Diaphragm stimulation control method and device, equipment, storage medium and program product

Abstract

The invention discloses a diaphragm stimulation control method and device, equipment, a storage medium and a program product. The method comprises the following steps: acquiring human chest impedance data through an electrical impedance tomography technology, and constructing a first lung ventilation image sequence according to the human chest impedance data; a global ventilation volume curve is extracted from the first lung ventilation image sequence, breathing cycle key points are determined according to the global ventilation volume curve, and the breathing cycle key points comprise at least one of an inspiration starting point, an inspiration peak point, an expiration starting point and an expiration end point; determining the inspiration triggering opportunity of the next cycle according to the breathing cycle key points, triggering diaphragm electrical stimulation according to the inspiration triggering opportunity, and collecting a stimulated second lung ventilation image sequence; and extracting a ventilation effect feedback index from the second lung ventilation image sequence, and adaptively adjusting diaphragm electrical stimulation parameters according to the ventilation effect feedback index.

Description

Technical Field

[0001] This application relates to the field of respiratory medical monitoring technology, and more specifically, to a method, device, equipment, storage medium, and program product for controlling diaphragmatic stimulation. Background Technology

[0002] In the field of respiratory medicine, patients with respiratory dysfunction often require diaphragmatic stimulation techniques to assist breathing in order to improve lung ventilation efficiency and ensure stable respiratory function.

[0003] Existing diaphragmatic stimulation systems primarily rely on airflow sensors and chest cuff pressure sensors to acquire respiratory-related signals, thereby triggering stimulation actions. However, airflow sensors require connection to the airway, making them unsuitable for non-invasive treatment scenarios; chest cuff pressure sensors have limited measurement accuracy, making it difficult to accurately identify key respiratory phases such as the onset of inspiration and peak expiratory phase; furthermore, existing systems lack a real-time feedback mechanism for stimulation effects, failing to dynamically adjust stimulation parameters based on the patient's actual ventilation status, resulting in low adaptability. Summary of the Invention

[0004] The main purpose of this application is to provide a method, device, equipment, storage medium and program product for controlling diaphragmatic stimulation, which can achieve non-invasive and precise respiratory phase recognition and adaptive adjustment of stimulation parameters, thereby improving the synchronicity, safety and therapeutic effect of diaphragmatic stimulation.

[0005] To achieve the above objectives, a first aspect of this application proposes a diaphragm stimulation control method, comprising: acquiring human chest impedance data using electrical impedance tomography (EIT) and constructing a first lung ventilation image sequence based on the human chest impedance data; extracting a global ventilation curve from the first lung ventilation image sequence and determining key points of the respiratory cycle based on the global ventilation curve, wherein the key points of the respiratory cycle include at least one of the following: inspiratory start point, inspiratory peak point, expiratory start point, and expiratory end point; determining the inspiratory triggering timing for the next cycle based on the key points of the respiratory cycle, triggering diaphragm electrical stimulation according to the inspiratory triggering timing, and acquiring a second lung ventilation image sequence after stimulation; extracting a ventilation effect feedback index from the second lung ventilation image sequence and adaptively adjusting diaphragm electrical stimulation parameters based on the ventilation effect feedback index.

[0006] According to the diaphragm stimulation control method provided in this application, the step of triggering diaphragm electrical stimulation according to the inspiratory trigger timing and acquiring a second lung ventilation image sequence after stimulation includes: triggering diaphragm electrical stimulation according to the inspiratory trigger timing, suppressing stimulation artifacts through multiple parallel mechanisms during stimulation, and acquiring a second lung ventilation image sequence after stimulation; wherein, the multiple parallel mechanisms include at least one of the following: a temporal shielding mechanism, an artifact template elimination mechanism, and a wavelet domain noise suppression mechanism; the temporal shielding mechanism refers to pausing the acquisition of human chest impedance data for a preset duration before stimulation and delaying the resumption of sampling for a preset duration after stimulation to avoid interference from the stimulation signal; the artifact template elimination mechanism refers to generating a reverse compensation signal based on a known electrical stimulation transmission waveform to cancel the power frequency and motion artifacts at the receiving end; the wavelet domain noise suppression mechanism refers to performing wavelet threshold filtering on ventilation signals and image pixel changes to correct signal distortion during stimulation.

[0007] According to the diaphragm stimulation control method provided in this application, the step of determining the inspiratory triggering time of the next cycle based on the key points of the respiratory cycle includes: determining the cycle length of the most recent N historical respiratory cycles and the phase shift corresponding to each key point of the respiratory cycle; obtaining the predicted cycle length by calculating the mean of the N historical respiratory cycles and adaptively estimating the predicted phase shift; and calculating the inspiratory triggering time of the next cycle based on the predicted cycle length, the predicted phase shift, and the end-expiratory time of the previous historical respiratory cycle.

[0008] According to the diaphragm stimulation control method provided in this application, the calculation of the inspiratory triggering time of the next cycle based on the predicted cycle length, the predicted phase drift, and the end-expiratory time of the previous historical respiratory cycle includes: inspiratory triggering time of the next cycle = end-expiratory time of the previous historical respiratory cycle + predicted cycle length - predicted phase drift - preset pre-triggering time; wherein, the preset pre-triggering time is the advance triggering time for synchronizing diaphragm contraction with natural inspiratory action.

[0009] According to the diaphragm stimulation control method provided in this application, the method for acquiring human chest impedance data through electrical impedance tomography includes: using a first electrode pair as an excitation electrode pair to apply a high-frequency constant current excitation signal to the human chest; using a second electrode pair as a acquisition electrode pair to acquire a differential voltage response signal modulated by the human chest impedance; and according to a preset electrode rotation strategy, using a third electrode pair as an excitation electrode pair and a fourth electrode pair as an acquisition electrode pair, and entering the next measurement time slot to repeat the operation of applying the excitation signal and acquiring the response signal; wherein the first electrode pair and the second electrode pair are different electrode pairs, and the third electrode pair and the fourth electrode pair are different electrode pairs.

[0010] According to the diaphragm stimulation control method provided in this application, the step of extracting ventilation effect feedback indicators from the second lung ventilation image sequence and adaptively adjusting diaphragm electrical stimulation parameters based on the ventilation effect feedback indicators includes: extracting ventilation effect feedback indicators from the second lung ventilation image sequence, wherein the ventilation effect feedback indicators include at least one of the following: maximum pulmonary ventilation increase, left and right lung ventilation balance, lung ventilation area, expansion improvement rate, and respiratory cycle matching degree; comparing the ventilation effect feedback indicators with preset thresholds according to a preset index threshold and parameter adjustment mapping relationship; if the ventilation effect feedback indicators do not reach the preset threshold, adjusting the diaphragm electrical stimulation parameters in the forward direction according to a preset step size; if the ventilation effect feedback indicators exceed the preset threshold, adjusting the diaphragm electrical stimulation parameters in the reverse direction according to a preset step size; if the ventilation effect feedback indicators are within the preset threshold range, keeping the current diaphragm electrical stimulation parameters unchanged; wherein the diaphragm electrical stimulation parameters include at least one of the following: stimulation current intensity, stimulation pulse width, stimulation frequency, and stimulation waveform.

[0011] This application also provides a diaphragm stimulation control device, comprising the following modules: an acquisition module and a processing module; the acquisition module is used to acquire human chest impedance data using electrical impedance tomography; the processing module is used to construct a first lung ventilation image sequence based on the human chest impedance data; extract a global ventilation curve from the first lung ventilation image sequence, and determine key points of the respiratory cycle based on the global ventilation curve, the key points of the respiratory cycle including at least one of the following: inspiratory start point, inspiratory peak point, expiratory start point, and expiratory end point; determine the inspiratory triggering timing for the next cycle based on the key points of the respiratory cycle, and trigger diaphragm electrical stimulation according to the inspiratory triggering timing; the acquisition module is used to acquire a second lung ventilation image sequence after stimulation; the processing module is used to extract ventilation effect feedback indicators from the second lung ventilation image sequence, and adaptively adjust diaphragm electrical stimulation parameters based on the ventilation effect feedback indicators.

[0012] This application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the computer program to implement any of the diaphragm stimulation control methods described above.

[0013] This application also provides a non-transitory computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the diaphragm stimulation control method as described above.

[0014] This application also provides a computer program product, including a computer program that, when executed by a processor, implements any of the diaphragm stimulation control methods described above.

[0015] The technical solutions provided by the embodiments of this application may include the following beneficial effects: In this application, since human chest impedance data can be acquired and lung ventilation image sequence can be constructed using electrical impedance tomography, and global ventilation curve can be extracted and key points of the respiratory cycle can be determined based on the image sequence, non-invasive respiratory signal acquisition can be achieved, which is suitable for non-invasive respiratory therapy scenarios. Because it can accurately identify key points of the respiratory cycle such as the inspiratory start point and inspiratory peak point based on the global ventilation curve extracted from the lung ventilation image sequence, it solves the problem of limited measurement accuracy and difficulty in accurately identifying key respiratory phases of traditional chest band pressure sensors, thus improving the accuracy of respiratory phase identification. Since the inspiratory triggering timing of the next cycle can be determined based on the key points of the respiratory cycle, and the diaphragm electrical stimulation is triggered according to the inspiratory triggering timing, the precise prediction and synchronization of diaphragm electrical stimulation and human natural breathing are achieved, which greatly improves the stimulation synchronization accuracy of the respiratory assist device. Because it is possible to acquire second lung ventilation image sequences after stimulation, extract ventilation effect feedback indicators from the second lung ventilation image sequences, and adaptively adjust diaphragmatic electrical stimulation parameters based on the ventilation effect feedback indicators, a closed-loop control mechanism of stimulation-feedback-adjustment is formed. Therefore, real-time monitoring of stimulation effect and dynamic optimization of parameters are realized, avoiding the drawbacks of existing systems that lack real-time feedback and cannot adjust parameters according to the patient's actual ventilation situation, thus improving the synchronicity and adaptability of diaphragmatic stimulation. Attached Figure Description

[0016] The accompanying drawings, which form part of this application, are used to provide a further understanding of the application and to make other features, objects, and advantages of the application more apparent. The illustrative embodiments and descriptions of this application are used to explain the application and do not constitute an undue limitation of the application. In the drawings: Figure 1 A flowchart illustrating the diaphragm stimulation control method provided in this application; Figure 2 One of the structural schematic diagrams of the diaphragm stimulation control device provided in this application; Figure 3 This is the second schematic diagram of the diaphragm stimulation control device provided by the present invention; Figure 4 This is a schematic diagram of the structure of the electronic device provided by the present invention. Detailed Implementation

[0017] To enable those skilled in the art to better understand the present application, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present application, and not all embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative effort should fall within the scope of protection of the present application.

[0018] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate for the embodiments of this application described herein. Furthermore, the terms "comprising" and "having," and any variations thereof, are intended to cover non-exclusive inclusion; for example, a process, method, system, product, or apparatus that comprises a series of steps or units is not necessarily limited to those steps or units explicitly listed, but may include other steps or units not explicitly listed or inherent to such processes, methods, products, or apparatus.

[0019] In this application, the terms "upper," "lower," "left," "right," "front," "rear," "top," "bottom," "inner," "outer," "middle," "vertical," "horizontal," "lateral," and "longitudinal" indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. These terms are primarily for the purpose of better describing this application and its embodiments, and are not intended to limit the indicated device, element, or component to having a specific orientation, or to be constructed and operated in a specific orientation.

[0020] Furthermore, in addition to indicating location or positional relationship, some of the aforementioned terms may also have other meanings. For example, the term "above" may also be used in some cases to indicate a certain dependency or connection relationship. Those skilled in the art can understand the specific meaning of these terms in this application based on the specific circumstances.

[0021] Furthermore, the terms "installation," "setup," "equipped with," "connection," "linked," and "socketing" should be interpreted broadly. For example, "connection" can be a fixed connection, a detachable connection, or an integral structure; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or an internal connection between two devices, components, or parts. Those skilled in the art can understand the specific meaning of the above terms in this application according to the specific circumstances.

[0022] This application describes some exemplary embodiments for illustrative purposes. It should be understood that this application may be implemented in other ways not specifically shown in the accompanying drawings.

[0023] like Figure 1 As shown, this application provides a diaphragm stimulation control method, which can be applied to a diaphragm stimulation control device. The diaphragm stimulation control method may include steps S101-S104: S101. The diaphragm stimulation control device acquires human chest impedance data using electrical impedance tomography (EIT) technology and constructs a first lung ventilation image sequence based on the human chest impedance data.

[0024] Specifically, such as Figure 2 As shown, the diaphragm stimulation control device includes an EIT module, which comprises an EIT stimulation module, an EIT acquisition module, a high-speed switch module, an EIT control module, and an EIT power supply module. The diaphragm stimulation control device provides a stable and isolated power supply to the EIT stimulation module, EIT acquisition module, high-speed switching module, and EIT control module via the EIT power supply module, ensuring the coordinated operation of each submodule. The EIT control module sends control commands to the EIT stimulation module, driving it to generate a high-frequency constant current excitation signal with a preset frequency and amplitude, which is then conditioned and output to the high-speed switching module. Simultaneously, the EIT control module can also send electrode switching commands to the high-speed switching module, dynamically switching the injection electrode pairs according to a preset sequence using the adjacent injection method. This applies the high-frequency constant current excitation signal output from the EIT stimulation module to the human chest through the selected adjacent electrode pairs. While the excitation signal is applied, the EIT control module can control the high-speed switching module to select other electrode combinations not associated with the excitation electrode pairs as measurement electrode pairs. This allows the voltage response signal, modulated by the impedance of the human chest, to be transmitted to the EIT acquisition module through the measurement electrode pairs. The EIT acquisition module differentially amplifies and adjusts the signal bias of the received voltage response signal, and then the signal is converted to a digital signal by the built-in analog-to-digital converter. The converter (ADC) unit performs digital sampling, and then removes high-frequency noise and interference through low-pass filtering or Kalman filtering to obtain clean human chest impedance data. Finally, the EIT control module receives the digital human chest impedance data uploaded by the EIT acquisition module, calls the preset EIT image reconstruction algorithm for calculation and processing, and generates an image pixel matrix representing the impedance changes in different regions of the lung. This image pixel matrix represents the impedance changes in different regions of the lung. After integrating the whole chest impedance data acquired by multiple sets of electrode switching, a continuous first lung ventilation image sequence is constructed.

[0025] Optionally, the acquisition of human chest impedance data using electrical impedance tomography includes: using a first electrode pair as an excitation electrode pair to apply a high-frequency constant current excitation signal to the human chest; using a second electrode pair as a acquisition electrode pair to acquire a differential voltage response signal modulated by the human chest impedance; and according to a preset electrode rotation strategy, using a third electrode pair as an excitation electrode pair and a fourth electrode pair as an acquisition electrode pair, and entering the next measurement time slot to repeat the operation of applying the excitation signal and acquiring the response signal; wherein the first electrode pair and the second electrode pair are different electrode pairs, and the third electrode pair and the fourth electrode pair are different electrode pairs.

[0026] Specifically, the EIT control module first sends an initial electrode configuration command to the high-speed switch module, driving the high-speed switch module to accurately select the first electrode pair deployed on the human chest and switch it to the excitation channel. At the same time, it selects the second electrode pair that does not overlap with the first electrode pair and switches it to the acquisition channel. Subsequently, the high-frequency constant current excitation signal generated by the EIT stimulation module is transmitted to the first electrode pair and applied to the human chest through the excitation channel of the high-speed switch module. The differential voltage response signal after impedance modulation by the human chest is transmitted to the EIT acquisition module through the second electrode pair and the acquisition channel of the high-speed switch module, completing the signal interaction of the first measurement time slot.

[0027] After initial acquisition, the EIT control module sends a switching control signal to the high-speed switching module according to the preset electrode rotation strategy. The high-speed switching module quickly disconnects the excitation channel and acquisition channel of the previous measurement time slot and completes the electrode switching action within microseconds. The third electrode pair is switched to the excitation channel, and the fourth electrode pair, which does not overlap with the third electrode pair, is switched to the acquisition channel. During the switching process, the timing isolation between the excitation channel and the acquisition channel is strictly ensured to avoid signal interference caused by switching transients.

[0028] After the switch is completed, the next measurement time slot begins. The high-speed switching module can maintain the current electrode channel connection state and work with the EIT stimulation module and EIT acquisition module to repeatedly perform excitation signal application and response signal acquisition operations. Subsequently, following the same logic, the high-speed switching module continuously performs dynamic switching of multiple different electrode pairs. Each switch is precisely controlled by the module to ensure the strict distinction between the first electrode pair and the second electrode pair, and between the third electrode pair and the fourth electrode pair, and that there is no conflict in the electrode combinations of each measurement time slot. Finally, through the efficient dynamic switching of the high-speed switching module, multi-path, interference-free human chest impedance data acquisition is achieved.

[0029] Based on the above solution, on the one hand, by switching the high-speed switching module, the same set of electrodes can be flexibly switched to excitation electrodes or acquisition electrodes, thereby greatly reducing the number of electrodes deployed and simplifying the hardware structure and the complexity of wearing them on the human body; on the other hand, since the high-speed switching module can achieve strict timing isolation between the excitation channel and the acquisition channel, the switching action is completed in microseconds and avoids synchronous switching of the two channels, thus eliminating the overlap of excitation signals and acquisition signals and transient interference during switching, ensuring the purity and accuracy of the impedance measurement signal.

[0030] S102, the diaphragm stimulation control device extracts the global ventilation curve from the first lung ventilation image sequence and determines the key points of the respiratory cycle based on the global ventilation curve.

[0031] The key points of the respiratory cycle include at least one of the following: the start point of inhalation, the peak point of inhalation, the start point of exhalation, and the end point of exhalation.

[0032] Specifically, the diaphragm stimulation control device can first receive the first lung ventilation image sequence data through the EIT control module, call the image preprocessing algorithm, drive the built-in data processing unit to remove the background region of each frame in the sequence, accurately filter non-ventilation-related areas such as the chest wall edge and the heart pulsation area, and then use the automatic region of interest (ROI) segmentation algorithm to identify and separate the image regions corresponding to the left and right lungs to lock the core range of lung ventilation; then perform grayscale value summation operation on the pixel matrix of the left and right lung ROI regions in each frame to obtain the lung ventilation volume quantization value corresponding to a single frame image, and integrate the ventilation volume quantization values ​​of all frames in the order of the timestamp of the image sequence to form the original ventilation volume time-series waveform data.

[0033] Subsequently, the EIT control module further initiates a noise suppression process, processing the raw tidal volume time-series waveform data through a built-in low-pass filter or Kalman filter unit to filter out high-frequency interference and random noise, outputting a smooth and continuous global tidal volume curve. Based on this global tidal volume curve, a phase recognition algorithm is invoked to calculate the first and second derivatives of the curve in real time. Simultaneously, preset positive and negative thresholds are loaded to perform feature point analysis: when the first derivative is detected to be greater than or equal to the preset positive threshold, it is determined to be the inspiratory start point; when the first derivative is detected to be 0 and the second derivative is detected to be less than 0, it is determined to be the inspiratory peak point; when the first derivative is detected to be less than or equal to the preset negative threshold, it is determined to be the expiratory start point; when the value of the global tidal volume curve is detected to be close to the baseline and remains stable, it is determined to be the expiratory end point, ultimately completing the accurate identification and location of key points in the respiratory cycle.

[0034] S103. The diaphragm stimulation control device determines the inspiratory triggering time of the next cycle based on the key points of the respiratory cycle, triggers diaphragm electrical stimulation according to the inspiratory triggering time, and collects the second lung ventilation image sequence after stimulation.

[0035] Optionally, determining the inspiratory triggering timing of the next cycle based on the key points of the respiratory cycle includes: determining the cycle length of the most recent N historical respiratory cycles and the phase shift corresponding to each key point of the respiratory cycle; obtaining the predicted cycle length by calculating the mean of the N historical respiratory cycles and adaptively estimating the predicted phase shift; and calculating the inspiratory triggering timing of the next cycle based on the predicted cycle length, the predicted phase shift, and the end-expiration time of the previous historical respiratory cycle.

[0036] Specifically, the EIT control module of the diaphragm stimulation control device can call a historical data statistical algorithm to extract complete data from the most recent N historical respiratory cycles. Based on the identified key points of the respiratory cycle, it calculates the cycle length of each historical cycle, which is the time interval from the end of the previous expiration to the current end of expiration. Simultaneously, it records the phase offset of key points such as the inspiratory start point and the peak inspiratory point relative to the start of the cycle within each cycle. Subsequently, the EIT control module can calculate the cycle length of the N historical respiratory cycles using a mean algorithm to obtain the predicted cycle length T_pred=mean(T1, T2, ..., T...). n The system employs an adaptive filtering algorithm to analyze the phase shift of each cycle and dynamically estimates the predicted phase drift Δφ that may occur during respiration to compensate for minor fluctuations in the respiratory rhythm. Finally, the EIT control module can retrieve the end-expiration time t_last of the previous historical respiratory cycle, combine it with the calculated predicted cycle length T_pred and the predicted phase drift Δφ, and calculate the inspiratory trigger timing of the next cycle according to preset logic, providing a basis for precise synchronous stimulation.

[0037] Optionally, the step of calculating the inspiratory trigger timing for the next cycle based on the predicted cycle length, the predicted phase drift, and the end-expiratory time of the previous historical respiratory cycle includes: inspiratory trigger timing for the next cycle = end-expiratory time of the previous historical respiratory cycle + predicted cycle length - predicted phase drift - preset pre-trigger time; wherein, the preset pre-trigger time is the advance triggering duration to synchronize the diaphragm contraction with the natural inspiratory action.

[0038] Specifically, the EIT control module can use the end-expiratory time t_last of the previous historical respiratory cycle as a reference, and substitute the predicted cycle length T_pred, the predicted phase drift Δφ, and the preset pre-trigger time t_pre into the following formula: The inspiratory trigger time for the next cycle = the end of the expiration time of the previous historical respiratory cycle + the predicted cycle length - the predicted phase drift - the preset pre-trigger time. The preset pre-trigger time t_pre is a fixed duration set based on the characteristics of nerve conduction delay in the human diaphragm. For example, it can be 50-150ms. Its value can be finely adjusted according to the physiological state of different patients. Its core function is to advance the start time of diaphragm electrical stimulation to the predicted inhalation start point, ensuring that the moment when electrical stimulation drives diaphragm contraction is precisely synchronized with the body's natural inhalation action, and avoiding stimulation lag caused by nerve conduction delay.

[0039] Optionally, the step of triggering diaphragmatic electrical stimulation according to the inspiratory trigger timing and acquiring the second lung ventilation image sequence after stimulation includes: triggering diaphragmatic electrical stimulation according to the inspiratory trigger timing, suppressing stimulation artifacts through multiple parallel mechanisms during stimulation, and acquiring the second lung ventilation image sequence after stimulation; wherein, the multiple parallel mechanisms include at least one of the following: a temporal shielding mechanism, an artifact template elimination mechanism, and a wavelet domain noise suppression mechanism; the temporal shielding mechanism refers to pausing the acquisition of human chest impedance data for a preset duration before stimulation and resuming sampling after stimulation with a preset delay, so as to avoid interference from the stimulation signal; the artifact template elimination mechanism refers to generating a reverse compensation signal based on the known electrical stimulation transmission waveform to cancel the power frequency and motion artifacts at the receiving end; the wavelet domain noise suppression mechanism refers to performing wavelet threshold filtering on ventilation signals and image pixel changes to correct signal distortion during stimulation.

[0040] Specifically, such as Figure 2 As shown, the diaphragm stimulation control device also includes a base plate module and a diaphragm electrical stimulation module. The base plate module includes a base plate power supply module, a base plate control module, and a base plate transmission module. The diaphragm electrical stimulation module includes a constant current generation module, a current monitoring module, a diaphragm control module, and a diaphragm power supply module. The diaphragm stimulation control device can provide a stable and isolated power supply to the base plate control module and the base plate transmission module through the base plate power supply module, and provide an adapter power supply to the constant current generation module, the current monitoring module, and the diaphragm control module through the diaphragm power supply module, ensuring coordinated operation of stimulation and artifact suppression. The base plate control module can receive the inspiratory trigger signal uploaded by the EIT control module and send stimulation start commands and preset stimulation parameters to the diaphragm control module through the base plate transmission module. The diaphragm control module can respond to the commands, driving the constant current generation module to generate a diaphragm electrical stimulation signal that meets the parameter requirements, while simultaneously controlling the current monitoring module to monitor the actual value of the stimulation current in real time, ensuring stimulation safety. While the electrical stimulation signal is applied to the human body through the stimulation electrodes, the base plate control module can coordinate the EIT module to activate multiple parallel artifact suppression mechanisms, achieving anti-interference coordination between stimulation and acquisition. Regarding the timing shielding mechanism, the base plate control module can send timing control signals to the EIT control module. The EIT control module drives the high-speed switching module to pause the application of the high-frequency constant current excitation signal and impedance data acquisition for a preset duration before stimulation. After the diaphragm electrical stimulation ends, the EIT stimulation module and acquisition module resume operation for a preset duration. Interference from the strong electrical stimulation signal is directly avoided through timing avoidance. Regarding the artifact template elimination mechanism, the diaphragm control module can synchronize the known electrical stimulation emission waveform of the constant current generation module to the EIT control module through the base plate transmission module. The EIT control module can generate a reverse compensation signal based on the waveform and send it to the EIT acquisition module. When the EIT acquisition module acquires the voltage response signal, it uses the reverse compensation signal to cancel the power frequency interference and motion artifacts at the receiving end in real time. Regarding the wavelet domain noise suppression mechanism, the EIT control module can call the built-in wavelet threshold filtering algorithm after receiving the impedance data during stimulation uploaded by the EIT acquisition module to process the ventilation signal and image pixel change data, accurately filter artifact noise, and correct signal distortion.

[0041] With the protection of multiple parallel artifact suppression mechanisms, the EIT module can acquire human chest impedance data after stimulation through the EIT stimulation module, high-speed switch module, and EIT acquisition module in the same acquisition process as S101. The image is then reconstructed by the EIT control module, and finally the second lung ventilation image sequence is obtained.

[0042] Based on the above scheme, firstly, by coordinating the working timing of the EIT module and the diaphragm electrical stimulation module through the base plate module, the diaphragm electrical stimulation is precisely triggered according to the predicted inspiratory trigger timing, so that the diaphragm contraction is synchronized with the body's natural inspiratory action, which can significantly improve the synchronization accuracy of diaphragm stimulation; secondly, relying on a multi-parallel artifact suppression mechanism consisting of timing shielding, artifact template elimination, and wavelet domain noise suppression, the strong interference caused by electrical stimulation is offset from multiple dimensions such as timing avoidance, signal compensation, and noise filtering, which can ensure that pure impedance data can still be collected during the stimulation process, realizing the parallel operation of stimulation and imaging, and solving the pain point of imaging failure caused by stimulation interference in traditional technology; thirdly, the current monitoring module of the diaphragm electrical stimulation module monitors the stimulation current in real time, and with the power isolation design of the base plate module, it can effectively avoid safety risks such as overcurrent and leakage, and ensure the safety and consistency of the treatment process; fourthly, the acquired second lung ventilation image sequence maintains accuracy under the anti-interference mechanism, which can fully reflect the lung ventilation effect after stimulation, and provide a reliable data basis for subsequent adaptive adjustment of stimulation parameters based on lung imaging.

[0043] S104. The diaphragm stimulation control device extracts ventilation effect feedback indicators from the second lung ventilation image sequence and adaptively adjusts the diaphragm electrical stimulation parameters according to the ventilation effect feedback indicators.

[0044] Optionally, the step of extracting ventilation effect feedback indicators from the second lung ventilation image sequence and adaptively adjusting diaphragmatic electrical stimulation parameters based on the ventilation effect feedback indicators includes: extracting ventilation effect feedback indicators from the second lung ventilation image sequence, wherein the ventilation effect feedback indicators include at least one of the following: maximum pulmonary ventilation increase, left and right lung ventilation balance, lung ventilation area, expansion rate improvement, and respiratory cycle matching degree; comparing the ventilation effect feedback indicators with preset thresholds according to a preset index threshold and parameter adjustment mapping relationship; if the ventilation effect feedback indicators do not reach the preset threshold, adjusting the diaphragmatic electrical stimulation parameters in the forward direction according to a preset step size; if the ventilation effect feedback indicators exceed the preset threshold, adjusting the diaphragmatic electrical stimulation parameters in the reverse direction according to a preset step size; if the ventilation effect feedback indicators are within the preset threshold range, keeping the current diaphragmatic electrical stimulation parameters unchanged; wherein the diaphragmatic electrical stimulation parameters include at least one of the following: stimulation current intensity, stimulation pulse width, stimulation frequency, and stimulation waveform.

[0045] Specifically, after receiving the second lung ventilation image sequence acquired after stimulation, the EIT control module of the diaphragm stimulation control device can call the image feature extraction algorithm to perform ROI region segmentation and quantitative analysis on each frame of image: calculate the difference between the maximum lung ventilation before and after stimulation to obtain the increase in maximum lung ventilation, calculate the left and right lung ventilation balance by the ratio of left and right lung ventilation, count the total number of pixels in the lung ventilation area to obtain the lung ventilation area, compare the expansion amplitude of the target lung area before and after stimulation to obtain the expansion improvement rate, and analyze the fit between the stimulation cycle and the natural breathing cycle to obtain the breathing cycle matching degree.

[0046] Then, the EIT control module can transmit the extracted ventilation effect feedback indicators to the base plate control module through the base plate transmission module. The base plate control module can load the preset indicator thresholds and parameter adjustment mapping relationship. Subsequently, each feedback indicator is compared with the corresponding preset threshold one by one: if the increase in maximum lung ventilation does not reach the threshold or the improvement rate of expansion is insufficient, the base plate control module generates a positive adjustment command, increasing the stimulation current intensity or stimulation pulse width by a preset step size; if the ventilation balance between the left and right lungs exceeds the threshold range or the respiratory cycle matching is abnormal, a reverse adjustment command is generated, decreasing the stimulation intensity of the corresponding side or adjusting the stimulation frequency and duty cycle by a preset step size; if all ventilation effect feedback indicators are within the preset threshold range, a maintenance command is generated to keep the current diaphragmatic electrical stimulation parameters unchanged.

[0047] Finally, the base plate control module can send adjustment or maintenance commands to the diaphragm control module of the diaphragm electrical stimulation module through the base plate transmission module. The diaphragm control module can respond to the commands and drive the constant current generation module to adjust parameters such as stimulation current intensity, stimulation pulse width, stimulation frequency or stimulation waveform, or maintain the current parameter output to complete the adaptive adjustment based on ventilation effect feedback.

[0048] In this embodiment, because human chest impedance data can be acquired using electrical impedance tomography (EIT) and a lung ventilation image sequence can be constructed, and a global ventilation curve can be extracted from the image sequence to determine key points of the respiratory cycle, non-invasive respiratory signal acquisition can be achieved, making it suitable for non-invasive respiratory therapy scenarios. Because the global ventilation curve extracted from the lung ventilation image sequence can accurately identify key points of the respiratory cycle such as the inspiratory start point and inspiratory peak point, the problem of limited measurement accuracy and difficulty in accurately identifying key respiratory phases in traditional chest band pressure sensors is solved, thus improving the accuracy of respiratory phase identification. Furthermore, because the inspiratory triggering timing for the next cycle can be determined based on the key points of the respiratory cycle,… Diaphragmatic electrical stimulation is triggered according to the described inspiratory trigger timing, thus achieving precise prediction and synchronization between diaphragmatic electrical stimulation and natural human breathing, significantly improving the stimulation synchronization accuracy of the respiratory assist device. Since a second lung ventilation image sequence can be acquired after stimulation, ventilation effect feedback indicators can be extracted from the second lung ventilation image sequence, and diaphragmatic electrical stimulation parameters can be adaptively adjusted according to the ventilation effect feedback indicators, forming a closed-loop control mechanism of stimulation-feedback-adjustment. Therefore, real-time monitoring of stimulation effect and dynamic optimization of parameters are achieved, avoiding the shortcomings of existing systems that lack real-time feedback and cannot adjust parameters according to the patient's actual ventilation situation, thus improving the synchronization and adaptability of diaphragmatic stimulation.

[0049] The foregoing mainly describes the solutions provided by the embodiments of this application from a methodological perspective. To achieve the above functions, it includes corresponding hardware structures and / or software modules for executing each function. Those skilled in the art should readily recognize that, in conjunction with the units and algorithm steps of the various examples described in the embodiments disclosed herein, the embodiments of this application can be implemented in hardware or a combination of hardware and computer software. Whether a function is executed in hardware or by computer software driving hardware depends on the specific application and design constraints of the technical solution. Those skilled in the art can use different methods to implement the described functions for each specific application, but such implementation should not be considered beyond the scope of this application.

[0050] It should be noted that the steps shown in the flowchart in the accompanying drawings can be executed in a computer system such as a set of computer-executable instructions, and although a logical order is shown in the flowchart, in some cases the steps shown or described may be executed in a different order than that shown here.

[0051] The diaphragm stimulation control method provided in this application can be executed by a diaphragm stimulation control device or a control module for diaphragm stimulation control within that device. This application uses the diaphragm stimulation control device executing the diaphragm stimulation control method as an example to illustrate the diaphragm stimulation control device provided in this application.

[0052] It should be noted that the embodiments of this application can divide the diaphragm stimulation control device into functional modules according to the above method examples. For example, each function can be divided into its own functional module, or two or more functions can be integrated into one processing module. The integrated module can be implemented in hardware or as a software functional module. Optionally, the module division in the embodiments of this application is illustrative and only represents one logical functional division; other division methods may be used in actual implementation.

[0053] like Figure 3 As shown in the figure, this application embodiment provides a diaphragm stimulation control device 300. The diaphragm stimulation control device 300 includes: a data acquisition module 301 and a processing module 302; the data acquisition module 301 is used to acquire human chest impedance data using electrical impedance tomography (EIT); the processing module 302 is used to construct a first lung ventilation image sequence based on the human chest impedance data; extract a global ventilation curve from the first lung ventilation image sequence, and determine key points of the respiratory cycle based on the global ventilation curve, the key points of the respiratory cycle including at least one of the following: inspiratory start point, inspiratory peak point, expiratory start point, and expiratory end point; determine the inspiratory triggering timing for the next cycle based on the key points of the respiratory cycle, and trigger diaphragm electrical stimulation according to the inspiratory triggering timing; the data acquisition module 301 is used to acquire a second lung ventilation image sequence after stimulation; the processing module 302 is used to extract ventilation effect feedback indicators from the second lung ventilation image sequence, and adaptively adjust diaphragm electrical stimulation parameters based on the ventilation effect feedback indicators.

[0054] Optionally, the step of triggering diaphragmatic electrical stimulation according to the inspiratory trigger timing and acquiring the second lung ventilation image sequence after stimulation includes: triggering diaphragmatic electrical stimulation according to the inspiratory trigger timing, suppressing stimulation artifacts through multiple parallel mechanisms during stimulation, and acquiring the second lung ventilation image sequence after stimulation; wherein, the multiple parallel mechanisms include at least one of the following: a temporal shielding mechanism, an artifact template elimination mechanism, and a wavelet domain noise suppression mechanism; the temporal shielding mechanism refers to pausing the acquisition of human chest impedance data for a preset duration before stimulation and resuming sampling after stimulation with a preset delay, so as to avoid interference from the stimulation signal; the artifact template elimination mechanism refers to generating a reverse compensation signal based on the known electrical stimulation transmission waveform to cancel the power frequency and motion artifacts at the receiving end; the wavelet domain noise suppression mechanism refers to performing wavelet threshold filtering on ventilation signals and image pixel changes to correct signal distortion during stimulation.

[0055] Optionally, determining the inspiratory triggering timing of the next cycle based on the key points of the respiratory cycle includes: determining the cycle length of the most recent N historical respiratory cycles and the phase shift corresponding to each key point of the respiratory cycle; obtaining the predicted cycle length by calculating the mean of the N historical respiratory cycles and adaptively estimating the predicted phase shift; and calculating the inspiratory triggering timing of the next cycle based on the predicted cycle length, the predicted phase shift, and the end-expiration time of the previous historical respiratory cycle.

[0056] Optionally, the step of calculating the inspiratory trigger timing for the next cycle based on the predicted cycle length, the predicted phase drift, and the end-expiratory time of the previous historical respiratory cycle includes: inspiratory trigger timing for the next cycle = end-expiratory time of the previous historical respiratory cycle + predicted cycle length - predicted phase drift - preset pre-trigger time; wherein, the preset pre-trigger time is the advance triggering duration to synchronize the diaphragm contraction with the natural inspiratory action.

[0057] Optionally, the acquisition of human chest impedance data using electrical impedance tomography includes: using a first electrode pair as an excitation electrode pair to apply a high-frequency constant current excitation signal to the human chest; using a second electrode pair as a acquisition electrode pair to acquire a differential voltage response signal modulated by the human chest impedance; and according to a preset electrode rotation strategy, using a third electrode pair as an excitation electrode pair and a fourth electrode pair as an acquisition electrode pair, and entering the next measurement time slot to repeat the operation of applying the excitation signal and acquiring the response signal; wherein the first electrode pair and the second electrode pair are different electrode pairs, and the third electrode pair and the fourth electrode pair are different electrode pairs.

[0058] Optionally, the step of extracting ventilation effect feedback indicators from the second lung ventilation image sequence and adaptively adjusting diaphragmatic electrical stimulation parameters based on the ventilation effect feedback indicators includes: extracting ventilation effect feedback indicators from the second lung ventilation image sequence, wherein the ventilation effect feedback indicators include at least one of the following: maximum pulmonary ventilation increase, left and right lung ventilation balance, lung ventilation area, expansion rate improvement, and respiratory cycle matching degree; comparing the ventilation effect feedback indicators with preset thresholds according to a preset index threshold and parameter adjustment mapping relationship; if the ventilation effect feedback indicators do not reach the preset threshold, adjusting the diaphragmatic electrical stimulation parameters in the forward direction according to a preset step size; if the ventilation effect feedback indicators exceed the preset threshold, adjusting the diaphragmatic electrical stimulation parameters in the reverse direction according to a preset step size; if the ventilation effect feedback indicators are within the preset threshold range, keeping the current diaphragmatic electrical stimulation parameters unchanged; wherein the diaphragmatic electrical stimulation parameters include at least one of the following: stimulation current intensity, stimulation pulse width, stimulation frequency, and stimulation waveform.

[0059] In this embodiment, because human chest impedance data can be acquired using electrical impedance tomography (EIT) and a lung ventilation image sequence can be constructed, and a global ventilation curve can be extracted from the image sequence to determine key points of the respiratory cycle, non-invasive respiratory signal acquisition can be achieved, making it suitable for non-invasive respiratory therapy scenarios. Because the global ventilation curve extracted from the lung ventilation image sequence can accurately identify key points of the respiratory cycle such as the inspiratory start point and inspiratory peak point, the problem of limited measurement accuracy and difficulty in accurately identifying key respiratory phases in traditional chest band pressure sensors is solved, thus improving the accuracy of respiratory phase identification. Furthermore, because the inspiratory triggering timing for the next cycle can be determined based on the key points of the respiratory cycle,… Diaphragmatic electrical stimulation is triggered according to the described inspiratory trigger timing, thus achieving precise prediction and synchronization between diaphragmatic electrical stimulation and natural human breathing, significantly improving the stimulation synchronization accuracy of the respiratory assist device. Since a second lung ventilation image sequence can be acquired after stimulation, ventilation effect feedback indicators can be extracted from the second lung ventilation image sequence, and diaphragmatic electrical stimulation parameters can be adaptively adjusted according to the ventilation effect feedback indicators, forming a closed-loop control mechanism of stimulation-feedback-adjustment. Therefore, real-time monitoring of stimulation effect and dynamic optimization of parameters are achieved, avoiding the shortcomings of existing systems that lack real-time feedback and cannot adjust parameters according to the patient's actual ventilation situation, thus improving the synchronization and adaptability of diaphragmatic stimulation.

[0060] Figure 4 An example is a schematic diagram of the physical structure of an electronic device, such as... Figure 4As shown, the electronic device may include: a processor 410, a communications interface 420, a memory 430, and a communications bus 440, wherein the processor 410, the communications interface 420, and the memory 430 communicate with each other through the communications bus 440. The processor 410 can call logic instructions in the memory 430 to execute a diaphragm stimulation control method, which includes: acquiring human chest impedance data using electrical impedance tomography and constructing a first lung ventilation image sequence based on the human chest impedance data; extracting a global ventilation curve from the first lung ventilation image sequence and determining key points of the respiratory cycle based on the global ventilation curve, wherein the key points of the respiratory cycle include at least one of the following: inspiratory start point, inspiratory peak point, expiratory start point, and expiratory end point; determining the inspiratory triggering timing for the next cycle based on the key points of the respiratory cycle, triggering diaphragm electrical stimulation according to the inspiratory triggering timing, and acquiring a second lung ventilation image sequence after stimulation; extracting ventilation effect feedback indicators from the second lung ventilation image sequence and adaptively adjusting diaphragm electrical stimulation parameters based on the ventilation effect feedback indicators.

[0061] Furthermore, the logical instructions in the aforementioned memory 430 can be implemented as software functional units and, when sold or used as independent products, can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods described in the various embodiments of the present invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0062] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the diaphragm stimulation control method provided by the above methods. The method includes: acquiring human chest impedance data through electrical impedance tomography and constructing a first lung ventilation image sequence based on the human chest impedance data; extracting a global ventilation curve from the first lung ventilation image sequence and determining key points of the respiratory cycle based on the global ventilation curve. The key points of the respiratory cycle include at least one of the following: the start point of inspiration, the peak point of inspiration, the start point of expiration, and the end point of expiration; determining the inspiration triggering timing for the next cycle based on the key points of the respiratory cycle, triggering diaphragm electrical stimulation according to the inspiration triggering timing, and acquiring a second lung ventilation image sequence after stimulation; extracting ventilation effect feedback indicators from the second lung ventilation image sequence and adaptively adjusting diaphragm electrical stimulation parameters based on the ventilation effect feedback indicators.

[0063] In another aspect, the present invention also provides a non-transitory computer-readable storage medium storing a computer program thereon, which, when executed by a processor, implements the diaphragm stimulation control method provided by the above methods. The method includes: acquiring human chest impedance data using electrical impedance tomography (EIT) and constructing a first lung ventilation image sequence based on the human chest impedance data; extracting a global ventilation curve from the first lung ventilation image sequence and determining key points of the respiratory cycle based on the global ventilation curve, the key points of the respiratory cycle including at least one of the following: inspiratory start point, inspiratory peak point, expiratory start point, and expiratory end point; determining the inspiratory triggering timing for the next cycle based on the key points of the respiratory cycle, triggering diaphragm electrical stimulation according to the inspiratory triggering timing, and acquiring a second lung ventilation image sequence after stimulation; extracting ventilation effect feedback indicators from the second lung ventilation image sequence and adaptively adjusting diaphragm electrical stimulation parameters based on the ventilation effect feedback indicators.

[0064] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs. Those skilled in the art can understand and implement this without any creative effort.

[0065] Obviously, those skilled in the art should understand that the various units or steps of this application described above can be implemented using general-purpose computing devices. They can be centralized on a single computing device or distributed across a network of multiple computing devices. Optionally, they can be implemented using computer-executable program code, thereby storing them in a storage device for execution by a computing device, or fabricating them separately as individual integrated circuit modules, or fabricating multiple modules or steps into a single integrated circuit module. Thus, this application is not limited to any particular combination of hardware and software.

[0066] The above description is merely a preferred embodiment of this application and is not intended to limit this application. Various modifications and variations can be made to this application by those skilled in the art. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. A method for controlling diaphragmatic stimulation, characterized in that, include: Impedance data of the human chest were acquired using electrical impedance tomography, and a first lung ventilation image sequence was constructed based on the human chest impedance data. The global ventilation curve is extracted from the first lung ventilation image sequence, and the key points of the respiratory cycle are determined based on the global ventilation curve. The key points of the respiratory cycle include at least one of the following: the start point of inspiration, the peak point of inspiration, the start point of expiration, and the end point of expiration. Based on the key points of the respiratory cycle, determine the inspiratory triggering time for the next cycle, trigger diaphragmatic electrical stimulation according to the inspiratory triggering time, and collect the second lung ventilation image sequence after stimulation. The ventilation effect feedback index is extracted from the second lung ventilation image sequence, and the diaphragm electrical stimulation parameters are adaptively adjusted according to the ventilation effect feedback index.

2. The diaphragm stimulation control method according to claim 1, characterized in that, The step of triggering diaphragmatic electrical stimulation according to the inspiratory trigger timing and acquiring a second lung ventilation image sequence after stimulation includes: Diaphragmatic electrical stimulation is triggered according to the inspiratory trigger timing, and stimulation artifacts are suppressed through multiple parallel mechanisms during the stimulation process, as well as the second lung ventilation image sequence is acquired after stimulation. The multiple parallel mechanisms include at least one of the following: a timing masking mechanism, an artifact template elimination mechanism, and a wavelet domain noise suppression mechanism. The timing masking mechanism refers to pausing the acquisition of human chest impedance data for a preset duration before stimulation and resuming sampling after stimulation with a preset delay, so as to avoid interference from the stimulation signal. The artifact template elimination mechanism refers to generating a reverse compensation signal based on the known electrical stimulation emission waveform to cancel out the power frequency and motion artifacts at the receiving end. The wavelet domain noise suppression mechanism refers to performing wavelet threshold filtering on ventilation signals and image pixel changes to correct signal distortion during stimulation.

3. The diaphragm stimulation control method according to claim 1, characterized in that, The step of determining the inspiratory trigger timing for the next cycle based on the key points of the respiratory cycle includes: Determine the cycle length of the most recent N historical respiratory cycles and the phase offset corresponding to the key point of each respiratory cycle; The predicted cycle length is obtained by calculating the mean of the N historical respiratory cycles, and the predicted phase drift is adaptively estimated. Based on the predicted cycle length, predicted phase drift, and the end-expiration time of the previous historical respiratory cycle, the inspiratory trigger timing for the next cycle is calculated.

4. The diaphragm stimulation control method according to claim 3, characterized in that, The calculation of the inspiratory trigger timing for the next cycle based on the predicted cycle length, predicted phase drift, and the end-expiratory time of the previous historical respiratory cycle includes: The inspiratory trigger time for the next cycle = the end of the expiration time of the previous historical respiratory cycle + the predicted cycle length - the predicted phase drift - the preset pre-trigger time. The preset pre-trigger time is the advance triggering time that allows the diaphragm contraction to synchronize with the natural inhalation action.

5. The diaphragm stimulation control method according to claim 1, characterized in that, The acquisition of human chest impedance data via electrical impedance tomography includes: The first electrode pair is used as the excitation electrode pair to apply a high-frequency constant current excitation signal to the human chest. The second electrode pair is used as the acquisition electrode pair to acquire the differential voltage response signal after impedance modulation of the human chest. According to the preset electrode rotation strategy, the third electrode pair is used as the excitation electrode pair and the fourth electrode pair is used as the acquisition electrode pair. Then, the next measurement time slot is entered, and the operation of applying the excitation signal and acquiring the response signal is repeated. Wherein, the first electrode pair and the second electrode pair are different electrode pairs, and the third electrode pair and the fourth electrode pair are different electrode pairs.

6. The diaphragm stimulation control method according to claim 1, characterized in that, The step of extracting ventilation effect feedback indicators from the second lung ventilation image sequence and adaptively adjusting diaphragmatic electrical stimulation parameters based on the ventilation effect feedback indicators includes: The ventilation effect feedback index is extracted from the second lung ventilation image sequence. The ventilation effect feedback index includes at least one of the following: the increase in maximum lung ventilation, the balance of ventilation between the left and right lungs, the area of ​​the lung ventilation region, the improvement rate of the degree of expansion, and the degree of matching of the respiratory cycle. The mapping relationship is adjusted according to the preset index threshold and parameters, and the ventilation effect feedback index is compared with the preset threshold. If the ventilation effect feedback index does not reach the preset threshold, the diaphragm electrical stimulation parameters are adjusted forward according to the preset step size; if the ventilation effect feedback index exceeds the preset threshold, the diaphragm electrical stimulation parameters are adjusted backward according to the preset step size; if the ventilation effect feedback index is within the preset threshold range, the current diaphragm electrical stimulation parameters are kept unchanged. The diaphragm electrical stimulation parameters include at least one of the following: stimulation current intensity, stimulation pulse width, stimulation frequency, and stimulation waveform.

7. A diaphragm stimulation control device, characterized in that, include: Acquisition module and processing module; The acquisition module is used to acquire human chest impedance data using electrical impedance tomography (EIT) technology. The processing module is configured to construct a first lung ventilation image sequence based on the human chest impedance data; extract a global ventilation curve from the first lung ventilation image sequence, and determine key points of the respiratory cycle based on the global ventilation curve, wherein the key points of the respiratory cycle include at least one of the following: inspiratory start point, inspiratory peak point, expiratory start point, and expiratory end point; determine the inspiratory triggering timing for the next cycle based on the key points of the respiratory cycle, and trigger diaphragmatic electrical stimulation according to the inspiratory triggering timing; The acquisition module is used to acquire second lung ventilation image sequences after stimulation; The processing module is used to extract ventilation effect feedback indicators from the second lung ventilation image sequence and adaptively adjust the diaphragm electrical stimulation parameters according to the ventilation effect feedback indicators.

8. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the computer program, it implements the diaphragm stimulation control method as described in any one of claims 1 to 6.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the diaphragm stimulation control method as described in any one of claims 1 to 6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the diaphragm stimulation control method as described in any one of claims 1 to 6.

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