disturbance excitation signal, the potential difference of the voltage across the detection electrode is analyzed to obtain the original voltage response waveform of the detection electrode; Step S104: Bandpass filtering is performed on the original voltage response waveform to reconstruct the time-varying voltage response sequence of the detection electrode.

[0030] In step S101 above, during the continuous operation of the PCR amplification thermal cycle, the built-in temperature sensor of the device continuously collects temperature data inside the reaction system at fixed sampling time intervals and outputs independent real-time temperature values. Each real-time temperature value is compared with the pre-set annealing stage temperature range. The duration for which the real-time temperature value falls within the annealing stage temperature range is recorded in real time and defined as the holding time. The holding time is divided by the total annealing stage duration to obtain the duration percentage. When the duration percentage reaches a preset fixed proportion, the current moment is determined to be the end of the annealing stage. The result of the end of the annealing stage is converted into an execution command to trigger subsequent excitation operations, and this command is defined as the excitation application window identifier of the PCR reaction system. The excitation application window identifier is the unique identifier information that indicates the timing of AC impedance excitation, which can accurately lock the execution node at the end of the annealing stage and provide a unique timing basis for subsequent excitation application.

[0031] In step S102 above, after the excitation application window identifier is recognized and activated by the system, the signal generation module immediately outputs a sweep frequency alternating current with a constant amplitude to the detection electrode inside the PCR reaction system. The frequency of the sweep frequency alternating current changes continuously and uniformly within the range where the detection electrode can generate a stable and effective electrical response, and the frequency change is without abrupt changes or interruptions. The sweep frequency alternating current acts directly on the working interface of the detection electrode and interacts electrically with the PCR reaction system, forming a current perturbation excitation signal that can stably excite changes in the electrical characteristics of the electrode interface. The current perturbation excitation signal is an external excitation source that drives the detection electrode to generate a detectable electrical response, and can continuously and stably change the double-layer state of the electrode-reaction system contact interface, providing a stable excitation basis for subsequent voltage acquisition.

[0032] In step S103 above, during the entire process of the current disturbance excitation signal continuously acting on the detection electrode, the voltage acquisition module synchronously acquires the potential signals of the working end and the reference end of the detection electrode; the potential value of the working end of the detection electrode is defined as... The reference terminal potential value is defined as The potential difference across the electrodes is obtained by subtracting numerical values. The mathematical formula for calculating the potential difference is: The calculation process is performed point by point without omission or delay. The potential difference values ​​corresponding to all sampling times are arranged and combined in chronological order of acquisition time to form a continuous time sequence signal, which is defined as the original voltage response waveform of the detection electrode. The original voltage response waveform completely records all potential changes of the detection electrode under the action of current disturbance excitation signal, and includes both the effective response signal and the environmental interference signal.

[0033] In step S104 above, the original voltage response waveform is input into the bandpass filter module for signal processing. The passband frequency range of the bandpass filter module is preset to completely overlap with the frequency range of the swept AC current, allowing only signals within this frequency range to pass through. During the filtering process, all interference signals outside the passband frequency range are completely filtered out, retaining only the effective voltage signal that matches the frequency of the current disturbance excitation signal. The filtered effective voltage signal is rearranged and integrated according to the original acquisition sequence to restore the temporal continuity, ultimately forming the time-varying voltage response sequence of the detection electrode. The time-varying voltage response sequence is a pure time-series voltage data set after removing all interference signals, which can accurately reflect the real-time electrical response state of the contact interface between the detection electrode and the PCR reaction system under AC impedance excitation, without interference distortion or information loss.

[0034] The beneficial effects are as follows: By continuously acquiring temperature data, comparing numerical values, and calculating the duration proportions, the final annealing stage is accurately located, generating a unique timing excitation identifier to ensure the accuracy and uniqueness of the detection timing sequence; a stable excitation source is constructed by outputting a constant amplitude, continuously sweeping AC current, providing a stable and reliable excitation foundation for acquiring the electrical response at the electrode interface. Point-by-point acquisition of the dual-terminal potential and calculation of the potential difference using standardized formulas completely retain all potential change information, ensuring the integrity of signal acquisition; and bandpass filtering with a matched excitation frequency completely eliminates interference signals, reconstructing a pure timing voltage sequence and improving the purity and accuracy of the detection signal.

[0035] In step S2 above, using the AC impedance excitation signal applied to the detection electrode as a phase reference, phase hysteresis analysis is performed on the time-varying voltage response sequence to obtain the phase angle dispersion coefficient sequence of the PCR reaction system, including the following steps: Step S201: Using the AC impedance excitation signal applied to the detection electrode as a phase reference, coherent demodulation and separation are performed on the time-varying voltage response sequence to obtain the in-phase voltage component and the quadrature voltage component of the PCR reaction system. Step S202: Perform orthogonal phase fitting on the in-phase voltage component and the orthogonal voltage component to obtain the impedance phase angle point sequence of the PCR reaction system; Step S203: The impedance phase angle point-by-point sequence is differentially compared with the preset resistive phase reference value to obtain the phase angle deviation distribution of the PCR reaction system. Step S204: The discreteness of the phase angle deviation distribution is calculated to obtain the phase angle dispersion coefficient sequence of the PCR reaction system.

[0036] In step S201 above, the AC impedance excitation signal is an external driving signal applied to the detection electrode to excite the interface electrical response. The phase of the signal output at the initial moment is set as a fixed phase reference, which remains constant and does not shift during the entire phase resolution process. The time-varying voltage response sequence is a set of pure time-series voltage data after the detection electrode is filtered and reconstructed under the excitation. The sequence is input into the coherent demodulation unit point by point. The coherent demodulation unit uses the fixed phase reference as a synchronization reference and performs orthogonal decomposition processing on the voltage signal at each time point. The decomposition process involves multiplying the voltage signal with the reference in-phase carrier and the reference quadrature carrier respectively and filtering to extract two independent voltage components. The voltage component that is completely in line with the direction of the fixed phase reference is the in-phase voltage component, and the voltage component that is perpendicular to the direction of the fixed phase reference is the quadrature voltage component. The in-phase voltage component and the quadrature voltage component are time-series data sets that appear in pairs. The combination of the two can completely restore all phase and amplitude information of the time-varying voltage response sequence without any loss of phase characteristics.

[0037] In step S202 above, the in-phase voltage component and the quadrature voltage component corresponding to each time point are synchronously input into the phase fitting unit. The fitting unit performs real-time numerical calculations on the two components at the same time point. The calculation process uses the in-phase voltage component as the horizontal reference and the quadrature voltage component as the vertical reference. The impedance phase angle at the current point is determined by the ratio of their values. This phase angle is the phase characterization of the impedance at the interface between the electrode and the reaction system at the current moment. The impedance phase angles calculated from all time points are arranged sequentially according to the original acquisition time sequence of the time-varying voltage response sequence to form a continuous time-series numerical set. This time-series numerical set is the point-by-point sequence of the impedance phase angle of the PCR reaction system. The point-by-point sequence of the impedance phase angle completely records the phase angle change of the electrode interface impedance over the entire time range, which is the basic data for subsequent deviation analysis.

[0038] In step S203 above, the resistive phase reference value is the standard impedance phase angle of the electrode interface under a purely resistive state without capacitive interference, which is a pre-calibrated fixed value. The impedance phase angle of each time point in the impedance phase angle point-by-point sequence is differentially calculated with the resistive phase reference value. The specific method of differential calculation is to subtract the resistive phase reference value from the impedance phase angle value of the current point, and the difference obtained is the phase angle deviation of the current point. The phase angle deviations of all time points are arranged sequentially according to the original acquisition time sequence to form a continuous set of numerical distributions. This set of numerical distributions is the phase angle deviation distribution of the PCR reaction system. The phase angle deviation distribution intuitively reflects the offset amplitude and distribution law of the impedance phase angle of each time point relative to the standard value.

[0039] In step S204 above, the discreteness of all values ​​in the phase angle deviation distribution is calculated. The discreteness is used to quantify the fluctuation and dispersion of the phase angle deviation. The calculation process strictly follows the standard deviation procedure. The mathematical formula for calculating the discreteness is: ; In the formula The value represents the degree of dispersion. For a single phase angle deviation, The arithmetic mean of the phase angle deviation. The total number of phase angle deviations is given. The discreteness values ​​corresponding to each time point are arranged sequentially according to the original acquisition time sequence to form a continuous set of time-series values. This set of time-series values ​​is the phase angle dispersion coefficient sequence of the PCR reaction system. The phase angle dispersion coefficient sequence can accurately quantify the discrete fluctuation of the electrical signal at the electrode interface and directly reflect the stability of the interface electrical state.

[0040] The beneficial effects are as follows: coherent demodulation decomposition is completed using a constant phase reference, fully preserving the phase amplitude characteristics of the voltage signal and improving the accuracy of phase analysis; point-by-point orthogonal fitting is used to calculate the phase angle, forming a point-by-point sequence of the full-time phase angle, which fully characterizes the phase change of the electrode interface impedance; point-by-point differential operation generates the phase angle deviation distribution, intuitively presenting the offset law of the phase angle relative to the standard value; the degree of discreteness is calculated according to the standard process, generating a dispersion coefficient sequence, and accurately quantifying the discrete state of the interface electrical signal.

[0041] In step S3 above, trend analysis is performed on the phase angle diffusion coefficient sequence to obtain the diffusion trend slope parameter of the PCR reaction system, including the following steps: Step S301: The phase angle dispersion coefficient sequence is truncated by annealing interval to obtain the annealing-specific fluctuation subsequence of the phase angle dispersion coefficient sequence; Step S302: Based on the annealing-specific wave subsequence, perform inter-cycle difference extraction on the phase angle dispersion coefficient sequence to obtain the cyclic attenuation difference component of the phase angle dispersion coefficient sequence; Step S303: Based on the cyclic attenuation difference component, perform multi-cyclic window recursive aggregation on the phase angle dispersion coefficient sequence to obtain the cumulative attenuation window mean of the phase angle dispersion coefficient sequence. Step S304: Based on the cumulative attenuation window mean, perform gradient fitting on the phase angle diffusion coefficient sequence to obtain the diffusion trend slope parameter of the PCR reaction system, including: Step S3041: Perform time-series point coordinate mapping on the cumulative decay window mean to obtain a scattered numerical coordinate group of the cumulative decay window mean. Step S3042: Based on the scattered numerical coordinate group, optimize the direction of the linear primitives of the cumulative decay window mean to obtain the optimal penetration trend trajectory of the cumulative decay window mean. Step S3043: The attenuation direction of the optimal penetration trend trajectory is measured to obtain the diffusion trend slope parameter of the PCR reaction system.

[0042] In step S301 above, the phase angle dispersion coefficient sequence is a continuous time series composed of the phase angle deviation dispersion values ​​at each time point during the entire PCR amplification process. Each value in the sequence corresponds to the detection result at a precise moment in the thermal cycle, and the sequence completely covers all thermal cycle stages of denaturation, annealing, and extension. Based on the fixed start and end points of the annealing stage in the thermal cycle, all values ​​whose time series fall within the start and end point range of the annealing stage are selected from the phase angle dispersion coefficient sequence, and the denaturation and extension stage values ​​whose time series exceed the range of the annealing stage are directly removed. The selected annealing stage-specific values ​​are arranged sequentially according to the original acquisition time series to form a continuous value subset without missing or redundant values. This value subset is the annealing-specific fluctuation subsequence of the phase angle dispersion coefficient sequence. The annealing-specific fluctuation subsequence is a pure target data set that only retains the signal characteristics of the detection period at the end of the annealing stage, which can completely eliminate the interference of non-target stage data on trend analysis.

[0043] In step S302 above, the annealing-specific fluctuation subsequences are grouped into independent units based on a single PCR thermal cycle. Each group of annealing-specific fluctuation subsequences uniquely corresponds to the annealing stage detection data of one thermal cycle, and the time points and sampling quantity of each group of data are completely consistent. The annealing-specific fluctuation subsequence corresponding to the thermal cycle with the thermal cycle with the previous thermal cycle is subtracted one-to-one at the exact same time point. The operation rule is to subtract the value of the previous cycle from the value of the current cycle point. The difference results obtained from the operation of all time points are arranged in sequence according to the original sampling time sequence to form a continuous difference set that characterizes the value change of adjacent cycles. This set is the cycle decay difference component of the phase angle dispersion coefficient sequence. The cycle decay difference component is the time-series data that quantifies the decay amplitude of the dispersion coefficient in the annealing stage between adjacent thermal cycles, and can directly reflect the cycle-by-cycle dynamic change amplitude of the electrical state of the electrode interface.

[0044] In step S303 above, a fixed number of consecutive thermal cycles are preset as a single recursive calculation window. The number of thermal cycles included in the calculation window is a fixed value throughout the process, and the window sliding step size is consistent with the duration of a single thermal cycle. Starting from the first thermal cycle of PCR amplification, all cycle decay difference components included in the current calculation window are accumulated one by one. The sum obtained is divided by the total number of thermal cycles included in the calculation window to obtain the cumulative decay average value of the current window. The calculation window is slid backward according to the fixed step size, and the accumulation and averaging operations are repeated until the cycle decay difference components of all thermal cycles are covered. The cumulative decay average value obtained from all calculation windows is then calculated.

[0045] Arranged sequentially according to the order in which the windows are generated, a continuous set of average values ​​is formed. This set is the cumulative attenuation window mean of the phase angle dispersion coefficient sequence; the mathematical formula for calculating the cumulative attenuation window mean is: ; in Single-window cumulative decay mean To calculate the total number of loops contained in the window, The cumulative attenuation window means the difference in attenuation within a single cycle within the window. The mean value of the cumulative attenuation window is a smoothed quantization result of the attenuation changes in multiple cycles, which can eliminate random fluctuations in single-cycle data and stably present the long-term trend of the signal.

[0046] In step S3041 above, a unique correspondence is established between the mean of each cumulative decay window and the thermal cycle number corresponding to the calculation window to which the mean belongs. The thermal cycle number is used as the horizontal axis coordinate of the Cartesian coordinate system, and the mean of the cumulative decay window is used as the vertical axis coordinate of the Cartesian coordinate system. Each set of correspondences is converted into an independent coordinate point in the Cartesian coordinate system. All coordinate points are combined in chronological order to form a complete set of coordinate points. This set is the scattered numerical coordinate set of the mean of the cumulative decay window. The scattered numerical coordinate set is the coordinate data after the decay mean is standardized and mapped to the thermal cycle time series, providing an accurate basic data carrier for subsequent trend trajectory fitting.

[0047] In step S3042 above, all coordinate points in the scattered numerical coordinate group are used as the fitting object. The general expression of the fitted line is set as the vertical axis value equals the slope of the line multiplied by the horizontal axis value plus the line intercept. All possible combinations of line slope and line intercept in the Cartesian coordinate system are traversed. For each combination, the perpendicular distance from each coordinate point to the line is calculated one by one. The perpendicular distance of each coordinate point is squared, and all the squared results are added together to obtain the total squared distance corresponding to the line. The mathematical formula for the total squared distance is: ; in The sum of squares of the total distance. The coordinate point number, This represents the total number of coordinate points in the scattered numerical coordinate system. For the first The y-axis values ​​of each coordinate point The slope of the fitted line, For the first The x-axis values ​​of each coordinate point To find the intercept of the fitted line, we compare the sum of squared total distances corresponding to all line combinations and select the line corresponding to the line combination with the smallest sum of squared total distances. This line is the optimal cross-trajectory trajectory of the cumulative decay window mean. The optimal cross-trajectory trajectory is a standard straight line that fits the overall change law of the scattered points without bias and can truly reflect the overall change direction and rate of the cumulative decay window mean.

[0048] In step S3043 above, two valid coordinate points with different horizontal coordinates are selected on the optimal through-trajectory trajectory, defined as the first coordinate point and the second coordinate point respectively. The horizontal coordinate of the first coordinate point is... The vertical axis coordinate is The x-axis coordinate of the second coordinate point is The vertical axis coordinate is Subtracting the ordinate value of the first coordinate point from the ordinate value of the second coordinate point yields the change in the ordinate value; subtracting the lateral axis value of the first coordinate point from the lateral axis value of the second coordinate point yields the change in the lateral axis index. Dividing the change in the ordinate value by the change in the lateral axis index gives the final ratio, which is the diffusion trend slope parameter of the PCR reaction system. The mathematical formula for calculating the diffusion trend slope parameter is as follows: The diffusion trend slope parameter is a characteristic value that accurately quantifies how fast the phase angle diffusion coefficient changes with the advancement of thermal cycling. It can directly characterize the rate of change and the strength of the trend of the inhibition state at the electrode interface.

[0049] The beneficial effects are as follows: it accurately extracts values ​​from the annealing stage to form a dedicated subsequence, eliminates interference from non-target data, focuses on the core detection signal, calculates the attenuation difference component by calculating the difference between each point in a cycle, accurately quantifies the change amplitude of the interface state of adjacent cycles, obtains the attenuation mean by multi-window sliding recursive aggregation, smooths random fluctuations, stably presents the long-term trend of the signal, generates a scatter coordinate group by mapping time-series coordinates, establishes a standardized correlation between the attenuation mean and the cycle time series, traverses all directions to find the optimal trend trajectory, fits the overall change law of the scatter points without bias, calculates the slope parameter by measuring the trajectory at two points, accurately quantifies the rate of change of the interface state, and improves the accuracy of trend analysis.

[0050] In step S4 above, using a preset electrode contamination warning boundary as the criterion, the diffusion trend slope parameter of the PCR reaction system is critically determined to obtain the interface inhibition state diagnostic indicator of the PCR reaction system, including the following steps: Step S401: Based on the preset electrode contamination warning boundary, the deviation tolerance of the diffusion trend slope parameter is compared to obtain the boundary exceedance quantification value of the diffusion trend slope parameter. Step S402: Based on the boundary exceedance quantification value, the diffusion trend slope parameter is classified and analyzed for inhibition level to obtain the transient interface inhibition level code of the PCR reaction system. Step S403: Perform cumulative situation analysis on the transient interface inhibition level code to obtain the interface inhibition state diagnostic identifier of the PCR reaction system.

[0051] In step S401 above, the electrode contamination warning boundary is a critical slope value obtained by repeated experiments of multiple sets of standard non-contamination detection electrodes under normal PCR amplification conditions. This value is a preset and fixed judgment benchmark used to distinguish between the electrode interface being in a normal state and a contamination suppression state. The diffusion trend slope parameter is a characteristic value obtained by gradient fitting in the early stage, which characterizes the rate of change of the phase angle diffusion coefficient with the advancement of thermal cycling. The diffusion trend slope parameter and the electrode contamination warning boundary are numerically subtracted, and the absolute value of the difference is taken. The final non-negative value is the boundary exceedance quantification value of the diffusion trend slope parameter. The boundary exceedance quantification value is used to accurately quantify the deviation of the diffusion trend slope parameter from the warning boundary. The value is positively correlated with the degree of abnormal deviation of the electrode interface.

[0052] In step S402 above, a three-level fixed inhibition level judgment standard is pre-set based on the numerical range of the boundary exceedance quantification value. The thresholds at each level are determined through an electrode interface inhibition degree gradient experiment. The first level threshold corresponds to the critical value of slight deviation, and the second level threshold corresponds to the critical value of significant deviation. The first level threshold is always less than the second level threshold. The currently obtained boundary exceedance quantification value is compared with the first level threshold and the second level threshold in turn. When the boundary exceedance quantification value is less than the first level threshold, it is judged as mild interface inhibition. When the boundary exceedance quantification value is greater than or equal to the first level threshold and less than the second level threshold, it is judged as moderate interface inhibition. When the boundary exceedance quantification value is greater than or equal to the second level threshold, it is judged as severe interface inhibition. The above three judgment results are converted into unique corresponding standardized digital codes. This code is the transient interface inhibition level code of the PCR reaction system. The transient interface inhibition level code is the unique coding information that identifies the instantaneous inhibition degree of the electrode interface within a single thermal cycle.

[0053] In step S403 above, a fixed number of continuous thermal cycles are preset as a data window for situation assessment. The number of cycles within the data window is a system preset value and remains unchanged throughout. The transient interface inhibition level code corresponding to each thermal cycle within the data window is continuously extracted. All level codes are arranged sequentially according to the order of thermal cycles to form a level code time sequence. The values ​​of adjacent level codes in the time sequence are compared one by one. When the values ​​of all adjacent level codes remain the same or continue to increase, it is determined that the electrode interface inhibition state is continuous or aggravated. When the values ​​of adjacent level codes continue to decrease, it is determined that the electrode interface inhibition state is gradually relieved. When all level codes correspond to no inhibition state, it is determined that the electrode interface is in a normal state. The above three assessment results are converted into unique state identifiers. These identifiers are the interface inhibition state diagnostic identifiers of the PCR reaction system. The interface inhibition state diagnostic identifiers are the final state judgment results obtained by comprehensively analyzing the data from multiple cycles and are directly used as the basis for subsequent cooling rate adjustments.

[0054] The beneficial effects are as follows: by using the absolute value of the difference to generate a quantitative value based on the calibration benchmark value, the slope deviation is accurately quantified, ensuring the stability and reliability of the anomaly judgment benchmark; by setting the hierarchical threshold based on the gradient experiment and generating a standardized level code, the degree of inhibition is clearly distinguished, and a standardized identification of the single-cycle state is achieved; by accumulating and analyzing the multi-cycle time series to generate diagnostic labels, the long-term state is comprehensively judged, improving the accuracy and stability of the interface inhibition state diagnosis.

[0055] In step S5 above, based on the interface inhibition state diagnostic identifier, the cooling rate parameter of the next thermal cycle in the PCR amplification process is adaptively degraded and remapped, and the mapping result is encoded as a corrected cooling rate instruction for the PCR reaction system, including the following steps: Step S501: Scale the interface inhibition state diagnostic identifier with urgency to obtain the inhibition urgency level code of the interface inhibition state diagnostic identifier. Step S502, based on a preset cooling rate compensation mapping table, performs a mapping inversion on the suppression urgency level code to obtain the reduction correction ratio coefficient of the cooling rate parameter, including: Step S5021: Discretize the suppression urgency level code to obtain the adjacent discrete node pairs that match the level code in the preset cooling rate compensation mapping table; Step S5022: Perform linear interpolation calculation based on the adjacent discrete node pairs to obtain the continuous domain correction reference value of the cooling rate parameter; Step S5023: Apply convergence limiting constraint to the continuous domain correction reference value to obtain the reduction correction ratio coefficient of the cooling rate parameter; Step S503: Based on the reduction correction ratio coefficient, the cooling rate parameter of the next thermal cycle of the PCR amplification process is reduced to obtain the intervention-state cooling rate calibration value of the PCR amplification process. Step S504: The calibration value of the intervention state cooling rate is compiled into instructions to obtain the corrected cooling rate instructions for the PCR reaction system.

[0056] In step S501 above, the interface inhibition state diagnostic identifier is the final judgment result obtained by comprehensively considering the interface inhibition state of the electrodes in multiple thermal cycles. It includes four distinct states: normal, mild inhibition, moderate inhibition, and severe inhibition. Fixed urgency levels are pre-assigned to each of the four states: normal state corresponds to the lowest urgency level, mild inhibition corresponds to the second lowest urgency level, moderate inhibition corresponds to the higher urgency level, and severe inhibition corresponds to the highest urgency level. After matching the interface inhibition state diagnostic identifier to the corresponding urgency level, it is converted into a standardized digital code according to a unified coding rule. This standardized digital code is the inhibition urgency level code of the interface inhibition state diagnostic identifier. The inhibition urgency level code is a unique code that identifies the urgency of the cooling rate adjustment. The level of the code is positively correlated with the urgency of the parameter adjustment.

[0057] In step S5021 above, the cooling rate compensation mapping table is a two-dimensional data comparison table obtained in advance through multiple sets of electrode interface suppression and control experiments. The table is arranged in ascending order of the values ​​of the suppression urgency level code. Each level code corresponds to a unique reduction correction benchmark coefficient. Taking the currently obtained suppression urgency level code as the search target, the numerical matching search is performed row by row in the cooling rate compensation mapping table. The two data nodes that are closest in value and are respectively less than and greater than the current level code are selected. The combination of these two data nodes is the adjacent discrete node pair that matches the level code. The adjacent discrete node pair is the basic data combination used to calculate the continuous correction value, which can ensure that the calculation result fits the overall numerical change law of the mapping table.

[0058] In step S5022 above, the adjacent discrete node pair includes two parts: the previous neighbor node and the next neighbor node. The level code value of the previous neighbor node is less than the current suppression urgency level code, and the level code value of the next neighbor node is greater than the current suppression urgency level code. First, the reduction correction reference coefficient, the level code value of the previous neighbor node, the reduction correction reference coefficient, and the level code value of the next neighbor node are extracted. Then, the level code value of the previous neighbor node is subtracted from the current suppression urgency level code to obtain the first difference. The coefficient value of the previous neighbor node is subtracted from the coefficient value of the next neighbor node to obtain the second difference. The level code value of the previous neighbor node is subtracted from the level code value of the next neighbor node to obtain the third difference. The first difference and the second difference are multiplied and then divided by the third difference. The result is then added to the coefficient value of the previous neighbor node. The final continuous smooth value is the continuous domain correction reference value of the cooling rate parameter. The continuous domain correction reference value is a smooth transition correction value to eliminate the jump of discrete node values.

[0059] In step S5023 above, the minimum and maximum allowable values ​​of the descent correction ratio coefficient are determined in advance through a PCR equipment operation safety test. This value range is the safe and effective range for adjusting the cooling rate of the PCR equipment. The continuous domain correction reference value is compared with the minimum and maximum allowable values ​​in turn. If the continuous domain correction reference value is less than the minimum allowable value, the minimum allowable value is directly used. If the continuous domain correction reference value is greater than the maximum allowable value, the maximum allowable value is directly used. If the continuous domain correction reference value is between the two, the original value is retained. The final value obtained after constraint processing is the descent correction ratio coefficient of the cooling rate parameter. The descent correction ratio coefficient is a standardized ratio parameter used to adjust the original cooling rate.

[0060] In step S523 above, the cooling rate parameter is the original cooling rate value preset for the next thermal cycle in the PCR amplification process. The original cooling rate parameter is multiplied by the cooling rate correction coefficient, and the resulting product value is the intervention-state cooling rate calibration value of the PCR amplification process. The intervention-state cooling rate calibration value is the target cooling rate value after precise adjustment based on the inhibition state of the electrode interface, which can be fully adapted to the actual operating state of the current electrode interface.

[0061] In step S54 above, the calibrated value of the intervention state cooling rate is a simple numerical parameter. The PCR thermal cycling control module cannot directly recognize the pure numerical parameter. According to the instruction encoding rules preset by the PCR equipment, the calibrated value of the intervention state cooling rate is converted bit by bit into an electrical signal encoding format that the equipment can recognize. The executable control instruction formed after encoding is the corrected cooling rate instruction of the PCR reaction system. The corrected cooling rate instruction is a dedicated execution instruction that is directly transmitted to the PCR thermal cycling module and drives the equipment to adjust the cooling rate.

[0062] The beneficial effects are as follows: the hierarchical scaling generates a suppression urgency level code, accurately identifying the urgency of parameter adjustment and providing a clear basis for rate correction; it accurately retrieves adjacent discrete node pairs from the mapping table, locking the interpolation reference data and ensuring that the calculation results conform to the data patterns; the step-by-step operation obtains the continuous domain correction reference value, eliminating the jumpiness of discrete data and improving the smoothness of parameter transition; the convergence limit constraint obtains the reduction correction ratio coefficient, limiting the parameter adjustment range and ensuring the safe and stable operation of the equipment; the proportional multiplication obtains the intervention state cooling rate calibration value, accurately matching the electrode interface state and improving the adaptability of rate control; and the instruction compilation generates the correction cooling rate command, realizing the precise execution of parameter adjustment and ensuring the implementation of the control effect.

[0063] In step S6 above, during the PCR amplification process after the modified cooling rate command takes effect, the re-acquired phase angle diffusion coefficient sequence is subjected to reverse trend verification to obtain the electrode interface activity recovery confirmation indicator of the PCR reaction system, including the following steps: Step S601: After the modified cooling rate command takes effect, the phase angle diffusion coefficient sequence during the PCR amplification process is collected to obtain the coefficient time-series distribution result of the PCR amplification process; Step S602: Based on the standard phase angle diffusion baseline of the PCR reaction system, the time distribution results of the coefficients are baseline normalized to obtain the calibrated time data of the PCR reaction system. Step S603: Based on the calibrated time series data, reverse feature analysis is performed on the phase angle diffusion coefficient sequence to obtain the trend change feature results of the PCR reaction system; Step S604: Perform feature adaptation evaluation on the trend change characteristic results to obtain the activity recovery degree parameter of the PCR reaction system; Step S605: Based on the activity recovery degree parameter, determine the inhibition relief status of the electrode interface of the PCR reaction system to obtain the activity recovery confirmation identifier of the electrode interface of the PCR reaction system.

[0064] In step S601 above, after the corrected cooling rate command is successfully transmitted to the PCR amplification control module and takes effect, the PCR amplification equipment completes the cooling action of the thermal cycle according to the corrected cooling rate parameters and enters a stable operating state. At the end of the annealing stage of the first complete thermal cycle after the correction command takes effect, the entire operation process of AC impedance excitation, voltage signal acquisition, phase analysis, and discreteness calculation is strictly repeated to re-acquire and calculate the complete phase angle dispersion coefficient sequence. This sequence completely retains all sampling time points, time sequence correspondences, and numerical characteristics without any data truncation, loss, or tampering. The re-acquired sequence is arranged continuously according to the original sampling time sequence to form a complete and continuous time series data set. This time series data set is the coefficient time series distribution result of the PCR amplification process. The coefficient time series distribution result is the real original measured data of the electrical state of the electrode interface after the cooling rate correction measure is implemented, which fully carries all characteristic information of the interface activity change.

[0065] In step S602 above, the standard phase angle diffusion baseline is the standard time-series reference data obtained by averaging all experimental data after the detection electrode is in an ideal normal working state without contamination, interface inhibition, or signal interference, through multiple repeated parallel experiments under the same PCR amplification conditions and the same acquisition parameters. Each time-series point of this baseline corresponds to a unique standard value, which can be used as a unified benchmark for determining interface activity. During baseline normalization, the measured value of each time-series point in the coefficient time-series distribution result is divided point by point with the standard value of the same time-series point in the standard phase angle diffusion baseline. The normalization ratio of a single point is obtained by dividing the measured value by the standard value. The normalization ratios of all time-series points are arranged sequentially according to the original sampling time sequence to form a standardized data set that eliminates system benchmark bias, operating condition bias, and electrode initial bias. This standardized data set is the calibrated time-series data of the PCR reaction system. The calibrated time-series data can eliminate all biases caused by non-interfacial activity and truly reflect the actual relative change of electrode interface activity.

[0066] In step S603 above, the reverse feature analysis takes the calibrated time series data as the core analysis object, and at the same time retrieves the abnormal phase angle dispersion coefficient sequence before the execution of the corrected cooling rate command as a comparison benchmark. The two sets of data are compared and analyzed point by point and cycle by cycle according to the same time series position and thermal cycle number. Three types of core feature information are extracted one by one. The first type is the numerical offset change feature of the calibrated time series data relative to the standard baseline. The second type is the discrete fluctuation convergence feature of the calibrated time series data itself. The third type is the trend direction feature of the data regressing to the standard baseline. The above three types of feature information are fully integrated according to the time series and cycle order to form a feature set containing all recovery-related information. This feature set is the trend change feature result of the PCR reaction system. The trend change feature result is a complete feature basis for quantifying the recovery trend of electrode interface activity after cooling rate correction.

[0067] In step S604 above, the feature adaptation evaluation compares the three core features in the trend change feature results with the standard feature information corresponding to the standard phase angle diffusion baseline in a precise dimension-by-dimensional and point-by-point matching process. The ratio of the number of feature dimensions that are completely matched to the total number of feature dimensions is calculated, and then combined with the convergence amplitude of the numerical offset for comprehensive calculation to obtain a quantitative value that comprehensively reflects the degree of interface activity recovery. This quantitative value is the activity recovery degree parameter of the PCR reaction system. The value range of the activity recovery degree parameter is between zero and one. The closer the value is to one, the higher the degree of activity recovery of the electrode interface. The closer the value is to zero, the lower the degree of recovery. The actual recovery state of the interface activity can be accurately quantified.

[0068] In step S605 above, a fixed activity recovery judgment threshold is pre-calibrated through an electrode interface gradient inhibition and recovery verification experiment. This threshold is the only standard for distinguishing whether the electrode interface inhibition state is relieved or not. The activity recovery degree parameter is directly compared with this judgment threshold. The unified rule is as follows: first, a fixed status code is assigned according to the recovery result, with 1 assigned to successful recovery and 0 assigned to failed recovery; then, a fixed instruction header is concatenated with the status code to generate a unique identifier that can be recognized by the device; when the activity recovery degree parameter is greater than or equal to the judgment threshold, it is determined that the inhibition state of the electrode interface is completely relieved and the electrode activity is successfully recovered; when the activity recovery degree parameter is less than the judgment threshold, it is determined that the inhibition state of the electrode interface is not relieved and the electrode activity is not recovered. The above-mentioned clear judgment results are converted into a unique status identifier according to the unified rule. This status identifier is the electrode interface activity recovery confirmation identifier of the PCR reaction system. The electrode interface activity recovery confirmation identifier is the final judgment result for verifying whether the cooling rate correction measure is effective, and can directly provide a status basis for subsequent PCR thermal cycling operation.

[0069] The beneficial effects are as follows: after the command takes effect, the entire acquisition process is reproduced to obtain the time-series distribution results; the corrected interface measured data is fully preserved to ensure the authenticity of the status monitoring; baseline normalization at each point generates calibration data, eliminating all-dimensional system biases and improving the accuracy of interface activity analysis; multi-dimensional reverse comparison and analysis extracts trend features, fully covering all key information of interface activity recovery and highlighting the recovery change pattern; recovery parameters are calculated by feature matching at each dimension, comprehensively quantifying the interface activity recovery status, avoiding single feature judgment bias; threshold comparison judgment generates confirmation marks, intuitively verifying the effectiveness of control measures and providing clear status basis for subsequent cyclic operation.

[0070] The flowchart provided in this embodiment is not intended to indicate that the operations of the method will be performed in any particular order, or that all operations of the method are included in every case. Furthermore, the method may include additional operations. Within the scope of the technical concept provided by the method in this embodiment, additional variations can be made to the above method.

[0071] It should be understood that in some embodiments, the components may be implemented using hardware, software, firmware, or a combination thereof. In the above embodiments, multiple steps or methods may be implemented using software or firmware stored in memory and executed by a suitable instruction execution system.

[0072] This embodiment also provides a real-time detection system for abnormal electrical signals during PCR amplification, such as... Figure 2 As shown, it includes a memory 20, a processor 10, and a computer program 21 stored on the memory 20 and running on the processor 10. When the computer program 21 is executed by the processor 10, it implements the steps of a real-time detection method for abnormal electrical signals during PCR amplification in any of the above embodiments.

[0073] The computer program 21 used to perform the operations of this invention may be assembly instructions, Instruction Set Architecture (ISA) instructions, machine instructions, machine-dependent instructions, microcode, firmware instructions, status setting data, integrated circuit configuration data, or source code or object code written in any combination of one or more programming languages ​​and procedural programming languages. The computer program 21 may execute entirely on the user's computer, partially on the user's computer, as a standalone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the latter case, the remote computer may be connected to the user's computer via any type of network, including a Local Area Network (LAN) or Wide Area Network (WAN), or may be connected to an external computer (e.g., via the Internet using an Internet service provider). In some embodiments, to perform aspects of this invention, electronic circuits, including, for example, programmable logic circuits and field-programmable gate arrays (FPGAs), may execute computer-readable program instructions using status information from computer-readable program instructions to personalize the electronic circuits.

[0074] Therefore, those skilled in the art should recognize that although numerous exemplary embodiments of the present invention have been shown and described in detail herein, many other variations or modifications conforming to the principles of the present invention can be directly determined or derived from the disclosure of the present invention without departing from the spirit and scope of the invention. Thus, the scope of the present invention should be understood and construed as covering all such other variations or modifications.

Claims

1. A method for real-time detection of abnormal electrical signals during PCR amplification, characterized in that, include: S1. At the end of the annealing stage of the PCR amplification process, the detection electrode in the PCR reaction system is excited by AC impedance to obtain the time-varying voltage response sequence of the detection electrode. S2. Using the AC impedance excitation signal applied to the detection electrode as a phase reference, perform phase lag analysis on the time-varying voltage response sequence to obtain the phase angle dispersion coefficient sequence of the PCR reaction system. S3. Perform trend analysis on the phase angle diffusion coefficient sequence to obtain the diffusion trend slope parameter of the PCR reaction system; S4. Using the preset electrode contamination warning boundary as the judgment criterion, the diffusion trend slope parameter of the PCR reaction system is critically judged to obtain the interface inhibition state diagnostic identifier of the PCR reaction system. S5. Based on the interface inhibition state diagnostic identifier, the cooling rate parameter of the next thermal cycle of the PCR amplification process is adaptively decelerated and remapped, and the mapping result is encoded as the corrected cooling rate instruction of the PCR reaction system. S6. During the PCR amplification process after the modified cooling rate command takes effect, the phase angle diffusion coefficient sequence that has been re-acquired is checked against the reverse trend to obtain the electrode interface activity recovery confirmation mark of the PCR reaction system.

2. The real-time detection method for abnormal electrical signals according to claim 1, characterized in that, At the end of the annealing phase of the PCR amplification process, the detection electrode in the PCR reaction system is subjected to AC impedance excitation to obtain the time-varying voltage response sequence of the detection electrode, including: During the thermal cycling of the PCR amplification process, the real-time temperature value of the PCR reaction system is captured in real time. Based on the real-time temperature value, the annealing stage of the PCR reaction system is identified to obtain the excitation application window identifier of the PCR reaction system. Based on the excitation application window identifier, a constant amplitude swept AC current sequence is injected into the detection electrode in the PCR reaction system to obtain the current perturbation excitation signal of the detection electrode; Under the action of the current disturbance excitation signal, the potential difference of the voltage across the detection electrode is analyzed to obtain the original voltage response waveform of the detection electrode; The original voltage response waveform is bandpass filtered to reconstruct the time-varying voltage response sequence of the detection electrode.

3. The real-time detection method for abnormal electrical signals according to claim 1, characterized in that, Using the AC impedance excitation signal applied to the detection electrode as a phase reference, phase hysteresis analysis is performed on the time-varying voltage response sequence to obtain the phase angle dispersion coefficient sequence of the PCR reaction system, including: Using the AC impedance excitation signal applied to the detection electrode as a phase reference, the time-varying voltage response sequence is coherently demodulated and separated to obtain the in-phase voltage component and the quadrature voltage component of the PCR reaction system. The in-phase voltage component and the quadrature voltage component are orthogonally phase fitted to obtain the impedance phase angle point sequence of the PCR reaction system; The phase angle deviation distribution of the PCR reaction system is obtained by differentially comparing the impedance phase angle point-by-point sequence with the preset resistive phase reference value. The phase angle deviation distribution is discretely calculated to obtain the phase angle dispersion coefficient sequence of the PCR reaction system.

4. The real-time detection method for abnormal electrical signals according to claim 1, characterized in that, Trend analysis was performed on the phase angle diffusion coefficient sequence to obtain the diffusion trend slope parameter of the PCR reaction system, including: The annealing interval is truncated from the phase angle dispersion coefficient sequence to obtain the annealing-specific fluctuation subsequence of the phase angle dispersion coefficient sequence; Based on the annealing-specific wave subsequence, the phase angle dispersion coefficient sequence is subjected to inter-cycle difference extraction to obtain the cyclic decay difference component of the phase angle dispersion coefficient sequence; Based on the cyclic decay difference component, the phase angle diffusion coefficient sequence is subjected to multi-cyclic window recursive aggregation to obtain the cumulative decay window mean of the phase angle diffusion coefficient sequence. Based on the cumulative attenuation window mean, gradient fitting is performed on the phase angle diffusion coefficient sequence to obtain the diffusion trend slope parameter of the PCR reaction system.

5. The real-time detection method for abnormal electrical signals according to claim 4, characterized in that, Based on the cumulative attenuation window mean, gradient fitting is performed on the phase angle diffusion coefficient sequence to obtain the diffusion trend slope parameter of the PCR reaction system, including: The mean of the cumulative decay window is mapped to time-series point coordinates to obtain a scattered numerical coordinate group of the mean of the cumulative decay window. Based on the scattered numerical coordinate set, the straight line element direction of the cumulative decay window mean is optimized to obtain the optimal penetration trend trajectory of the cumulative decay window mean. The attenuation direction of the optimal penetration trend trajectory is measured to obtain the diffusion trend slope parameter of the PCR reaction system.

6. The real-time detection method for abnormal electrical signals according to claim 1, characterized in that, Using a preset electrode contamination warning boundary as a criterion, the diffusion trend slope parameter of the PCR reaction system is critically determined to obtain a diagnostic indicator of the interface inhibition state of the PCR reaction system, including: Based on the preset electrode contamination warning boundary, the deviation tolerance of the diffusion trend slope parameter is compared to obtain the boundary exceedance quantification value of the diffusion trend slope parameter. Based on the quantified value of the boundary exceedance, the diffusion trend slope parameter is classified and analyzed for suppression hierarchy to obtain the transient interface suppression level code of the PCR reaction system. The transient interface inhibition level code is cumulatively analyzed to obtain the interface inhibition state diagnostic identifier of the PCR reaction system.

7. The real-time detection method for abnormal electrical signals according to claim 1, characterized in that, Based on the interface inhibition state diagnostic identifier, the cooling rate parameter of the next thermal cycle in the PCR amplification process is adaptively degraded and remapped, and the mapping result is encoded as a corrected cooling rate instruction for the PCR reaction system, including: The urgency scale of the interface inhibition state diagnostic identifier is applied to obtain the inhibition urgency level code of the interface inhibition state diagnostic identifier; Based on a preset cooling rate compensation mapping table, a mapping inversion is performed on the suppression urgency level code to obtain the reduction correction ratio coefficient of the cooling rate parameter. Based on the aforementioned reduction correction ratio, the cooling rate parameter of the next thermal cycle in the PCR amplification process is compensated for the reduction, thereby obtaining the intervention-state cooling rate calibration value of the PCR amplification process. The calibration value of the intervention-state cooling rate is compiled into instructions to obtain the corrected cooling rate instructions for the PCR reaction system.

8. The real-time detection method for abnormal electrical signals according to claim 7, characterized in that, Based on a preset cooling rate compensation mapping table, a mapping inversion is performed on the suppression urgency level code to obtain the reduction correction coefficient of the cooling rate parameter, including: Discretize the suppression urgency level code to obtain adjacent discrete node pairs that match the level code in the preset cooling rate compensation mapping table; Based on the adjacent discrete node pairs, linear interpolation is performed to obtain the continuous domain correction reference value of the cooling rate parameter. By applying convergence limiting constraints to the continuous domain correction reference value, the reduction correction ratio coefficient of the cooling rate parameter is obtained.

9. The real-time detection method for abnormal electrical signals according to claim 1, characterized in that, During the PCR amplification process after the modified cooling rate command takes effect, the re-acquired phase angle diffusion coefficient sequence is subjected to reverse trend verification to obtain the electrode interface activity recovery confirmation indicator of the PCR reaction system, including: After the modified cooling rate command takes effect, the phase angle diffusion coefficient sequence during the PCR amplification process is collected to obtain the time-series distribution results of the coefficients during the PCR amplification process; Based on the standard phase angle diffusion baseline of the PCR reaction system, the time-series distribution results of the coefficients are baseline normalized to obtain the calibrated time-series data of the PCR reaction system. Based on the calibrated time series data, reverse feature analysis was performed on the phase angle dispersion coefficient sequence to obtain the trend change characteristics of the PCR reaction system. The trend change characteristics are evaluated for feature adaptation to obtain the activity recovery parameters of the PCR reaction system. Based on the activity recovery degree parameter, the inhibition recovery status of the electrode interface of the PCR reaction system is determined to obtain the activity recovery confirmation identifier of the electrode interface of the PCR reaction system.

10. A real-time detection system for abnormal electrical signals, characterized in that, include: A processor and a memory, the memory storing computer program instructions that, when executed by the processor, implement the steps of the real-time detection method for abnormal electrical signals according to any one of claims 1-9.

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