Implantable closed-loop neurostimulation system and its stimulation parameter modulation methods

Abstract

This application provides an implantable closed-loop neurostimulation system and a method for regulating its stimulation parameters. The method includes: measuring impedance by applying a dual-frequency test current to multiple electrodes to obtain a first composite impedance signal; obtaining a three-dimensional spatial impedance gradient based on the spatial coordinates of each electrode and its corresponding impedance value; regulating the stimulation parameters of an electrical stimulation pulse according to the three-dimensional spatial impedance gradient and a first impedance change rate determined based on the first composite impedance signal; measuring impedance during a first time period after applying the electrical stimulation pulse to obtain a second composite impedance signal, and acquiring a first local field potential signal of the region where the multiple electrodes are located during the first time period; and calibrating the regulated stimulation parameters when the second composite impedance signal satisfies a first condition and / or the first local field potential signal satisfies a second condition.

Description

Technical Field

[0001] This application relates to the field of neuromodulation technology, and more specifically, to an implantable closed-loop neurostimulation system and a method for regulating its stimulation parameters. Background Technology

[0002] Epilepsy is a neurological disorder that typically requires long-term neuromodulation therapy. Implantable closed-loop neurostimulation systems are widely used because they can respond in real-time to the patient's brain electrical activity. Existing implantable systems usually detect abnormal neural activity based on electrophysiological signals such as local field potentials (LFP) or high-frequency oscillations (HFOs) and trigger stimulation intervention when a progenitor event is detected.

[0003] However, LFP signals are susceptible to interference from electromyography, eye movements, and device artifacts, resulting in a high false trigger rate in low signal-to-noise ratio environments. Furthermore, LFP reflects the result of neuronal population firing, not early pathological changes in the tissue microenvironment, leading to a delay in intervention timing. Additionally, existing systems typically use fixed stimulation parameters (e.g., current intensity, electrode combination), making it difficult to adapt to individual patient differences and dynamic disease progression.

[0004] Therefore, there is an urgent need for an implantable closed-loop neural stimulation system that can adaptively modulate closed-loop neural activity based on changes in tissue impedance. Summary of the Invention

[0005] This application addresses the shortcomings of existing methods by proposing an implantable closed-loop neurostimulation system and a method for regulating its stimulation parameters. The aim is to solve the problem that existing implantable systems cannot perform adaptive closed-loop neurostimulation based on changes in tissue impedance.

[0006] In a first aspect, embodiments of this application provide an implantable closed-loop neurostimulation system, comprising:

[0007] Multiple electrodes implanted in the brain;

[0008] A dual-frequency impedance measurement circuit is used to apply a dual-frequency test current to the multiple electrodes and collect the response voltage before applying an electrical stimulation pulse to the multiple electrodes to generate a first composite impedance signal, and to apply the dual-frequency test current to the multiple electrodes again and collect the response voltage during a first time period after the electrical stimulation pulse ends to generate a second composite impedance signal.

[0009] A local field potential recording circuit is used to synchronously acquire the first local field potential signal of the region where the multiple electrodes are located during the first time period after the end of the electrical stimulation pulse.

[0010] The processing module is used to process the first composite impedance signal to obtain the first impedance change rate;

[0011] The spatial gradient calculation module is used to obtain the three-dimensional spatial impedance gradient based on the spatial coordinates of each electrode and the corresponding impedance value, wherein the spatial coordinates of the multiple electrodes are pre-stored in the storage unit;

[0012] The stimulation parameter control module is used to control the stimulation parameters of the electrical stimulation pulse based on the first impedance change rate and the three-dimensional spatial impedance gradient.

[0013] A neural stimulation driving circuit is used to output electrical stimulation pulses to the plurality of electrodes according to the adjusted stimulation parameters;

[0014] The calibration module is used to calibrate the modulated stimulation parameters when the second composite impedance signal meets a first condition and / or the first local field potential signal meets a second condition.

[0015] Secondly, embodiments of this application provide a method for regulating stimulation parameters of an implantable closed-loop neurostimulation system, wherein the regulation method is performed by the implantable closed-loop neurostimulation system as described in the first aspect, and the method includes:

[0016] The first composite impedance signal is obtained by applying a dual-frequency test current to the multiple electrodes and performing impedance measurement.

[0017] Based on the spatial coordinates of each electrode and its corresponding impedance value, a three-dimensional spatial impedance gradient is obtained.

[0018] The stimulation parameters of the electrical stimulation pulse are adjusted based on the three-dimensional spatial impedance gradient and the first impedance change rate determined based on the first composite impedance signal.

[0019] Impedance measurement is performed during the first time period after an electrical stimulation pulse is applied based on the regulated stimulation parameters to obtain a second composite impedance signal, and a first local field potential signal is obtained in the region where the plurality of electrodes are located during the first time period.

[0020] When the second composite impedance signal satisfies the first condition and / or the first local field potential signal satisfies the second condition, the modulated stimulation parameters are calibrated.

[0021] Thirdly, embodiments of this application also disclose a signal processing system, including the implantable closed-loop neurostimulation system as described in the first aspect.

[0022] Fourthly, embodiments of this application also disclose a computer-readable storage medium storing a computer program that, when executed by a processor, implements one or more of the control methods described in the embodiments of the second aspect of this application.

[0023] Fifthly, embodiments of this application also disclose a computer program product, including a computer program that, when executed by a processor, implements one or more of the control methods described in the embodiments of the second aspect of this application.

[0024] The beneficial technical effects of the technical solutions provided in this application include:

[0025] By processing the composite impedance signal obtained from dual-frequency test current to determine the rate of impedance change, changes in the tissue microenvironment prior to the onset of abnormal neural activity are identified, thereby improving the sensitivity of abnormal neural activity detection. Furthermore, the relative phase difference between multiple electrodes can be modulated using a three-dimensional spatial impedance gradient to achieve focused stimulation in a specific direction. Simultaneously, the stimulation current intensity is dynamically adjusted in conjunction with the rate of impedance change, enabling precise spatiotemporal coordinated intervention. Finally, calibration is performed after electrical stimulation to optimize stimulation parameters and avoid the accumulation of ineffective stimulation, thus forming an effective and complete closed-loop control scheme.

[0026] Additional aspects and advantages of this application will be set forth in part in the description which follows, and will become apparent from the description or may be learned by practice of this application. Attached Figure Description

[0027] The above and / or additional aspects and advantages of this application will become apparent and readily understood from the following description of the embodiments taken in conjunction with the accompanying drawings, wherein:

[0028] Figure 1 This is a schematic diagram of the structure of an implantable closed-loop neurostimulation system provided in an embodiment of this application;

[0029] Figure 2 A flowchart illustrating a method for adjusting stimulation parameters of an implantable closed-loop neurostimulation system provided in this application embodiment;

[0030] Figure 3 This is a schematic diagram of the signal processing system provided in an embodiment of this application. Detailed Implementation

[0031] The embodiments of this application are described below with reference to the accompanying drawings. It should be understood that the embodiments described below with reference to the accompanying drawings are exemplary descriptions for explaining the technical solutions of the embodiments of this application, and do not constitute a limitation on the technical solutions of the embodiments of this application.

[0032] Those skilled in the art will understand that, unless specifically stated otherwise, the terms "described" and "the" as used herein may also include plural forms. It should be further understood that the term "comprising" as used in this application's specification means the presence of the stated features, integers, steps, operations, elements, and / or components, but does not exclude implementations of other features, information, data, steps, operations, elements, components, and / or combinations thereof supported by this art. It should be understood that when we say an element is "connected" or "coupled" to another element, the element may be directly connected or coupled to the other element, or it may mean that the element and the other element are connected through an intermediate element. Furthermore, "connected" or "coupled" as used herein may include wireless connections or wireless coupling. The term "and / or" as used herein refers to at least one of the items defined by the term; for example, "A and / or B" may be implemented as "A," or as "B," or as "A and B."

[0033] To make the objectives, technical solutions, and advantages of this application clearer, the embodiments of this application will be described in further detail below with reference to the accompanying drawings.

[0034] Existing implantable systems typically detect abnormal neural activity based on electrophysiological signals such as local field potentials (LFP) or high-frequency oscillations (HFOs) and trigger stimulation intervention when a precursor event is detected.

[0035] However, LFP signals are susceptible to interference from electromyography, eye movements, and device artifacts, resulting in a high false trigger rate in low signal-to-noise ratio environments. Furthermore, LFP reflects the result of neuronal population firing, not early pathological changes in the tissue microenvironment, leading to a delay in intervention timing. Additionally, existing systems typically use fixed stimulation parameters (e.g., current intensity, electrode combination), making it difficult to adapt to individual patient differences and dynamic disease progression.

[0036] Therefore, existing implantable systems cannot perform adaptive closed-loop neuromodulation based on changes in tissue impedance.

[0037] In view of the shortcomings of the prior art, the embodiments of this application aim to solve the following technical problems:

[0038] 1. How to improve the sensitivity of abnormal neural activity detection and avoid the problem of delayed intervention;

[0039] 2. How to achieve coordinated control of stimulation current intensity and stimulation direction based on the time-varying nature and three-dimensional spatial distribution characteristics of impedance;

[0040] 3. After applying electrical stimulation, how to accurately assess the intervention effect and dynamically calibrate the stimulation parameters to form a complete closed loop of regulation.

[0041] The technical solution of this application and how it solves the above-mentioned technical problems are described in detail below with specific embodiments. It should be noted that the following embodiments can be referenced, borrowed, or combined with each other, and the same terms, similar features, and similar implementation steps in different embodiments will not be described again.

[0042] The implantable closed-loop neurostimulation system and its stimulation parameter control method proposed in this application will be described in detail below with reference to the accompanying drawings.

[0043] In some embodiments, an implantable closed-loop neurostimulation system is provided, such as Figure 1 As shown, the implantable closed-loop neurostimulation system 10 includes: multiple electrodes 11 implanted in the cranium, a dual-frequency impedance measurement circuit 12, a local field potential recording circuit 13, a sliding window differential processing module 14, a spatial gradient calculation module 15, a stimulation parameter control module 16, a neurostimulation driving circuit 17, and a calibration module 18, as well as a storage unit. The storage unit pre-stores the spatial coordinates of the multiple electrodes 11. The input terminals of the dual-frequency impedance measurement circuit 12 and the local field potential recording circuit 13 are respectively connected to the multiple electrodes 11. The input terminal of the sliding window differential processing module 14 is connected to the output terminal of the dual-frequency impedance measurement circuit 12. The input terminal of the spatial gradient calculation module 15 is connected to the dual-frequency impedance measurement circuit 12 and the storage unit. The first input terminal of the stimulation parameter control module 16 is connected to the output terminal of the sliding window differential processing module 14, and the second input terminal of the stimulation parameter control module 16 is connected to the output terminal of the spatial gradient calculation module 15. The output terminal of the stimulation parameter control module 16 is connected to the input terminal of the neurostimulation driving circuit 17, and the output terminal of the neurostimulation driving circuit 17 is connected to the multiple electrodes 11. The first input terminal of the calibration module 18 is connected to the dual-frequency impedance measurement circuit 12, and the second input terminal of the calibration module 18 is connected to the local field potential recording circuit 13. The output terminal of the calibration module 18 is connected to the stimulation parameter control module 16.

[0044] In some embodiments, the dual-frequency impedance measurement circuit 12 is used to apply a dual-frequency test current to the multiple electrodes 11 before applying an electrical stimulation pulse to the multiple electrodes 11 and to collect the response voltage to generate a first composite impedance signal. Then, during a first time period after the electrical stimulation pulse ends, the dual-frequency test current is applied to the multiple electrodes again and the response voltage is collected to generate a second composite impedance signal. The local field potential recording circuit 13 is used to synchronously collect the first local field potential signal of the region where the multiple electrodes are located during the first time period after the electrical stimulation pulse ends. The sliding window differential processing module 14 is used to perform sliding window filtering differential processing on the first composite impedance signal and output a first impedance change rate. The spatial gradient calculation module 15 is used to obtain a three-dimensional spatial impedance gradient by fitting the spatial coordinates of each electrode and its corresponding impedance value using the least squares method. The stimulation parameter control module 16 is used to control the stimulation parameters of the electrical stimulation pulse based on the first impedance change rate received from the sliding window differential processing module 14 and the three-dimensional spatial impedance gradient received from the spatial gradient calculation module 15. The neural stimulation driving circuit 17 is used to output electrical stimulation pulses to the multiple electrodes 11 according to the controlled stimulation parameters. The calibration module 18 is used to determine whether the second composite impedance signal received from the dual-frequency impedance measurement circuit 12 meets the first condition, or whether the first local field potential signal received from the local field potential recording circuit 13 meets the second condition, and when the first condition and / or the second condition are met, it sends a calibration command to the stimulation parameter control module 16 to update the controlled stimulation parameters.

[0045] Optionally, the first time period can be in the range of 50ms to 200ms.

[0046] It should be understood that, in the embodiments of this application, the storage unit may be ROM (Read-Only Memory) or other types of static storage devices capable of storing static information and instructions, RAM (Random Access Memory) or other types of dynamic storage devices capable of storing information and instructions, or EEPROM (Electrically Erasable Programmable Read Only Memory), CD-ROM (Compact Disc Read-Only Memory) or other optical disc storage, optical disk storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0047] In some embodiments, the dual-frequency impedance measurement circuit 12 and the neural stimulation driving circuit 17 are independent hardware circuits.

[0048] In some embodiments, the dual-frequency impedance measurement circuit 12 may include: a microcontroller, a digital-to-analog converter (DAC), a micro-current constant source, an amplifier, a low-pass filter, an analog-to-digital converter (ADC), and a high-voltage protection switch. Specifically, the microcontroller controls the DAC to output a dual-frequency sine wave, which is converted into a precisely amplitude AC test current by the micro-current constant source and applied to the implanted multiple electrodes via the high-voltage protection switch. The response voltage between the electrodes is sent to the amplifier for differential amplification via the high-voltage protection switch, filtered by the low-pass filter, and then input to the ADC for conversion into a digital signal before being output.

[0049] It should be understood that the aforementioned high-voltage protection switch is disconnected during nerve stimulation, isolating the measurement circuit from the high-voltage stimulation pulse, and closed during the impedance measurement period to achieve safe and high-precision tissue impedance acquisition. Optionally, the impedance measurement period can be 50-200 ms before the application of the electrical stimulation pulse. Alternatively, the impedance measurement period can be 50-200 ms after a delay of at least 5 ms following the application of the electrical stimulation pulse. In other words, the impedance measurement used for closed-loop effect verification can be initiated at least 5 ms after the application of the electrical stimulation pulse. This avoids interference from the strong electrical signal (stimulation artifact) generated by the stimulation pulse with the weak impedance measurement signal, thereby ensuring the accuracy and reliability of the measurement results. A measurement period of 50-200 ms ensures the capture of a stable neurophysiological response.

[0050] In some embodiments, the local field potential recording circuit 13 may include a protection circuit, an amplifier, a bandpass filter, a digital-to-digital converter, and a fast recovery control switch. The protection circuit is connected to multiple electrodes to clamp high voltage, limit current, and block DC current, allowing neural signals from 0.1 to 300 Hz to pass through. The amplifier amplifies the neural signal output from the protection circuit with high common-mode rejection. The amplified analog signal is filtered by the bandpass filter and then converted into a digital signal by the input analog-to-digital converter before being output. The main controller controls the fast recovery control switch to close during neural stimulation, short-circuiting the amplifier input to prevent saturation, and to open after stimulation to resume signal acquisition.

[0051] Optionally, the aforementioned protection circuit may include: a high-voltage protection diode, a series current-limiting resistor, and an AC coupling capacitor connected in sequence. The anode of the high-voltage protection diode is grounded, and the cathode is connected to the power supply, used to limit the transient high voltage introduced by the electrodes within a safe range. The series current-limiting resistor is used to suppress the current amplitude. The AC coupling capacitor is used to block the DC component, allowing the AC component within the neurophysiological signal frequency band (e.g., 0.1~300 Hz) to pass through, ensuring the safety of biological tissue and the stability of signal acquisition.

[0052] Optionally, the number of the aforementioned protection circuits is the same as the number of electrodes. That is, one protection circuit corresponds to one electrode.

[0053] In some embodiments, the neural stimulation driving circuit 17 may include: a main controller, a digital-to-analog converter, an H-bridge current driver, a DC blocking capacitor, a multi-channel high-voltage analog switch, and a current monitoring unit. The main controller generates current amplitude and pulse timing commands based on the regulated stimulation parameters, which are then converted into analog reference signals by the digital-to-analog converter. The H-bridge current driver generates precise biphasic current pulses based on the reference signal and couples them to the multi-channel high-voltage analog switch via the DC blocking capacitor. The multi-channel high-voltage analog switch applies the current pulses to designated electrode pairs according to electrode selection commands. The current monitoring unit samples the output current in real time and feeds it back to the main controller to verify charge balance and stimulation safety.

[0054] Optionally, the number of DC blocking capacitors is the same as the number of electrodes. That is, one electrode corresponds to one DC blocking capacitor. Furthermore, the multi-channel high-voltage analog switch corresponds one-to-one with multiple electrodes. In other words, one electrode corresponds to one high-voltage analog switch.

[0055] In some embodiments, the stimulation parameter control module 16 is specifically used to: control the stimulation current intensity of the electrical stimulation pulse based on the first impedance change rate, and control the relative phase difference of the electrical stimulation pulses between multiple electrodes based on the three-dimensional spatial impedance gradient.

[0056] Optionally, the modulated stimulation current intensity I is obtained using the following formula:

[0057] ,

[0058] Where I0 is the preset reference stimulation current intensity; This is the absolute value of the rate of change of the first impedance, in Ω / s; i 1 represents the trigger threshold for the rate of change of impedance; k 1 represents the gain coefficient, which takes a value greater than 0; c 1 is the sensitivity factor, and its value is greater than 0; tanh( ) is the hyperbolic tangent function;

[0059] Optionally, the adjusted relative phase difference is obtained using the following formula:

[0060] ,

[0061] Where, Δ ij Electrode i With electrodes j The relative phase difference between the electrical stimulation pulses; k2 is the phase scaling factor, with a value ranging from 0.5 to 2; For from the electrode i Pointing electrode j Position vector; The impedance gradient vector in three-dimensional space. for The length of the mold, for The length of the module.

[0062] In some embodiments, the first composite impedance signal and / or the second composite impedance signal R ( t It can be obtained through the following formula:

[0063] ,

[0064] in, R LF ( t ) represents the real part impedance at low frequencies. X HF ( t ) represents the high-frequency imaginary impedance, ranging from 1 to 10 kHz at low frequencies and from 50 to 200 kHz at high frequencies; α , β The preset weighting coefficients, and α + β = 1.

[0065] In this embodiment, the calibration module is specifically used to: adjust the weighting coefficient corresponding to the low-frequency real impedance. α Weighting coefficients corresponding to the high-frequency imaginary impedance β Alternatively, by adjusting the trigger threshold of the impedance change rate. i 1. Adjust the intensity of the stimulation current for the next electrical stimulation pulse.

[0066] In some embodiments, the calibration module adjusts the weighting coefficient corresponding to the low-frequency real part impedance. α Weighting coefficients corresponding to the high-frequency imaginary impedance β Specifically, it is used to: weight the coefficient corresponding to the real part of the low-frequency impedance. α Increase Δ α And the weighting coefficients corresponding to the high-frequency imaginary impedance. β Lower Δ β Among them, the adjusted weighting coefficients α The value ranges from 0.6 to 0.9, and the adjusted weighting coefficient... β The value ranges from 0.1 to 0.4.

[0067] Optionally, adjust the trigger threshold for the rate of change of impedance. i1. Includes: triggering threshold for impedance change rate. i 1. Adjust Δ i , where Δ i The value of is greater than 0, after adjustment i 1 is greater than or equal to 0.2 Ω / s.

[0068] In some embodiments, the second composite impedance signal satisfies a first condition, including: the ratio of the absolute value of the second impedance change rate to the absolute value of the first impedance change rate is greater than a first threshold. Optionally, the second impedance change rate is obtained by performing sliding window filtering and differentiation processing on the second composite impedance signal.

[0069] In some embodiments, the first local field potential signal satisfies a second condition, including: the power ratio of the local field potential signal is greater than a second threshold. Optionally, the power ratio is the ratio of the average power of the first local field potential signal during a first time period to the average power of the second local field potential signal during a second time period before the application of the electrical stimulation pulse. Optionally, the second time period ranges from 50 ms to 200 ms.

[0070] In some embodiments, the impedance measurement performed within a first time period after the application of an electrical stimulation pulse based on the modulated stimulation parameters is performed within a first time period at least three time periods after the end of the electrical stimulation pulse, and the start time of the first time period is no earlier than the end time of the third time period. Optionally, the time range of the third time period is greater than or equal to 5 ms.

[0071] In some embodiments, the length of the sliding window is adjusted based on the change in the first impedance rate.

[0072] It should be understood that the controller in the above embodiments may include a processor. The processor may include a CPU (Central Processing Unit), a general-purpose processor, a DSP (Digital Signal Processor), an ASIC (Application Specific Integrated Circuit), an FPGA (Field-Programmable Gate Array), or other programmable logic devices, transistor logic devices, hardware components, or any combination thereof. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. The processor may also be a combination that implements computing functions, such as a combination of one or more microprocessors, a combination of a DSP and a microprocessor, etc.

[0073] The implantable closed-loop neurostimulation system provided in this application embodiment can achieve the following... Figure 2 The various processes implemented in the method embodiments shown will not be described again here to avoid repetition.

[0074] Based on the same inventive concept, embodiments of this application provide a method for adjusting stimulation parameters of an implantable closed-loop neurostimulation system. This implantable closed-loop neurostimulation system may include the implantable closed-loop neurostimulation system described in the above embodiments. The implantable closed-loop neurostimulation system includes multiple electrodes implanted intracranially, and the method is performed by this implantable closed-loop neurostimulation system. Figure 2 As shown, the method includes:

[0075] S1. Impedance measurement is performed by applying dual-frequency test current to multiple electrodes to obtain the first composite impedance signal.

[0076] In some embodiments, before applying electrical stimulation pulses to multiple electrons, weak AC test currents of low frequency (e.g., 1–10 kHz) and high frequency (e.g., 50–200 kHz) can be alternately applied to multiple electrodes, and the corresponding voltage responses can be acquired simultaneously. Based on the voltage responses, the low-frequency real impedance and the high-frequency imaginary impedance are demodulated respectively, and the first composite impedance signal is obtained by fitting the low-frequency real impedance and the high-frequency imaginary impedance with weighting coefficients.

[0077] Optionally, the first composite impedance signal R ( t It can be obtained through the following formula:

[0078]

[0079] in, R LF ( t ) represents the real part impedance at low frequencies. X HF ( t ) represents the high-frequency imaginary impedance. α , β The preset weighting coefficients, and α + β = 1.

[0080] Optionally, the magnitude of the weak AC test current can be 1~10 µA peak-to-peak value, with a preferred value of 5 µA peak-to-peak value, to ensure that the applied charge density is below the neuron's electrical activation threshold, thereby achieving perturbation-free impedance monitoring.

[0081] S2. Process the first composite impedance signal to obtain the first impedance change rate.

[0082] In some embodiments, the first composite impedance signal can be subjected to sliding window filtering and differentiation processing to obtain the first impedance change rate.

[0083] It should be understood that in the embodiments of this application, the impedance change rate dR / dt is calculated based on the composite impedance time series of a single target channel and is used to characterize the instantaneous rate of change of local tissue electrical properties.

[0084] In some embodiments, step S2 can be implemented through the following process:

[0085] 1. Based on sampling rate f s = 200 ~ 1000Hz continuously acquire composite impedance signals to obtain discrete composite impedance time series. R [ n ]= R ( nT s ),in, T s =1 / f s .

[0086] 2. Select a length of N Rectangular sliding windows (e.g.: N = 5~10 points, corresponding to 5~50 ms), perform a moving average filter with a length of 5~10 sampling points on the discrete composite impedance time series to obtain a smoothed impedance series:

[0087] .

[0088] 3. Based on the smoothed impedance sequence, the difference between two adjacent points is calculated using the backward difference formula, and then divided by the sampling period to obtain the first impedance change rate:

[0089] .

[0090] In some embodiments, the length of the sliding window can be adaptively adjusted based on the change in the first impedance rate.

[0091] In some embodiments, when a sustained increase in the first impedance change rate is detected, the length of the sliding window is shortened to improve the response speed; otherwise, the length of the sliding window is extended to suppress noise.

[0092] Optionally, the filter derivative is fitted with a third-order polynomial. The length N of the sliding window is initially set to 7 sampling points. When the first impedance change rate dR / dt is detected to be monotonically increasing for 3 consecutive times, N is shortened to 3. When the fluctuation amplitude of dR / dt is less than the preset tolerance for 5 consecutive times, N is restored to 7.

[0093] S3. Based on the spatial coordinates of each electrode and its corresponding impedance value, the three-dimensional spatial impedance gradient is obtained.

[0094] In some embodiments, the three-dimensional spatial impedance gradient is obtained by least squares fitting based on the spatial coordinates of each electrode and its corresponding impedance value among multiple electrodes.

[0095] It should be understood that in the embodiments of this application, the three-dimensional spatial impedance gradient G is obtained by spatial differential reconstruction based on the impedance measurement values ​​of multiple electrode positions and the spatial coordinates of multiple electrodes at the same sampling time, and is used to characterize the spatial non-uniformity of impedance.

[0096] In some embodiments, step S3 can be implemented through the following process:

[0097] 1. Obtain the spatial coordinates of each electrode. r i = ( x i , y i , z i );

[0098] 2. For the i-th electrode, calculate its directional derivative estimate relative to its neighboring electrode j:

[0099] .

[0100] 3. Constructing overdetermined linear systems A G = D, solved using the least squares method:

[0101] ,

[0102] The three-dimensional spatial impedance gradient vector G = ( G x , G y , G z The unit is Ω / mm. The three-dimensional vector G represents the rate of change and direction of impedance in space (i.e., pointing in the direction of the fastest impedance increase, and the vector magnitude represents the rate of change (Ω / mm) in that direction), and can be used to determine the direction of the stimulation electric field (e.g., applying current along the gradient direction to focus the intervention).

[0103] Optionally, A is a matrix determined based on the spatial positions of multiple electrodes, in the following form:

[0104] ,

[0105] In matrix A, each row corresponds to an electrode, and each column corresponds to a direction in (x, y, z). Matrix A represents the weight of each electrode's position in three-dimensional space in response to the gradient.

[0106] Optionally, D is a matrix (or vector) determined based on the impedance values ​​at multiple electrodes, in the following form:

[0107] ,

[0108] in, R i It indicates at time. t The measured number i Tissue impedance of one or the i-th pair of electrodes (e.g., stimulation electrode a and measurement electrode b).

[0109] S4. Based on the first impedance change rate and the three-dimensional spatial impedance gradient, adjust the stimulation parameters of the electrical stimulation pulse.

[0110] In some embodiments, step S4 may include:

[0111] The intensity of the stimulation current of the electrical stimulation pulse is adjusted based on the first impedance change rate; and,

[0112] The relative phase difference of electrical stimulation pulses between multiple electrodes is controlled by adjusting the three-dimensional spatial impedance gradient.

[0113] Because in the seconds to tens of seconds before the onset of abnormal neural activity, extracellular K+ in brain tissue... + Increased concentration and narrowing of the extracellular space lead to a rapid decrease in impedance, thus the rate of change of impedance... dR / dt <0 and amplitude | dR / dt | Increase. Usually adopted dR / dt The degree of urgency characterizes abnormal neural activity, that is, how much intervention is required. Therefore, in the embodiments of this application, it can be... dR / dt Correlate it with current intensity. If | dR / dt | Slow changes are addressed with lower current interventions to suppress slow, abnormal neural activity. If | dR / dt | In the event of rapid changes, a higher electrical current is used to intervene and suppress urgent abnormal neural activity.

[0114] Since the impedance gradient can characterize the direction of the most drastic impedance change (e.g., if the impedance is low on the left and high on the right, the impedance gradient points to the right, meaning the abnormal region is on the left), and the effect of nerve electrical stimulation is related to the direction and intensity distribution of the electric field, the electric field lines can be made to pass through the abnormal region to achieve the optimal modulation result. The direction of the electric field is determined by the positions of the anode and cathode; that is, if the current flows from the anode to the cathode, the direction of the electric field can be understood as the direction from the anode to the cathode. Therefore, in the embodiments of this application, when there are multiple channel electrodes, the direction of the electric field can be controlled by adjusting the relative phase of the multi-channel stimulation pulses, so that the electric field is applied along the direction characterized by the impedance gradient or in the opposite direction, thereby achieving precise intervention and reducing energy consumption.

[0115] In some embodiments, the modulated stimulation current intensity I is obtained by the following formula:

[0116] .

[0117] Where I0 is the preset reference stimulation current intensity; This is the absolute value of the rate of change of the first impedance, in Ω / s; i 1 represents the trigger threshold for the rate of change of impedance; k 1 represents the gain coefficient, which takes a value greater than 0; c 1 is the sensitivity factor, and its value is greater than 0; tanh( ) is the hyperbolic tangent function.

[0118] Optional, gain coefficient k 1 is used to set the maximum boost factor of the stimulation current intensity.

[0119] Optional, sensitivity factor c 1. Used to adjust the steepness of the current response curve.

[0120] Optionally, the output value of the hyperbolic tangent function varies in the interval [0, 1], which can achieve smooth nonlinear adjustment of the stimulation current intensity.

[0121] In the above embodiments, by introducing parameters k 1 and c 1. It makes the intensity of the stimulation current adjustable and robust, and can avoid overstimulation caused by transient noise.

[0122] In some embodiments, the adjusted relative phase difference is obtained by the following formula:

[0123] .

[0124] Where, Δ ij Electrode i With electrodesj The relative phase difference between the electrical stimulation pulses; k 2 is the phase scaling factor, with a value ranging from 0.5 to 2; For from the electrode i Pointing electrode j Position vector; This is the three-dimensional impedance gradient vector, pointing in the direction of the fastest increase in impedance. for The length of the mold, for The length of the module.

[0125] Optional, electrodes i With electrodes j These are two spatially adjacent electrodes located within brain tissue, satisfying the following condition: distance (For example: 5 mm). Wherein, Δ ij = i j , It is used to achieve phase coordination control between multiple electrodes and generate a directional electric field.

[0126] Optional, phase scaling factor k 2 is used to adjust focus sharpness. That is to say, after... k 2. The phase difference is obtained after scaling to ensure that the electric field energy is concentrated in the target direction.

[0127] Optional, for and The dot product represents the electrode pair ( i , j The cosine of the angle between the direction of the line connecting the impedance gradient and the opposite direction of the impedance gradient.

[0128] S5. During the first time period after applying an electrical stimulation pulse based on the regulated stimulation parameters, impedance measurement is performed to obtain a second composite impedance signal, and the first local field potential signal of the region where multiple electrodes are located is obtained during the first time period.

[0129] Optionally, the first time period can be in the range of 50ms to 200ms.

[0130] In some embodiments, the first time period is 50–200 ms after the end of the electrical stimulation pulse. Optionally, an impedance measurement similar to step S1 is performed within 50–200 ms after the end of the electrical stimulation pulse to generate a second composite impedance signal.

[0131] It should be understood that the impedance measurement in step S1 is performed continuously during system operation to monitor tissue status in real time. The impedance measurement in step S5 refers to obtaining a second composite impedance signal within 50-200 ms after the end of electrical stimulation using the same dual-frequency measurement method as in step S1 to ensure data comparability, but the timing of the impedance measurement differs from the routine monitoring in step S1.

[0132] In the embodiments of this application, Local Field Potential (LFP) is a core electrophysiological signal in the fields of neuroscience and brain-computer interfaces. It refers to low-frequency, continuous extracellular voltage fluctuations generated by the postsynaptic potentials and ion current activities of a large number of neurons in a local area of ​​brain tissue (typically within a few hundred micrometers). The frequency range is typically 0.1 Hz to 300 Hz, and the amplitude is 10 µV to 1 mV. LFP can be used to monitor abnormal neural activity; for example, a significant increase in LFP power before an epileptic seizure can provide an early warning several seconds in advance.

[0133] In some embodiments, the first local field potential signal can be used to determine whether the electrical stimulation pulse effectively inhibits abnormal neural activity (such as attenuation of high-frequency oscillating FOs). Optionally, the first local field potential signal is acquired from multiple electrode channels within 50–200 ms after the electrical stimulation ends.

[0134] S6. When the second composite impedance signal satisfies the first condition and / or the first local field potential signal satisfies the second condition, the regulated stimulation parameters are calibrated.

[0135] In some embodiments, if the second composite impedance signal satisfies the first condition and / or the first local field potential signal satisfies the second condition, it indicates that the current electrical stimulation has not effectively inhibited abnormal neural activity. Therefore, it is necessary to calibrate the regulated stimulation parameters.

[0136] In some embodiments, the second composite impedance signal satisfying the first condition may include: the ratio of the absolute value of the second impedance change rate to the absolute value of the first impedance change rate is greater than a first threshold (e.g., 0.6). Optionally, the second impedance change rate is obtained by differential processing of the second composite impedance signal using sliding window filtering.

[0137] It should be understood that if the rate of change of impedance remains high (e.g., greater than 0.6), then the impedance has not recovered, and therefore it can be determined that the electrical stimulation did not effectively inhibit the abnormal neural activity.

[0138] In some embodiments, the first local field potential signal satisfying the second condition may include: the power ratio of the local field potential signal is greater than a second threshold (e.g., 0.7). Optionally, the power ratio is the ratio of the average power of the first local field potential signal during a first time period to the average power of the second local field potential signal during a second time period before the application of the electrical stimulation pulse.

[0139] Optionally, the second time period can range from 50ms to 200ms.

[0140] Optionally, the average power of the first local field potential signal is: the average power of the local field potential signal collected from multiple electrode channels in the 80-200 Hz frequency band within 50-200 ms after the end of electrical stimulation.

[0141] Optionally, the average power of the second local field potential signal is the average power of the local field potential signal acquired from multiple electrode channels in the 80-200 Hz frequency band within 50 ms to 200 ms before the application of the electrical stimulation pulse.

[0142] It should be understood that if the power ratio of LFP is still large (e.g., greater than 0.7), then LFP has not decayed, and therefore it can be determined that the electrical stimulation did not effectively inhibit abnormal neural activity.

[0143] It should also be understood that the values ​​in the first time period and the values ​​in the second time period may be the same or different, and this application embodiment does not limit this.

[0144] In some embodiments, the second composite impedance signal R ( t It can be obtained through the following formula:

[0145] ,

[0146] in, R LF ( t ) represents the real part impedance at low frequencies. X HF ( t ) represents the high-frequency imaginary impedance, ranging from 1 to 10 kHz at low frequencies and from 50 to 200 kHz at high frequencies; α , β The preset weighting coefficients, and α + β = 1;

[0147] In some embodiments, calibrating the modulated stimulation parameters in step S6 above may include:

[0148] By adjusting the weighting coefficient corresponding to the low-frequency real impedance αWeighting coefficients corresponding to the high-frequency imaginary impedance β Alternatively, by adjusting the trigger threshold of the impedance change rate. i 1. Adjust the intensity of the stimulation current for the next electrical stimulation pulse.

[0149] In this embodiment, the calibration process optimizes parameters for the control of stimulation intensity. Spatial guidance parameters (such as phase difference) are determined by initial implantation positioning and slow clinical programming and are not considered during the rapid closed-loop calibration process. That is, the relative phase difference between the multiple electrodes remains unchanged during the calibration process.

[0150] In some embodiments, the weighting factor corresponding to the low-frequency real part impedance is adjusted. α Weighting coefficients corresponding to the high-frequency imaginary impedance β This may include: a weighting factor corresponding to the real part of the low-frequency impedance. α Increase Δ α And the weighting coefficients corresponding to the high-frequency imaginary impedance. β Lower Δ β Among them, Δ α >0, Δ β >0.

[0151] It should be understood that when suppression is determined to be ineffective, it indicates that the current composite impedance is insufficiently sensitive to the prodromal state of epilepsy. This is because low-frequency real impedance is more sensitive to changes in extracellular fluid (such as K...). + (Accumulation), while the high-frequency imaginary part is significantly affected by colloid proliferation, therefore it can be improved by... α To enhance the ability to respond to acute ion dynamics.

[0152] Optional, adjusted weighting coefficients α The value range is between 0.6 and 0.9 (i.e., 0.6 ≤ 0.9). α ≤ 0.9), adjusted weighting coefficient β The value ranges from 0.1 to 0.4 (i.e., 0.1 ≤ 0.4). β ≤ 0.4). In this embodiment, if α Too low (e.g., α <0.6) will result in insensitivity to rapid impedance changes; if α Too high (e.g., α A value >0.9 might ignore tissue structure information, reducing specificity. Therefore, α The value of satisfies 0.6 ≤ α When the value is ≤ 0.9, a better balance between sensitivity and stability can be achieved.

[0153] In some embodiments, the trigger threshold for adjusting the rate of change of impedance is adjusted. i 1. This can include: setting a trigger threshold for the rate of change of impedance. i1. Adjust Δ i In this embodiment, by lowering the trigger threshold of the impedance change rate, the trigger sensitivity can be reduced, thereby allowing for earlier intervention.

[0154] Optional, Δ i The value of is greater than 0, after adjustment i 1 is greater than or equal to 0.2 Ω / s. It should be understood that the rate of change of impedance |dR / dt| due to normal physiological fluctuations is usually <0.2 Ω / s; therefore, i Setting the lower limit of 1 to 0.2 Ω / s can avoid excessive stimulation caused by noise from breathing, blood flow, etc.

[0155] In some embodiments, the impedance measurement performed within a first time period after the application of an electrical stimulation pulse based on the modulated stimulation parameters is performed within a first time period at least three time periods after the end of the electrical stimulation pulse, and the start time of the first time period is no earlier than the end time of the third time period. Optionally, the first time period (e.g., 50~200ms) is located after the third time period (≥ 5ms), and the two do not overlap.

[0156] In other words, in the embodiments of this application, to avoid interference from the strong electrical signal (stimulation artifact) generated by the stimulation pulse with the weak impedance measurement signal, all impedance measurements after electrical stimulation are initiated only after a delay of at least 5 ms following the end of the electrical stimulation pulse. This ensures sufficient attenuation of the stimulation artifact, thereby ensuring the accuracy and reliability of the measurement results. Optionally, measurements for verifying the closed-loop effect are performed within a time window of 50–200 ms after the stimulation ends to ensure the capture of a stable neurophysiological response.

[0157] In some embodiments, the drive circuit for applying the dual-frequency test current and the drive circuit for outputting the electrical stimulation pulse are independent hardware circuits.

[0158] Optionally, the drive circuit for applying the dual-frequency test current can be as follows: Figure 1 The dual-frequency impedance measurement circuit 12 shown is not limited to this.

[0159] Optionally, the drive circuit for outputting electrical stimulation pulses can be as follows: Figure 1 The neural stimulation driving circuit 17 shown is not limited to this.

[0160] In this embodiment, the implantable closed-loop neurostimulation system includes: independent hardware circuits for outputting stimulation pulses and impedance testing, respectively, which can ensure that the microampere-level test current path is completely disconnected when stimulation current is applied, thereby avoiding signal crosstalk and device damage.

[0161] In summary, the embodiments of this application provide a highly robust, adaptive, and low-false-trigger closed-loop neural stimulation modulation method, which can achieve the following technical effects:

[0162] 1. It can improve the sensitivity of abnormal neural activity detection. Specifically, based on the impedance change rate obtained by sliding window differentiation of the composite impedance signal obtained by dual-frequency test current, it can determine the changes in the tissue microenvironment before the onset of abnormal neural activity. Compared with the traditional LFP method, it can provide an early warning several seconds earlier and has stronger anti-interference ability.

[0163] 2. The stimulation parameters achieve precise spatiotemporal coordination. By fitting the three-dimensional spatial impedance gradient using the least squares method, the relative phase difference between multiple electrodes can be controlled to achieve stimulation focusing in a specific direction. At the same time, the current intensity is dynamically adjusted in combination with the impedance change rate, thereby achieving precise intervention.

[0164] 3. A self-calibrating closed-loop control scheme is provided. Specifically, within 50-200 ms after electrical stimulation, the second composite impedance signal and local field potential are simultaneously acquired. The effectiveness of the intervention is determined by the degree of impedance recovery and / or LFP power attenuation. If the expected results are not achieved, the weight of the composite impedance or the trigger threshold is automatically calibrated to optimize the stimulation parameters and avoid the accumulation of ineffective stimulation.

[0165] 4. Impedance measurement is performed within a time window of ≥5 ms after the end of the electrical stimulation pulse to effectively avoid interference from stimulation artifacts. At the same time, a physically isolated drive circuit is used to ensure the measurement accuracy of the microampere-level test current, thereby ensuring the reliability of the measurement and the safety of the system.

[0166] Based on the same principles as the methods shown in the embodiments of this application, the embodiments of this application also provide a signal processing system, which includes the implantable closed-loop neurostimulation system provided in the above embodiments.

[0167] In an alternative embodiment, a signal processing system, such as Figure 3 As shown, Figure 3 The signal processing system 20 shown includes a processor 21 and a memory 23. The processor 21 is communicatively connected to the memory 23, for example, via a bus 22.

[0168] Processor 21 may be a CPU (Central Processing Unit), general-purpose processor, DSP (Digital Signal Processor), ASIC (Application Specific Integrated Circuit), FPGA (Field-Programmable Gate Array), or other programmable logic device, transistor logic device, hardware component, or any combination thereof, including the chip or implantable closed-loop neurostimulation system described in any of the above embodiments. It can implement or execute the various exemplary logic blocks, modules, and circuits described in conjunction with the disclosure of this application. Processor 21 may also be a combination that implements computational functions, such as including one or more microprocessor combinations, a combination of DSP and microprocessor, etc.

[0169] Bus 22 may include a pathway for transmitting information between the aforementioned components. Bus 22 may be a PCI (Peripheral Component Interconnect) bus or an EISA (Extended Industry Standard Architecture) bus, etc. Bus 22 may be divided into address bus, data bus, control bus, etc. For ease of representation, Figure 3 The bus is represented by a single thick line, but this does not mean that there is only one bus or one type of bus.

[0170] The memory 23 may be a ROM (Read-Only Memory) or other type of static storage device capable of storing static information and instructions, RAM (Random Access Memory) or other type of dynamic storage device capable of storing information and instructions, or it may be an EEPROM (Electrically Erasable Programmable Read Only Memory), a CD-ROM (Compact Disc Read-Only Memory) or other optical disc storage, optical disc storage (including compressed optical discs, laser discs, optical discs, digital universal optical discs, Blu-ray discs, etc.), magnetic disk storage media or other magnetic storage devices, or any other medium capable of carrying or storing desired program code in the form of instructions or data structures and accessible by a computer, but not limited thereto.

[0171] The memory 23 is used to store computer programs that execute the embodiments of this application, and the execution is controlled by the processor 21. The processor 21 is used to execute the computer programs stored in the memory 23 to implement the steps shown in the foregoing method embodiments.

[0172] This application provides a computer-readable storage medium storing a computer program. When the computer program is executed by a processor, it can implement the steps and corresponding content of the aforementioned method embodiments.

[0173] This application also provides a computer program product, including a computer program that, when executed by a processor, can implement the steps and corresponding content of the aforementioned method embodiments.

[0174] In the description of this application, the terms "center," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate directions or positional relationships based on the exemplary directions or positional relationships shown in the accompanying drawings. They are used to facilitate the description or simplification of the embodiments of this application and are not intended to indicate or imply that the device or component referred to must have a specific orientation or be constructed and operated in a specific orientation. Therefore, they should not be construed as limitations on this application.

[0175] 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 technical features indicated. Therefore, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. In the description of this application, unless otherwise stated, "a plurality of" means two or more.

[0176] In the description of this application, it should be noted that, unless otherwise expressly specified and limited, the terms "installation," "connection," and "joining" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal communication between two components. Those skilled in the art can understand the specific meaning of the above terms in this application based on the specific circumstances.

[0177] In the description of this specification, specific features, structures, materials, or characteristics may be combined in any suitable manner in one or more embodiments or examples.

[0178] The above description is only a partial implementation of this application. It should be noted that for those skilled in the art, other similar implementation methods based on the technical concept of this application, without departing from the technical concept of this application, also fall within the protection scope of the embodiments of this application.

Claims

1. An implantable closed-loop neurostimulation system, characterized in that, include: Multiple electrodes implanted in the brain; A dual-frequency impedance measurement circuit is used to apply a dual-frequency test current to the multiple electrodes and collect the response voltage before applying an electrical stimulation pulse to the multiple electrodes to generate a first composite impedance signal, and to apply the dual-frequency test current to the multiple electrodes again and collect the response voltage during a first time period after the electrical stimulation pulse ends to generate a second composite impedance signal. A local field potential recording circuit is used to synchronously acquire the first local field potential signal of the region where the multiple electrodes are located during the first time period after the end of the electrical stimulation pulse. The processing module is used to process the first composite impedance signal to obtain the first impedance change rate; The spatial gradient calculation module is used to obtain the three-dimensional spatial impedance gradient based on the spatial coordinates of each electrode and the corresponding impedance value, wherein the spatial coordinates of the multiple electrodes are pre-stored in the storage unit; The stimulation parameter control module is used to control the stimulation parameters of the electrical stimulation pulse based on the first impedance change rate and the three-dimensional spatial impedance gradient. A neural stimulation driving circuit is used to output electrical stimulation pulses to the plurality of electrodes according to the regulated stimulation parameters; The calibration module is used to calibrate the modulated stimulation parameters when the second composite impedance signal meets a first condition and / or the first local field potential signal meets a second condition.

2. The implantable closed-loop neurostimulation system according to claim 1, characterized in that, The dual-frequency impedance measurement circuit and the neural stimulation driving circuit are independent hardware circuits.

3. The implantable closed-loop neural stimulation system according to claim 1 or 2, wherein the stimulation parameter control module is specifically used for: The intensity of the stimulation current of the electrical stimulation pulse is adjusted based on the first impedance change rate. The relative phase difference of electrical stimulation pulses between multiple electrodes is controlled based on the three-dimensional spatial impedance gradient. in, The modulated stimulation current intensity I is obtained by the following formula: ， Where I0 is the preset reference stimulation current intensity; This is the absolute value of the first impedance change rate, in Ω / s; θ 1 represents the trigger threshold for the rate of change of impedance; k 1 represents the gain coefficient, which takes a value greater than 0; γ 1 is the sensitivity factor, and its value is greater than 0; tanh( ) is the hyperbolic tangent function; The adjusted relative phase difference is obtained using the following formula: ， Where, Δ ij Electrode i With electrodes j The relative phase difference between the electrical stimulation pulses; k 2 is the phase scaling factor, with a value ranging from 0.5 to 2; For from the electrode i Pointing electrode j Position vector; The impedance gradient vector in three-dimensional space. for The length of the mold, for The length of the module.

4. The implantable closed-loop neurostimulation system according to claim 1 or 2, wherein the first composite impedance signal and / or the second composite impedance signal R ( t It can be obtained through the following formula: ， in, R LF ( t ) represents the real part impedance at low frequencies. X HF ( t ) represents the high-frequency imaginary impedance, where the low frequency is 1 to 10 kHz and the high frequency is 50 to 200 kHz; α , β The preset weighting coefficients, and α + β = 1; The calibration module is specifically used to: adjust the weighting coefficient corresponding to the low-frequency real part impedance. α The weighting coefficient corresponding to the high-frequency imaginary impedance β Alternatively, by adjusting the trigger threshold of the impedance change rate. θ 1. Adjust the intensity of the stimulation current for the next electrical stimulation pulse.

5. The implantable closed-loop neurostimulation system according to claim 4, wherein the calibration module adjusts the weighting coefficient corresponding to the low-frequency real impedance. α The weighting coefficient corresponding to the high-frequency imaginary impedance β When, specifically used for: The weighting coefficient corresponding to the low-frequency real part impedance α Increase Δ α And the weighting coefficients corresponding to the high-frequency imaginary part impedance. β Lower Δ β ,in, Adjusted weighting coefficients α The value ranges from 0.6 to 0.9, and the adjusted weighting coefficient... β The value ranges from 0.1 to 0.4; Adjusting the trigger threshold of the impedance change rate θ 1. Includes: The trigger threshold for the rate of change of impedance θ 1. Adjust Δ θ , where Δ θ The value of is greater than 0, after adjustment θ 1 is greater than or equal to 0.2 Ω / s.

6. The implantable closed-loop neurostimulation system according to claim 1 or 2, wherein the second composite impedance signal satisfies the first condition, including: The ratio of the absolute value of the second impedance change rate to the absolute value of the first impedance change rate is greater than the first threshold, wherein the second impedance change rate is obtained by performing sliding window filtering and differentiation processing on the second composite impedance signal. The first local field potential signal satisfies the second condition, including: the power ratio of the local field potential signal is greater than the second threshold, wherein the power ratio is the ratio of the average power of the first local field potential signal during the first time period to the average power of the second local field potential signal during the second time period before the application of the electrical stimulation pulse.

7. In the implantable closed-loop neurostimulation system according to claim 1 or 2, the impedance measurement performed during a first time period after the application of an electrical stimulation pulse based on the modulated stimulation parameters is performed during the first time period after a delay of at least a third time period following the end of the electrical stimulation pulse, and the start time of the first time period is not earlier than the end time of the third time period.

8. The implantable closed-loop neurostimulation system according to claim 6, wherein the length of the sliding window is adjusted based on the change in the first impedance rate.

9. A signal processing system, characterized in that, Including the implantable closed-loop neurostimulation system as described in any one of claims 1 to 8.

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