Electrical impedance tomography data processing method and device and storage medium

Abstract

The invention relates to an electrical impedance tomography data processing method and device and a storage medium, and the method comprises the steps: obtaining a plurality of pieces of channel data of a plurality of electrodes in a measurement region; for each electrode, based on the channel data, obtaining an electrode state characteristic parameter; when the electrode state characteristic parameters of the plurality of electrodes are all in a characteristic threshold range, polling and uploading channel data channel by channel at an interval of N frames to an upper computer; otherwise, determining an abnormal channel in all channels corresponding to the plurality of electrodes based on the electrode state characteristic parameters of the plurality of electrodes; determining to-be-uploaded data according to the channel data of the abnormal channel, and simultaneously uploading the to-be-uploaded data to an upper computer at an interval of M frames less than N frames; and other channels except the abnormal channel upload channel data of other channels to an upper computer in a channel-by-channel polling manner at an interval of N frames. According to the invention, the problem of large data processing amount in the data transmission and processing process is solved.

Description

Technical Field

[0001] The present application relates to the field of electrical impedance tomography, and in particular to a method, device and storage medium for electrical impedance tomography data processing. Background Art

[0002] Electrical impedance tomography (EIT) is a noninvasive medical functional imaging technique. It utilizes an array of electrodes placed on the human body surface. By injecting a safe current and measuring the voltage signal, the technique reconstructs the internal electrical impedance distribution and changes. This technique offers advantages such as being radiation-free, simple in system structure, and fast in imaging speed. It holds broad application prospects in dynamic monitoring of cardiovascular, esophageal, and gastric physiological processes. Existing EIT systems face significant technical bottlenecks in high-speed imaging scenarios: using a 16-electrode mode, a single image requires the acquisition of 256 channels of data, and long-term monitoring can generate tens of GB of data. Directly transmitting raw data presents challenges such as large data volumes, high storage requirements, and insufficient transmission speeds. Especially for high-speed imaging, raw data transmission and processing become bottlenecks, limiting the imaging speed and real-time performance of EIT systems. Related technologies employ simplified processing (such as setting abnormal signals to zero) or adjusting the excitation frequency, but these approaches often result in large amounts of raw data to be transmitted.

[0003] Currently, no effective solution has been proposed to the problem of large amount of original data transmission in related technologies. Summary of the Invention

[0004] The embodiments of the present application provide an electrical impedance imaging data processing method and storage medium to at least solve the problem of large original data transmission volume in the related art.

[0005] In a first aspect, an embodiment of the present application provides a method for processing electrical impedance imaging data, the method comprising:

[0006] Acquire multiple channel data of multiple electrodes in the measurement area;

[0007] For each electrode, obtaining electrode state characteristic parameters based on the channel data;

[0008] When the electrode state characteristic parameters of the plurality of electrodes are all within the characteristic threshold range, the channel data are uploaded to the host computer by polling channel by channel at intervals of N frames; N is a positive integer;

[0009] otherwise, determining an abnormal channel among all channels corresponding to the plurality of electrodes based on the electrode state characteristic parameters of the plurality of electrodes;

[0010] According to the channel data of the abnormal channel, determine the data to be uploaded, and upload the data to be uploaded to the host computer at the same time at an interval of M frames; among all the channels except the abnormal channel, poll the channel data of the other channels one by one at an interval of N frames and upload them to the host computer; M is a positive integer, and M is less than N.

[0011] In some embodiments, determining the data to be uploaded based on the channel data of the abnormal channel includes:

[0012] Calculate the abnormal waveform correlation coefficient of each abnormal channel for the channel data of the abnormal channel in the current frame and the previous K frames; K is a positive integer;

[0013] determining a first abnormal channel whose abnormal waveform correlation coefficient is lower than a correlation coefficient threshold, and identifying channel data of the first abnormal channel as the data to be uploaded;

[0014] A second abnormal channel having an abnormal waveform correlation coefficient higher than a correlation coefficient threshold is determined, and current frame data of the second abnormal channel is marked with an abnormal identifier and notified to the host computer.

[0015] In some embodiments, obtaining electrode state characteristic parameters for each electrode based on the channel data includes:

[0016] For each electrode, performing orthogonal demodulation on multiple frames of channel data to obtain multiple voltage modulus values;

[0017] The voltage modulus values are summed and variances are calculated to obtain the electrode state characteristic parameters.

[0018] In some embodiments, obtaining electrode state characteristic parameters for each electrode based on the channel data includes:

[0019] For each electrode, performing orthogonal demodulation on multiple frames of channel data to obtain multiple voltage modulus values;

[0020] The voltage modulus values are summed and variances are calculated to obtain the electrode state characteristic parameters.

[0021] In some embodiments, obtaining electrode state characteristic parameters for each electrode based on the channel data further includes:

[0022] For each electrode, multiple channel data are subjected to signal correlation analysis to obtain multiple signal correlation coefficients;

[0023] Among the multiple signal correlation coefficients, the number of target signals having signal correlation coefficients higher than a signal correlation threshold is screened and counted to obtain the electrode state characteristic parameter.

[0024] In some embodiments, after obtaining the electrode state characteristic parameter for each electrode based on the channel data, the method further includes:

[0025] Obtaining an electrode detachment state according to the electrode state characteristic parameters, and uploading the electrode detachment state to a host computer;

[0026] Based on the channel data and the electrode detachment status, the electrode contact impedance is calculated for each electrode; based on the electrode contact impedance, the electrode contact status is obtained, and the electrode contact status is uploaded to the host computer.

[0027] In some embodiments, obtaining the electrode detachment status according to the electrode status characteristic parameters and uploading the electrode detachment status to a host computer includes:

[0028] When the electrode state characteristic parameter is not within a preset characteristic parameter threshold range, the electrode detachment state is set as abnormal, and the electrode detachment state is uploaded to the host computer;

[0029] When the electrode state characteristic parameter is within a preset characteristic parameter threshold range, the electrode detachment state is set to normal.

[0030] In some embodiments, calculating the electrode contact impedance for each electrode based on the channel data and the electrode detachment status includes:

[0031] When the electrode detachment state is normal, the electrode contact impedance is calculated for each electrode based on the voltage modulus corresponding to the channel data.

[0032] In some embodiments, obtaining the electrode contact state based on the electrode contact impedance and uploading the electrode contact state to the host computer includes:

[0033] When the electrode contact impedance is not within a preset impedance range, the electrode contact state is set to abnormal, and the electrode contact state is uploaded to the host computer;

[0034] When the electrode contact impedance is within a preset impedance range, the electrode contact state is set to normal.

[0035] In a second aspect, an embodiment of the present application provides an electrical impedance imaging data processing device, the device comprising:

[0036] A channel data acquisition module is used to obtain multiple channel data of multiple electrodes in the measurement area;

[0037] A characteristic parameter extreme module is used to obtain electrode state characteristic parameters for each electrode based on the channel data;

[0038] A normal state uploading module is used to upload the channel data to the host computer by polling channel by channel at intervals of N frames when the electrode state characteristic parameters of the plurality of electrodes are all within the characteristic threshold range; N is a positive integer;

[0039] an abnormal channel identification module, configured to determine an abnormal channel among all channels corresponding to the plurality of electrodes based on electrode state characteristic parameters of the plurality of electrodes;

[0040] The abnormal state uploading module is used to determine the data to be uploaded based on the channel data of the abnormal channel, and upload the data to be uploaded to the host computer at the same time at an interval of M frames; for all channels except the abnormal channel, the channel data of the other channels are polled channel by channel at an interval of N frames and uploaded to the host computer; M is a positive integer, and M is less than N.

[0041] In a third aspect, a storage medium is provided in this embodiment, on which a computer program is stored. When the program is executed by a processor, the electrical impedance imaging data processing method described in the first aspect is implemented.

[0042] Compared with the related art, the electrical impedance imaging data processing method and storage medium provided in the embodiment of the present application obtain multiple channel data of multiple electrodes in the measurement area; for each electrode, based on the channel data, obtain electrode state characteristic parameters; when the electrode state characteristic parameters of multiple electrodes are all within the characteristic threshold range, the channel data are uploaded to the host computer by polling channel by channel at intervals of N frames; N is the interval parameter, and is a positive integer; otherwise, the interval parameter is adjusted based on the electrode state characteristic parameters of multiple electrodes; according to the adjusted interval parameter, the channel data are uploaded to the host computer by polling channel by channel, which solves the problem of large raw data processing volume and slow transmission during data transmission and processing in the electrical impedance imaging system in the prior art.

[0043] The details of one or more embodiments of the present application are set forth in the following drawings and description to make other features, objects, and advantages of the present application more readily apparent. BRIEF DESCRIPTION OF THE DRAWINGS

[0044] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0045] Figure 1 This is a hardware structure block diagram of a terminal for an electrical impedance imaging data processing method according to an embodiment of the present application;

[0046] Figure 2 is a flow chart of a method for processing electrical impedance imaging data according to an embodiment of the present application;

[0047] Figure 3 is a structural block diagram of an electrical impedance imaging data processing device according to an embodiment of the present application;

[0048] Figure 4 This is an electrical impedance tomography system framework according to an embodiment of the present application;

[0049] Figure 5 This is a structural block diagram of an electrical impedance imaging system according to an embodiment of the present application. DETAILED DESCRIPTION

[0050] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application is described and illustrated below in conjunction with the accompanying drawings and examples. It should be understood that the specific embodiments described herein are only used to explain the present application and are not intended to limit the present application. Based on the embodiments provided in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application. In addition, it can also be understood that although the efforts made in this development process may be complex and lengthy, for ordinary technicians in the field related to the contents disclosed in the present application, some changes such as design, manufacturing or production based on the technical contents disclosed in the present application are only conventional technical means and should not be understood as the contents disclosed in the present application being insufficient.

[0051] References to "embodiments" in this application mean that a particular feature, structure, or characteristic described in connection with the embodiment may be included in at least one embodiment of the application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it refer to independent or alternative embodiments that are mutually exclusive of other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described in this application may be combined with other embodiments unless there is a conflict.

[0052] Unless otherwise defined, technical or scientific terms used herein shall have the ordinary meaning as understood by persons of ordinary skill in the art to which this application belongs. The terms "a," "an," "an," "the," and similar expressions used herein do not denote limitations on quantity and may refer to either the singular or the plural. The terms "comprise," "include," "have," and any variations thereof, used herein, are intended to cover non-exclusive inclusions. For example, a process, method, system, product, or apparatus comprising a series of steps or modules (units) is not limited to the listed steps or units but may also include steps or units not listed, or may include other steps or units inherent to the process, method, product, or apparatus. The terms "connected," "connected," "coupled," and similar expressions used herein are not limited to physical or mechanical connections but may include electrical connections, whether direct or indirect. As used herein, "plurality" means greater than or equal to two. "And / or" describes an association between associated objects, indicating that three possible relationships exist. For example, "A and / or B" may mean: A exists alone; A and B exist simultaneously; or B exists alone. The terms "first", "second", "third" and the like involved in this application are merely used to distinguish similar objects and do not represent a specific ordering of the objects.

[0053] The method embodiment provided in this embodiment can be executed in a terminal, a computer or a similar computing device. Taking running on a terminal as an example, Figure 1 FIG. 1 is a hardware structure diagram of a terminal according to an electrical impedance imaging data processing method of an embodiment of the present application. Figure 1 As shown, the terminal may include one or more ( Figure 1 Only one is shown) a processor 102 (the processor 102 may include but is not limited to a microprocessor MCU or a programmable logic device FPGA) and a memory 104 for storing data. Optionally, the terminal may also include a transmission device 106 and an input / output device 108 for communication functions. It will be understood by those skilled in the art that Figure 1 The structure shown is only for illustration and does not limit the structure of the above terminal. Figure 1 More or fewer components than shown, or with Figure 1 Different configurations shown.

[0054] The memory 104 can be used for storing computer programs, for example, software programs and modules of application software, such as the computer program corresponding to the electrical impedance imaging data processing method in the embodiment of the present application, the processor 102 performs various functional applications and data processing by running the computer program stored in the memory 104, i.e., realizes the above method. The memory 104 may include a high-speed random access memory, and may also include a non-volatile memory, such as one or more magnetic storage devices, flash memory or other non-volatile solid-state memories. In some instances, the memory 104 may further include a memory remotely arranged relative to the processor 102, and these remote memories may be connected to the terminal via a network. Examples of the above-mentioned network include but are not limited to the Internet, an intranet, a local area network, a mobile communication network and a combination thereof.

[0055] Transmission device 106 is used to receive or transmit data via a network. A specific example of the aforementioned network may include a wireless network provided by the terminal's communications provider. In one embodiment, transmission device 106 includes a network interface controller (NIC), which can be connected to other network devices via a base station to enable communication with the Internet. In another embodiment, transmission device 106 may be a radio frequency (RF) module, which is used to communicate with the Internet wirelessly.

[0056] EIT technology, whose full name is bioelectrical impedance tomography, is a new type of medical functional imaging technology. Its working principle is to place a certain number of electrodes on the surface of the human body, inject a safe current and measure the surface voltage of other electrodes, and reconstruct the internal impedance value of the human body or the change value of the impedance based on the relationship between voltage and current. Since this method does not use radionuclides or rays and is harmless to the human body, it can be measured and reused multiple times, and the imaging speed is fast, with the characteristics of functional imaging. EIT technology has many advantages, such as being non-invasive to the human body, no ionization and radiation hazards, simple system structure, easy measurement, etc. It can be used for fast portable imaging, and has broad application prospects in continuous dynamic image monitoring of physiological activities of the human cardiovascular, esophageal, gastric, etc.

[0057] However, existing electrical impedance tomography (EIT) equipment still faces challenges in multi-channel signal acquisition and processing. Currently, typical EIT systems utilize a 16-electrode configuration, requiring 256 channels of data per image frame. Due to limitations in electrode distribution and control methods, the actual number of effective channels is limited to 192. This results in a large amount of raw data, potentially reaching tens of GB over extended monitoring periods.

[0058] This massive data volume is primarily driven by two factors: first, each channel needs to upload 128 points of waveform data; second, ensuring data integrity and accuracy requires a long monitoring period (typically one hour to several days). In this situation, directly transmitting raw data would obviously present challenges such as large data volumes, high storage requirements, and insufficient transmission speeds. Especially in situations requiring high-speed imaging, such as real-time monitoring at 100 or 50 frames per second, the transmission and processing of raw data becomes a bottleneck, severely restricting the imaging speed and real-time performance of the EIT system.

[0059] In order to solve the problem of large amount of raw data processing and slow transmission in the data transmission and processing process of the electrical impedance imaging system, this embodiment provides an electrical impedance imaging data processing method. Figure 2 is a flow chart of a method for processing electrical impedance imaging data according to an embodiment of the present application. Figure 2 As shown, the process includes the following steps:

[0060] Step S201: Acquire multiple channel data of multiple electrodes in a measurement area.

[0061] Specifically, in the electrical impedance measurement system, channel data for the measurement area is acquired through the following process: First, several electrodes are evenly distributed along the chest, with a tight arrangement ensuring sensitive sensing of human physiological activity. For ease of description, the following description primarily uses a 16-electrode solution as an example; other numbers can also be used depending on the actual application scenario. During excitation, the host computer configures the excitation current from a constant current source and selects the corresponding excitation electrode pair (electrodes 1 and 9) via the excitation selector switch. A safe current is injected into the human load, while adjacent measurement electrode pairs simultaneously receive voltage signals. During signal acquisition, the 16 electrodes act as excitation electrode pairs in a round-robin manner. Each round of excitation generates 16 channels of measurement data, and after 16 rounds of polling, a frame of 256-channel raw data is accumulated. Each channel corresponds to a pair of excitation electrodes and a pair of measurement electrodes. The channel data consists of the voltage time-domain waveform data collected from the measurement electrodes after current is injected into the excitation electrodes. Due to limitations in electrode distribution and control methods, the actual number of effective channels is 192. After the received analog signal is processed by the filtering and amplifying circuit, 16 analog-to-digital conversion modules (AD) synchronously complete the analog-to-digital conversion. The converted digital signal is temporarily stored in a buffer pool of several frames (such as 20 frames), providing raw channel data for subsequent electrode status evaluation and data processing.

[0062] Step S202: For each electrode, obtain electrode state characteristic parameters based on channel data.

[0063] Specifically, 16 electrodes (numbered 1 to 16) generate a total of 256 channels of data. Taking electrode 1 as an example, its associated electrode data covers 60 channels (when electrode 1 is used for positive excitation, the associated data is 16; when electrode 1 is used for negative excitation, the associated data is also 16; when electrode 1 is used for positive measurement, the associated data is 14; when electrode 1 is used for negative measurement, the associated data is also 14, for a total of 60 associated channels). By performing signal correlation analysis and / or variance sum analysis on the 60-channel data associated with electrode 1, the electrode state characteristic parameter is obtained. This parameter can be used to evaluate the stability of electrode 1.

[0064] Step S203 , when the electrode state characteristic parameters of the plurality of electrodes are all within the characteristic threshold range, the channel data are uploaded to the host computer by polling channel by channel at intervals of N frames, where N is a positive integer.

[0065] Specifically, when it is detected within a period of time that the electrode state characteristic parameters of the 16 electrodes all meet the preset threshold requirements, the system defaults to an interval of N=100 frames (which can be configured as a positive integer as needed), and polls and uploads waveform data channel by channel in the order of 1 to 256. After traversing 256 channels, the host computer can obtain periodic sampling information of all channels.

[0066] Step S204: otherwise, based on the electrode state characteristic parameters of the multiple electrodes, determine the abnormal channels among all the channels corresponding to the multiple electrodes.

[0067] Specifically, a normal threshold range is set for the state characteristic parameters of each electrode, and the state characteristic parameters of each electrode are compared with the corresponding threshold range. If the characteristic parameters of an electrode exceed the normal threshold range, the channel corresponding to the electrode is determined to be an abnormal channel, and the abnormal channel list is updated in real time. When the electrode state characteristic parameters return to the normal range, the corresponding channel is removed from the abnormal channel list. Conversely, if the newly added electrode characteristic parameters exceed the threshold range, its corresponding channel is added to the abnormal channel list.

[0068] Step S205: Determine the data to be uploaded based on the channel data of the abnormal channel, and upload the data to be uploaded to the host computer at the same time at an interval of M frames; among all channels except the abnormal channel, poll the channel data of other channels one by one at an interval of N frames and upload them to the host computer; M is a positive integer, and M is less than N.

[0069] Specifically, data to be uploaded is identified based on the channel data of the abnormal channel. This data can be data from all or a portion of the abnormal channels. Subsequently, the data to be uploaded is uploaded to the host computer at an interval of M frames, which is less than N frames. Simultaneously, data from all channels other than the abnormal channel is uploaded channel by channel at an interval of N frames, implementing a differentiated data upload strategy for abnormal and normal channels. The M-frame interval can also be adjusted in real time based on the number of channels. If the number of abnormal channels exceeds a certain threshold, the upload frequency can be appropriately reduced to avoid transmission congestion caused by excessive uploading of channel data from the abnormal channels. For abnormal channel data, the upload frequency can also be adaptively adjusted based on the electrode state characteristic parameters of the abnormal channel data. For example, if the variance sum of a channel is low (high stability), indicating a stable signal, the upload frequency can be adaptively reduced. If the variance sum of a channel is high (low stability), indicating an unstable signal, the upload frequency can be adaptively increased to preserve more details.

[0070] In the above steps, real-time monitoring of the electrode status is achieved by acquiring multi-electrode multi-channel data and calculating the electrode status characteristic parameters. When the electrode status is normal, the data is polled and uploaded channel by channel at an interval of N frames. When an abnormality occurs, the abnormal channel is determined and the abnormal channel data is uploaded at a high frequency at a shorter interval of M frames. The normal channel is still polled and uploaded at an interval of N frames. This mechanism effectively reduces the amount of data transmission under normal conditions while ensuring accurate capture and real-time upload of abnormal conditions. In addition, it can also improve data transmission efficiency, reduce system bandwidth occupancy, and realize differentiated data upload and resource optimization configuration for electrode status monitoring.

[0071] In some embodiments, determining the data to be uploaded based on the channel data of the abnormal channel includes:

[0072] Calculate the abnormal waveform correlation coefficient of each abnormal channel for the channel data of the abnormal channel in the current frame and the previous K frames; K is a positive integer;

[0073] determining a first abnormal channel whose abnormal waveform correlation coefficient is lower than a correlation coefficient threshold, and identifying channel data of the first abnormal channel as the data to be uploaded;

[0074] A second abnormal channel having an abnormal waveform correlation coefficient higher than a correlation coefficient threshold is determined, and current frame data of the second abnormal channel is marked with an abnormal identifier and notified to the host computer.

[0075] Specifically, for the channel data of the abnormal channel in the current frame and the previous K frames, the Pearson correlation coefficient algorithm can be used to calculate the similarity between the waveform of the current frame channel data of the channel and the waveform of the previous K frames of the channel data. When the abnormal waveform correlation coefficient of a channel is lower than the correlation coefficient threshold, it indicates that the waveform has changed significantly and is different from the historical data waveform. The channel is determined to be the first abnormal channel, and then the channel data of the channel in the current frame is used as the data to be uploaded; if the correlation coefficient of the abnormal channel is higher than the threshold, it means that the current waveform and the historical waveform are repetitive, then it is identified as the second abnormal channel, and the current frame data of the second abnormal channel is marked only with the abnormal identifier and notified to the host computer.

[0076] In the above steps, by calculating the waveform similarity of the current frame and the previous K frames of the abnormal channel, the current frame data of the first abnormal channel with an abnormal waveform correlation coefficient lower than the threshold and significant waveform changes is identified as data to be uploaded. For the second abnormal channel with a correlation coefficient higher than the threshold and a repetitive waveform, only the current frame data is marked with an identifier and the host computer is notified. This realizes hierarchical processing of abnormal channel data, and while accurately capturing waveform mutation anomalies, it reduces the transmission volume of repeated abnormal data, improves the efficiency and pertinence of abnormal data uploading, and reduces system bandwidth occupancy and data processing pressure.

[0077] In some embodiments, obtaining electrode state characteristic parameters for each electrode based on channel data includes:

[0078] For each electrode, performing orthogonal demodulation on multiple frames of channel data to obtain multiple voltage modulus values;

[0079] The variance and the variance of multiple voltage modulus values are calculated to obtain the electrode state characteristic parameters.

[0080] Specifically, one frame of image requires 256 channels of data from 16 electrodes. The 60 channels of data associated with each electrode (electrode 1, for example) are subjected to orthogonal demodulation. The DC component is obtained by multiplying the two orthogonal local oscillator signals with the input AC voltage signal, and then low-pass filtering is performed. The voltage modulus is then synthesized using a square root operation. One modulus is generated for each channel per frame, and a total of 60 voltage modulus values are generated for the 60 channels of a single electrode. For each channel's 20 frames of voltage modulus values, the single-channel variance is first calculated using the following formula:

[0081] ;

[0082] in, is the variance of a single channel data, is the ith voltage modulus, is the average value of the voltage modulus, and N is the number of frames (here N=20).

[0083] Then, the variance values of the 60 channels associated with a single electrode were accumulated to obtain the variance sum. A larger value indicated a worse electrode contact stability.

[0084] In the above embodiment, by performing orthogonal demodulation on the 60 channels of data associated with each electrode to obtain voltage moduli and calculating the sum of variances across 20 frames of data, quantitative analysis of the electrode contact status is achieved. When an electrode is detached, the voltage moduli of its associated channels fluctuate more sharply, and the sum of variances increases significantly. This improves the accuracy of identifying abnormal conditions such as electrode detachment compared to traditional single-channel threshold detection methods. It also provides reliable characteristic parameter support for subsequent dynamic adjustment of data transmission strategies.

[0085] In some embodiments, obtaining electrode state characteristic parameters for each electrode based on the channel data further includes:

[0086] For each electrode, multiple channel data are subjected to signal correlation analysis to obtain multiple signal correlation coefficients;

[0087] Among the multiple signal correlation coefficients, the number of target signals having signal correlation coefficients higher than a signal correlation threshold is screened and counted to obtain the electrode state characteristic parameter.

[0088] Specifically, the Pearson correlation coefficient is calculated for the waveform data of the 60 channels associated with each electrode and the standard sine wave reference signal. The formula is as follows:

[0089] ;

[0090] Among them, Xi is the channel waveform sampling value; Yi is the standard waveform sampling value; n is the number of samples, that is, the number of X, Y data pairs; r is the Pearson correlation coefficient, the value range is [-1,1], r>0 is positive correlation, r<0 is negative correlation, The closer it is to 1, the stronger the linear correlation.

[0091] After calculation, channels with correlation coefficients above a threshold are selected as target signals, and their number is counted as a characteristic parameter for the electrode status. This parameter directly reflects the stability of electrode contact. When an electrode falls off, the waveform distortion of the abnormal channel causes a decrease in the correlation coefficient, reducing the number of target signals. If this number falls below a preset value (e.g., 50), the electrode status is considered abnormal. This process provides accurate characteristic basis for subsequent dynamic adjustment of data transmission strategies.

[0092] In the above steps, the Pearson correlation coefficient is calculated between the waveform data of the 60 channels associated with each electrode and a standard sine wave, and the number of target signals above the threshold is screened and counted, thus achieving quantitative monitoring of electrode contact stability. Compared with traditional single-channel threshold detection methods, this improves the accuracy of identifying abnormal conditions such as electrode detachment. At the same time, it provides reliable characteristic parameter support for subsequent dynamic adjustment of data transmission strategies.

[0093] In some embodiments, after obtaining electrode state characteristic parameters for each electrode based on the channel data, the electrical impedance imaging data processing method may further include the following steps:

[0094] According to the electrode state characteristic parameters, the electrode shedding state is obtained and the electrode shedding state is uploaded to the host computer;

[0095] Based on the channel data and the electrode detachment status, the electrode contact impedance is calculated for each electrode; based on the electrode contact impedance, the electrode contact status is obtained and uploaded to the host computer.

[0096] Specifically, after calculating the electrode state characteristic parameters, it can be determined whether the electrode has fallen off. If the electrode state characteristic parameters are not within a preset range, the electrode is determined to be in a fallen-off state, and a data file containing the electrode number and the fallen-off state identifier is sent to the host computer. Afterwards, for electrodes that have not been determined to be fallen off, the electrode contact impedance is calculated based on the voltage modulus and constant excitation current corresponding to the channel data. Then, the electrode contact state is determined based on the value of the electrode contact impedance, and the electrode contact state is uploaded to the host computer.

[0097] In the above steps, electrode status characteristic parameters are calculated based on channel data to determine electrode detachment status, and contact impedance is calculated for electrodes that have not detached to determine contact status. This enables multi-dimensional and precise monitoring of the electrode's working state. Simultaneously, electrode status data is uploaded to the host computer in real time, allowing the host computer to make appropriate electrode adjustments based on the reported results.

[0098] In some embodiments, obtaining the electrode detachment status according to the electrode state characteristic parameters and uploading the electrode detachment status to the host computer includes:

[0099] When the electrode state characteristic parameter is not within the preset characteristic parameter threshold range, the electrode detachment state is set as abnormal, and the electrode detachment state is uploaded to the host computer;

[0100] When the electrode state characteristic parameter is within the preset characteristic parameter threshold range, the electrode detachment state is set to normal.

[0101] Specifically, the system calculates the sum of variances or Pearson correlation coefficient characteristic parameters for each electrode's 60 channel data and compares them with a preset threshold range. For example, if the sum of variances exceeds the threshold or the number of channels with a correlation coefficient below 0.6 exceeds 50, the characteristic parameter is determined to be outside the threshold range. At this time, the system automatically sets the electrode's shedding status flag as abnormal and encapsulates a data packet containing the electrode number (1-16), status flag, and timestamp and uploads it to the host computer in real time. If the characteristic parameters are all within the threshold range (for example, the sum of variances is ≤200 and the number of channels with a correlation coefficient <0.6 is ≤5), the shedding status is set to normal.

[0102] In the above steps, by judging whether the electrode status characteristic parameters are within the threshold range, the electrode detachment status is accurately identified and reported in real time, so that the host computer can perform corresponding electrode adjustment operations according to the reported results.

[0103] In some embodiments, calculating the electrode contact impedance for each electrode based on the channel data and the electrode detachment status includes:

[0104] When the electrode detachment state is normal, the electrode contact impedance is calculated for each electrode based on the voltage modulus corresponding to the channel data.

[0105] Specifically, for electrodes in a normal electrode detachment state, the voltage modulus output by the orthogonal demodulation module and the known constant excitation current are used to calculate the electrode contact impedance using the four-electrode contact impedance measurement method. Assuming that the electrodes are arranged in a ring, with 1, 2, 3, 4...16 electrodes, the current excitation is injected through the outer electrode, and the inner electrode is switched to measure the voltage. The contact impedance is derived from the total impedance of the two measurements. The core is to eliminate tissue impedance and simplify the calculation by assuming that the contact impedances of adjacent / symmetrical electrodes are approximately equal. The steps for calculating electrode contact impedance using the four-electrode contact impedance measurement method are as follows:

[0106] Step 1: Set up electrodes and excitation mode.

[0107] First, the functions of the four electrodes A, B, C, and D are clearly defined. A and B, or A and D, will serve as current injection electrodes, while B and C will be fixed as voltage measurement electrodes. Furthermore, a constant current source is configured to ensure that the current I injected into the tissue remains stable in amplitude and frequency, providing a reliable excitation signal foundation for subsequent measurements and calculations.

[0108] Step 2: Collect voltage data by scenario.

[0109] Make the first set of measurements (V AB_BC ), A and B are used as current injection electrodes to inject current I into the tissue, and the voltage between them is measured through electrodes B and C. The measured value V AB_BCWill include the B electrode contact impedance Z B The voltage generated, V AB_BC ≈Z B ×I+V BC , where V BC is the actual voltage between electrodes B and C.

[0110] Then the second set of measurements (V AD_BC ), switch the current injection electrodes to A and D, keep the injection current I unchanged, and still measure the voltage through the B and C electrodes. Since the B electrode is not used as a current injection electrode at this time, its contact impedance has a great influence on the measured value V AD_BC The influence of V AD_BC ≈V BC .

[0111] Step 3: Calculate the electrode contact impedance.

[0112] After obtaining two sets of measurement data, according to the formula Z B =(V AB_BC -V AD_BC ) / I, the contact impedance Z of electrode B can be calculated B .

[0113] In the above steps, by adopting the four-electrode contact impedance measurement method, when the electrode detachment state is normal, the orthogonal demodulated voltage modulus and the constant excitation current are used to accurately calculate the contact impedance, providing data support for the refined evaluation of the electrode contact state.

[0114] In some embodiments, obtaining the electrode contact state based on the electrode contact impedance and uploading the electrode contact state to the host computer includes:

[0115] When the electrode contact impedance is not within a preset impedance range, the electrode contact state is set to abnormal, and the electrode contact state is uploaded to the host computer;

[0116] When the electrode contact impedance is within a preset impedance range, the electrode contact state is set to normal.

[0117] Specifically, for electrodes that have not fallen off, the contact impedance is calculated using the four-electrode method and compared to a preset impedance threshold range (e.g., the normal range is 1kΩ-50kΩ). If the impedance value exceeds 50kΩ (e.g., 55kΩ) or is less than 1kΩ (e.g., 0.8kΩ), the contact impedance is determined to be outside the threshold range. In this case, the contact status flag of the electrode is set to abnormal, and a data packet containing the electrode number (1-16), status flag, and timestamp is encapsulated and sent to the host computer.

[0118] In the above steps, by judging whether the electrode state characteristic parameters are within the threshold range, the electrode contact state is accurately identified and reported in real time, so that the host computer can perform corresponding electrode adjustment operations according to the reported results.

[0119] Figure 3 FIG. 1 is a structural block diagram of an electrical impedance imaging data processing device according to an embodiment of the present application. Figure 3 As shown, the device includes:

[0120] A channel data acquisition module 31 is used to acquire multiple channel data of multiple electrodes in the measurement area;

[0121] A characteristic parameter calculation module 32 is used to obtain electrode state characteristic parameters for each electrode based on the channel data;

[0122] The normal state uploading module 33 is used to upload the channel data to the host computer by polling channel by channel at intervals of N frames when the electrode state characteristic parameters of the plurality of electrodes are all within the characteristic threshold range; N is a positive integer;

[0123] an abnormal channel identification module 34, configured to determine an abnormal channel among all channels corresponding to the plurality of electrodes based on electrode state characteristic parameters of the plurality of electrodes;

[0124] The abnormal status uploading module 35 is used to determine the data to be uploaded based on the channel data of the abnormal channel, and upload the data to be uploaded to the host computer at the same time at an interval of M frames; for all channels except the abnormal channel, the channel data of the other channels are polled channel by channel at an interval of N frames and uploaded to the host computer; M is a positive integer, and M is less than N.

[0125] It should be noted that the above modules can be functional modules or program modules, and can be implemented through software or hardware. For modules implemented through hardware, the above modules can be located in the same processor; or the above modules can be located in different processors in any combination.

[0126] Figure 4 The electrical impedance tomography system framework according to an embodiment of the present application includes:

[0127] The host computer 401 is used as the control and data exchange core of the system. The host computer sends instructions downward to configure the FPGA firmware and the operating parameters of the entire measurement system. At the same time, it receives data such as electrode contact impedance and signal characteristics sent back after processing by the FPGA firmware, thereby realizing monitoring of the measurement process, data display and analysis.

[0128] Configuration command 402 is used to receive host computer instructions, generate precise configuration commands, issue signal frequency, amplitude and other parameter settings to the direct digital frequency synthesizer (DDS), send output current specification instructions to the constant current source, and transmit electrode selection control information to the excitation selection switch, providing logical control for the generation and application of excitation signals.

[0129] The direct digital frequency synthesizer 403 is used to synthesize a digital signal of specific frequency, phase, and amplitude according to the configuration command of the FPGA firmware, which serves as the input reference of the constant current source, provides a precise signal source for the subsequent generation of stable excitation current, and ensures that the frequency characteristics of the excitation signal meet the measurement requirements.

[0130] Constant current source 404 receives the output signal from the direct digital synthesizer (DDS) and converts it into a constant current. Through an internal feedback regulation mechanism, it maintains the stability and accuracy of the output current and outputs a current suitable for electrode excitation to the excitation selector switch, establishing a current loop between the electrode and the human body load.

[0131] The excitation selection switch 405 is used to switch the internal path and select the corresponding electrode according to the configuration command of the FPGA firmware, accurately apply the excitation current output by the constant current source to the target electrode, realize time-sharing excitation of multiple electrodes, and adapt the system's requirements for contact impedance measurement of different electrodes.

[0132] The human body load 406 is used as a component of the current loop. When the excitation current is injected through the electrodes, the human body load generates a voltage response due to its own physiological characteristics (such as resistance and capacitance distribution) and the electrode contact state. The voltage signal contains the information required for measurement, such as the electrode contact impedance.

[0133] The filter amplifier 407 is used to process the weak voltage signal collected by the electrode. The filter circuit filters out noise interference such as power frequency and environmental electromagnetic interference. The amplifier circuit increases the amplitude of the useful signal to an appropriate range, providing a clear and recognizable voltage signal for analog-to-digital converter (AD) conversion.

[0134] Analog-to-digital converter 408 converts the filtered and amplified analog voltage signal into a digital signal. Leveraging its multi-channel parallel conversion capabilities, it simultaneously collects signals from 1 to 16 electrodes, discretizing the continuous analog value into a digital value, providing basic data for the FPGA firmware's digital signal processing.

[0135] The 20-frame buffer 409 receives the digital signal converted by the analog-to-digital converter (AD) and buffers it in units of 20 frames. It temporarily stores and organizes multi-channel data, providing continuous and regular data input for subsequent algorithm modules such as signal variance calculation and correlation calculation.

[0136] The 20 frames of voltage signals 410 are used to convert the 20 frames of raw data into 20 frames of voltage data, which serve as the core input for signal variance and calculation, electrode contact impedance calculation, and other steps.

[0137] Signal variance sum calculation 411 is used to calculate the signal variance sum based on 20 frames of voltage signal data. By analyzing the variance sum, the voltage signal fluctuation and stability are evaluated, which helps determine signal quality and provides a basis for subsequent algorithm adjustments and data reliability assessment.

[0138] Electrode contact impedance calculation 412 is used to combine the excitation current parameters (obtained by the constant current source configuration) with the preprocessed voltage signal, apply the four-electrode method algorithm, eliminate tissue impedance interference, and accurately derive the contact impedance value between the electrode and the human body load.

[0139] Raw signal correlation calculation 413 is used to extract raw channel data from the 20-frame buffer and analyze the correlation between the channel data and the standard sine wave. This evaluates the voltage signal fluctuation and stability, assists in determining signal quality, and provides a basis for subsequent algorithm adjustments and data reliability assessments.

[0140] Upload waveform data for one channel every N frames 414. This selects single-channel waveform data from cached or processed data according to a preset interval strategy, packages it, and uploads it to the host computer. While ensuring data validity, the upload volume is controlled, allowing the host computer to obtain waveform information from different time periods and channels for in-depth analysis.

[0141] Frame data integration 415 is used to integrate multi-dimensional processed data such as electrode contact impedance, signal variance, and abnormality identification into a single frame format. This packs the scattered data into a unified data frame for efficient analysis and processing by the host computer, ensuring complete and accurate measurement results.

[0142] Figure 5 5 is a structural block diagram of an electrical impedance imaging system according to an embodiment of the present application, which includes a data acquisition module 51 , a data processing and control module 52 and a communication module 53 .

[0143] The data acquisition module 51 includes 16 electrodes evenly distributed along the chest. The electrodes are excited in opposite directions, and adjacent electrodes are measured, with polling performed according to a specific pattern. Each electrode is made of flexible piezoresistive material, with a conductor sewn onto the piezoresistive material. The length of the electrode is 3:1 compared to the length of the elastic connecting band. The electrodes are arranged in a tight arrangement, and when tightened, they can fully sense the forces acting on the electrodes in both directions due to positional changes.

[0144] The data processing and control module 52 is used for data processing and control, performs corresponding data processing on the AD analog-to-digital converted data in the FPGA, receives the AD analog-to-digital converted data, controls the programmable gain amplifier and other filtering circuits, and switches the excitation and measurement of the 16 electrodes.

[0145] Communication module 53 uses high-speed Ethernet cables to achieve real-time data transmission between the FPGA and the host computer, supporting dual-mode communication using the TCP / IP protocol stack and custom data frame structures. Equipped with dual Gigabit Ethernet PHY chips, the module achieves 4Gbps full-duplex transmission with the FPGA via the RGMII interface. Differential signaling technology ensures resistance to electromagnetic interference in medical environments. Data encapsulation utilizes a dynamic framing mechanism, with each frame containing a 128-byte payload and a 16-bit CRC checksum. Hardware acceleration enables protocol stack offloading, keeping transmission latency to under 50μs. The module is equipped with eight priority queues, enabling QoS-tiered transmission of physiological signal data from different electrode groups. Link aggregation functionality enables dynamic bandwidth load balancing. The physical interface utilizes a shielded RJ45 connector, compliant with the IEEE 802.3ab standard, supporting both PoE power and data transmission. A fiber optic media conversion interface is also provided to enable scalable transmission over distances exceeding 100 meters.

[0146] In addition, in conjunction with the electrical impedance imaging data processing method in the above embodiments, embodiments of the present application may provide a storage medium for implementation. The storage medium stores a computer program; when the computer program is executed by a processor, any of the electrical impedance imaging data processing methods in the above embodiments is implemented.

[0147] It should be noted that the user information (including but not limited to user device information, user personal information, etc.) and data (including but not limited to data used for analysis, stored data, displayed data, etc.) involved in this application are all information and data authorized by the user or fully authorized by all parties.

[0148] Those skilled in the art will appreciate that all or part of the processes in the above-mentioned embodiments can be implemented by instructing the relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the above-mentioned embodiments. In particular, any reference to memory, database, or other media used in the embodiments provided in this application can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, optical memory, high-density embedded non-volatile memory, resistive random access memory (ReRAM), magnetic random access memory (MRAM), ferroelectric random access memory (FRAM), phase change memory (PCM), graphene memory, etc. Volatile memory can include random access memory (RAM) or external cache memory, etc. By way of illustration and not limitation, RAM can take various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM). The databases involved in the various embodiments provided herein may include at least one of a relational database and a non-relational database. Non-relational databases may include, but are not limited to, distributed databases based on blockchains. The processors involved in the various embodiments provided herein may be, but are not limited to, general-purpose processors, central processing units (CPUs), graphics processing units (GPUs), digital signal processors (DSPs), programmable logic devices (PLDs), data processing logic devices based on quantum computing, and the like.

[0149] Those skilled in the art should understand that the various technical features of the above-described embodiments can be combined arbitrarily. In order to make the description concise, not all possible combinations of the various technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0150] The above-described embodiments merely represent several implementation methods of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present invention. It should be noted that a person skilled in the art could make various modifications and improvements without departing from the spirit of the present application, all of which fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A method for processing electrical impedance imaging data, characterized in that: include: Acquire multiple channel data of multiple electrodes in the measurement area; For each electrode, obtaining electrode state characteristic parameters based on the channel data; When the electrode state characteristic parameters of the plurality of electrodes are all within the characteristic threshold range, the channel data are uploaded to the host computer by polling channel by channel at intervals of N frames; N is a positive integer; otherwise, determining an abnormal channel among all channels corresponding to the plurality of electrodes based on the electrode state characteristic parameters of the plurality of electrodes; Determine the data to be uploaded according to the channel data of the abnormal channel, and upload the data to be uploaded to the host computer at the same time at an interval of M frames; Among all the channels, except for the abnormal channel, the channel data of the other channels are polled channel by channel at intervals of N frames and uploaded to the host computer; M is a positive integer, and M is less than N.

2. The electrical impedance imaging data processing method according to claim 1, wherein: The determining the data to be uploaded according to the channel data of the abnormal channel includes: Calculate the abnormal waveform correlation coefficient of each abnormal channel for the channel data of the abnormal channel in the current frame and the previous K frames; K is a positive integer; determining a first abnormal channel whose abnormal waveform correlation coefficient is lower than a correlation coefficient threshold, and identifying channel data of the first abnormal channel as the data to be uploaded; A second abnormal channel having an abnormal waveform correlation coefficient higher than a correlation coefficient threshold is determined, and current frame data of the second abnormal channel is marked with an abnormal identifier and notified to the host computer.

3. The electrical impedance imaging data processing method according to claim 1, wherein: The electrode state characteristic parameters are obtained for each electrode based on the channel data, including: For each electrode, performing orthogonal demodulation on multiple frames of channel data to obtain multiple voltage modulus values; The voltage modulus values are summed and variances are calculated to obtain the electrode state characteristic parameters.

4. The electrical impedance imaging data processing method according to claim 1, wherein: The step of obtaining electrode state characteristic parameters for each electrode based on the channel data further includes: For each electrode, multiple channel data are subjected to signal correlation analysis to obtain multiple signal correlation coefficients; Among the multiple signal correlation coefficients, the number of target signals having signal correlation coefficients higher than a signal correlation threshold is screened and counted to obtain the electrode state characteristic parameter.

5. The electrical impedance imaging data processing method according to claim 1, wherein: After obtaining the electrode state characteristic parameters for each electrode based on the channel data, the method further includes: Obtaining an electrode detachment state according to the electrode state characteristic parameters, and uploading the electrode detachment state to a host computer; Based on the channel data and the electrode detachment status, the electrode contact impedance is calculated for each electrode; based on the electrode contact impedance, the electrode contact status is obtained, and the electrode contact status is uploaded to the host computer.

6. The electrical impedance imaging data processing method according to claim 5, characterized in that: The method of obtaining an electrode detachment state according to the electrode state characteristic parameter and uploading the electrode detachment state to a host computer includes: When the electrode state characteristic parameter is not within a preset characteristic parameter threshold range, the electrode detachment state is set as abnormal, and the electrode detachment state is uploaded to the host computer; When the electrode state characteristic parameter is within a preset characteristic parameter threshold range, the electrode detachment state is set to normal.

7. The electrical impedance imaging data processing method according to claim 6, characterized in that: The calculating, for each electrode, the electrode contact impedance based on the channel data and the electrode detachment state includes: When the electrode detachment state is normal, the electrode contact impedance is calculated for each electrode based on the voltage modulus corresponding to the channel data.

8. The electrical impedance imaging data processing method according to claim 7, wherein: The obtaining of the electrode contact state based on the electrode contact impedance and uploading the electrode contact state to the host computer includes: When the electrode contact impedance is not within a preset impedance range, the electrode contact state is set to abnormal, and the electrode contact state is uploaded to the host computer; When the electrode contact impedance is within a preset impedance range, the electrode contact state is set to normal.

9. An electrical impedance imaging data processing device, characterized in that: The device comprises: A channel data acquisition module is used to obtain multiple channel data of multiple electrodes in the measurement area; A characteristic parameter calculation module is used to obtain electrode state characteristic parameters for each electrode based on the channel data; A normal state uploading module is used to upload the channel data to the host computer by polling channel by channel at intervals of N frames when the electrode state characteristic parameters of the plurality of electrodes are all within the characteristic threshold range; N is a positive integer; an abnormal channel identification module, configured to determine an abnormal channel among all channels corresponding to the plurality of electrodes based on electrode state characteristic parameters of the plurality of electrodes; The abnormal state uploading module is used to determine the data to be uploaded based on the channel data of the abnormal channel, and upload the data to be uploaded to the host computer at the same time at an interval of M frames; for all channels except the abnormal channel, the channel data of the other channels are polled channel by channel at an interval of N frames and uploaded to the host computer; M is a positive integer, and M is less than N.

10. A storage medium, characterized in that: The storage medium stores a computer program, wherein the computer program is configured to execute the electrical impedance imaging data processing method according to any one of claims 1 to 8 when running.

Images