Electrosurgical tissue impedance measurement system and method based on frequency domain analysis

Abstract

The invention discloses an electrosurgical tissue impedance measurement system and method based on frequency domain analysis. The system comprises a main energy generation module, a modulation signal generation module, an output superposition module, a signal acquisition module, an impedance calculation module and a feedback control module. The main energy generation module outputs a high-frequency main waveform for tissue cutting or blood coagulation; the modulation signal generation module is used for generating a modulation signal, and the modulation signal comprises one of a multi-cosine signal or a multi-frequency sweep-frequency signal and a pseudo-random sequence; the output superposition module is used for superposing the modulation signal into the main waveform; the signal acquisition module synchronously acquires tissue voltage and current signals after the modulation signal is loaded; the impedance calculation module is used for performing frequency domain analysis on the voltage and current signals acquired by the signal acquisition module, extracting frequency components corresponding to modulation signals by using fast Fourier transform (FFT), phase lock detection (PLL) or a time-frequency analysis algorithm, and performing frequency domain analysis on multi-cosine signals or frequency sweep signals; by comparing the amplitude ratio and the phase difference of the corresponding frequency components of the modulation signal output end and the response end, the impedance Z = RZ < Z of the measured tissue is inverted according to the known reference impedance, and Z is the impedance of the measured tissue; rZ is the amplitude of the measured impedance and reflects the magnitude of the impedance; < Z represents the phase difference between the voltage and the current; for a pseudo-random sequence signal, a matched filter is used for carrying out related detection on an input signal, and a pseudo-random sequence value is extracted so as to obtain a system signal and control data; a feedback control module adjusts the output power or the cutting / coagulation mode of the electrosurgical equipment in real time according to the tissue impedance obtained through calculation and the dynamic change of the tissue impedance; wherein the dynamic change is a group of dynamic sequence values of the impedance of the measured tissue from the time dimension. By means of the design, real-time accurate measurement can be achieved, the anti-interference capability is high, errors are small, and efficient and safe cutting / blood coagulation can be achieved.

Description

Technical Field

[0001] This invention relates to the field of medical devices, and in particular to an electrosurgical tissue impedance measurement system and method based on frequency domain analysis. Background Technology

[0002] In modern surgery, electrosurgical energy platforms and instruments are widely used for procedures such as tissue cutting, separation, coagulation and hemostasis, and vascular closure. Precise energy control can reduce the risk of tissue carbonization or adhesion. Tissue impedance, temperature, and pressure parameters are core indicators of intelligent energy control, with tissue impedance measurement being particularly crucial. This measurement significantly improves the accuracy of energy transfer, reduces thermal damage, and enhances instrument safety. With advancements in medicine and product development, increasingly sophisticated electrosurgical energy products are being used clinically, expanding their applicability and becoming indispensable tools for physicians.

[0003] In existing technologies, electrosurgical devices typically calculate tissue impedance by monitoring the voltage / current waveform transmitted to the tissue and relying on high-speed synchronous sampling and time-domain equation solving. This method has the following drawbacks: high measurement error: the high-frequency signal output by the electrosurgical device contains noise, and tissue impedance changes dynamically, leading to waveform distortion during measurement and low accuracy in time-domain calculation; high hardware cost: it requires high-speed analog-to-digital converters, complex filtering circuits, and high-performance processors to complete synchronous sampling and time-domain operations; poor real-time performance: due to the complexity of the calculation, it cannot quickly reflect real-time changes in tissue state, affecting surgical safety.

[0004] Therefore, it is necessary to find a new impedance measurement method and system to improve measurement accuracy and real-time performance, reduce hardware complexity, adapt to impedance differences in different types of tissues (such as blood vessels, nerves, fat, etc.), optimize energy control strategies, and ensure the safety and efficiency of surgical procedures. Summary of the Invention

[0005] To solve the above-mentioned technical problems, the present invention provides the following technical solution:

[0006] An electrosurgical tissue impedance measurement system based on frequency domain analysis includes: a main energy generation module, a modulation signal generation module, an output superposition module, a signal acquisition module, an impedance calculation module, and a feedback control module. The main energy generation module outputs a high-frequency main waveform for tissue cutting or coagulation. The modulation signal generation module generates a modulation signal, which includes one of a polysine signal or a multi-frequency sweep signal and a pseudo-random sequence. The output superposition module superimposes the modulation signal onto the main waveform. The signal acquisition module synchronously acquires the tissue voltage and current signals after the modulation signal is applied. The impedance calculation module performs frequency domain analysis on the voltage and current signals acquired by the signal acquisition module, using Fast Fourier Transform (FFT), Phase-Locked Detection (PLL), or time-frequency analysis algorithms to extract the frequency components corresponding to the modulation signal. For polysine signals or sweep signals, the impedance of the measured tissue Z = R is derived by comparing the amplitude ratio and phase difference of the corresponding frequency components at the output and response ends of the modulation signal, based on a known reference impedance. Z ∠Z, where Z is the impedance of the tissue being measured; R Z It is the amplitude of the measured impedance, reflecting the magnitude of the impedance; ∠Z represents the phase difference between voltage and current; for pseudo-random sequence signals, a matched filter is used to perform correlation detection on the input signal to extract pseudo-random sequence values ​​in order to obtain system signals and control data: the feedback control module adjusts the output power or cutting / coagulation mode of the electrosurgical equipment in real time according to the calculated tissue impedance and its dynamic changes, where the dynamic changes are a set of dynamic sequence values ​​of the measured tissue impedance from a time dimension.

[0007] Furthermore, the amplitude R of the measured impedance Z =(R V / R I )R Z0 , where R Z0 Given the amplitude of the modulation source impedance, R V =V1 / V2, R I = I1 / I2, where V1, V2, I1, and I2 are the amplitudes of components at a certain frequency, V1 is the amplitude of the modulation voltage, V2 is the amplitude of the response voltage, I1 is the amplitude of the modulation current, and I2 is the amplitude of the response current. The ratio R V / R I The difference in energy absorption of the reaction tissue to modulated signals of different frequencies.

[0008] Furthermore, ∠Z=Φ V -Φ I , where Φ V It is the phase of the voltage across the measured impedance, Φ I It is the phase of the current of the impedance being measured. If the phase difference is positive, it means that the voltage leads the current, i.e., an inductive load. If the phase difference is negative, it means that the current leads the voltage, i.e., a capacitive load.

[0009] Furthermore, the main energy generation module includes a high-frequency inverter circuit, whose output high-frequency waveform forms a loop with the return electrode in contact with the patient through an isolation transformer, thereby completing energy transmission.

[0010] Furthermore, the modulation signal generation module includes a digital signal processor (DSP) and a field-programmable gate array (FPGA), wherein the DSP is responsible for generating polysine signals or frequency sweep signals, and the FPGA is responsible for generating pseudo-random sequences as modulation signal sources.

[0011] Furthermore, the digital modulation signal generated by the DSP / FPGA is output as an analog signal by the digital-to-analog converter (DAC), and then coupled to the main waveform output port through the output superposition module to superimpose the modulation signal onto the main waveform.

[0012] Furthermore, the signal acquisition module uses a high-precision differential voltage sensor and a current sensor to simultaneously acquire the voltage and current waveforms of the tissue end after the modulation signal is applied. The bandwidth of the two sensors is greater than 100kHz. The acquired analog signal is digitized by a high-resolution analog-to-digital converter (ADC) with a sampling rate of not less than 100kHz to ensure the capture of the frequency components of the modulation signal.

[0013] Furthermore, the impedance calculation module, including a low-cost microcontroller or DSP, performs frequency domain analysis and impedance calculation on the digital signal obtained by ADC sampling.

[0014] Furthermore, an electrosurgical device includes the aforementioned frequency domain analysis-based electrosurgical tissue impedance measurement system.

[0015] Furthermore, a method for measuring electrosurgical tissue impedance based on frequency domain analysis is also protected, the method comprising the following steps:

[0016] Generate high-frequency master waveform: The high-frequency master waveform for tissue cutting or coagulation is output through the main energy generation module;

[0017] Generate a modulated signal: A modulated signal is generated by a modulation signal generation module. The modulated signal includes one of a polysine signal or a multi-frequency sweep signal and a pseudo-random sequence.

[0018] Modulation signal superposition: The modulation signal is superimposed onto the main waveform through the output superposition module;

[0019] Signal acquisition: The signal acquisition module synchronously acquires the tissue voltage and current signals after the modulation signal is applied;

[0020] Frequency Domain Analysis and Impedance Calculation: The impedance calculation module performs frequency domain analysis on the voltage and current signals acquired by the signal acquisition module. It uses Fast Fourier Transform (FFT), Phase-Locked Detection (PLL), or time-frequency analysis algorithms to extract the frequency components corresponding to the modulation signal. For polysine signals or swept-frequency signals, by comparing the amplitude ratio and phase difference of the corresponding frequency components at the modulation signal output and response terminals, the impedance of the measured tissue Z = R is derived based on the known reference impedance. Z ∠Z, where Z is the impedance of the tissue being measured; R Z It represents the amplitude of the measured impedance, reflecting the magnitude of the impedance; ∠Z represents the phase difference between voltage and current; for pseudo-random sequence signals, a matched filter is used to perform correlation detection on the input signal, extracting the pseudo-random sequence value to obtain system signals and control data.

[0021] Feedback control: The feedback control module adjusts the output power or cutting / coagulation mode of the electrosurgical equipment in real time based on the calculated tissue impedance and its dynamic changes.

[0022] The technical solution of this application has the following beneficial effects:

[0023] Real-time accurate measurement: By introducing polysine or sweep frequency modulation signals into the output waveform, real-time monitoring of tissue impedance is achieved by updating it every millisecond, enabling rapid response to changes in tissue state (such as increased impedance during coagulation).

[0024] Broadband impedance analysis: Multi-frequency sweep signals can obtain the broadband impedance characteristics of tissues near the dominant frequency, which helps to identify tissue types and lesion characteristics.

[0025] Enhanced anti-interference capability: The modulation signal is orthogonal to the main operating frequency and the spectrum is separated, which can avoid mutual coupling interference; the pseudo-random sequence signal has spread spectrum characteristics, which effectively suppresses electromagnetic noise, so that the control signal can still be reliably measured and transmitted in a strong interference environment.

[0026] Reduce measurement errors: Frequency domain analysis methods naturally filter out time domain noise, which can significantly reduce impedance measurement errors; impedance calculation can be completed in a single modulation cycle, adapting to dynamic changes during tissue solidification.

[0027] Safe and efficient cutting / coagulation: The system dynamically adjusts the output power based on real-time impedance feedback to prevent thermal damage caused by instrument overheating, ensuring the safety and efficiency of the cutting or coagulation process. Attached Figure Description

[0028] The above is merely an overview of the technical solution of the present invention. In order to better understand the technical means of the present invention, the present invention will be further described in detail below with reference to the accompanying drawings and specific embodiments.

[0029] Figure 1This is a schematic diagram of the electrosurgical tissue impedance measurement system based on frequency domain analysis of the present invention. Detailed Implementation

[0030] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0031] An electrosurgical tissue impedance measurement system based on frequency domain analysis includes: a main energy generation module, a modulation signal generation module, an output superposition module, a signal acquisition module, an impedance calculation module, and a feedback control module. The main energy generation module outputs a high-frequency main waveform for tissue cutting or coagulation. The modulation signal generation module generates a modulation signal, which includes one of a polysine signal or a multi-frequency sweep signal and a pseudo-random sequence. The output superposition module superimposes the modulation signal onto the main waveform. The signal acquisition module synchronously acquires the tissue voltage and current signals after the modulation signal is applied. The impedance calculation module performs frequency domain analysis on the voltage and current signals acquired by the signal acquisition module, using Fast Fourier Transform (FFT), Phase-Locked Detection (PLL), or time-frequency analysis algorithms to extract the frequency components corresponding to the modulation signal. For polysine signals or sweep signals, the impedance of the measured tissue Z = R is derived by comparing the amplitude ratio and phase difference of the corresponding frequency components at the output and response ends, based on a known reference impedance. Z ∠Z, where Z is the impedance of the tissue being measured, and R Z The amplitude of the measured impedance reflects the magnitude of the impedance, and ∠Z represents the phase difference between voltage and current. For pseudo-random sequence signals, a matched filter is used to perform correlation detection on the input signal to extract pseudo-random sequence values, thereby obtaining system signals and control data. The feedback control module adjusts the output power or cutting / coagulation mode of the electrosurgical equipment in real time based on the calculated tissue impedance and its dynamic changes. The dynamic changes refer to a set of dynamic sequence values ​​of the measured tissue impedance from a time perspective. The main energy generation module includes a high-frequency inverter circuit, whose output high-frequency waveform forms a loop with the return electrode in contact with the patient through an isolation transformer, thereby completing energy transfer.

[0032] Furthermore, the amplitude R of the measured impedance Z =(R V / R I )R Z0 , among which, among which, R Z0 Given the amplitude of the modulation source impedance, R V =V1 / V2, R I= I1 / I2, where V1, V2, I1, and I2 are the amplitudes of components at a certain frequency, V1 is the amplitude of the modulation voltage, V2 is the amplitude of the response voltage, I1 is the amplitude of the modulation current, and I2 is the amplitude of the response current. The ratio R V / R I The difference in energy absorption of the reaction tissue to modulated signals of different frequencies.

[0033] Furthermore, ∠Z=Φ V -Φ I , where Φ V It is the phase of the voltage across the measured impedance, Φ I It is the phase of the current of the impedance being measured. If the phase difference is positive, it means that the voltage leads the current, i.e., an inductive load. If the phase difference is negative, it means that the current leads the voltage, i.e., a capacitive load.

[0034] The modulation signal generation module includes a digital signal processor (DSP) and a field-programmable gate array (FPGA). The DSP is responsible for generating polysine signals or frequency sweep signals, while the FPGA is responsible for generating pseudo-random sequences as the modulation signal source. Preferably, the pseudo-random sequence is a Gold code. The digital modulation signal generated by the DSP / FPGA is output as an analog signal via a digital-to-analog converter (DAC). After output, it is filtered by a low-pass filter to suppress high-frequency harmonics, and then coupled to the main waveform output port through an isolation transformer and an output superposition module to superimpose the modulation components onto the main waveform.

[0035] The technical solution of this application supports multiple modulation signal formats:

[0036] Multisine signal: Two or more small-amplitude sinusoidal modulation components are generated near the main operating frequency for real-time impedance measurement.

[0037] Multi-frequency sweep signal: Using linear frequency modulation (LFM) or frequency hopping, it continuously scans within a given frequency range to obtain wideband impedance characteristics.

[0038] Pseudo-random sequences: used for anti-interference communication or spread spectrum measurement to improve the system's anti-EMI capability.

[0039] The main parameters of the modulated signal include:

[0040] Frequency offset: The offset relative to the main operating frequency, such as an increase or decrease of a few kilohertz around the main frequency of 50kHz.

[0041] Modulation depth: The ratio of the amplitude of the modulating signal to the amplitude of the main wave, generally not exceeding 10%.

[0042] Pseudo-random sequence parameters: Gold codes, m-sequences, etc. can be used, and the length and chip rate can be configured according to system requirements; a Barker code synchronization header is usually added for frame positioning.

[0043] The signal acquisition module employs high-precision differential voltage and current sensors to simultaneously acquire the voltage and current waveforms at the tissue terminals after the modulation signal is applied. Both sensors have bandwidths greater than 100kHz. The acquired analog signals are digitized by a high-resolution analog-to-digital converter (ADC) with a sampling rate of at least 100kHz to ensure the capture of the frequency components of the modulation signal. The acquired digital signals are then used for subsequent analysis. The high-precision ADC simultaneously acquires the output voltage and current after the modulation signal is applied, ensuring the capture of all modulation components. The ADC samples synchronously with the modulation signal for subsequent frequency domain analysis.

[0044] The impedance calculation module, including a low-cost microcontroller or DSP, performs frequency domain analysis and impedance calculation on the digital signal obtained from ADC sampling. Specifically, the acquired voltage and current signals are processed as follows:

[0045] Spectrum separation: Extracting the frequency components corresponding to the superimposed modulated signal using FFT;

[0046] Amplitude and phase analysis of the measured impedance: Calculate the amplitude ratio and phase difference of each frequency component; if the amplitude R of the modulation source impedance is known. Z0 The tissue impedance R is then calculated based on the amplitude ratio and the reference impedance. Z =(R V / R I )R Z0 , where R V =V1 / V2, R I = I1 / I2, where V1, V2, I1, and I2 are the amplitudes of components at a certain frequency, V1 is the amplitude of the modulation voltage, V2 is the amplitude of the response voltage, I1 is the amplitude of the modulation current, and I2 is the amplitude of the response current. The ratio R V / R I The study investigates the differences in energy absorption by tissues to modulated signals of different frequencies. Phase difference calculation involves extracting the phase difference using a phase-locked loop (PLL) or Hilbert transform. The amplitude of the modulated signal is used as a reference to define the starting point for phase difference measurement. The attenuation or enhancement of the response signal's amplitude reflects the tissue's energy absorption characteristics, indirectly affecting the dynamic change of the phase difference. A complex expression for impedance is constructed using the signal amplitude ratio and phase difference, enabling high-precision measurement of the impedance phase angle. Through the aforementioned frequency domain analysis method, the amplitude and phase information of the tissue impedance are obtained, thus allowing the inversion of the tissue impedance.

[0047] The feedback control module uses impedance calculation results to dynamically adjust the output parameters of the electrosurgical equipment. Based on real-time impedance changes, such as a sudden increase in impedance during cutting, the system automatically reduces output power or changes the working mode to match the tissue condition and achieve adaptive tissue protection.

[0048] The electrosurgical tissue impedance measurement system based on frequency domain analysis described in this application begins operation after system initialization, including the following steps:

[0049] Initialization: When the system starts, it loads a pseudo-random sequence (such as Gold code) and a frequency sweep table, calibrates and records the reference impedance value.

[0050] Real-time monitoring: The collected voltage V and current I signals are processed every millisecond, and impedance is analyzed based on polysine modulation signals to achieve high-frequency real-time impedance updates.

[0051] Frequency sweep analysis: A multi-frequency sweep measurement is initiated approximately every 40 milliseconds, performing point-by-point excitation and measurement on the frequency band near the dominant frequency, and updating the tissue impedance spectrum database. Abrupt impedance changes may indicate instrument adhesion or other tissue abnormalities.

[0052] Control Communication: PN codes are used to encode and transmit the foot switch status and output power setting. At the receiving end, these codes are decoded using a matched filter and fed back to the DSP for output adjustment. This communication method has error correction capabilities and can reliably transmit control commands even in environments with strong electromagnetic interference.

[0053] This application also discloses a method for measuring electrosurgical tissue impedance based on frequency domain analysis, the method comprising the following steps:

[0054] Generate high-frequency master waveform: The high-frequency master waveform for tissue cutting or coagulation is output through the main energy generation module;

[0055] Generate adjustment signal: Generate a modulation signal through a modulation signal generation module. The modulation signal includes one of a polysine signal or a multi-frequency sweep signal and a pseudo-random sequence.

[0056] Modulation signal superposition: The modulation signal is superimposed onto the main waveform through the output superposition module;

[0057] Signal acquisition: The signal acquisition module synchronously acquires the tissue voltage and current signals after the modulation signal is applied;

[0058] Frequency Domain Analysis and Impedance Calculation: The impedance calculation module performs frequency domain analysis on the voltage and current signals acquired by the signal acquisition module. It uses Fast Fourier Transform (FFT), Phase-Locked Detection (PLL), or time-frequency analysis algorithms to extract the frequency components corresponding to the modulated signal. For polysine signals or swept-frequency signals, the impedance of the measured tissue Z = R is derived by comparing the amplitude ratio and phase difference of the corresponding frequency components at the output and response terminals, based on the known reference impedance. Z ∠Z, where Z is the impedance of the tissue being measured, and R ZThis represents the amplitude of the measured impedance, reflecting its magnitude. ∠Z represents the phase difference between voltage and current. For pseudo-random sequence signals, a matched filter is used to perform correlation detection on the input signal, extracting the pseudo-random sequence values ​​to obtain system signals and control data.

[0059] Feedback control: Based on the calculated tissue impedance and its dynamic changes, the output power or cutting / coagulation mode of the electrosurgical equipment is adjusted in real time. The dynamic changes are a set of dynamic sequence values ​​of the measured tissue impedance from a time perspective.

[0060] Example 1: Real-time impedance monitoring of multi-cosine modulated signals

[0061] Parameter design: Assuming the main operating frequency is 50kHz, two sinusoidal modulation components can be generated near this frequency, with offsets of, for example, –2kHz (48kHz) and +2kHz (52kHz), and a modulation depth of 10%. The two sinusoids are output in phase. The acquisition time at each frequency point must meet the bandwidth requirements to ensure the accuracy of spectrum separation.

[0062] Implementation: The DSP generates two sine waves at the required frequencies, which are then converted by the DAC and superimposed onto the main waveform. At the acquisition end, the response signals of the tissue terminal voltages V(f1), V(f2) and currents I(f1), I(f2) at the two frequencies are obtained respectively.

[0063] Impedance calculation: Calculate the voltage amplitude ratio, current amplitude ratio, and phase difference of the two signals respectively. Based on the known reference impedance, calculate the impedance amplitude Z of the two signals respectively. Construct a complex expression for the impedance using the signal amplitude ratio and phase difference to achieve high-precision measurement of the impedance phase angle.

[0064] Function: This method achieves real-time impedance measurement through two narrowband signals, and the measurement result can be updated every millisecond; the use of dual frequency points can avoid specific noise frequency bands (such as 50 / 60Hz power grid harmonics) and improve the ability to resist narrowband interference.

[0065] Example 2: Broadband Impedance Analysis of Multi-Frequency Sweep Signals

[0066] Parameter design: The main frequency is 50kHz, with a configurable sweep range of 45kHz to 55kHz, covering ±5kHz of the main frequency. The frequency step can be selected, for example, 100Hz. Too small a step results in excessive computation, while too large a step may miss details. The dwell time at each frequency point must be sufficiently stable (depending on the system bandwidth). Linear frequency modulation (LFM) or discrete frequency hopping can be used to avoid the nonlinear effects of continuous frequency sweeping. Sufficient signal dynamic range must be ensured to detect even slight impedance changes.

[0067] Implementation: The DSP outputs sine waves of corresponding frequencies sequentially according to preset frequency points. After each frequency point is output, the voltage V(f) and current I(f) signals at the tissue end are simultaneously acquired and saved. After all frequency points are completed, the impedance data at different frequencies are fitted in the control unit to obtain the impedance-frequency curve.

[0068] Function: Multi-frequency sweeps can obtain broadband impedance characteristics of tissues, comprehensively reflecting changes in tissue electrical properties, which helps support the classification and diagnosis of tissue pathological states (e.g., observing a significant increase in high-frequency impedance during coagulation). Slower sweep cycles (e.g., once every 40 ms) are sufficient to cover the dynamic changes in tissue physiological processes.

[0069] Example 3: Anti-interference communication control for pseudo-random sequence signals

[0070] Parameter design: Gold code is used as the pseudo-random modulation signal, for example, a Gold code of length 127. The chip rate is selected according to the system design (e.g., hundreds of kHz to MHz). Binary phase shift keying (BPSK) modulation is used, and the modulation depth can be set to, for example, 5%. A synchronization header (e.g., a 13-bit Barker code, approximately 130 μs) is added before each frame for frame synchronization.

[0071] Implementation: The FPGA generates a Gold code sequence, which is then superimposed onto the main waveform for modulation. At the receiver, a matched filter is used to capture the autocorrelation peaks of the PN code, and the encoded information is demodulated. The encoded information can carry control commands such as the foot switch status and target power, and simple error correction coding is used to improve anti-interference capability.

[0072] Functions: The noise-like characteristics of Gold codes help suppress environmental electromagnetic interference, enabling stable communication and improving the signal-to-noise ratio by more than 20dB. The code also supports multiple access communication, facilitating collaborative work among multiple devices, thereby improving the reliability and scalability of the system in electromagnetic interference environments.

[0073] To meet the safety and compatibility requirements of medical devices, this system also adopts the following safety design:

[0074] Electrical safety: The amplitude of the modulated signal is far below the human safety threshold; the modulated signal output is isolated from the main circuit by means of opto-isolation to prevent the modulated signal current from flowing into the patient circuit; the system leakage current meets the relevant safety standards.

[0075] Electromagnetic compatibility: The modulation signal is filtered by a low-pass filter before output to suppress high-frequency harmonics; the modulation module is physically isolated from the main circuit and is arranged with a shielded structure to reduce electromagnetic interference.

[0076] In summary, this method, by superimposing a known modulation signal onto the electrosurgical energy output waveform and using frequency domain analysis techniques to separate and analyze the signal, enables real-time and accurate measurement of tissue impedance. This significantly improves the anti-interference capability and real-time performance of the measurement system and effectively reduces hardware costs.

[0077] Other embodiments of the invention will readily occur to those skilled in the art upon consideration of the invention disclosed in the specification and embodiments. This application is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein. The specification and embodiments are to be considered exemplary only, and the true scope and spirit of the invention are indicated by the claims.

[0078] It should be understood that the present invention is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. An electrosurgical tissue impedance measurement system based on frequency domain analysis, comprising: The system includes a main energy generation module, a modulation signal generation module, an output superposition module, a signal acquisition module, an impedance calculation module, and a feedback control module. The main energy generation module outputs a high-frequency main waveform for tissue cutting or coagulation. The modulation signal generation module generates a modulation signal, which includes one of a polysine signal or a multi-frequency sweep signal and a pseudo-random sequence. The output superposition module superimposes the modulation signal onto the main waveform. The signal acquisition module synchronously acquires the tissue voltage and current signals after the modulation signal is applied. The impedance calculation module performs frequency domain analysis on the voltage and current signals acquired by the signal acquisition module, using Fast Fourier Transform (FFT), Phase-Locked Detection (PLL), or time-frequency analysis algorithms to extract the frequency components corresponding to the modulation signal. For polysine signals or sweep signals, by comparing the amplitude ratio and phase difference of the corresponding frequency components at the output and response ends of the modulation signal, the impedance of the measured tissue Z = R is derived based on the known reference impedance. Z ∠Z, where Z is the impedance of the tissue being measured; R Z It is the amplitude of the measured impedance, reflecting the magnitude of the impedance; ∠Z represents the phase difference between voltage and current; for pseudo-random sequence signals, a matched filter is used to perform correlation detection on the input signal to extract pseudo-random sequence values ​​in order to obtain system signals and control data: the feedback control module adjusts the output power or cutting / coagulation mode of the electrosurgical equipment in real time according to the calculated tissue impedance and its dynamic changes, where the dynamic changes are a set of dynamic sequence values ​​of the measured tissue impedance from a time dimension.

2. The electrosurgical tissue impedance measurement system based on frequency domain analysis as described in claim 1, characterized in that, The amplitude R of the measured impedance Z =(R V / R I )R Z0 , where R Z0 Given the modulation source impedance, R V =V1 / V2, R I = I1 / I2, where V1, V2, I1, and I2 are the amplitudes of components at a certain frequency, V1 is the amplitude of the modulation voltage, V2 is the amplitude of the response voltage, I1 is the amplitude of the modulation current, and I2 is the amplitude of the response current. The ratio R V / R I The difference in energy absorption of the reaction tissue to modulated signals of different frequencies.

3. The electrosurgical tissue impedance measurement system based on frequency domain analysis as described in claim 1, characterized in that, ∠Z=Φ V -Φ I , where Φ V It is the phase of the voltage across the measured impedance, Φ I It is the phase of the current of the impedance being measured. If the phase difference is positive, it means that the voltage leads the current, i.e., an inductive load. If the phase difference is negative, it means that the current leads the voltage, i.e., a capacitive load.

4. The electrosurgical tissue impedance measurement system based on frequency domain analysis as described in any one of claims 1-3, characterized in that, The main energy generation module includes a high-frequency inverter circuit, whose output high-frequency waveform forms a loop with the return electrode in contact with the patient through an isolation transformer, thereby completing energy transmission.

5. The electrosurgical tissue impedance measurement system based on frequency domain analysis as described in any one of claims 1-3, characterized in that, The modulation signal generation module includes a digital signal processor (DSP) and a field-programmable gate array (FPGA), wherein the DSP is responsible for generating polysine signals or frequency sweep signals, and the FPGA is responsible for generating pseudo-random sequences as modulation signal sources.

6. The electrosurgical tissue impedance measurement system based on frequency domain analysis as described in claim 5, characterized in that, The digital modulation signal generated by the DSP / FPGA is output as an analog signal by the digital-to-analog converter (DAC). After output, it is filtered by a low-pass filter to suppress high-frequency harmonics, and coupled to the main waveform output port through an isolation transformer and an output superposition module to superimpose the modulation component onto the main waveform.

7. The electrosurgical tissue impedance measurement system based on frequency domain analysis as described in any one of claims 1-3, characterized in that, The signal acquisition module uses a high-precision differential voltage sensor and a current sensor to simultaneously acquire the voltage and current waveforms of the tissue end after the modulation signal is applied. The bandwidth of the two sensors is greater than 100kHz. The acquired analog signal is digitized by a high-resolution analog-to-digital converter (ADC) with a sampling rate of not less than 100kHz to ensure the capture of the frequency components of the modulation signal.

8. The electrosurgical tissue impedance measurement system based on frequency domain analysis as described in any one of claims 1-3, characterized in that, Impedance calculation module, including low-cost microcontroller or DSP, performs frequency domain analysis and impedance calculation on the digital signal obtained by ADC sampling.

9. An electrosurgical device comprising an electrosurgical tissue impedance measurement system based on frequency domain analysis as described in any one of claims 1-8.

10. A method for measuring electrosurgical tissue impedance using the frequency domain analysis-based electrosurgical tissue impedance measurement system as described in any one of claims 1-8, comprising the following steps: Generate high-frequency master waveform: The high-frequency master waveform for tissue cutting or coagulation is output through the main energy generation module; Generate a modulated signal: A modulated signal is generated by a modulation signal generation module. The modulated signal includes one of a polysine signal or a multi-frequency sweep signal and a pseudo-random sequence. Modulation signal superposition: The modulation signal is superimposed onto the main waveform through the output superposition module; Signal acquisition: The signal acquisition module synchronously acquires the tissue voltage and current signals after the modulation signal is applied; Frequency Domain Analysis and Impedance Calculation: The impedance calculation module performs frequency domain analysis on the voltage and current signals acquired by the signal acquisition module. It uses Fast Fourier Transform (FFT), Phase-Locked Detection (PLL), or time-frequency analysis algorithms to extract the frequency components corresponding to the modulation signal. For polysine signals or swept-frequency signals, by comparing the amplitude ratio and phase difference of the corresponding frequency components at the modulation signal output and response terminals, the impedance of the measured tissue Z = R is derived based on the known reference impedance. Z ∠Z, where Z is the impedance of the tissue being measured; R Z It represents the amplitude of the measured impedance, reflecting the magnitude of the impedance; ∠Z represents the phase difference between voltage and current; for pseudo-random sequence signals, a matched filter is used to perform correlation detection on the input signal, extracting the pseudo-random sequence value to obtain system signals and control data; Feedback control: The feedback control module adjusts the output power or cutting / coagulation mode of the electrosurgical equipment in real time based on the calculated tissue impedance and its dynamic changes.

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