Wearable multichannel gastric electricity acquisition system

Abstract

The invention relates to the technical field of gastric electricity detection instruments, in particular to a wearable multi-channel gastric electricity acquisition system which adopts a modular design of a gastric electricity acquisition electrode bandage, a detection host and an information terminal. The detection host can be assembled on a stomach electricity collection electrode bandage and worn on a subject for use, multi-channel stomach electricity signal collection is executed through the stomach electricity collection electrode bandage, and the detection host integrates skin contact impedance detection and analog-to-digital conversion functions. Under the condition of ensuring that the skin contact impedance is in a normal state, each path of converted stomach electricity digital signal is sent to an information terminal; and the information terminal interacts with the detection host to send an operation control instruction, and performs processing according to each path of fed-back stomach electricity digital signal to obtain a stomach electricity state detection result of the subject. According to the invention, a subject can wear the device to detect the gastric function state, the use threshold is effectively reduced, and the device is suitable for families, communities and mobile medical scenes and is more beneficial to early screening and long-term management of gastric diseases.

Description

Technical Field

[0001] This invention relates to the field of gastric electrical activity detection devices, and in particular to a wearable multi-channel gastric electrical activity acquisition system. Background Technology

[0002] Gastrointestinal diseases are prevalent in modern society. Currently, the main diagnostic methods for stomach diseases include gastroscopy, imaging examinations, and gastric juice analysis. However, these methods can cause discomfort to patients to varying degrees and can also cause some damage to the body. Electrogastrogram (EGG) is a non-invasive detection technique that uses skin electrodes placed on the abdomen to capture and record the electrical activity of the stomach, thereby providing important information about the functional state of the stomach.

[0003] Gastric electromyography (EGG) activity includes spike potentials and slow waves. Due to the filtering effect of the human abdomen, EGG signals recorded by skin electrodes on the abdomen typically contain only slow waves and interference signals, and do not include spike potentials. Slow waves are generated by Caljal interstitial cells located between the circular and longitudinal muscles of the stomach, originating from the pacing area at the greater third of the stomach curvature. They propagate downwards along the perigastric circumference and towards the pylorus at a certain speed, coordinating the contractions of gastric smooth muscle cells both spatially and temporally. This coordinated contraction and relaxation forms the peristaltic movement of the gastrointestinal tract; therefore, the frequency and propagation speed of slow waves can determine the rhythmicity and speed of gastric peristalsis. Gastric peristalsis not only promotes the mixing of food with digestive juices but also contributes to the physical grinding, chemical digestion, and emptying of food, and is closely related to the physiological function of the stomach. Measuring gastric slow waves can provide information about gastric motility and rhythm.

[0004] EGG signals are characterized by low frequency, low amplitude, and low signal-to-noise ratio, making them susceptible to interference from ECG, respiration, motion artifacts, skin contact impedance, and 50Hz power frequency. They are nonlinear and non-stationary signals. According to the EGG frequency range classification standards in the "Standards for Electrogastrography Examination and its Evaluation (Trial Implementation)," the frequency of a normal person's EGG signal is approximately 3 cycles per minute (cpm), with a variation range of 2–4 cpm.

[0005] EGG (extragastric electrocardiography) is a non-invasive and low-cost method with advantages such as high repeatability, no contraindications, and good patient compliance. It can monitor the electrical activity of the stomach for a long time, thereby indirectly reflecting the stomach's motility, and has broad application prospects. However, existing gastric electrocardiography systems often have the following drawbacks:

[0006] First, the positioning of surface gastric electrophysiological (GE) electrodes is complex. For the same subject, a significant amount of time is required for electrode positioning and adjustment before each test. This cumbersome and inefficient process not only increases the workload of medical staff but may also lead to excessively long waiting times for patients. Furthermore, since surface gastric GE electrodes are usually patch-type, they are not stable when attached to the subject's skin. Therefore, the subject needs to lie down on the bed while the electrodes are attached to the gastric GE data collection area in the subject's stomach and abdomen for testing. This prevents the subject from moving during the test, further increasing inconvenience. All these factors reduce the convenience and accessibility of GE testing.

[0007] Second, the lack of contact impedance detection function means that the existing system cannot detect the contact impedance between the electrode and the skin. Operators find it difficult to accurately judge the connection quality between the electrode and the skin. This not only affects the accuracy of signal acquisition, but may also lead to a longer test time, or even require repeated testing due to poor signal quality, increasing patient discomfort and testing costs.

[0008] Third, the equipment is large in size and inconvenient to carry, making it difficult to meet the needs of daily dynamic monitoring. This fixed usage mode limits the application of EGG examination in home, community or mobile medical scenarios, which is not conducive to the early detection and long-term management of gastric diseases. Summary of the Invention

[0009] To address the shortcomings of existing technologies, this invention provides a wearable multi-channel gastric electrophysiological acquisition system. By adopting a modular wearable design of the detection host and information terminal, subjects can wear the system to detect gastric function status, reducing detection time and cost and improving detection convenience.

[0010] To solve the above-mentioned technical problems, the present invention adopts the following technical solution:

[0011] A wearable multi-channel gastric electrical signal acquisition system includes a gastric electrical signal acquisition electrode bandage, a detection host, and an information terminal;

[0012] The gastric electrical signal acquisition electrode bandage is worn on the subject. The gastric electrical signal acquisition electrode bandage has 8 channels of gastric electrical signal acquisition electrodes installed on it corresponding to the subject's gastric electrical signal acquisition area, which is used to acquire gastric electrical signals from the subject through multiple channels.

[0013] The detection host can be installed on the gastric electrical signal acquisition electrode bandage. The detection host includes a skin contact impedance detection circuit module, a signal acquisition circuit module, a main controller module, and a Bluetooth module. The skin contact impedance detection circuit module is used to detect the skin contact impedance signal in real time and transmit it to the main controller module. The signal acquisition circuit module includes 8 signal conditioning circuits and 2 right leg drive circuits. The 8 signal conditioning circuits are used to connect to the 8 channels of gastric electrical signal acquisition electrodes in the gastric electrical signal acquisition electrode bandage, and to filter, amplify, and condition the gastric electrical signal acquired by each channel of gastric electrical signal acquisition electrode. The 8 signal conditioning circuits are divided into two groups, and the 4 signal conditioning circuits in each group share one right leg drive circuit to reduce common-mode interference before transmitting the signal to the main controller module. The main controller module is used to receive operation control commands from the information terminal through the Bluetooth module, coordinate the operation of the skin contact impedance detection circuit module, the signal acquisition circuit module, and the Bluetooth module, and, when the skin contact impedance is analyzed to be in a normal state, perform analog-to-digital conversion on each gastric electrical signal processed by the signal acquisition circuit module, and send the obtained gastric electrical digital signals to the outside through the Bluetooth module.

[0014] The information terminal is used to interface with the Bluetooth module of the detection host, send operation control commands to the detection host, receive various gastric electrical digital signals sent by the detection host and perform correlation analysis, identify and determine the dominant channel from the multi-channel gastric electrical digital signals, and obtain the gastric electrical state detection results of the subject based on the gastric electrical digital signal of the dominant channel.

[0015] As a preferred embodiment, the gastric electrocardiogram (GEG) acquisition electrode bandage includes a fabric elastic bandage for wearing on the subject's body. The fabric elastic bandage has an array of buckle holes for mounting the GEG detection electrodes, and a mounting component for mounting the detection host. The GEG detection electrodes have a contact detection end and a conductive connection end that are electrically conductive to each other, and also include a wire and a mounting nut for connecting the conductive connection end. The contact detection end is used to contact the subject's skin as a detection contact point. The conductive connection end has a connecting base plate and a mounting post extending outward from the base plate, and the mounting post has an external thread. During installation, after the mounting post portion of the conductive connection end of the GEG detection electrode passes through the buckle hole on the fabric elastic bandage, one end of the wire connects to the mounting post to form a conductive contact. Then, the mounting nut with an internal thread engages with the external thread of the mounting post, so that the fabric elastic bandage and one end of the wire are pressed and fixed between the mounting nut and the connecting base plate, thereby achieving fixed installation of the GEG detection electrode at the buckle hole position of the fabric elastic bandage.

[0016] As a preferred embodiment, the skin contact impedance detection circuit module in the detection host includes a first multiplexer, a second multiplexer, and a waveform conversion circuit.

[0017] The first and second multiplexers are respectively connected to the main controller module for communication, and the main controller module generates an amplitude of V. in The square wave pulse signal is time-division multiplexed to control the first multiplexer to output the square wave pulse signal in eight time-division multiplexing modes. These eight time-division outputs are each connected to one of the eight gastric electrical sensing electrodes in the gastric electrical sensing electrode bandage via reference resistors. Each reference resistor forms a voltage divider network with one channel of the gastric electrical sensing electrode, thus dividing the skin contact impedance Z sensed by the gastric electrical sensing electrode. s The change is converted into output voltage V out The fluctuations satisfy R ref The reference resistor value is used as the reference value; the node between each reference resistor and the gastric electrocardiogram (GEG) acquisition electrode of one channel is respectively connected to different input channels of the second multiplexer, which is controlled by the main controller module, and converts the output voltage V of each channel. out Output to waveform conversion circuit;

[0018] The waveform conversion circuit is used to convert the output voltage V out The signal is shaped into a digital rectangular wave and sent to the main controller module. The pulse width T of the digital rectangular wave signal is... pw Skin contact resistance Z s The following mapping relationship exists:

[0019] T pw =k·Z s +C;

[0020] Where k and C are constants determined through calibration.

[0021] As a preferred embodiment, the main control module of the detection host receives the digital rectangular wave signal output by the waveform conversion circuit, and determines the pulse width T of the digital rectangular wave signal accordingly. pw The skin contact impedance Z of each channel is calculated using the following formula. s :

[0022]

[0023] The main controller module is also used to send an abnormal skin contact impedance warning message for the corresponding channel to the information terminal via Bluetooth when it is determined that the skin contact impedance of any channel exceeds a preset threshold.

[0024] As a preferred embodiment, in the signal acquisition circuit module of the detection host, each signal conditioning circuit includes a passive low-pass filter circuit, a preamplifier circuit, an active band-pass filter circuit, and a post-amplifier circuit cascaded in sequence; the passive low-pass filter circuit is used to initially filter out low-frequency signals below 0.01Hz;

[0025] The preamplifier circuit is used to amplify the signal after preliminary filtering for the first time.

[0026] The active bandpass filter circuit is used to filter out interference signals higher than 0.2Hz from the signal after the first amplification.

[0027] The subsequent amplifier circuit is used to amplify the filtered signal a second time.

[0028] As a preferred embodiment, the processing flow of the information terminal for multi-channel gastric electrical digital signals includes:

[0029] S1. Signal noise reduction and reconstruction processing:

[0030] Empirical mode decomposition (EMD) was performed on the digital gastric electrical signals of each channel, and then the IMF components obtained from the decomposition were used to reconstruct the digital gastric electrical signals of the corresponding channels to obtain the reconstructed gastric electrical signals of each channel.

[0031] S2, Feature Extraction:

[0032] For the gastric electrical reconstructed signal of each channel, the power percentage feature of its different gastric motility state types is extracted, and the gastric motility state type corresponding to the maximum value of the power percentage feature is taken as the gastric motility state type of the corresponding channel's gastric electrical reconstructed signal; the gastric motility state type includes normal gastric motility, slow gastric motility, and tachygastric motility;

[0033] S3, Multi-channel correlation analysis:

[0034] Correlation analysis was performed on the digital gastric electrical signals of each channel, and the maximum correlation coefficient and propagation delay between different channels were extracted. The information flow between different channels was quantified by the transfer entropy, thereby identifying the dominant channel. The gastric motility state type to which the gastric electrical reconstructed signal of the dominant channel belongs was used as the gastric motility state detection result of the subject.

[0035] As a preferred embodiment, in S1, the specific processing steps for the digital gastric electrical signal of each channel include:

[0036] S101. After acquiring the digital gastric electrical signal of the channel, first use a digital bandpass filter to digitally filter the digital gastric electrical signal, then perform empirical mode decomposition on the digitally filtered digital gastric electrical signal, and calculate the main frequency of each IMF component obtained by decomposition. Only retain the IMF components with the main frequency in the frequency range of 1 to 10 cpm as the effective IMF components.

[0037] S102. For the valid IMF components retained in the channel, try all possible combinations and superpositions of consecutive IMF components. Each combination and superposition constitutes a candidate signal, thereby forming multiple candidate signals.

[0038] S103. For each candidate signal in this channel, calculate its normalized autocorrelation function at lag k sampling points, where k ranges from 60 to 120:

[0039]

[0040] Where R(k) represents the normalized autocorrelation function; s(n) represents the candidate signal; s(n+k) represents the candidate signal after lagging by k sampling points; N s The number of sampling points contained in the candidate signal;

[0041] Then, the peak value is found in the normalized autocorrelation function of each candidate signal after lag by a different number of sampling points, and this peak value is taken as the peak value of the autocorrelation function of the candidate signal; thus, the peak value of the autocorrelation function of each candidate signal in the channel is obtained.

[0042] S104. Select the candidate signal with the largest peak value of the autocorrelation function in the channel as the gastric electrical remodeling signal of the channel.

[0043] As a preferred embodiment, in S2, the specific processing steps for the gastric electrical reconstruction signal of each channel include:

[0044] S201. The gastric electrical reconstructed signal of the channel is segmented, and the power spectrum of each segment is calculated to obtain the main frequency and main power of each segment. The sum of the main power of each segment is taken as the total power of the gastric electrical reconstructed signal.

[0045] S202. Determine the frequency range of different gastric motility state types according to the gastric electrical signal frequency range division standard. The gastric motility state types include normal gastric motility, slow gastric motility, and rapid gastric motility. Then, classify the gastric motility state types of the segmented signals according to the frequency range of the gastric motility state type where the main frequency of each segmented signal is located. Then, calculate the sum of the main power of each segmented signal classified into each gastric motility state type as the power value of the gastric electrical reconstructed signal in the corresponding gastric motility state type.

[0046] S203. Using the power value of a single gastric motility state type as the denominator and the total power of the gastric electrical reconstructed signal as the numerator, calculate the power percentage characteristics of the gastric electrical reconstructed signal in different gastric motility state types respectively, and take the gastric motility state type corresponding to the maximum value of the power percentage characteristics as the gastric motility state type to which the gastric electrical reconstructed signal of this channel belongs.

[0047] As a preferred embodiment, the operation control commands sent by the information terminal to the detection host include single-person mode detection commands and dual-person mode detection commands, which are used to instruct the detection host to perform single-person mode detection or dual-person mode detection, respectively. In single-person mode detection, all 8 channels of gastric electroencephalogram (GEG) digital signals, or 4 channels of GEG digital signals, are used as a group for correlation analysis. In dual-person mode detection, the 8 channels of GEG digital signals are divided into two groups, and correlation analysis is performed on the 4 channels of GEG digital signals in each group.

[0048] As a preferred approach, in S3, correlation analysis is performed on the digital gastric electrical signals of each channel within each group. The specific steps are as follows:

[0049] S301. Calculate the normalized cross-correlation function between the gastric electrical digital signals of different channels within the group, thereby finding the propagation delay corresponding to the maximum correlation coefficient and determining the signal transmission direction between the gastric electrical digital signals of different channels within the group.

[0050] Among them, any two channels Ch within the group x ,Ch y The normalized cross-correlation function R between gastric electrophysiological digital signals xy (τ) is:

[0051]

[0052] Where x(n) is the channel Ch x The signal amplitude at the nth sampling point in the digital gastric electroencephalogram (GEO) signal, y(n) is the signal amplitude of channel Ch. y The signal amplitude of the nth sampling point in the digital gastric electrocardiogram, where n = 1, 2, ..., N, and N is the number of sampling points in the digital gastric electrocardiogram; They are channel Ch x Channel Ch y The average amplitude of the digital gastric electroencephalogram; τ is the number of sampling points corresponding to the time delay, with a value range of [-τ]. max ,+τ max ], τ max The number of sampling points corresponding to the preset maximum time delay; y(n+τ) represents the number of channels Ch. y The signal amplitude at the (n+τ)th sampling point in the digital gastric electroencephalogram;

[0053] Then, find the normalized cross-correlation function R across all possible values ​​of τ. xy The maximum value of (τ) is taken as the maximum correlation coefficient R. max R max =max τ |R xy (τ)|;If R maxIf the correlation coefficient is less than or equal to a preset threshold, then the channel Ch is determined to be... x ,Ch y There is no correlation between them; if R max If the correlation coefficient is greater than a preset threshold, then the channel Ch is determined to be... x ,Ch y The channels between them are related, and the maximum correlation coefficient R is set. max The corresponding value of τ is determined as the propagation delay τ. d If τ d A value greater than 0 indicates that the signal transmission direction is from channel Ch. x Transmission Channel Ch y If τ d If ≤0, it indicates that the signal transmission direction is from channel Ch. y Transmission Channel Ch x ;

[0054] Therefore, the signal transmission direction between the digital gastric electrical signals of every two related channels within the group is determined;

[0055] S302. Calculate the transfer entropy between the gastric electrical digital signals of the relevant channels within the group, and determine the dominant direction of information flow between the gastric electrical digital signals of the relevant channels within the group.

[0056] Among them, any two related channels Ch within the group x ,Ch y Between the digital signals of gastric electrical activity, from channel Ch y To Channel Ch x Transitive entropy TE y→x And from channel Ch x To Channel Ch y Transitive entropy TE x→y They are respectively:

[0057]

[0058]

[0059] Where x(n) and x(n+1) are channels Ch x The signal amplitudes at the nth and (n+1)th sampling points in the digital gastric electroencephalogram (GEG) signal, y(n) and y(n+1) are respectively the values ​​of channel Cj. y The signal amplitudes at the nth and (n+1)th sampling points in the digital gastric electrocardiogram (DGE) signal; p(x(n+1)|x(n)) represents the signal amplitudes at channel Ch in the historical data of the digital gastric electrocardiogram (DGE) signal. x When the amplitude of the nth sampling point is x(n), channel Ch xThe probability that the amplitude of the (n+1)th sampling point is x(n+1); p(x(n+1)|x(n),y(n)) represents the probability of channel Ch in the historical data of gastric electrocardiogram digital signal. x The amplitude of the nth sampling point is x(n), and the channel Ch y When the amplitude of the nth sampling point is y(n), channel Ch x The probability that the amplitude of the (n+1)th sampling point is x(n+1); p(y(n+1)|y(n)) represents the probability of channel Ch in the historical data of gastric electrocardiogram digital signal. y When the amplitude of the nth sampling point is y(n), channel Ch y The probability that the amplitude of the (n+1)th sampling point is y(n+1); p(y(n+1)|x(n),y(n)) represents the probability of channel Ch in the historical data of gastric electrocardiogram digital signal. x The amplitude of the nth sampling point is x(n), and the channel Ch y When the amplitude of the nth sampling point is y(n), channel Ch y The probability that the amplitude of the (n+1)th sampling point is y(n+1);

[0060] Then, compare the transfer entropy in both directions; if TE x→y >TE y→x Then the dominant direction of information flow is determined to be from channel Ch. x To Channel Ch y If TE x→y <TE y→x Then the dominant direction of information flow is determined to be from channel Ch. y To Channel Ch x ;

[0061] Therefore, the dominant direction of information flow between the digital signals of gastric electrocardiogram (ECG) of every two related channels within the group is determined, and then an information flow network is constructed with the channels of the EEG digital signals as nodes and the transfer entropy value between channels as the weight of the directed edges.

[0062] S303. Calculate the weighted out-degree of each node in the information flow network, and take the channel corresponding to the node with the highest weighted out-degree as the dominant channel, so as to take the gastric motility state type of the gastric electrical reconstruction signal of the dominant channel as the gastric motility state detection result of the subject.

[0063] Compared with the prior art, the present invention has the following advantages:

[0064] 1. The wearable multi-channel gastric electroacupuncture acquisition system of the present invention adopts a modular design of gastric electroacupuncture acquisition electrode bandage, detection host and information terminal. The gastric electroacupuncture acquisition electrode bandage performs multi-channel gastric electroacupuncture signal acquisition, and the detection host and information terminal work together to perform gastric electroacupuncture detection. This simplifies the design of the internal functional modules of the detection host. Under the existing electronic technology conditions, the detection host can be integrated into a small box-shaped electronic device, realizing the lightweight and miniaturization of the detection host device. It can be installed on the gastric electroacupuncture acquisition electrode bandage in various ways.

[0065] 2. The wearable multi-channel gastric electrocardiogram (ECG) acquisition system of this invention allows users to wear the ECG acquisition electrode bandage and the detection host on their body for ECG testing, eliminating the need for prolonged bed rest and improving user convenience. Furthermore, the eight ECG acquisition electrodes can be flexibly attached and detached from the ECG acquisition electrode bandage, allowing for adjustment to a suitable testing position based on the subject's body shape. The skin contact impedance detection function quickly determines the contact status of the ECG acquisition electrodes, effectively avoiding poor signal quality or invalid measurements due to poor contact. These factors enable even untrained users to independently perform ECG measurements at home, reducing the difficulty of use and saving time.

[0066] 3. The wearable multi-channel gastric electrical activity acquisition system of the present invention can be set to select a single-person mode to detect one subject, or to select a two-person mode to detect two subjects simultaneously, according to the user's needs. In the two-person mode, the gastric electrical activity detection results of two subjects can be obtained at the same time, which effectively improves the utilization efficiency of the device and saves time costs.

[0067] 4. The wearable multi-channel gastric electroacupuncture acquisition system of the present invention can effectively reduce the threshold for using gastric electroacupuncture detection equipment. It is suitable for home, community and mobile medical scenarios. Users do not need to be fixed in the examination room for a long time for bed testing. They can conduct self-monitoring at home, which significantly improves the user experience and reduces the occupation of hospital resources. It helps to achieve early screening and long-term management of gastric diseases. Attached Figure Description

[0068] To make the objectives, technical solutions, and advantages of the invention clearer, the invention will now be described in further detail with reference to the accompanying drawings, wherein:

[0069] Figure 1 This is a schematic diagram of the architecture of the wearable multi-channel gastric electroacupuncture acquisition system of the present invention;

[0070] Figure 2 This is a structural example diagram of the fabric elastic bandage in an embodiment of the wearable multi-channel gastric electrocardiogram acquisition system of the present invention;

[0071] Figure 3 This is a schematic diagram of the installation structure of gastric electrical detection electrodes on the buckle holes of a fabric elastic bandage in an embodiment of the wearable multi-channel gastric electrical acquisition system of the present invention.

[0072] Figure 4 This is a schematic diagram illustrating an embodiment of the wearable multi-channel gastric electroacupuncture acquisition system of the present invention in use.

[0073] Figure 5 This is a schematic diagram of the circuit composition of the skin contact impedance detection module in the wearable multi-channel gastric electroacupuncture system of the present invention.

[0074] Figure 6 This is a flowchart of the signal noise reduction and reconstruction process for gastric electrical signals in the wearable multi-channel gastric electrical acquisition system of the present invention;

[0075] Figure 7 This is a flowchart illustrating the feature extraction and processing of a single-channel reconstructed gastric electrical signal in the wearable multi-channel gastric electrical signal acquisition system of the present invention. Detailed Implementation

[0076] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. The components of the embodiments of the present invention described and shown in the accompanying drawings can generally be arranged and designed in various different configurations. Therefore, the following detailed description of the embodiments of the present invention provided in the accompanying drawings is not intended to limit the scope of the claimed invention, but only to illustrate selected embodiments of the invention. All other embodiments obtained by those skilled in the art based on the embodiments of the present invention without inventive effort are within the scope of protection of the present invention.

[0077] To make the technical solution and advantages of the present invention clearer, the embodiments of the present invention will be further described in detail below.

[0078] This invention proposes a wearable multi-channel gastric electrophysiological acquisition system, such as... Figure 1As shown, the system includes a gastric electrical signal acquisition electrode bandage, a detection host, and an information terminal. The gastric electrical signal acquisition electrode bandage is worn by the subject and has eight channels of gastric electrical signal acquisition electrodes installed on it corresponding to the subject's gastric electrical signal acquisition area, for multi-channel gastric electrical signal acquisition. The detection host can be installed on the gastric electrical signal acquisition electrode bandage for easy wearable testing. The detection host includes a skin contact impedance detection circuit module, a signal acquisition circuit module, a main controller module, and a Bluetooth module. The skin contact impedance detection circuit module is used to detect the skin contact impedance signal in real time and transmit it to the main controller module. The signal acquisition circuit module includes 8 signal conditioning circuits and 2 right leg drive circuits. The 8 signal conditioning circuits are used to connect to the 8 channels of gastric electrical signal acquisition electrodes in the gastric electrical signal acquisition electrode bandage, and to filter, amplify, and condition the gastric electrical signal acquired by each channel of gastric electrical signal acquisition electrode. The 8 signal conditioning circuits are divided into two groups, with each group of 4 signal conditioning circuits sharing one right leg drive circuit to reduce common-mode interference before transmitting the signal to the main controller module. The main controller module is used to receive operation control commands from the information terminal via the Bluetooth module, coordinate the operation of the skin contact impedance detection circuit module, the signal acquisition circuit module, and the Bluetooth module, and, when the skin contact impedance is analyzed to be in a normal state, perform analog-to-digital conversion processing on each gastric electrical signal processed by the signal acquisition circuit module, and transmit the resulting gastric electrical digital signals externally via the Bluetooth module. The information terminal is used to interface with the Bluetooth module of the detection host, send operation control commands to the detection host, receive various gastric electrical digital signals sent by the detection host and perform correlation analysis, identify and determine the dominant channel from the multi-channel gastric electrical digital signals, and obtain the gastric electrical state detection results of the subject based on the gastric electrical digital signal of the dominant channel.

[0079] This invention relates to a wearable multi-channel gastric electrocardiogram (ECG) acquisition system, which employs a modular design comprising a gastric ECG acquisition electrode bandage, a detection host, and an information terminal. The detection host is mounted on the ECG acquisition electrode bandage and worn by the subject. The bandage performs multi-channel ECG signal acquisition. The detection host integrates skin contact impedance detection and analog-to-digital conversion functions, ensuring normal skin contact impedance before sending the converted ECG digital signals to the information terminal. The information terminal can use a device with Bluetooth and information processing capabilities, such as a mobile phone, tablet, or desktop computer used by the subject. Leveraging its processing power, the information terminal interacts with the detection host, sending operational control commands and processing the received ECG digital signals to obtain the subject's ECG status detection results. This wearable design allows subjects to perform gastric function status monitoring while wearing the device, effectively lowering the barrier to entry and making it suitable for home, community, and mobile healthcare scenarios. It also facilitates early screening and long-term management of gastric diseases.

[0080] The following is a detailed description of each part of the wearable multi-channel gastric electroacupuncture acquisition system of the present invention.

[0081] 1. Gastric electroacupuncture electrode bandage

[0082] In specific application implementation, such as Figure 2 As shown, the gastric electrocardiogram (GEG) acquisition electrode bandage 1 includes a fabric elastic bandage 101 for wearing on the subject's body. The fabric elastic bandage 101 has an array of buckle holes 102 for mounting GEG detection electrodes, and a mounting component 103 for mounting the detection host. Figure 3 As shown, the gastric electrophysiological detection electrode 2 has a contact detection end 201 and a conductive connection end 202 that are electrically conductive to each other. It also includes a wire 203 and a mounting nut 204 for connecting the conductive connection end 202. The contact detection end 201 is used to contact the subject's skin as a detection contact point. The conductive connection end 202 has a connecting base plate 2021 and a mounting post 2022 extending outward from the base plate, and the mounting post 2022 has an external thread. During installation, the conductive connection end of the gastric electrophysiological detection electrode 2... After the mounting post 2022 passes through the buckle hole 101 on the elastic fabric bandage 1, one end of the wire 203 is connected to the mounting post 2022 to form a conductive contact. Then, the mounting nut 204 with internal threads is threaded to the external thread of the mounting post 2022, so that the elastic fabric bandage 101 and one end of the wire 203 are pressed and fixed between the mounting nut 204 and the connecting base plate 2021, thereby realizing the fixed installation of the gastric electrodetection electrode 2 at the buckle hole 102 position of the elastic fabric bandage 1.

[0083] In practice, the elastic fabric bandage for the gastric electrical signal acquisition electrode bandage can be designed as a loop-shaped elastic fabric bandage that is worn over the head, or as a long strip-shaped elastic fabric bandage that is fastened at both ends with snaps. At the same time, different sizes of elastic fabric bandages, such as large, medium, and small, can be designed according to the different body types of the subjects. The array of buckle holes on the gastric electrical signal acquisition electrode bandage can be designed with the spacing between adjacent holes as needed, for example, the spacing between adjacent buckle holes can be designed to be 1cm, which facilitates the flexible placement of the gastric electrical signal acquisition electrodes.

[0084] In practical implementation, the gastric electrophysiological detection electrode of the electrophysiological acquisition electrode bandage can use the medical Ag / AgCl electrode commonly used in existing patch-type gastric electrophysiological detection electrodes at the contact detection end, with an additional conductive metal mounting post structure added on top of it; the end of the wire connected to the mounting post can be designed as a coil structure that matches the size of the mounting post, making it easy for the end of the wire to be directly fitted onto the mounting post for installation, increasing convenience; the mounting nut is preferably made of insulating materials such as plastic to reduce external contact interference.

[0085] In practice, because the detection host and information terminal work together to perform gastric electrocardiogram (ECG) detection, the internal functional module design of the detection host is simplified. Under current electronic technology conditions, the detection host can be integrated into a small, box-shaped electronic device, achieving lightweight and miniaturized design. It can be mounted on the ECG acquisition electrode bandage in various ways. For example, if a hook is designed on the casing of the detection host, the mounting components on the ECG acquisition electrode bandage can be designed as a strap or loop for engaging with the hook; or, as a simpler design approach, such as... Figure 4 As shown, the mounting component on the gastric electrical activity acquisition electrode bandage 1 can be designed as a hanging bag that can accommodate the detection host 3. The detection host 3 is placed in the hanging bag on the gastric electrical activity acquisition electrode bandage 1. At the same time, the 8-channel gastric electrical activity acquisition electrodes 2 are assembled on the gastric electrical activity acquisition electrode bandage corresponding to the gastric electrical activity acquisition area of ​​the subject. They are connected to the signal acquisition circuit module interface of the detection host 3 through wires. The detection host 3 communicates with the subject's mobile phone, tablet or other device as an information terminal 4 via Bluetooth to carry out interactive operation of gastric electrical activity detection.

[0086] In this way, on the one hand, by using a gastric electrocardiogram (ECG) acquisition electrode bandage to assemble the ECG detection electrodes and the main unit, users can wear the bandage and the main unit on their body to perform ECG measurements, eliminating the need for prolonged bed rest and allowing for a certain range of movement, thus improving the convenience of ECG measurement. On the other hand, the eight-channel ECG acquisition electrodes can be flexibly installed and removed from the bandage, allowing for adjustment to a suitable testing position based on the subject's body shape. Furthermore, once the testing position is determined for the same subject, no further adjustments or repeated testing are needed. In addition, the main unit integrates a skin contact impedance detection function, allowing the subject to quickly determine the contact status of the ECG acquisition electrodes based on the feedback information, effectively avoiding poor signal quality or invalid measurements due to poor contact. All these factors enable users without professional training to independently perform ECG measurements at home, reducing the difficulty of use and saving time. Therefore, the wearable multi-channel gastric electrocardiogram (GEC) acquisition system of the present invention can effectively reduce the threshold for using GEC detection devices, and is suitable for home, community and mobile medical scenarios. Users do not need to be fixed in the examination room for long periods of time for bed testing, and can conduct self-monitoring at home, which significantly improves the user experience and reduces the occupation of hospital resources, and helps to achieve early screening and long-term management of gastric diseases.

[0087] 2. Testing the host computer

[0088] As mentioned earlier, the detection host mainly includes a skin contact impedance detection circuit module, a signal acquisition circuit module, a main controller module, and a Bluetooth module.

[0089] In specific implementation, such as Figure 5 As shown, the skin contact impedance detection circuit module in the detection host includes a first multiplexer, a second multiplexer, and a waveform conversion circuit.

[0090] The first and second multiplexers are respectively connected to the main controller module for communication, and the main controller module generates an amplitude of V. in The square wave pulse signal is time-division multiplexed to control the first multiplexer to output the square wave pulse signal in eight time-division multiplexing modes. These eight time-division outputs are each connected to one of the eight gastric electrical sensing electrodes in the gastric electrical sensing electrode bandage via reference resistors. Each reference resistor forms a voltage divider network with one channel of the gastric electrical sensing electrode, thus dividing the skin contact impedance Z sensed by the gastric electrical sensing electrode. s The change is converted into output voltage V out The fluctuations satisfy R refThe reference resistor value is used as the reference value; the node between each reference resistor and the gastric electrocardiogram (GEG) acquisition electrode of one channel is respectively connected to different input channels of the second multiplexer, which is controlled by the main controller module, and converts the output voltage V of each channel. out Output to waveform conversion circuit.

[0091] The waveform conversion circuit is used to convert the output voltage V out The waveform is shaped into a digital rectangular wave signal and sent to the main controller module. This waveform conversion circuit is a commonly used circuit for skin contact impedance detection. Specifically, the waveform conversion circuit is usually composed of an RC integrator circuit and a voltage comparator. Its working principle is as follows: after the square wave excitation signal passes through the above voltage divider network, V... out The amplitude of the voltage carries impedance information; this voltage charges and discharges the RC circuit, forming a voltage whose amplitude is affected by V. out A modulated ramp signal; this ramp signal is modulated by a fixed threshold voltage V. th Comparison is performed in the comparator; due to V th The timing of the output voltage transition depends on the RC charging voltage reaching V. th The speed, which is directly determined by V out The amplitude is determined by the wave size. Therefore, the pulse width T of the rectangular wave output by the waveform conversion circuit is... pw With Z s There exists a monotonic mapping relationship between them; through system calibration, T can be established. pw With Z s The mapping relationship between them can be represented as:

[0092] T pw =k·Z s +C;

[0093] Where k and C are constants determined through calibration.

[0094] During the approval impedance testing, the main control module of the testing host controls the skin contact impedance detection circuit module to emit square wave pulse signals through multiple channels, and then receives the digital rectangular wave signal output by the waveform conversion circuit. The pulse width T of the digital rectangular wave signal is then used to determine the appropriate signal. pw The skin contact impedance Z of each channel is calculated using the following formula. s :

[0095]

[0096] If the skin contact impedance of each channel does not exceed the preset threshold, it indicates that the gastric electrocardiogram (ECG) detection electrodes of each channel are in good contact with the subject's skin and the detection can be carried out normally. At this time, the main controller module will send the processed ECG digital signals to the outside via the Bluetooth module. If the main controller module determines that the skin contact impedance of any channel exceeds the preset threshold, it indicates that the ECG detection electrodes of the corresponding channel may have poor contact, affecting the detection. The main controller module will then send an abnormal skin contact impedance warning message for the corresponding channel to the information terminal via the Bluetooth module to notify the subject to check or adjust.

[0097] In practical implementation, the signal acquisition circuit module of the detection host includes a passive low-pass filter circuit, a preamplifier circuit, an active band-pass filter circuit, and a post-amplifier circuit, all cascaded together. The passive low-pass filter circuit initially filters out low-frequency signals below 0.01Hz; the preamplifier circuit amplifies the initially filtered signal for the first time; the active band-pass filter filters out interference signals above 0.2Hz from the first amplified signal; and the post-amplifier circuit amplifies the second filtered signal for the second time. Through the signal conditioning circuit, effective signals are retained as much as possible, noise interference signals are filtered out, and the signal amplitude is adjusted to be within the acceptable range of the analog-to-digital conversion of the main control module, thereby improving signal detection accuracy. The right leg drive circuit has high input impedance and low output impedance, serving as impedance matching to prevent common-mode interference from being converted into differential-mode interference.

[0098] The main controller module is used to coordinate the operation of various functional modules in the detection host. For example, it receives and parses the operation control command information received from the information terminal via the Bluetooth module; captures the rectangular wave pulse width characteristics output by the waveform conversion circuit, calculates the skin contact impedance value of each channel, and if the skin contact impedance of any channel exceeds the threshold, it sends a warning command for the corresponding channel via the Bluetooth module; if the skin contact impedance of each channel is normal, it acquires the analog gastric electrical signal output by the signal acquisition circuit module at a preset sampling frequency, and performs analog-to-digital conversion to convert it into a digital gastric electrical signal; it encapsulates the converted digital gastric electrical signal and sends it outward via the Bluetooth module.

[0099] In addition, a display module can be added to the testing host, controlled by the main controller module, to display preset prompts based on system status or command requirements. In practical applications, it is best to use an e-ink screen based on an SPI interface, which consumes power only during refresh, helping to reduce display power consumption and extend the operating time of the testing host.

[0100] In specific implementation, the preferred power supply method for the detection host is a rechargeable independent power supply, which facilitates wearable use without a wired power source. The main controller module obtains the output voltage of the power detection circuit, detects the power of the independent power supply, calculates and controls the display module to update the display of information such as the remaining battery power status. Of course, the power supply circuit can also be designed to be compatible with wired power supply, supporting continued use by connecting a wired power source when the power of the independent power supply is insufficient.

[0101] 3. Information terminal

[0102] As mentioned earlier, in practical implementation, the information terminal can use terminal devices with Bluetooth and information processing capabilities, such as mobile terminals like smartphones and tablets used by the subjects, or computer terminals like desktop computers. Leveraging the processing power of the information terminal, it interacts and collaborates with the detection host. The information terminal's processing function for multi-channel gastric electrical digital signals can be executed by loading an application program into the information terminal.

[0103] In the design of this invention, the information terminal supports two measurement modes: single-person mode and dual-person mode. In single-person mode, the system utilizes all eight signal acquisition channels to acquire gastric electrical signals from a single subject. This mode offers two default sub-mode options: "8 channels" and "4 channels." When the user selects the "4 channels" sub-mode, the system defaults to using channels 1-4 for signal acquisition and subsequent analysis; when the user selects the "8 channels" sub-mode, the system uses channels 1-8 for signal acquisition and subsequent analysis. In dual-person mode, the system divides the eight channels into two groups, defaulting to assigning channels 1-4 to the first subject and channels 5-8 to the second subject, thus allowing simultaneous acquisition of four-channel gastric electrical signals from two subjects. In the subsequent signal processing and analysis, the algorithm flow for single-channel feature extraction is completely consistent between the two modes. The core difference between the two lies in the logical division of the analysis objects: in single-person mode, the calculation results of all enabled channels belong to the same subject and multi-channel correlation analysis is performed; in dual-person mode, the system will independently perform two complete signal processing and feature extraction processes for channels 1-4 and channels 5-8, and associate the results with the first and second subjects respectively, without performing cross-group correlation analysis between the two groups of channels.

[0104] In practical applications, users can control the start and stop of signal acquisition and set functions such as timed measurement through the application software interface of the information terminal. During the acquisition process, the waveform display interface in the application software of the information terminal can support real-time display of the raw gastric electrical waveforms of each channel. After the acquisition is completed, the application software of the information terminal stores the raw gastric electrical signals in a timestamped format file in local memory for subsequent analysis and processing.

[0105] Specifically, the processing flow of multi-channel gastric electrical digital signals by the information terminal includes:

[0106] S1. Signal noise reduction and reconstruction processing:

[0107] Empirical mode decomposition (EMD) was performed on the digital gastric electrical signals of each channel. Then, the IMF components obtained from the decomposition were used to reconstruct the digital gastric electrical signals of the corresponding channels, resulting in reconstructed gastric electrical signals for each channel.

[0108] The specific processing flow for the digital gastric electrical signals of each channel is as follows: Figure 6 As shown, it includes the following steps:

[0109] S101. After acquiring the digital gastric electrical signal of the channel, first use a digital bandpass filter to digitally filter the digital gastric electrical signal, then perform Empirical Mode Decomposition (EMD) on the digitally filtered digital gastric electrical signal, and calculate the dominant frequency of each IMF component obtained by decomposition. Only retain the IMF components with the dominant frequency in the frequency range of 1 to 10 cpm (i.e. 0.0167 to 0.167 Hz) as the effective IMF components.

[0110] The purpose of this step is to eliminate interference from irrelevant noise.

[0111] S102. For the valid IMF components retained in the channel, try all possible combinations and superpositions of consecutive IMF components. Each combination and superposition constitutes a candidate signal, thereby forming multiple candidate signals.

[0112] In this step, all possible combinations and superpositions of consecutive IMF components are tried for the valid IMF components retained in the channel. For example, starting from any i-th IMF component, 1, 2, ... are taken consecutively until all valid IMF components are taken to form multiple candidate signals.

[0113] S103. For each candidate signal in this channel, calculate its normalized autocorrelation function at lag k sampling points, where k ranges from 60 to 120:

[0114]

[0115] Where R(k) represents the normalized autocorrelation function; s(n) represents the candidate signal; s(n+k) represents the candidate signal after lagging by k sampling points; N s The number of sampling points contained in the candidate signal;

[0116] Then, the peak value is found in the normalized autocorrelation function of each candidate signal after lagging by a different number of sampling points, and this peak value is taken as the autocorrelation function peak value of the candidate signal; thus, the peak value of the autocorrelation function of each candidate signal in the channel is obtained.

[0117] S104. Select the candidate signal with the largest peak value of the autocorrelation function in the channel as the gastric electrical remodeling signal of the channel.

[0118] This processing yields a reconstructed signal that ensures the most significant periodicity within the normal gastric electrical rhythm range, preserving the main characteristics of the gastric electrical signal.

[0119] S2, Feature Extraction:

[0120] For the gastric electrical reconstructed signal of each channel, the power percentage feature of its different gastric motility state types is extracted, and the gastric motility state type corresponding to the maximum value of the power percentage feature is taken as the gastric motility state type to which the gastric electrical reconstructed signal of the corresponding channel belongs; the gastric motility state type includes normal gastric motility, slow gastric motility, and fast gastric motility.

[0121] The specific processing procedure for the gastric electrical remodeling signal of each channel is as follows: Figure 7 As shown, it includes the following steps:

[0122] S201. The gastric electrical reconstructed signal of the channel is segmented, and the power spectrum of each segment is calculated to obtain the main frequency and main power of each segment. The sum of the main power of each segment is taken as the total power of the gastric electrical reconstructed signal.

[0123] In this step, the segmentation of the gastric electrical reconstructed signal is for the purpose of discretizing it and then performing analysis on the main frequency and main power.

[0124] S202. Determine the frequency range of different gastric motility state types according to the gastric electrical signal frequency range classification standard. The gastric motility state types include normal gastric motility, slow gastric motility, and rapid gastric motility. Then, classify the gastric motility state types of the segmented signals according to the frequency range of the gastric motility state type where the main frequency of each segmented signal is located. Then, calculate the sum of the main power of each segmented signal classified into each gastric motility state type as the power value of the gastric electrical reconstructed signal in the corresponding gastric motility state type.

[0125] In this step, when determining the frequency range of different gastric motility types according to the gastric electrical signal frequency range classification standard, the gastric electrical signal frequency range classification standard in the "Gastric Electrogastrography Examination and its Evaluation Standard (Trial)" can be referred to.

[0126] S203. Using the power value of a single gastric motility state type as the denominator and the total power of the gastric electrical reconstructed signal as the numerator, calculate the power percentage characteristics of the gastric electrical reconstructed signal in different gastric motility state types respectively, and take the gastric motility state type corresponding to the maximum value of the power percentage characteristics as the gastric motility state type to which the gastric electrical reconstructed signal of this channel belongs.

[0127] Through this process, it is possible to determine whether the gastric electrical remodeling signals of different channels belong to the state of normal gastric motility, slow gastric motility, or tachygastric motility.

[0128] S3, Multi-channel correlation analysis:

[0129] Correlation analysis was performed on the digital gastric electrical signals of each channel, and the maximum correlation coefficient and propagation delay between different channels were extracted. The information flow between different channels was quantified by the transfer entropy, thereby identifying the dominant channel. The gastric motility state type to which the gastric electrical reconstructed signal of the dominant channel belongs was used as the gastric motility state detection result of the subject.

[0130] As mentioned earlier, the information terminal can control the detection host to execute single-person or dual-person detection modes. Therefore, the corresponding operation control commands sent by the information terminal to the detection host include single-person mode detection commands and dual-person mode detection commands, which are used to instruct the detection host to execute single-person mode detection or dual-person mode detection, respectively. In single-person mode detection, all 8 channels of gastric electrocardiogram (GEG) digital signals, or 4 channels of GEG digital signals, are used as a group for correlation analysis. In dual-person mode detection, the 8 channels of GEG digital signals are divided into two groups, and correlation analysis is performed on the 4 channels of GEG digital signals in each group.

[0131] When performing correlation analysis on each group of digital gastric electrical signals, it is necessary to calculate the normalized cross-correlation function and transfer entropy of all possible pairwise combinations between channels within the group. Therefore, in the 8-channel single-person mode, it is necessary to calculate the normalized cross-correlation function and transfer entropy of all possible pairwise combinations between the 8 channels, resulting in a total of 28 pairs of combinations. In the 4-channel single-person mode or the dual-person mode, the pairwise combinations within each group are analyzed for the 4 channels, resulting in 6 pairs of combinations per group. Channel relationships across groups are not calculated.

[0132] The correlation analysis of the gastric electrical digital signals of each channel within each group is performed, and the specific steps are as follows:

[0133] S301. Calculate the normalized cross-correlation function between the gastric electrical digital signals of different channels within the group, thereby finding the propagation delay corresponding to the maximum correlation coefficient and determining the signal transmission direction between the gastric electrical digital signals of different channels within the group.

[0134] Among them, any two channels Ch within the group x,Ch y The normalized cross-correlation function R between gastric electrophysiological digital signals xy (τ) is used to measure the linear similarity of gastric electrical signals from two corresponding channels under different time delays, and its expression is:

[0135]

[0136] Where x(n) is the channel Ch x The signal amplitude at the nth sampling point in the digital gastric electroencephalogram (GEO) signal, y(n) is the signal amplitude of channel Ch. y The signal amplitude of the nth sampling point in the digital gastric electrocardiogram, where n = 1, 2, ..., N, and N is the number of sampling points in the digital gastric electrocardiogram; They are channel Ch x Channel Ch y The average amplitude of the digital gastric electroencephalogram; τ is the number of sampling points corresponding to the time delay, with a value range of [-τ]. max ,+τ max ], τ max This represents the number of sampling points corresponding to the preset maximum time delay. In specific applications, this number can be preset based on the number of sampling points corresponding to the maximum physiological propagation time of the gastric slow wave; y(n+τ) represents the channel Ch. y The signal amplitude at the (n+τ)th sampling point in the digital gastric electroencephalogram (GEG) signal.

[0137] Then, find the normalized cross-correlation function R across all possible values ​​of v. xy The maximum value of (τ) is taken as the maximum correlation coefficient R. max R max =max τ |R xy (τ)|, this value is used to characterize the linear correlation strength of the corresponding two-channel gastric electrophysiological digital signals under optimal alignment; if R max If the correlation coefficient is less than or equal to a preset threshold, then the channel Ch is determined to be... x ,Ch y There is no correlation between them; if R max If the correlation coefficient is greater than a preset threshold, then the channel Ch is determined to be... x ,Ch y The points between these points represent the relevant channels. For each relevant channel, the maximum correlation coefficient R is... max The corresponding value of τ is determined as the propagation delay τ. d Determine the propagation delay τ d The value state of τ; if τ d A value greater than 0 indicates that the signal transmission direction is from channel Ch. x Transmission Channel Ch y If τ dIf ≤0, it indicates that the signal transmission direction is from channel Ch. y Transmission Channel Ch x .

[0138] This determines the signal transmission direction between the digital gastric electrical signals of every two related channels within the group.

[0139] S302. Calculate the transfer entropy between the gastric electrical digital signals of the relevant channels within the group, and determine the dominant direction of information flow between the gastric electrical digital signals of the relevant channels within the group.

[0140] Among them, any two related channels Ch within the group x ,Ch y Between the digital signals of gastric electrical activity, from channel Ch y To Channel Ch x Transitive entropy TE y→x And from channel Ch x To Channel Ch y Transitive entropy TE x→y They are respectively:

[0141]

[0142] Where x(n) and x(n+1) are channels Ch x The signal amplitudes at the nth and (n+1)th sampling points in the digital gastric electroencephalogram (GEG) signal, y(n) and y(n+1) are respectively the values ​​of channel Ch. y The signal amplitudes at the nth and (n+1)th sampling points in the digital gastric electrocardiogram (DGE) signal; p(x(n+1)|x(n)) represents the signal amplitudes at channel Ch in the historical data of the digital gastric electrocardiogram (DGE) signal. x When the amplitude of the nth sampling point is x(n), channel Ch x The probability that the amplitude of the (n+1)th sampling point is x(n+1); p(x(n+1)|x(n),y(n)) represents the probability of channel Ch in the historical data of gastric electrocardiogram digital signal. x The amplitude of the nth sampling point is x(n), and the channel Ch y When the amplitude of the nth sampling point is y(n), channel Ch x The probability that the amplitude of the (n+1)th sampling point is x(n+1); p(y(n+1)|y(n)) represents the probability of channel Ch in the historical data of gastric electrocardiogram digital signal. y When the amplitude of the nth sampling point is y(n), channel Ch y The probability that the amplitude of the (n+1)th sampling point is y(n+1); p(y(n+1)|x(n),y(n)) represents the probability of channel Ch in the historical data of gastric electrocardiogram digital signal. x The amplitude of the nth sampling point is x(n), and the channel Ch yWhen the amplitude of the nth sampling point is y(n), channel Ch y The probability that the amplitude of the (n+1)th sampling point is y(n+1);

[0143] Then, compare the transfer entropy in both directions; if TE x→y >TE y→x Then the dominant direction of information flow is determined to be from channel Ch. x To Channel Ch y If TE x→y <TE y→x Then the dominant direction of information flow is determined to be from channel Ch. y To Channel Ch x Furthermore, if TE occurs... x→y =TE y→x In this case, it indicates that channel Ch x ,Ch y There is no correlation between them, and there is no significant direct propagation relationship between the two channels; however, since the combination of uncorrelated channels has been excluded by the normalized cross-correlation function analysis, the situation where the propagation entropy in the two directions is equal usually does not occur in this stage.

[0144] Therefore, the dominant direction of information flow between the digital signals of gastric electroencephalography (GEG) of every two related channels within the group is determined, and then an information flow network is constructed with the channels of the GEG digital signals as nodes and the transfer entropy value between channels as the weights of the directed edges.

[0145] In the above steps, the normalized cross-correlation function between different channels is calculated to determine the relevant channels, and then the transfer entropy is calculated for the relevant channels to analyze the dominant direction of information flow. This is because the computational complexity of the transfer entropy is much higher than that of the normalized cross-correlation function. If the linear correlation between the gastric electrocardiogram digital signals of two channels is very weak (i.e., R...), the calculation will be more complex. max If the correlation coefficient is less than or equal to the preset threshold, it indicates that there may be no significant direct propagation relationship between them or that the signal quality is poor. In this case, the computationally intensive transfer entropy analysis can be skipped, and it can be directly assumed that there are no effective directed edge weights in the information flow network between these two channels, which can simplify the computation to a certain extent. At the same time, the signal transmission direction between the correlated channels found through normalized cross-correlation function analysis also reflects the physical temporal relationship of signal transmission on the body surface to a certain extent. In practical implementation, it can also be used to cross-validate with the dominant direction of information flow obtained from subsequent analysis. When the two directions are consistent, the physiological credibility of the analysis results is enhanced; when they are inconsistent, it indicates that there may be complex nonlinear interactions or calculation errors, and further verification analysis can be performed.

[0146] S303. Calculate the weighted out-degree of each node in the information flow network, and take the channel corresponding to the node with the highest weighted out-degree as the dominant channel, so as to take the gastric motility state type of the gastric electrical reconstruction signal of the dominant channel as the gastric motility state detection result of the subject.

[0147] In this step, the information output capability of the corresponding channel is quantified by the weighted out-degree of each node in the information flow network. For single-person mode, the weighted out-degree of 8 nodes needs to be calculated; for dual-person mode, the weighted out-degree of two sets of 4 nodes is calculated separately. The node with the highest weighted out-degree, whose information flow direction best matches the anatomical direction of propagation from the gastric pacemaker area to the pylorus, is identified as the dominant channel. The gastric motility state type of the gastric electrical reconstructed signal of the dominant channel is then used as the subject's gastric motility state detection result. That is, if the gastric electrical reconstructed signal of the dominant channel belongs to the normal, bradykinesic, or tachykinesic state type, the subject's gastric motility state detection result is determined accordingly as normal, bradykinesic, or tachykinesic. Thus, the gastric motility state detection of the subject is completed, and the detection result is displayed on the information terminal.

[0148] Therefore, the wearable multi-channel gastric electrocardiogram (GEG) acquisition system of the present invention can be set to a single-person mode to detect one subject, or a two-person mode to detect two subjects simultaneously, according to the user's needs. In the two-person mode, each subject needs to wear a fabric elastic bandage. The eight-channel GEG acquisition electrodes are divided into two groups. For example, the electrodes for channels 1-4 are installed on the fabric elastic bandages worn by the first subject, and the electrodes for channels 5-8 are installed on the fabric elastic bandages worn by the second subject. The system will independently perform two complete signal processing and feature extraction processes for channels 1-4 and channels 5-8, respectively, and associate the results with the first and second subjects. No cross-group correlation analysis is performed between the two groups of channels, thus simultaneously obtaining the GEG status detection results of two subjects, effectively improving equipment utilization efficiency and saving time costs.

[0149] Furthermore, as an extended functional design, the information terminal can also, in the aforementioned step S2 processing of the gastric electrical reconstruction signal for each channel, such as... Figure 7 As shown, after obtaining the main frequency of each segment signal, the frequency instability coefficient (DFIC) of each segment signal can also be calculated:

[0150]

[0151] Then, the obtained frequency instability coefficient (DFIC) of each segment signal is also displayed on the information terminal as one of the visualization information to characterize the frequency stability performance of different segment signals.

[0152] Furthermore, the information terminal can visualize all intermediate data and information involved in the gastric electrocardiogram (GC-GC) test, facilitating observation by the test subjects. Additionally, the terminal can store all test data in a local database for easy access later; if the terminal is connected to a network, it can also encrypt and upload the data to the cloud for remote storage.

[0153] In summary, compared with the prior art, the present invention has the following technical advantages:

[0154] 1. The wearable multi-channel gastric electroacupuncture acquisition system of the present invention adopts a modular design of gastric electroacupuncture acquisition electrode bandage, detection host and information terminal. The gastric electroacupuncture acquisition electrode bandage performs multi-channel gastric electroacupuncture signal acquisition, and the detection host and information terminal work together to perform gastric electroacupuncture detection. This simplifies the design of the internal functional modules of the detection host. Under the existing electronic technology conditions, the detection host can be integrated into a small box-shaped electronic device, realizing the lightweight and miniaturization of the detection host device. It can be installed on the gastric electroacupuncture acquisition electrode bandage in various ways.

[0155] 2. The wearable multi-channel gastric electrocardiogram (ECG) acquisition system of this invention allows users to wear the ECG acquisition electrode bandage and the detection host on their body for ECG testing, eliminating the need for prolonged bed rest and improving user convenience. Furthermore, the eight ECG acquisition electrodes can be flexibly attached and detached from the ECG acquisition electrode bandage, allowing for adjustment to a suitable testing position based on the subject's body shape. The skin contact impedance detection function quickly determines the contact status of the ECG acquisition electrodes, effectively avoiding poor signal quality or invalid measurements due to poor contact. These factors enable even untrained users to independently perform ECG measurements at home, reducing the difficulty of use and saving time.

[0156] 3. The wearable multi-channel gastric electrical activity acquisition system of the present invention can be set to select a single-person mode to detect one subject, or to select a two-person mode to detect two subjects simultaneously, according to the user's needs. In the two-person mode, the gastric electrical activity detection results of two subjects can be obtained at the same time, which effectively improves the utilization efficiency of the device and saves time costs.

[0157] 4. The wearable multi-channel gastric electroacupuncture acquisition system of the present invention can effectively reduce the threshold for using gastric electroacupuncture detection equipment. It is suitable for home, community and mobile medical scenarios. Users do not need to be fixed in the examination room for a long time for bed testing. They can conduct self-monitoring at home, which significantly improves the user experience and reduces the occupation of hospital resources. It helps to achieve early screening and long-term management of gastric diseases.

[0158] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention and not to limit the technical solutions. Those skilled in the art should understand that any modifications or equivalent substitutions to the technical solutions of the present invention without departing from the spirit and scope of the present invention should be covered within the scope of the claims of the present invention.

Claims

1. A wearable multi-channel gastric electrocardiogram (GECG) acquisition system, characterized in that, Includes gastric electroacupuncture electrode bandage, detection host, and information terminal; The gastric electrical signal acquisition electrode bandage is worn on the subject. The gastric electrical signal acquisition electrode bandage has 8 channels of gastric electrical signal acquisition electrodes installed on it corresponding to the subject's gastric electrical signal acquisition area, which is used to acquire gastric electrical signals from the subject through multiple channels. The detection host can be installed on the gastric electrical acquisition electrode bandage. The detection host includes a skin contact impedance detection circuit module, a signal acquisition circuit module, a main controller module, and a Bluetooth module. The skin contact impedance detection circuit module is used to detect the skin contact impedance signal in real time and transmit it to the main controller module. The signal acquisition circuit module includes eight signal conditioning circuits and two right leg drive circuits. The eight signal conditioning circuits are used to connect to the eight channels of gastric electrical signal acquisition electrodes in the gastric electrical signal acquisition electrode bandage, respectively, and to filter, amplify, and condition the gastric electrical signals acquired by each channel of the gastric electrical signal acquisition electrode. The eight signal conditioning circuits are divided into two groups, with four signal conditioning circuits in each group sharing one right leg drive circuit to reduce common-mode interference before transmitting the signals to the main controller module. The main controller module is used to receive operation control commands from the information terminal via the Bluetooth module, coordinate the operation of the skin contact impedance detection circuit module, the signal acquisition circuit module, and the Bluetooth module, and, when the skin contact impedance is analyzed to be in a normal state, perform analog-to-digital conversion on the gastric electrical signals processed by the signal acquisition circuit module, and transmit the resulting digital gastric electrical signals externally via the Bluetooth module. The information terminal is used to interface with the Bluetooth module of the detection host, send operation control commands to the detection host, receive various gastric electrical digital signals sent by the detection host and perform correlation analysis, identify and determine the dominant channel from the multi-channel gastric electrical digital signals, and obtain the gastric electrical state detection results of the subject based on the gastric electrical digital signal of the dominant channel.

2. The wearable multi-channel gastric electrocardiogram acquisition system according to claim 1, characterized in that, The gastric electroacupuncture acquisition electrode bandage includes a fabric elastic bandage for wearing on the subject's body, the fabric elastic bandage having an array of buckle holes for mounting gastric electroacupuncture detection electrodes, and mounting parts for mounting the detection host. The gastric electrophysiological detection electrode has a contact detection end and a conductive connection end that are electrically conductive to each other. It also includes a wire and a mounting nut for connecting the conductive connection end. The contact detection end is used to contact the subject's skin as a detection contact point. The conductive connection end has a connecting base plate and a mounting post extending outward from the base plate, and the mounting post is provided with an external thread. During installation, after the mounting post portion of the conductive connection end of the gastric electrophysiological detection electrode passes through the buckle hole on the elastic fabric bandage, one end of the wire is connected to the mounting post to form a conductive contact. Then, the mounting nut with an internal thread engages with the external thread of the mounting post, so that the elastic fabric bandage and one end of the wire are pressed and fixed between the mounting nut and the connecting base plate, thereby achieving the fixed installation of the gastric electrophysiological detection electrode at the buckle hole position of the elastic fabric bandage.

3. The wearable multi-channel gastric electrocardiogram acquisition system according to claim 1, characterized in that, The skin contact impedance detection circuit module in the detection host includes a first multiplexer, a second multiplexer, and a waveform conversion circuit; The first and second multiplexers are respectively connected to the main controller module for communication, and the main controller module generates an amplitude of V. in The square wave pulse signal is time-division multiplexed to control the first multiplexer to output the square wave pulse signal in eight time-division multiplexing modes. These eight time-division outputs are each connected to one of the eight gastric electrical sensing electrodes in the gastric electrical sensing electrode bandage via reference resistors. Each reference resistor forms a voltage divider network with one channel of the gastric electrical sensing electrode, thus dividing the skin contact impedance Z sensed by the gastric electrical sensing electrode. s The change is converted into output voltage V out The fluctuations satisfy R ref The reference resistor value is used as the reference value; the node between each reference resistor and the gastric electrocardiogram (GEG) acquisition electrode of one channel is respectively connected to different input channels of the second multiplexer, which is controlled by the main controller module, and converts the output voltage V of each channel. out Output to waveform conversion circuit; The waveform conversion circuit is used to convert the output voltage V out The signal is shaped into a digital rectangular wave and sent to the main controller module. The pulse width T of the digital rectangular wave signal is... pw Skin contact resistance Z s The following mapping relationship exists: T pw =k·Z s +C; Where k and C are constants determined through calibration.

4. The wearable multi-channel gastric electrocardiogram acquisition system according to claim 3, characterized in that, The main control module of the detection host receives the digital rectangular wave signal output by the waveform conversion circuit, and determines the pulse width T of the digital rectangular wave signal accordingly. pw The skin contact impedance Z of each channel is calculated using the following formula. s : The main controller module is also used to send an abnormal skin contact impedance warning message for the corresponding channel to the information terminal via Bluetooth when it is determined that the skin contact impedance of any channel exceeds a preset threshold.

5. The wearable multi-channel gastric electrocardiogram acquisition system according to claim 1, characterized in that, In the signal acquisition circuit module of the detection host, each signal conditioning circuit includes a passive low-pass filter circuit, a preamplifier circuit, an active band-pass filter circuit, and a post-amplifier circuit cascaded in sequence; the passive low-pass filter circuit is used to initially filter out low-frequency signals below 0.01Hz; The preamplifier circuit is used to amplify the signal after preliminary filtering for the first time. The active bandpass filter circuit is used to filter out interference signals higher than 0.2Hz from the signal after the first amplification. The subsequent amplifier circuit is used to amplify the filtered signal a second time.

6. The wearable multi-channel gastric electrocardiogram acquisition system according to claim 1, characterized in that, The information terminal's processing flow for multi-channel gastric electrical digital signals includes: S1. Signal noise reduction and reconstruction processing: Empirical mode decomposition (EMD) was performed on the digital gastric electrical signals of each channel, and then the IMF components obtained from the decomposition were used to reconstruct the digital gastric electrical signals of the corresponding channels to obtain the reconstructed gastric electrical signals of each channel. S2, Feature Extraction: For the gastric electrical reconstructed signal of each channel, the power percentage feature of its different gastric motility state types is extracted, and the gastric motility state type corresponding to the maximum value of the power percentage feature is taken as the gastric motility state type of the corresponding channel's gastric electrical reconstructed signal; the gastric motility state type includes normal gastric motility, slow gastric motility, and tachygastric motility; S3, Multi-channel correlation analysis: Correlation analysis was performed on the digital gastric electrical signals of each channel, and the maximum correlation coefficient and propagation delay between different channels were extracted. The information flow between different channels was quantified by the transfer entropy, thereby identifying the dominant channel. The gastric motility state type to which the gastric electrical reconstructed signal of the dominant channel belongs was used as the gastric motility state detection result of the subject.

7. The wearable multi-channel gastric electrocardiogram acquisition system according to claim 6, characterized in that, In S1, the specific processing steps for the digital gastric electrical signal of each channel include: S101. After acquiring the digital gastric electrical signal of the channel, first use a digital bandpass filter to digitally filter the digital gastric electrical signal, then perform empirical mode decomposition on the digitally filtered digital gastric electrical signal, and calculate the main frequency of each IMF component obtained by decomposition. Only retain the IMF components with the main frequency in the frequency range of 1 to 10 cpm as the effective IMF components. S102. For the valid IMF components retained in the channel, try all possible combinations and superpositions of consecutive IMF components. Each combination and superposition constitutes a candidate signal, thereby forming multiple candidate signals. S103. For each candidate signal in this channel, calculate its normalized autocorrelation function at lag k sampling points, where k ranges from 60 to 120: Where R(k) represents the normalized autocorrelation function; s(n) represents the candidate signal; s(n+k) represents the candidate signal after lagging by k sampling points; N s The number of sampling points contained in the candidate signal; Then, the peak value is found in the normalized autocorrelation function of each candidate signal after lag by a different number of sampling points, and this peak value is taken as the peak value of the autocorrelation function of the candidate signal; thus, the peak value of the autocorrelation function of each candidate signal in the channel is obtained. S104. Select the candidate signal with the largest peak value of the autocorrelation function in the channel as the gastric electrical remodeling signal of the channel.

8. The wearable multi-channel gastric electrocardiogram acquisition system according to claim 6, characterized in that, In S2, the specific processing steps for the gastric electrical remodeling signal of each channel include: S201. The gastric electrical reconstructed signal of the channel is segmented, and the power spectrum of each segment is calculated to obtain the main frequency and main power of each segment. The sum of the main power of each segment is taken as the total power of the gastric electrical reconstructed signal. S202. Determine the frequency range of different gastric motility state types according to the gastric electrical signal frequency range division standard. The gastric motility state types include normal gastric motility, slow gastric motility, and rapid gastric motility. Then, classify the gastric motility state types of the segmented signals according to the frequency range of the gastric motility state type where the main frequency of each segmented signal is located. Then, calculate the sum of the main power of each segmented signal classified into each gastric motility state type as the power value of the gastric electrical reconstructed signal in the corresponding gastric motility state type. S203. Using the power value of a single gastric motility state type as the denominator and the total power of the gastric electrical reconstructed signal as the numerator, calculate the power percentage characteristics of the gastric electrical reconstructed signal in different gastric motility state types respectively, and take the gastric motility state type corresponding to the maximum value of the power percentage characteristics as the gastric motility state type to which the gastric electrical reconstructed signal of this channel belongs.

9. The wearable multi-channel gastric electrocardiogram acquisition system according to claim 6, characterized in that, The operation control commands sent by the information terminal to the detection host include single-person mode detection commands and dual-person mode detection commands, which are used to instruct the detection host to perform single-person mode detection or dual-person mode detection, respectively. In single-person mode detection, all 8 channels of gastric electrocardiogram (GEG) digital signals, or 4 channels of GEG digital signals, are used as a group for correlation analysis. In dual-person mode detection, the 8 channels of GEG digital signals are divided into two groups, and correlation analysis is performed on the 4 channels of GEG digital signals in each group.

10. The wearable multi-channel gastric electrocardiogram acquisition system according to claim 9, characterized in that, In S3, correlation analysis is performed on the digital gastric electrical signals of each channel within each group. The specific steps are as follows: S301. Calculate the normalized cross-correlation function between the gastric electrical digital signals of different channels within the group, thereby finding the propagation delay corresponding to the maximum correlation coefficient and determining the signal transmission direction between the gastric electrical digital signals of different channels within the group. Among them, any two channels Ch within the group x ,Ch y The normalized cross-correlation function R between gastric electrophysiological digital signals xy (τ) is: Where x(n) is the channel Ch x The signal amplitude at the nth sampling point in the digital gastric electroencephalogram (GEO) signal, y(n) is the signal amplitude of channel Ch. y The signal amplitude of the nth sampling point in the digital gastric electrocardiogram, where n = 1, 2, ..., N, and N is the number of sampling points in the digital gastric electrocardiogram; They are channel Ch x Channel Ch y The average amplitude of the digital gastric electroencephalogram; τ is the number of sampling points corresponding to the time delay, with a value range of [-τ]. max ,+τ max ], τ max The number of sampling points corresponding to the preset maximum time delay; y(n+τ) represents the number of channels Ch. y The signal amplitude at the (n+τ)th sampling point in the digital gastric electroencephalogram; Then, find the normalized cross-correlation function R across all possible values ​​of τ. xy The maximum value of (τ) is taken as the maximum correlation coefficient R. max R max =max τ |R xy (n)|;If R max If the correlation coefficient is less than or equal to a preset threshold, then the channel Ch is determined to be... x ,Ch y There is no correlation between them; if R max If the correlation coefficient is greater than a preset threshold, then the channel Ch is determined to be... x ,Ch y The channels between them are related, and the maximum correlation coefficient R is set. max The corresponding value of τ is determined as the propagation delay τ. d If τ d >0 indicates that the signal transmission direction is from channel Ch. x Transmission Channel Ch y If τ d If ≤0, it indicates that the signal transmission direction is from channel Ch. y Transmission Channel Ch x ; Therefore, the signal transmission direction between the digital gastric electrical signals of every two related channels within the group is determined; S302. Calculate the transfer entropy between the gastric electrical digital signals of the relevant channels within the group, and determine the dominant direction of information flow between the gastric electrical digital signals of the relevant channels within the group. Among them, any two related channels Ch within the group x ,Ch y Between the digital signals of gastric electrophysiology, from channel Ch y To Channel Ch x Transitive entropy TE y→x And from channel Ch x To Channel Ch y Transitive entropy TE x→y They are respectively: Where x(n) and x(n+1) are channels Ch x The signal amplitudes at the nth and (n+1)th sampling points in the digital gastric electroencephalogram (GEG) signal, y(n) and y(n+1) are respectively the values ​​of channel Ch. y The signal amplitudes at the nth and (n+1)th sampling points in the digital gastric electrocardiogram (DGE) signal; p(x(n+1)|x(n)) represents the signal amplitudes at channel Ch in the historical data of the digital gastric electrocardiogram (DGE) signal. x When the amplitude of the nth sampling point is x(n), channel Ch x The probability that the amplitude of the (n+1)th sampling point is x(n+1); p(x(n+1)|x(n),y(n)) represents the probability of channel Ch in the historical data of gastric electrocardiogram digital signal. x The amplitude of the nth sampling point is x(n), and the channel Ch y When the amplitude of the nth sampling point is y(n), channel Ch x The probability that the amplitude of the (n+1)th sampling point is x(n+1); p(y(n+1)|y(n)) represents the probability of channel Ch in the historical data of gastric electrocardiogram digital signal. y When the amplitude of the nth sampling point is y(n), channel Ch y The probability that the amplitude of the (n+1)th sampling point is y(n+1); p(y(n+1)|x(n),y(n)) represents the probability of channel Ch in the historical data of gastric electrocardiogram digital signal. x The amplitude of the nth sampling point is x(n), and the channel Ch y When the amplitude of the nth sampling point is y(n), channel Ch y The probability that the amplitude of the (n+1)th sampling point is y(n+1); Then, compare the transfer entropy in both directions; if TE x→y >TE y→x Then the dominant direction of information flow is determined to be from channel Ch. x To Channel Ch y If TE x→y <TE y→x Then the dominant direction of information flow is determined to be from channel Ch. y To Channel Ch x ; Therefore, the dominant direction of information flow between the digital signals of gastric electrocardiogram (ECG) of every two related channels within the group is determined, and then an information flow network is constructed with the channels of the EEG digital signals as nodes and the transfer entropy value between channels as the weight of the directed edges. S303. Calculate the weighted out-degree of each node in the information flow network, and take the channel corresponding to the node with the highest weighted out-degree as the dominant channel, so as to take the gastric motility state type of the gastric electrical reconstruction signal of the dominant channel as the gastric motility state detection result of the subject.

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