A gastric function regulation system based on gastric rhythm information feedback

Abstract

This invention discloses a gastric function regulation system based on gastric rhythm information feedback, comprising a gastric function regulation device, a client, and a cloud platform. The client controls the start and stop of the gastric function regulation device and processes and analyzes the gastric electrical signals collected by the device to obtain gastric rhythm parameters for the current time period. These parameters are then used to obtain vagus nerve stimulation parameters. The gastric function regulation device applies vagus nerve stimulation to the body according to the vagus nerve stimulation parameters, and also collects gastric electrical signals. The cloud platform stores historical usage records, including stimulation parameters and changes in gastric rhythm parameters during use. This invention uses changes in gastric rhythm during stimulation and the user's historical usage to provide feedback and guide vagus nerve stimulation parameters, achieving a more precise and individualized gastric function regulation process.

Description

Technical Field

[0001] This invention belongs to the field of gastric function regulation technology, specifically relating to a gastric function regulation system based on gastric rhythm information feedback. Background Technology

[0002] Electrogastrogram (EGG) is a non-invasive technique that records gastric electrical signals from the abdominal surface using surface electrodes. It can reflect the functional state of gastric motility to some extent and has certain clinical value. Analyzing EGG signals reveals the rhythmic information of slow gastric waves—a major regulator of gastric motility—including frequency, amplitude, and propagation direction. Slow gastric waves originate in the proximal pacemaker region and exhibit uneven amplitude and velocity characteristics as they propagate towards the pylorus. The propagation pattern and rhythmic information of slow gastric waves are key components of human digestive function. Studies have found that abnormal slow gastric waves are associated with various digestive system diseases, including gastroparesis, dyspepsia, and gastroesophageal reflux.

[0003] Chinese patent CN111467678A relates to a multifunctional implantable gastrointestinal stimulation system. This system includes a gastric tube and a gastric stimulator. The gastric stimulator includes a sealed outer shell, with stimulation electrodes and sensors connected to its surface. The sensors include a miniature pressure sensor, a temperature sensor, and a pH sensor. A central processing module, a power processing module, and a communication module are housed within the sealed outer shell. A guidewire is inserted into the gastric tube, with one end connected to the central processing module, power processing module, and communication module within the sealed outer shell, and the other end fixedly connected to an external controller. The external controller has a display screen and a control panel on its outer surface. Chinese patent CN112155527A discloses a meridian acupoint stimulation device for promoting gastrointestinal motility, including an acupoint stimulation module, a blood oxygen detection module, a body temperature detection module, a heart rate detection module, a blood pressure detection module, a data processing module, an acupoint detection module, and a central control module. By vibrating or applying low-frequency electrical stimulation to the Zhongwan (CV12), Guanyuan (CV4), and two Tianshu (ST25) acupoints, it effectively promotes gastrointestinal peristalsis and facilitates defecation.

[0004] However, existing technologies for gastrointestinal stimulation are either invasive gastrointestinal stimulation systems that require operation by professional doctors, which not only carry certain risks but also have certain limitations; or, although they are non-invasive acupoint stimulation, their effectiveness is not evaluated based on physiological indicators that truly reflect changes in the gastrointestinal tract. Summary of the Invention

[0005] To address the aforementioned problems in the prior art, this invention provides a gastric function regulation system based on gastric rhythm information feedback. The technical problem to be solved by this invention is achieved through the following technical solution: This invention provides a gastric function regulation system based on gastric rhythm information feedback, characterized in that it includes a gastric function regulation device, a client, and a cloud platform, wherein... The client is used to control the start and end of the gastric function regulation device, and is also used to acquire the gastric electrical signals collected by the gastric function regulation device for processing and analysis to obtain the gastric rhythm parameters of the current time period, and then obtain the vagus nerve stimulation parameters of the next time period through the gastric rhythm parameters of the current time period. The gastric function regulation device is externally connected to a vagus nerve stimulation electrode in the ear, which is used to apply vagus nerve stimulation that can regulate gastric function according to the vagus nerve stimulation parameters, and is also used to connect a gastric electrical signal acquisition electrode to the abdomen to acquire gastric electrical signals. The cloud is used to store historical usage records, which include changes in stimulation parameters and gastric rhythm parameters during the usage process.

[0006] In one embodiment of the present invention, the gastric function regulation device includes an internal controller, a stimulation current signal generator, a physiological signal acquisition amplifier, and a power supply module, wherein, The internal controller is used to control the physiological signal acquisition amplifier to acquire the gastric electrical signal of the current period and transmit it to the client. It is also used to receive the vagus nerve stimulation parameters of the next period fed back by the client and send them to the stimulation current signal generator. The stimulation current signal generator is externally connected to a vagus nerve stimulation electrode, and is used to generate a vagus nerve stimulation signal according to the vagus nerve stimulation parameters and transmit it to the vagus nerve stimulation electrode. The physiological signal acquisition amplifier is connected to an external gastric electrical signal acquisition electrode, which is used to acquire gastric electrical signals during the regulation process and upload them to the client. The power module is used to provide isolated power to the internal controller, the stimulation current signal generator, and the physiological signal acquisition amplifier.

[0007] In one embodiment of the present invention, the gastric function regulation device is electrically connected to the gastric electrical signal acquisition electrode, the gastric electrical signal acquisition electrode comprising five acquisition electrodes, one reference electrode, and one ground electrode, wherein... The first sampling point is located at the xiphoid process; the second sampling point is located at the midpoint between the xiphoid process and the navel; the fourth sampling point is located at the intersection of the horizontal line of the first sampling point and the vertical line of the midclavicular line; the fifth sampling point is located at the intersection of the horizontal line of the second sampling point and the vertical line of the midclavicular line; and the third sampling point is located at the intersection of the diagonals of the rectangle formed by the other four sampling points. The grounding electrode is located on the left abdomen, above the iliac crest; The reference electrode is symmetrically arranged with respect to the third acquisition site.

[0008] In one embodiment of the present invention, the client includes a switch module, a communication module, a data processing module, an analysis module, and a display module, wherein, The switch module is used to turn the gastric function regulating device on and off; The communication module is used to acquire gastric electrical signals collected by the gastric function regulation device; The data processing module is used to process the gastric electrical signal of the current time period to obtain the gastric rhythm parameters of the current time period. The gastric rhythm parameters include the gastric electrical dominant frequency, gastric electrical amplitude and the proportion of normal slow gastric waves. The analysis module is used to analyze and compare the gastric electrical dominant frequency, gastric electrical amplitude, and proportion of normal slow gastric waves with their corresponding normal ranges in the current time period, so as to obtain the vagus nerve stimulation intensity in the next time period. The display module is used to display the gastric electrical signal waveform, gastric rhythm parameters, and vagus nerve stimulation parameters in real time. The communication module is also used to feed back the vagus nerve stimulation intensity for the next time period to the gastric function regulation device.

[0009] In one embodiment of the present invention, the data processing module includes a power spectrum analysis unit, a filtering unit, a gastric electrical signal analysis unit, an artifact detection unit, and a gastric rhythm feature extraction unit, wherein, The power spectrum analysis unit is used to process the gastric electrical signal of the current time period, obtain the power spectrum of the gastric electrical signal of the current time period, and select the gastric electrical signal with the largest power spectrum among the gastric electrical signals collected by multiple gastric electrical signal acquisition electrodes. The filtering unit is used to filter the gastric electrical signal with the largest power spectrum to obtain the filtered gastric electrical signal. The gastric electrical signal analysis unit is used to analyze the filtered gastric electrical signal to obtain the analyzed phase information and instantaneous amplitude; The artifact recognition unit is used to screen out large amplitude vibrations caused by body movement and non-monotonic phase changes introduced by linear interference, and to obtain the screened gastric electrical signal. The gastric rhythm feature extraction unit is used to obtain the gastric rhythm parameters for the current time period based on the filtered gastric electrical signals.

[0010] In one embodiment of the present invention, the power spectrum analysis unit is specifically used for: Determine the length of the gastric electrical signal acquired during the T time interval. N and sampling rate To determine the frequency resolution that satisfies the Nyquist law ; Generate a data window sequence based on the Slepian sequence:

[0011] in, n This indicates the start time of each data window within the raw gastric electrical signal. k The number of data windows is determined by the bandwidth parameter p of the data windows:

[0012] ; The acquired raw gastric electrocardiogram (ECG) signal is multiplied by the generated data window sequence to obtain... k A windowed data sequence and the windowed data sequence Perform a discrete Fourier transform to obtain the characteristic coefficients. :

[0013] in, This represents the product of the time index and the frequency index, where t represents time. For the characteristic coefficients Perform adaptive average weighting, using the ratio of the feature coefficients of each feature coefficient to... As weighting coefficients, the power spectrum of gastric electrical activity is obtained. : , in, .

[0014] In one embodiment of the present invention, the client further includes a judgment module, which is used to determine whether the vagus nerve stimulation intensity of the next time period is less than the preset maximum stimulation current intensity. If so, the vagus nerve stimulation intensity of the next time period is sent to the internal processor; if not, the vagus nerve stimulation intensity of the previous time period is sent to the internal processor.

[0015] In one embodiment of the present invention, the analysis module is specifically used for: The gastric electrical frequency is compared with its corresponding normal range. When the gastric electrical frequency is within its normal range, the result is obtained. When the dominant frequency of gastric electrical activity is less than the minimum value of its normal range, It is equal to the difference between the minimum value of the normal range of gastric electrical frequency and the gastric electrical frequency; when the gastric electrical frequency is greater than the maximum value of its normal range, It is equal to the difference between the main frequency of gastric electrical activity and its maximum value within the normal range; The gastric electrical amplitude is compared with its corresponding normal range. When the gastric electrical amplitude is within its normal range, the result is obtained. When the gastric electrical amplitude is less than the minimum value of its normal range, It is equal to the difference between the minimum value of the normal range of gastric electrical amplitude and the gastric electrical amplitude; when the gastric electrical amplitude is greater than the maximum value of its normal range, It is equal to the difference between the gastric electrical amplitude and its maximum value within the normal range; The normal proportion of slow gastric waves is compared with its corresponding normal range. When the normal proportion of slow gastric waves is within its normal range, the result is obtained. When the proportion of normal slow waves in the stomach is less than the minimum value of its normal range, It is equal to the difference between the minimum value of the normal range of slow gastric wave proportion and the normal slow gastric wave proportion; when the normal slow gastric wave proportion is greater than its maximum value within the normal range, It is equal to the difference between the proportion of normal slow waves in the stomach and the maximum value of its normal range; Calculate the current intensity of vagal nerve stimulation in the next time period:

[0016] Where m = 1, 2, 3, This represents the current intensity of the vagus nerve stimulation used in the previous time period. for The weight, This is the gain coefficient.

[0017] In one embodiment of the present invention, the analysis module is further configured to: When the gastric electrical frequency, the gastric electrical amplitude, and the proportion of normal slow gastric waves are all within their normal ranges, a command is sent to the switch module to turn off the gastric function regulation device.

[0018] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. This invention provides a gastric function regulation system based on gastric rhythm information feedback. It activates the user's vagus nerve complex non-invasively via the vagus nerve, using stimulated gastric rhythm parameters to provide feedback regulation of vagus nerve stimulation parameters. This maximizes the activation of the vagus nerve complex, regulating the gastric function system to a normal level. The system is simple to operate, can be self-administered, and features a visualized usage process and a report on gastric function improvement. This gastric function regulation system is the first to combine vagus nerve stimulation technology with gastric rhythm parameters. By analyzing changes in gastric rhythm during stimulation, it provides feedback guidance for vagus nerve stimulation parameters, achieving a more precise and individualized gastric function regulation process. This system can maximally regulate the user's gastric function system and promote appetite.

[0019] 2. The client-side APP of this invention enables control of the gastric function regulation device and visualization of gastric electrical signals, gastric rhythm parameters, and vagus nerve stimulation; the cloud provides storage for user historical data and usage reports. The wearable gastric electrical acquisition band designed in the gastric electrical acquisition section of the device enables a more portable and accurate acquisition process.

[0020] The present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0021] Figure 1 This is a schematic diagram of a gastric function regulation system based on gastric rhythm information feedback provided in an embodiment of the present invention; Figure 2 This is a schematic diagram of a vagus nerve and gastric electroacupuncture acquisition device provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of vagus nerve stimulation of the ear pole provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of a gastric electrical data acquisition device and a wearable gastric electrical data acquisition belt provided in an embodiment of the present invention; Figure 5 This is a framework diagram of a client provided in an embodiment of the present invention; Figure 6 This is a schematic diagram of a display module for a client provided in an embodiment of the present invention; Figure 7 This is a flowchart illustrating the use of a gastric function regulation system based on gastric rhythm information feedback, provided in an embodiment of the present invention. Figure 8 This is a power spectrum analysis diagram of a gastric electrical signal provided in an embodiment of the present invention; Figure 9 This is an example diagram of the calculation result of the normal slow wave proportion provided by an embodiment of the present invention. Detailed Implementation

[0022] To further illustrate the technical means and effects adopted by the present invention to achieve the intended purpose, the following detailed description of a gastric function regulation system based on gastric rhythm information feedback proposed according to the present invention is provided in conjunction with the accompanying drawings and specific embodiments.

[0023] The foregoing and other technical contents, features, and effects of the present invention will be clearly presented in the following detailed description of specific embodiments in conjunction with the accompanying drawings. Through the description of the specific embodiments, a more in-depth and concrete understanding can be gained of the technical means and effects adopted by the present invention to achieve its intended purpose. However, the accompanying drawings are for reference and illustration only and are not intended to limit the technical solutions of the present invention.

[0024] It should be noted that, in this document, relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations are intended to cover non-exclusive inclusion, such that an article or apparatus comprising a list of elements includes not only those elements but also other elements not expressly listed. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the article or apparatus that includes said element.

[0025] Please see Figure 1 , Figure 1 This is a schematic diagram of a gastric function regulation system based on gastric rhythm information feedback provided by an embodiment of the present invention. The gastric function regulation system includes a gastric function regulation device 100, a client 200, and a cloud 300. The client 200 is used to control the start and end of the gastric function regulation device 100, and also to acquire, process, and analyze the gastric electrical signals collected by the gastric function regulation device 100 to obtain the gastric rhythm parameters for the current time period, and then obtain the vagus nerve stimulation parameters for the next time period based on the gastric rhythm parameters for the current time period. The gastric function regulation device 100 is used to connect external vagus nerve stimulation electrodes to the user's ear to apply vagus nerve stimulation that can regulate gastric function, and to connect external gastric electrical signal acquisition electrodes to the user's abdomen to collect the user's gastric electrical signals, which are then uploaded to the client for real-time display and analysis to guide changes in the vagus nerve stimulation parameters. The cloud 300 is used to store the user's historical usage records, including changes in stimulation parameters and gastric rhythm parameters during use. Through repeated use and iterations, the user can achieve more precise regulation of gastric function.

[0026] In other words, the gastric function regulation system of this embodiment comprises three parts: the first part is a gastric function regulation device for applying vagus nerve stimulation and collecting gastric electrical signals; the second part is a client for interaction between the user and the gastric function regulation device; and the third part is a cloud platform for storing user data. These three parts work together to regulate the user's gastric function system and adjust appetite.

[0027] Further, please see Figure 2 , Figure 2This is a schematic diagram of a vagus nerve and gastric electrical signal acquisition device provided in an embodiment of the present invention. The gastric function regulation device 100 includes an internal controller 101, a stimulation current signal generator 102, a physiological signal acquisition amplifier 103, and a power module 104. The internal controller 101 controls the physiological signal acquisition amplifier 103 to acquire the gastric electrical signal of the human body in the current time period and transmit it to the client 200. It also receives vagus nerve stimulation parameters for the next time period from the client 200 and sends them to the stimulation current signal generator 102. The stimulation current signal generator 102 is externally connected to a vagus nerve stimulation electrode and is used to generate a vagus nerve stimulation signal according to the vagus nerve stimulation parameters and transmit it to the vagus nerve stimulation electrode. The physiological signal acquisition amplifier 103 is externally connected to a gastric electrical signal acquisition electrode and is used to acquire the user's gastric electrical signal during gastric function regulation and upload it to the client for analysis. The power module 104 provides isolated power to the internal controller 101, the stimulation current signal generator 102, and the physiological signal acquisition amplifier 103.

[0028] It is worth noting that the gastric function regulation device 100 is electrically connected to the vagus nerve stimulation electrode. One end of the vagus nerve stimulation electrode is fixed to the vagus nerve stimulation port of the gastric function regulation device 100, and the other end is fixed to the user's left ear. The electrode part connected to the ear is as follows: Figure 3 As shown. The positive electrode of this vagus nerve stimulation electrode is located at the cymba conchae (or medial side of the tragus) of the left ear, and the negative electrode is located at the medial side of the tragus (or cymba conchae) of the left ear. In addition, this gastric function modulation device 100 can also be connected to other vagus nerve stimulation electrodes, such as those used to stimulate the vagus nerve in the neck. In principle, stimulation electrodes are generally used to stimulate sites richly innervated by the vagus nerve, such as the aforementioned cymba conchae, tragus, or neck. The vagus nerve stimulation pulse is as follows: stimulation frequency of 25Hz; "on" phase with a duration of 30-60s; "off" phase with a duration of 60-120s; pulse width of 250-500μs; stimulation current intensity <5mA. The stimulation intensity during the "on" phase is the current intensity obtained from gastric rhythm parameters, and the stimulation current intensity during the "off" phase is zero. These stimulation parameter ranges are known and can enhance vagus nerve efferent activity.

[0029] Furthermore, the gastric function regulation device 100 is electrically connected to the gastric electrical signal acquisition electrode. One end of the gastric electrical signal acquisition electrode is fixed to the gastric electrical signal acquisition port of the gastric function regulation device, and the other end is fixed to the abdominal surface of the human body, located in the stomach area, such as... Figure 4As shown. The gastric electrocardiogram (GND) signal acquisition electrode consists of seven points, five of which are acquisition electrodes, and the remaining two are a reference electrode and a ground electrode, respectively. The first acquisition point 1 is located at the xiphoid process; the second acquisition point 2 is located at the midpoint between the xiphoid process and the navel; the fourth acquisition point 4 is located at the intersection of the horizontal line of the first acquisition point 1 and the vertical line of the midclavicular line; the fifth acquisition point 5 is located at the intersection of the horizontal line of the second acquisition point 2 and the vertical line of the midclavicular line; and the third acquisition point 3 is located at the intersection of the diagonals of the rectangle formed by the remaining four acquisition points 1, 2, 4, and 5. The ground electrode (GND) is located in the left abdomen, above the iliac crest, and the reference electrode (REF) is placed symmetrically with the third acquisition point 3.

[0030] The positions of the gastric electrical signal acquisition electrodes described above are the verified optimal gastric electrical signal acquisition sites. The part connecting the gastric electrical signal acquisition electrodes to the body is a wearable gastric electrical signal acquisition strap. Users can wear it themselves after cleaning their abdominal skin. Once the device is running, the impedance of each gastric electrical signal acquisition electrode can be used to check if the acquisition strap is worn correctly. The fixed connection part of this wearable gastric electrical signal acquisition strap can be as follows: Figure 4 The two ends are fitted with Velcro or buckles that allow the user to adjust the length of the acquisition band according to their body shape. The internal structure of the gastric electrical signal acquisition band includes all the electrodes for acquiring gastric electrical signals, a reference electrode, and a ground electrode. Each electrode has a lead-out wire inside the wearable gastric electrical signal acquisition band, which converges outside the band and connects to the gastric electrical signal acquisition port of the gastric function regulation device 100. This wearable gastric electrical signal acquisition band comes in different models to provide a more accurate and convenient gastric electrical signal acquisition method for users of different body types. In addition to using the acquisition band, the gastric electrical signal acquisition electrodes can also be used using electrode harnesses. One end of the electrode harness is divided into seven single-ended connections that attach to the various gastric electrical signal acquisition points on the abdomen. The other end of the electrode harness connects to the gastric electrical signal acquisition port of the device.

[0031] Furthermore, the client 200 allows the user to control the gastric function regulation device 100; it displays real-time gastric electrical signal waveforms, gastric rhythm parameters, and vagus nerve stimulation parameters during user use. Importantly, the client can process and analyze the gastric electrical signals collected by the gastric function regulation device 100 to obtain gastric rhythm parameters, including the dominant frequency of gastric electrical signals (the peak frequency within the power spectrum), gastric electrical amplitude, and the proportion of normal slow waves in the stomach. These gastric rhythm parameters are important peripheral indicators of vagus nerve stimulation regulating gastric function. Therefore, by analyzing the gastric electrical signals monitored during vagus nerve stimulation in the previous fixed time period, the client obtains the corresponding gastric rhythm parameters and guides the current intensity of vagus nerve stimulation in the next fixed time period based on these changes in gastric rhythm. This feedback mechanism maximizes the activation of the user's vagus nerve complex, regulates the user's gastric function system, and regulates appetite.

[0032] Please see Figure 5 , Figure 5 This is a schematic diagram of a client provided in an embodiment of the present invention. The client 200 includes a switch module 201, a communication module 202, a data processing module 203, an analysis module 204, and a display module 205. The switch module 201 is used to turn the gastric function regulation device 100 on and off; the communication module 202 is used to acquire gastric electrical signals collected by the gastric function regulation device 100; the data processing module 203 is used to process the gastric electrical signals of the current time period to obtain gastric rhythm parameters of the current time period, including the gastric electrical dominant frequency, gastric electrical amplitude, and the proportion of normal slow gastric waves; the analysis module 204 is used to analyze and compare the gastric electrical dominant frequency, gastric electrical amplitude, and the proportion of normal slow gastric waves of the current time period with their corresponding normal ranges to obtain vagus nerve stimulation parameters for the next time period; the display module 205 is used to display the gastric electrical signal waveform, gastric rhythm parameters, and vagus nerve stimulation parameters in real time, such as... Figure 6 The communication module 202 is also used to feed back the vagus nerve stimulation parameters for the next time period to the gastric function regulation device 100.

[0033] In this embodiment, the client 200 is a smart mobile device, which can be a tablet or a mobile phone, and is presented in the form of an APP.

[0034] Specifically, after the user turns on the gastric function regulation device 100 via the switch module 201, they can send a start command to the gastric function regulation device 100 via the start button on the client 200. Upon receiving the command, the internal processor 101 of the gastric function regulation device 100 controls the device to start operating. After the device starts operating, it will display the waveform of the gastric electrical signal in real time on the client 200, along with chart information related to gastric rhythm obtained through the internal data processing module, for the user to view. In addition, the client 200 will also display vagus nerve stimulation parameters, which can be automatically obtained from calculated gastric rhythm parameters or set by the user, such as... Figure 6 As shown. When a user wants to end the use, they can do so by pressing the end button. After each use, the client 200 will upload and store the gastric rhythm parameters and vagus nerve stimulation parameters recorded during the use process to the cloud 300, and generate a gastric function improvement report on the cloud 300 for the user to retrieve and view. This report includes changes in gastric rhythm and vagus nerve stimulation intensity throughout the use process. Furthermore, the client will retrieve the previous usage record for the next use and set the optimal stimulation parameters from the previous use as the initial stimulation parameters for this use, enabling more precise and individualized control for each user to regulate their gastric function and appetite.

[0035] The system's cloud storage is used to store each user's usage record, including gastric rhythm and vagus nerve stimulation parameters during use. When the client reads historical data, it automatically retrieves the parameter information from the user's most recent usage and provides a detailed report on the user's usage process.

[0036] When using this gastric function regulation system, users need to wear vagus nerve stimulation electrodes (located on the ear or neck, or other points innervated by the vagus nerve) and gastric electrical signal acquisition electrodes (wearable gastric electrical signal acquisition straps or electrode harnesses). Before wearing, clean the areas of the body that will contact the acquisition or stimulation electrodes with alcohol swabs and exfoliating scrub to reduce the impedance at each point, thereby achieving better stimulation and obtaining high-quality gastric electrical signals. After wearing the electrodes, open the gastric function regulation device 100 through the client APP. The system will automatically detect the impedance of the stimulation electrodes and issue a prompt sound if the impedance is too high, reminding the user to wear them again until the impedance meets the requirements, at which point the subsequent operations can be performed.

[0037] Further, please see Figure 7 , Figure 7 This is a flowchart illustrating the usage of a gastric function regulation system based on gastric rhythm information feedback, provided in an embodiment of the present invention. After the system begins execution, the client controls the gastric function regulation device 100 to first collect the user's gastric electrical signal during a time interval T (T being 5-10 minutes), and uploads this signal to the client in real time for display and analysis. For the gastric electrical signal during time interval T, the system analyzes its dominant frequency, amplitude, and the proportion of normal slow waves, displaying and storing the results to provide the user with their initial gastric rhythm parameters. If the user is using the system for the first time, the initial stimulation current intensity IT... k For IT ini (IT ini The initial stimulation current intensity is typically 0.5-1.5 mA (for vagus nerve stimulation). If the user has prior usage history, the initial stimulation current intensity should be IT. k The best stimulation current intensity IT will be used from the last usage record stored in the cloud. k+1 .

[0038] After synchronous acquisition of vagal nerve stimulation and gastric electrical signals during the T time interval, the gastric rhythm parameters during this T time interval are analyzed in real time to obtain the gastric electrical dominant frequency Df (cpm), gastric electrical amplitude Amp (uv), and the proportion of normal gastric slow waves Nsw (%).

[0039] Furthermore, the data processing module 203 includes a power spectrum analysis unit, a filtering unit, a gastric electrical signal analysis unit, an artifact recognition unit, and a gastric rhythm feature extraction unit.

[0040] The power spectrum analysis unit is used to process the gastric electrical signals of the current time period, obtain the power spectrum of the gastric electrical signals of the current time period, and select the gastric electrical signals with the largest power spectrum among the gastric electrical signals collected by multiple gastric electrical signal acquisition electrodes.

[0041] Specifically, the power spectrum analysis unit of this embodiment of the invention uses a multi-window spectrum estimation method to obtain the power spectrum of the gastric electroencephalogram (GEG) signal. The basic idea of ​​the multi-window spectrum estimation method is to obtain a cluster of data window functions by minimizing the frequency leakage outside half the bandwidth, based on the Rayleigh-Ritz minimization problem. This cluster of window functions replaces the single window function. This cluster of window functions is mutually orthogonal, and each window function samples the signal differently. Information lost by one window function can be recovered by another window function, thereby maintaining the offset at an acceptable level. Using a cluster of orthogonal window functions to process random signals can reduce spectral leakage caused by the limited data length.

[0042] Since it is impossible to directly measure and calculate an infinitely long signal, this embodiment analyzes finite time segments of the gastric electrical signal. Specifically, time segments of 50-100 seconds are extracted from the gastric electrical signal over a time interval T, with an 80%-90% overlap between each segment. Each segment is then periodically extended to obtain a virtual infinitely long signal, which is finally subjected to a Fourier transform. Truncation of the gastric electrical signal distorts the spectrum, shifting the original frequency (the fundamental frequency) from the signal's center frequency. The energy at that point is dispersed across two relatively wide frequency bands. To reduce this spectral energy leakage, this patent employs different truncation functions, or window functions, to truncate the signal.

[0043] The specific calculation steps are as follows: (1) Determine the length N and sampling rate of the gastric electrocardiogram signal collected during time interval T. To determine the frequency resolution that satisfies the Nyquist law .

[0044] (2) Generate data window A Slepian sequence is a data window used in multi-window spectral estimation methods. It is a set of orthogonal functions, also known as a discrete spherical sequence. To indicate the first 100 sequence samples, of which 100 samples are available. This represents the length of the sequence sample of the k-th Slepian sequence. This represents the time-half-bandwidth product. n Indicates the first k The first Slepian sequence n A sample, abbreviated as This sequence satisfies the following two conditions: i. Each window function has a unit energy, that is:

[0045] Where K represents the number of Slepian sequences.

[0046] ii. These window functions are mutually orthogonal, that is:

[0047] To satisfy the above two conditions, the Slepian sequence can be generated using the following formula:

[0048] in, n This indicates the start time of each data window within the raw gastric electrical signal. k The number of data windows is determined by the bandwidth parameter p of the data windows.

[0049]

[0050]

[0051] (3) Calculation of characteristic coefficients The acquired raw gastric electrical signals are multiplied by the generated data window sequence to obtain k windowed data sequences. And perform the following discrete Fourier transform to obtain the characteristic coefficients:

[0052] The above formula is the formula for the Discrete Fourier Transform. Representing the product of the time index and the frequency index, it is a modulation factor used for analyzing time-series signals in the frequency domain. , frequency components, t Indicates time.

[0053] (4) Adaptive weighting For characteristic coefficients Perform adaptive average weighting, using the ratio of the feature coefficients of each feature coefficient to... As weighting coefficients, the power spectrum of gastric electrical activity can be obtained. .

[0054] , in, .

[0055] Under normal circumstances, high-quality electrogastrography (EGG) recordings exhibit unique spectral characteristics. Therefore, this embodiment calculates the power spectrum of each EGG lead, such as... Figure 8 As shown, the power spectrum of the gastric electrical signal was obtained by selecting the lead with the highest power at the peak frequency for subsequent analysis.

[0056] Furthermore, the filtering unit is used to filter the gastric electrical signal with the largest power spectrum to obtain the filtered gastric electrical signal. Specifically, a third-order FIR filter and a zero-phase filter are used for bidirectional filtering to perform bandpass filtering of 0.033-0.067Hz on the gastric electrical signal with the largest power spectrum, with a transition band of 0.15.

[0057] Subsequently, the gastric electrical signal analysis unit is used to analyze the filtered gastric electrical signal to obtain the analyzed phase information and instantaneous amplitude.

[0058] Specifically, in order to better analyze the phase change of the gastric electrical signal, this embodiment uses Hilbert transform to transform the one-dimensional gastric electrical signal into an analytic signal on a two-dimensional complex plane. The complex modulus and argument of the signal represent the amplitude and phase of the signal, respectively. That is, the envelope (instantaneous amplitude) and analytic phase of the analytic signal can be calculated.

[0059] First, the filtered gastric electrical signal is transformed to the frequency domain using a Discrete Fourier Transform (DFT). Then, it is multiplied by the Hilbert filter coefficients in the frequency domain, and finally transformed back to the time domain using an Inverse Fourier Transform (IFT) to obtain the analytical representation of the gastric electrical signal. In the following formulas... and All of these represent the gastric electrical signals with the highest power spectrum mentioned above.

[0060] The Hilbert transform of the gastric electrical signal is calculated using the following formula:

[0061] in, Indicates time.

[0062] The analytical process of the Hilbert transform is as follows:

[0063] in, express The imaginary part of the Hilbert transform, This represents the obtained analytical signal.

[0064] The formula for calculating instantaneous amplitude is as follows:

[0065] The formula for calculating the analytical phase is as follows:

[0066] The artifact detection unit is used to screen out large amplitude vibrations caused by body movement and non-monotonic phase changes introduced by linear interference, and obtain the gastric electrical signal after screening.

[0067] (1) Large amplitude caused by body movement Under normal circumstances, the amplitude of slow waves in gastric electrical activity is around 50-250uV. When the subject moves or accidentally touches the electrode wire, causing disturbance, the amplitude of the gastric electrical signal will change significantly. Typically, single-cycle waves with amplitudes greater than 500uV are identified and removed. The specific steps are as follows: First, the instantaneous amplitude of the gastric electrical signal is obtained according to the Hilbert transform. The location where the amplitude is greater than the threshold of 500uV is identified and denoted as T. For each location... T represents the entire time period of the current gastric electrical signal. The peak detection algorithm identifies the position of each peak and finds its corresponding slow wave cycle, which is the interval between the previous peak and the next peak, denoted as T. Mark and extract all gastric electrical signals The corresponding part.

[0068] (2) Nonlinear interference introduces non-monotonic phase changes Because the physiological processes such as contraction and relaxation of gastrointestinal smooth muscle are relatively stable, the amplitude and frequency of gastric electrical signals also remain relatively stable, and therefore can be approximated as linear. The Hilbert transform is essentially a linear operator, and the analytic phase is calculated based on the amplitude and phase of the new function. Since linear operators satisfy the superposition principle, the analytic phase of the Hilbert transform can also be obtained by calculating the analytic phase of each frequency component separately and then summing them to obtain the analytic phase of the entire function, thus satisfying the linear property. When the analytic phase of a signal undergoes a nonlinear change, it indicates the presence of a nonlinear component in the signal. This nonlinear component may originate from various factors, such as the nonlinear dynamic mechanism of the signal source, the influence of noise or interference, etc. The specific implementation steps are as follows: First, the distribution of cycle lengths is calculated based on the analytical phase to determine the threshold. Edges in the gastric electrical signal where the phase derivative change is greater than -1 are identified, and the time difference between each edge, i.e., the cycle length, is calculated. Then, the mean and standard deviation of the cycle lengths are calculated, and the threshold is set to the mean minus or plus three times the standard deviation. Next, artifacts are detected based on the phase time series. Cycles that are too short or too long, as well as non-monotonic increasing cycles in the signal, are identified and marked with red areas in the graph, and the time point information corresponding to the artifacts is extracted. Artifact labels are constructed based on the identified artifact information, and the parameters at artifact locations are not calculated in subsequent calculations of gastric rhythm parameters.

[0069] Furthermore, the gastric rhythm feature extraction unit is used to obtain the gastric rhythm parameters for the current time period based on the filtered gastric electrical signals. Specifically, it needs to obtain the gastric electrical dominant frequency, gastric electrical amplitude, and the proportion of normal slow gastric waves for the current time period.

[0070] (1) Gastric electrical frequency and power Within the defined normal gastric electrical frequency range (0.033~0.067Hz), locate the local maximum value (peak value) in the power spectrum of each gastric electrical channel, and record the frequency and power corresponding to the peak value. This frequency is the dominant frequency of gastric electrical activity, and the power is the dominant power at the dominant frequency. The calculated results are as follows: Figure 9 As shown, the power spectrum information of the five gastric electrical signals can be seen. The part between the two vertical lines is the normal gastric electrical frequency range. Among them, EGG4 has the largest power spectrum, and its main frequency is 3.12 cpm.

[0071] (2) Amplitude First, the filtered and artifact-detected gastric electroencephalogram (GEG) signals are differentially analyzed to obtain the rate of change, and a sign function is used to determine the sign of the rate of change. Then, a second-order difference is performed on the sign to obtain the sign variation. Positions where the sign changes to -2 are identified, corresponding to the maximum values ​​of the GEG signals, and positions where the sign changes to 2 are identified, corresponding to the minimum values. Next, it is determined whether the maximum and minimum value matrices of two GEG signals in each channel have the same length. If they do, the difference between the maximum and minimum value matrices is calculated, which represents the amplitude of the GEG signal. If they do not have the same length, it is determined which matrix has one more point, and the extra data point is then subjected to forward or backward difference analysis.

[0072] (3) Proportion of normal slow waves To estimate the period from the analytic phase obtained by the Hilbert transform, the analytic phase is first differentially divided. The differentially divided data is stored in a logic array, where each element is true or false, indicating whether the signal has a falling edge. The falling edge is the point where the signal changes from a high value to a low value, representing the start of each period.

[0073] Next, based on the position of the falling edge, find the corresponding timestamp. The timestamp is the time point when the signal was sampled. Return the index of the element that is true in the logic array, which is the position of the falling edge; use these indices to access the timestamp array to get the time point corresponding to the falling edge.

[0074] Subsequently, the time points corresponding to the falling edge are differentially analyzed, i.e., the interval between two adjacent time points is calculated. This yields the duration of each cycle, i.e., the cycle length, and allows us to determine which cycle lengths fall within the normal range. First, the indices of elements in the cycle length array that are less than the lower limit or greater than the upper limit are returned, indicating the positions of abnormal cycles. This allows us to calculate the number of abnormal cycles. Then, the total number of cycles is subtracted from the number of abnormal cycles to obtain the number of normal cycles. Finally, the number of normal cycles is divided by the total number of cycles to obtain the percentage of normal cycles. Figure 9The chart shows the calculated percentage of normal slow wave cycles. The dashed line represents the range of normal slow wave duration. As can be seen from the chart, the percentage of normal slow waves in this gastric electrical signal is 14.6%.

[0075] Furthermore, this embodiment also includes a judgment module, which is used to determine whether the vagus nerve stimulation intensity of the next time period is less than the preset maximum stimulation current intensity. If so, the vagus nerve stimulation intensity of the next time period is sent to the internal processor; if not, the vagus nerve stimulation intensity of the previous time period is sent to the internal processor.

[0076] The analysis module is specifically used for: The gastric electrical frequency is compared with its corresponding normal range. When the gastric electrical frequency is within its normal range, the result is obtained. When the dominant frequency of gastric electrical activity is less than the minimum value of its normal range, It is equal to the difference between the minimum value of its normal range and the main frequency of gastric electrical activity; when the main frequency of gastric electrical activity is greater than the maximum value of its normal range, It is equal to the difference between the main frequency of gastric electrical activity and its maximum value within the normal range; The gastric electrical amplitude is compared with its corresponding normal range. When the gastric electrical amplitude is within its normal range, the result is obtained. When the gastric electrical amplitude is less than the minimum value of its normal range, It is equal to the difference between the minimum value of its normal range and the gastric electrical amplitude; when the gastric electrical amplitude is greater than the maximum value of its normal range, It is equal to the difference between the gastric electrical amplitude and its maximum value within the normal range; The normal proportion of slow gastric waves is compared with its corresponding normal range. When the normal proportion of slow gastric waves is within its normal range, the result is obtained. When the proportion of normal slow waves in the stomach is less than the minimum value of its normal range, It is equal to the difference between the minimum value of its normal range and the proportion of normal slow gastric waves; when the proportion of normal slow gastric waves is greater than the maximum value of its normal range, It is equal to the difference between the proportion of normal slow waves in the stomach and the maximum value of its normal range; Calculate the current intensity of vagal nerve stimulation in the next time period:

[0077] Where m = 1, 2, 3, This represents the current intensity of the vagus nerve stimulation used in the previous time period. for The weight, This is the gain coefficient. This represents the difference between the dominant frequency of gastric electrical activity and its normal range. This represents the difference between the gastric electrical amplitude and its normal range. This represents the difference between the proportion of normal slow waves in the stomach and its normal range.

[0078] The analysis module is also used to: send a command to the switch module when the gastric electrical frequency, the gastric electrical amplitude, and the proportion of normal slow gastric waves are all within their normal range, so that the switch module turns off the gastric function regulation device.

[0079] When all three gastric rhythm indicators are within the normal range, it indicates that the user's gastric function has returned to normal, the device automatically terminates, and saves the parameters of this usage process to the cloud. If any of the three gastric rhythm indicators is outside the normal range, the algorithm will adjust the settings in real time based on the data for that time period. Based on the situation, calculate the vagus nerve stimulation intensity for the next time period. The calculation formula is:

[0080] Where m = 1, 2, 3, The intensity of the vagus nerve stimulation current used in the previous time period T. for The weights can be determined based on gastric rhythm parameters. The gain coefficient is used to make... and Keep it within a certain range.

[0081] This formula will take effect if any one of the following parameters—the dominant frequency of gastric electrical activity, the amplitude of gastric electrical activity, or the proportion of normal slow gastric waves—is outside the normal range. It is used to calculate the current intensity of vagal nerve stimulation in the next time interval T. ,if Less than the maximum stimulation current intensity that the human body can withstand Then it will be used The current intensity begins the next time interval T of vagal nerve stimulation and synchronized EGG data acquisition. If Greater than Then, the current intensity of the previous time period T is used to start the vagal nerve stimulation and synchronous EGG data acquisition for the next time period T.

[0082] Repeat the above steps until all gastric rhythm parameters reach the normal range, indicating that the user's gastric function has been regulated to normal. The device will then automatically terminate, and the client will display the user's gastric rhythm parameters and improvement status after the adjustment. Users can also end the gastric function regulation process at any time via the "End" button on the client app. The system has a maximum number of cycles and will automatically terminate if too many cycles are exceeded. In addition, the client app will upload the user parameters from this usage process to the cloud so that users can view historical usage reports for future use. The device uses the historically best vagus nerve stimulation intensity as the initial stimulation intensity to achieve a more precise and personalized gastric function regulation process.

[0083] This invention relates to a gastric function regulation system based on gastric rhythm information feedback. It activates the user's vagus nerve complex non-invasively via the vagus nerve, using stimulated gastric rhythm parameters to provide feedback regulation of vagus nerve stimulation parameters. This maximizes the activation of the vagus nerve complex, regulating the gastric function system to a normal level. The system is simple to operate, allowing for user self-management, and features a visualized usage process and gastric function improvement reports. This gastric function regulation system is the first to combine vagus nerve stimulation technology with gastric rhythm parameters. By analyzing changes in gastric rhythm during stimulation, it provides feedback guidance for vagus nerve stimulation parameters, achieving a more precise and individualized gastric function regulation process. This maximizes the regulation of the user's gastric function system and promotes appetite. The client APP of this invention enables control of the gastric function regulation device and visualizes gastric electrical signals, gastric rhythm parameters, and vagus nerve stimulation. The cloud provides storage for user historical data and usage reports. The wearable gastric electrical signal acquisition section of the device features a wearable gastric electrical signal acquisition belt, enabling a more portable and accurate acquisition process.

[0084] In the several embodiments provided by this invention, it should be understood that the apparatus and methods disclosed in this invention can be implemented in other ways. For example, the apparatus embodiments described above are merely illustrative. For example, the division of modules is merely a logical functional division, and in actual implementation, there may be other division methods. For example, multiple modules or components may be combined or integrated into another system, or some features may be ignored or not executed.

[0085] Furthermore, the functional modules in the various embodiments of the present invention can be integrated into one processing module, or each module can exist physically separately, or two or more modules can be integrated into one module. The integrated module can be implemented in hardware or in the form of hardware plus software functional modules.

[0086] The above description, in conjunction with specific preferred embodiments, provides a further detailed explanation of the present invention. It should not be construed that the specific implementation of the present invention is limited to these descriptions. For those skilled in the art, various simple deductions or substitutions can be made without departing from the concept of the present invention, and all such modifications and substitutions should be considered within the scope of protection of the present invention.

Claims

1. A gastric function regulation system based on gastric rhythm information feedback, characterized in that, This includes gastric function regulation devices, client applications, and the cloud platform, among which... The client is used to control the start and end of the gastric function regulation device, and is also used to acquire the gastric electrical signals collected by the gastric function regulation device for processing and analysis to obtain the gastric rhythm parameters of the current time period, and then obtain the vagus nerve stimulation parameters of the next time period through the gastric rhythm parameters of the current time period. The gastric function regulation device is externally connected to a vagus nerve stimulation electrode in the ear, which is used to apply vagus nerve stimulation that can regulate gastric function according to the vagus nerve stimulation parameters, and is also used to connect a gastric electrical signal acquisition electrode to the abdomen to acquire gastric electrical signals. The cloud is used to store historical usage records, which include changes in stimulation parameters and gastric rhythm parameters during the usage process. The client includes a switch module, a communication module, a data processing module, an analysis module, and a display module, wherein... The switch module is used to turn the gastric function regulating device on and off; The communication module is used to acquire gastric electrical signals collected by the gastric function regulation device; The data processing module is used to process the gastric electrical signal of the current time period to obtain the gastric rhythm parameters of the current time period. The gastric rhythm parameters include the gastric electrical dominant frequency, gastric electrical amplitude and the proportion of normal slow gastric waves. The analysis module is used to analyze and compare the gastric electrical dominant frequency, gastric electrical amplitude, and proportion of normal slow gastric waves with their corresponding normal ranges in the current time period, so as to obtain the vagus nerve stimulation intensity in the next time period. The display module is used to display the gastric electrical signal waveform, gastric rhythm parameters, and vagus nerve stimulation parameters in real time. The communication module is also used to feed back the vagus nerve stimulation intensity for the next time period to the gastric function regulation device; After the gastric function regulation system starts execution, the client controls the gastric function regulation device to first collect the user's gastric electrical signal during time period T, and upload the gastric electrical signal to the client in real time for display and analysis; for the gastric electrical signal during time period T, the system analyzes its gastric electrical frequency, gastric electrical amplitude, and the proportion of normal slow waves in the stomach, and displays and stores the results, allowing the user to obtain their initial gastric rhythm parameters; if the user is using the gastric function regulation system for the first time, the initial stimulation current intensity IT k For IT ini IT ini The initial stimulation current intensity is for typical vagus nerve stimulation. If the user has a prior usage history, the initial stimulation current intensity is IT. k The best stimulation current intensity IT will be used from the last usage record stored in the cloud. k+1 .

2. The gastric function regulation system based on gastric rhythm information feedback according to claim 1, characterized in that, The gastric function regulation device includes an internal controller, a stimulation current signal generator, a physiological signal acquisition amplifier, and a power supply module. The internal controller is used to control the physiological signal acquisition amplifier to acquire the gastric electrical signal of the current period and transmit it to the client. It is also used to receive the vagus nerve stimulation parameters of the next period fed back by the client and send them to the stimulation current signal generator. The stimulation current signal generator is externally connected to a vagus nerve stimulation electrode, and is used to generate a vagus nerve stimulation signal according to the vagus nerve stimulation parameters and transmit it to the vagus nerve stimulation electrode. The physiological signal acquisition amplifier is connected to an external gastric electrical signal acquisition electrode, which is used to acquire gastric electrical signals during the regulation process and upload them to the client. The power module is used to provide isolated power to the internal controller, the stimulation current signal generator, and the physiological signal acquisition amplifier.

3. The gastric function regulation system based on gastric rhythm information feedback according to claim 1, characterized in that, The gastric function regulation device is electrically connected to the gastric electrical signal acquisition electrode, which includes five acquisition electrodes, one reference electrode, and one ground electrode. The first sampling point is located at the xiphoid process; the second sampling point is located at the midpoint between the xiphoid process and the navel; the fourth sampling point is located at the intersection of the horizontal line of the first sampling point and the vertical line of the midclavicular line; the fifth sampling point is located at the intersection of the horizontal line of the second sampling point and the vertical line of the midclavicular line; and the third sampling point is located at the intersection of the diagonals of the rectangle formed by the other four sampling points. The grounding electrode is located on the left abdomen, above the iliac crest; The reference electrode is symmetrically arranged with respect to the third acquisition site.

4. The gastric function regulation system based on gastric rhythm information feedback according to claim 3, characterized in that, The data processing module includes a power spectrum analysis unit, a filtering unit, a gastric electrical signal analysis unit, an artifact detection unit, and a gastric rhythm feature extraction unit. The power spectrum analysis unit is used to process the gastric electrical signal of the current time period, obtain the power spectrum of the gastric electrical signal of the current time period, and select the gastric electrical signal with the largest power spectrum among the gastric electrical signals collected by multiple gastric electrical signal acquisition electrodes. The filtering unit is used to filter the gastric electrical signal with the largest power spectrum to obtain the filtered gastric electrical signal. The gastric electrical signal analysis unit is used to analyze the filtered gastric electrical signal to obtain the analyzed phase information and instantaneous amplitude; The artifact recognition unit is used to screen out large amplitude vibrations caused by body movement and non-monotonic phase changes introduced by linear interference, and to obtain the screened gastric electrical signal. The gastric rhythm feature extraction unit is used to obtain the gastric rhythm parameters for the current time period based on the filtered gastric electrical signals.

5. The gastric function regulation system based on gastric rhythm information feedback according to claim 4, characterized in that, The power spectrum analysis unit is specifically used for: Determine the length of the gastric electrical signal acquired during the T time interval. N and sampling rate To determine the frequency resolution that satisfies the Nyquist law ; Generate a data window sequence based on the Slepian sequence: in, n This indicates the start time of each data window within the raw gastric electrical signal. k The number of data windows is determined by the bandwidth parameter p of the data windows: ； The acquired raw gastric electrocardiogram (ECG) signal is multiplied by the generated data window sequence to obtain... k A windowed data sequence and the windowed data sequence Perform a discrete Fourier transform to obtain the characteristic coefficients. : in, This represents the product of the time index and the frequency index, where t represents time. For the characteristic coefficients Perform adaptive average weighting, using the ratio of the feature coefficients of each feature coefficient to... As weighting coefficients, the power spectrum of gastric electrical activity is obtained. : ， in, .

6. The gastric function regulation system based on gastric rhythm information feedback according to claim 4, characterized in that, The client also includes a judgment module, which is used to determine whether the vagus nerve stimulation intensity of the next time period is less than the preset maximum stimulation current intensity. If so, the vagus nerve stimulation intensity of the next time period is sent to the internal processor; otherwise, the vagus nerve stimulation intensity of the previous time period is sent to the internal processor.

7. The gastric function regulation system based on gastric rhythm information feedback according to claim 4, characterized in that, The analysis module is specifically used for: The gastric electrical frequency is compared with its corresponding normal range. When the gastric electrical frequency is within its normal range, the result is obtained. When the dominant frequency of gastric electrical activity is less than the minimum value of its normal range, It is equal to the difference between the minimum value of the normal range of gastric electrical frequency and the gastric electrical frequency; when the gastric electrical frequency is greater than the maximum value of its normal range, It is equal to the difference between the main frequency of gastric electrical activity and its maximum value within the normal range; The gastric electrical amplitude is compared with its corresponding normal range. When the gastric electrical amplitude is within its normal range, the result is obtained. When the gastric electrical amplitude is less than the minimum value of its normal range, It is equal to the difference between the minimum value of the normal range of gastric electrical amplitude and the gastric electrical amplitude; when the gastric electrical amplitude is greater than the maximum value of its normal range, It is equal to the difference between the gastric electrical amplitude and its maximum value within the normal range; The normal proportion of slow gastric waves is compared with its corresponding normal range. When the normal proportion of slow gastric waves is within its normal range, the result is obtained. ; When the proportion of normal slow waves in the stomach is less than the minimum value of its normal range, It is equal to the difference between the minimum value of the normal range of the proportion of slow gastric waves and the stated proportion of slow gastric waves. When the proportion of normal slow waves in the stomach is greater than its maximum value within the normal range, It is equal to the difference between the proportion of normal slow waves in the stomach and the maximum value of its normal range; Calculate the current intensity of vagal nerve stimulation in the next time period: Where m = 1, 2, 3, This represents the current intensity of the vagus nerve stimulation used in the previous time period. for The weight, This is the gain coefficient.

8. The gastric function regulation system based on gastric rhythm information feedback according to claim 7, characterized in that, The analysis module is also used for: When the gastric electrical frequency, the gastric electrical amplitude, and the proportion of normal slow gastric waves are all within their normal ranges, a command is sent to the switch module to turn off the gastric function regulation device.

Images