An adaptive temperature compensation method and system for brain electrical impedance tomography.

Abstract

This invention discloses an adaptive temperature compensation method and system for a brain electrical impedance tomography (EIT) system. The method involves setting up excitation for the brain EIT system, measuring electrical impedance data, determining a cooling phase, a deep hypothermia phase, and a rewarming phase, and simultaneously acquiring single-channel or multi-channel temperature data using the brain EIT system. The single-channel or multi-channel temperature data is then synchronously processed with the electrical impedance data. An individualized brain EIT temperature compensation model is established, trained using the temperature data from the synchronously processed cooling phase, and a temperature compensation coefficient is calculated. By acquiring multi-point temperature measurement data at the current and reference times, the electrical impedance data is corrected according to the temperature compensation coefficient, and EIT imaging is performed on the temperature-compensated data, thus achieving adaptive temperature compensation for the brain electrical impedance tomography system. This invention utilizes the characteristics of controlled cooling to achieve synchronous acquisition of multi-point temperature measurements and brain EIT, and trains individualized temperature compensation coefficients, effectively compensating for the impact of temperature changes on EIT measurement and imaging.

Description

Technical Field

[0001] This invention belongs to the field of electrical impedance tomography technology, specifically relating to an adaptive temperature compensation method and system for a brain electrical impedance tomography system. Background Technology

[0002] Electrical impedance tomography (EIT) is a non-invasive, radiation-free medical imaging technique with low requirements for the operating environment. It features high temporal resolution and sensitivity to changes in tissue electrical impedance. The working principle of an EIT system is as follows: a safe excitation current is applied to the body surface, the potential difference between two electrodes placed on the body surface is measured, and an image reconstruction algorithm is used to approximately reconstruct a tomographic image of the bioelectrical impedance characteristics within the human body.

[0003] However, the electrical impedance properties of biological tissues are sensitive to temperature. Existing research largely focuses on temperature compensation methods for the dielectric properties of biological tissues. For example, Jaspard et al. found that the temperature coefficient of blood conductivity is approximately 1% / degree. Baumann et al. studied the conductivity of human cerebrospinal fluid, finding it to be approximately 1.79 S / m at 37 degrees Celsius and approximately 1.45 S / m at 25 degrees Celsius, a variation of approximately 1.9% / degree. Foster et al. pointed out that temperature directly affects the activity of conductive ions; within the range of 20–40 degrees Celsius, the temperature coefficient of biological tissue conductivity can be linearly approximated by an empirical model of 2% / degree. In studies on the dielectric properties of bioactive tissues, the "two-electrode" or "four-electrode" method is often used to measure the dielectric properties of tissues under constant volume and temperature conditions. However, in electrical impedance tomography (EIT) systems, the data acquisition methods differ significantly from those used in dielectric property measurements.

[0004] Electrical impedance tomography (EIT) systems typically use a fixed excitation signal frequency and acquire a frame of measurement data by varying the excitation and measuring the potential difference between adjacent electrodes. Then, based on the data from the "current frame" and the "reference frame," the relative change in impedance within the region is reconstructed. The impact of temperature changes on EIT measurement data and imaging algorithms is particularly complex, especially in clinical applications of brain EIT monitoring, where the long monitoring time amplifies the effects of temperature variations. Specifically, in major cardiovascular or neurosurgical procedures, to effectively protect the brain, cardiopulmonary bypass is usually established and the patient's body temperature is lowered to approximately 24 degrees Celsius. This wide range of temperature variations severely interferes with impedance measurements and affects imaging results. Furthermore, due to significant individual differences in subjects' brain size and volume, using empirical linear models from dielectric property studies for compensation can introduce substantial errors and produce significant artifacts in EIT images.

[0005] Currently, there are few institutions conducting clinical research on brain electrical impedance tomography (EIT) both domestically and internationally, and the impact of individual subject temperature variations on EIT has not received sufficient attention. There is also no adaptive temperature compensation algorithm specifically designed for the excitation measurement modes unique to EIT systems. Summary of the Invention

[0006] The technical problem to be solved by the present invention is to provide an adaptive temperature compensation method and system for a brain electrical impedance tomography (EIT) system, which addresses the shortcomings of the prior art and solves the technical problem of temperature perturbation in brain EIT images.

[0007] The present invention adopts the following technical solution:

[0008] An adaptive temperature compensation method for a brain electrical impedance tomography system includes the following steps:

[0009] S1. Set the excitation of the brain EIT system, measure the electrical impedance data, determine the cooling section, deep low temperature section and rewarming section, and use the brain EIT system to synchronously collect single-channel or multi-channel temperature data.

[0010] S2. Synchronize the single-channel or multi-channel temperature data and electrical impedance data obtained in step S1.

[0011] S3. Establish a brain EIT temperature compensation model with individual differences. Use the temperature data of the cooling period after synchronous processing in step S2 to train the brain EIT temperature compensation model and calculate the temperature compensation coefficient.

[0012] S4. By collecting multi-point temperature measurement data at the current time and the reference time, the electrical impedance data obtained in step S1 is corrected according to the temperature compensation coefficient obtained in step S3, and EIT imaging is performed on the temperature-compensated data to realize the adaptive temperature compensation of the brain electrical impedance tomography system.

[0013] Specifically, in step S1, the single-channel / multi-channel temperature data collected at time n is t[n], and the temperature data collected in N frames is t=[t[1],t[2],...,t[N]].

[0014] Specifically, in step S1, the brain EIT uses a counter-excitation and proximity measurement method. Under each excitation, the potential difference between two adjacent electrodes (excluding the excitation electrode) is measured to form impedance measurement data. The impedance data are as follows:

[0015] V[n] = [v1[n],v2[n],...,v 192 [n] T

[0016] Where n is the frame sequence or frame number, v i[n] represents the measurement data of the i-th channel at time n, and T is...

[0017] Specifically, in step S2, multi-channel temperature data is acquired at the rising edge of the frame synchronization signal; and the frequency and data buffer of the brain EIT system are configured, and then 16 switching synchronization signals are generated to achieve synchronous acquisition of brain EIT and temperature.

[0018] Specifically, in step S3, curve fitting is performed on the boundary voltage time series of each channel. Based on the fitting results of each channel, the slope vector A of all channels is obtained, and the normalized fitting slope vector A is calculated. N Based on the normalized fitted slope vector A N The mean value M is used to determine the consistency index u of the temperature difference compensation coefficient, thus completing the temperature compensation of the brain EIT data.

[0019] Furthermore, the normalized fitted slope vector A N for:

[0020]

[0021] in, The impedance measurement data is at time t0.

[0022] Furthermore, the consistency index u of the temperature difference compensation coefficient is:

[0023]

[0024] Where δ is the variance of the normalized fitted slope vector.

[0025] Specifically, in step S4, based on the compensated data V1 * The reconstructed image x at time t1 with time t0 as the background frame is:

[0026]

[0027] Where J is the sensitivity matrix, α is the regularization parameter, R is the regularization moment, and V1 * The data is after compensation, and V0 is the impedance measurement data at the reference time.

[0028] Furthermore, the compensated data V1 * for:

[0029] V1 * =V1-M(T1-T0)V0

[0030] Where M is the mean of the normalized fitted slope vector, V1 is the current impedance measurement data, T1 is the current time, and T0 is the reference time.

[0031] In a second aspect, embodiments of the present invention provide an adaptive temperature compensation system for a brain electrical impedance tomography system, comprising:

[0032] The acquisition module sets the excitation of the brain EIT system, measures the electrical impedance data, determines the cooling stage, deep low temperature stage and rewarming stage, and uses the brain EIT system to synchronously acquire single-channel or multi-channel temperature data.

[0033] The synchronization module synchronizes the single-channel or multi-channel temperature data and electrical impedance data obtained by the acquisition module.

[0034] The signal processing and imaging module establishes a brain EIT temperature compensation model with individual differences. The model is trained using temperature data from the cooling phase after synchronous processing by the synchronization module, and the temperature compensation coefficient is calculated.

[0035] The compensation module collects multi-point temperature measurement data at the current and reference times, corrects the electrical impedance data obtained by the acquisition module based on the temperature compensation coefficient obtained by the signal processing and imaging module, and performs EIT imaging on the temperature-compensated data to achieve adaptive temperature compensation for the brain electrical impedance tomography system.

[0036] Compared with the prior art, the present invention has at least the following beneficial effects:

[0037] This invention discloses an adaptive temperature compensation method for a brain electrical impedance tomography (EIT) system. Utilizing the controlled cooling characteristic, the method collects data through a temperature sensor and an electrical impedance monitoring system, and adaptively calculates the EIT temperature compensation coefficient to effectively suppress artifacts caused by temperature disturbances and achieve imaging monitoring of impedance changes.

[0038] Furthermore, by placing temperature probes on the scalp surface, bilateral cochleas, and deep nasopharynx, approximate temperatures can be achieved, which is non-invasive and inexpensive.

[0039] Furthermore, by employing a counter-excitation mode, the electrical current can be applied more to the deep parts of the brain; by employing a proximity measurement mode, the dynamic range can be effectively adjusted to achieve high-precision brain EIT imaging.

[0040] Furthermore, biological tissue impedance is sensitive to temperature changes. A frame of data from the brain EIT system contains multiple sets of excitation measurements. This system is designed with an EIT excitation switching synchronization pulse. On the rising edge of the pulse, the switching of excitation electrodes and the synchronous acquisition of impedance and temperature data are completed simultaneously. Based on this, the time sensitivity of impedance temperature compensation can be guaranteed.

[0041] Furthermore, considering the characteristics of the EIT system, the measured data and temperature changes exhibit different patterns under different excitation measurement modes. Therefore, it is necessary to perform curve fitting on the boundary voltage time series of each channel. Based on the fitting results of each channel, the slope vector A for all channels is obtained, and then the normalized fitting slope vector A is calculated. N The normalized fitting slope vector represents the ratio of impedance change caused by a unit temperature change under a unit voltage.

[0042] Furthermore, the mean M and variance δ of the normalized fitted slope vector are calculated, and the consistency index u of the temperature coefficient is calculated based on the mean and variance. The consistency index of the temperature coefficient reflects the individualized impedance temperature compensation coefficient of the subject.

[0043] Furthermore, most current cranial EIT systems are temporal differential imaging systems. They calculate EIT images by measuring the relative changes in measurement data between the current frame and the reference frame. Based on the temperature and EIT measurement data at the current moment and the temperature and EIT measurement data at the reference moment, and using a personalized temperature compensation coefficient M, the measurement data at the current moment can be corrected.

[0044] Furthermore, using temperature-compensated data for brain EIT imaging can effectively suppress temperature artifacts, allowing brain EIT images to reflect intracranial impedance changes.

[0045] Furthermore, this system includes a brain EIT acquisition and control system, EIT electrodes, and a head multi-point temperature measurement system, which can be connected to head multi-point temperature sensing probes, extracorporeal circulation temperature control data, etc., to achieve synchronous acquisition of temperature and impedance data and temperature compensation.

[0046] It is understandable that the beneficial effects of the second aspect mentioned above can be found in the relevant descriptions in the first aspect mentioned above, and will not be repeated here.

[0047] In summary, this invention utilizes the characteristics of controlled cooling to achieve simultaneous acquisition of multi-point temperature measurement and brain EIT, and trains to obtain individualized temperature compensation coefficients, effectively compensating for the impact of temperature changes on EIT measurement and imaging.

[0048] The technical solution of the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. Attached Figure Description

[0049] Figure 1 Schematic diagram of a 16-electrode electrical impedance tomography system;

[0050] Figure 2 This is a schematic diagram illustrating the synchronization of temperature information and electrical impedance data acquisition.

[0051] Figure 3 This is a schematic diagram showing the linear fitting results between the measurement data from channel 1 and the nasopharyngeal temperature.

[0052] Figure 4 A schematic diagram of the measurement data for each channel;

[0053] Figure 5 This is a schematic diagram of temperature compensation.

[0054] Figure 6 This is a schematic diagram comparing the electrical impedance imaging effects before and after temperature compensation. Detailed Implementation

[0055] 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. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0056] In the description of this invention, it should be understood that the terms "comprising" and "including" indicate the presence of the described features, integrals, steps, operations, elements and / or components, but do not exclude the presence or addition of one or more other features, integrals, steps, operations, elements, components and / or collections thereof.

[0057] It should also be understood that the terms used in the present specification are only for the purpose of describing particular embodiments and are not intended to limit the present invention. As used in the present specification and the appended claims, the singular forms "a", "an", and "the" are intended to include the plural forms unless the context clearly indicates otherwise.

[0058] It should also be further understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. Additionally, the character " / " in this document generally indicates that the preceding and following objects have an "or" relationship.

[0059] It should be understood that although terms such as first, second, third, etc., may be used in the embodiments of the present invention to describe the preset range, these preset ranges should not be limited to these terms. These terms are only used to distinguish the preset ranges from one another. For example, without departing from the scope of the embodiments of the present invention, the first preset range may also be referred to as the second preset range, and similarly, the second preset range may also be referred to as the first preset range.

[0060] Depending on the context, the word "if" as used here can be interpreted as "when," "when," "in response to determination," or "in response to detection." Similarly, depending on the context, the phrase "if determination" or "if detection (of the stated condition or event)" can be interpreted as "when determination," "in response to determination," "when detection (of the stated condition or event)," or "in response to detection (of the stated condition or event)."

[0061] The accompanying drawings illustrate various structural schematic diagrams according to embodiments disclosed in this invention. These drawings are not to scale, and some details have been enlarged for clarity, and some details may have been omitted. The shapes of the various regions and layers shown in the drawings, as well as their relative sizes and positional relationships, are merely exemplary and may deviate from reality due to manufacturing tolerances or technical limitations. Furthermore, those skilled in the art can design regions / layers with different shapes, sizes, and relative positions as needed.

[0062] This invention provides an adaptive temperature compensation method for brain electrical impedance tomography (EIT) systems. Targeting the unique excitation measurement mode of EIT systems, the method calculates a fitting factor between impedance measurement data and temperature by measuring the temperature within the tomographic imaging region or approximating the temperature distribution within the region. This algorithm extracts a temperature compensation coefficient with individual differences, effectively compensating for temperature disturbances in the impedance measurement data. Correcting the EIT algorithm based on this factor effectively suppresses artifacts caused by temperature disturbances.

[0063] This invention discloses an adaptive temperature compensation method for a brain electrical impedance tomography system, comprising the following steps:

[0064] S1. Set the excitation of the brain EIT system, measure the impedance data, and use the brain EIT system to synchronously collect single-channel or multi-channel temperature data.

[0065] S101. Collect intracranial temperature;

[0066] Figure 1 In the diagram, 101 represents the electrode band of the brain EIT system, and 102 represents one electrode within that band. The EIT system typically consists of 8, 16, or 32 electrodes. The diagram shows the typical positions of 16 electrodes in a brain EIT system: electrode 1 is located 2 cm above the left ear, electrode 5 is located on the frontal vertex, electrode 9 is located 2 cm above the right ear, and electrode 13 is located at the back of the head. The electrode bands are usually located on the same cross-section and are evenly spaced.

[0067] 103 is the cable connecting the EIT electrode strip to the EIT system; through this cable, the EIT system generates a pair of excitation signals and applies them to the scalp surface, while simultaneously measuring the potential difference between each pair of the remaining electrodes.

[0068] 104 is a temperature sensor. To achieve non-invasive temperature monitoring of the head, the temperature sensor is usually placed in the following locations: nasopharynx, cochlea, and scalp surface.

[0069] 107 is the temperature resistance coefficient modeling algorithm module, 108 is the brain EIT temperature real-time compensation algorithm module, and 109 is the brain EIT imaging temperature perturbation correction module.

[0070] Real-time distribution of intracranial temperature is usually not available. In order to effectively measure or approximate intracranial temperature, this invention proposes to synchronously acquire single or multi-channel temperature data with a brain electrical impedance tomography (BIT) system.

[0071] Typically, nasopharyngeal temperature probes are used to collect and approximate intracranial temperature data in real time.

[0072] Preferably, multi-channel temperature data are collected using a nasopharyngeal temperature probe and bilateral cochlear temperature probes to reconstruct intracranial temperature distribution;

[0073] Preferably, the temperature change near the electrode is measured using a scalp surface temperature sensor;

[0074] Preferably, intracranial and blood temperatures are collected using nasopharyngeal and perfusion temperature probes, respectively.

[0075] Let the temperature data be t[n], representing the single-channel / multi-channel temperature information collected at time n. The temperature data collected in N frames is written as t = [t[1], t[2], ..., t[N]].

[0076] S102, Brain electrical impedance tomography stimulation and measurement

[0077] Brain electrical impedance tomography (BIT) systems typically consist of 8, 16, or 32 electrodes.

[0078] Please see Figure 1 It is a 16-electrode electrical impedance tomography system, which typically uses a counter-excitation and proximity measurement method in brain EIT.

[0079] In brain EIT, the reciprocal stimulation and proximity measurement method is typically used. A complete frame of brain EIT measurement has 192 measurement channels, denoted by V[n], as follows:

[0080] V[n] = [v1[n],v2[n],...,v 192 [n] T

[0081] Where n represents the frame sequence or frame number, and lowercase v i[n] represents the measurement data of the i-th channel at time n. Expanding the N-frame impedance measurement matrix, the N-frame impedance measurement matrix is ​​expressed as:

[0082] V = [V[1],V[2],V[3],…,V[N]]

[0083] The measurement matrix V has a dimension of 192×N, and the measurement sequence for each channel is defined as follows:

[0084] v i =[v i [1],v i [1],…,v i [N]

[0085] S2. Synchronize the temperature information obtained in step S1 with the electrical impedance data;

[0086] Please see Figure 2 The temperature information is synchronized with the impedance acquisition data, as follows:

[0087] 201 is the frame synchronization signal, 202 is the rising edge of the frame synchronization, 203 is the switching synchronization signal, 204 is the rising edge of the switching synchronization signal, and 205 represents the number of switching pulses within a frame.

[0088] In a typical 16-electrode brain EIT system, the number of intra-frame switching pulses is generally equal to the number of electrodes.

[0089] At the rising edge of the frame synchronization signal, multi-channel temperature data is acquired; and the frequency and data buffer of the brain EIT are configured. Subsequently, 16 switching synchronization signals are generated. At the rising edge of each switching synchronization pulse, the brain EIT system is configured with a pair of excitation electrodes.

[0090] Taking a typical 16-electrode system as an example, the excitation electrode pairs for each switch are: [1,9], [2,10], [3,11], [4,12], [5,13], [6,14], [7,15], [8,16], [9,1], [10,2], [11,3], [12,4], [13,5], [14,6], [15,7], [16,8].

[0091] S3. Establish a brain EIT temperature compensation model with individual differences. Use the data of the controlled cooling segment obtained in step S2 to train the brain EIT temperature compensation model and calculate the temperature compensation coefficient.

[0092] Select a cooling range where the temperature changes slowly and linearly with time.

[0093] Curve fitting is performed on the boundary voltage time series of each channel. The result of the curve fitting is a first-order polynomial, and the fitting formula is v.i [n] = a i t[n]+b i Where t[n] is the temperature at time n, and the fitting slope of the channel data is a. i The fitted cut point is b i .

[0094] The slope vectors for all 192 channels can be obtained from the fitting results of each channel.

[0095] A = [a1, a2, ..., a 192 ]

[0096] Calculate the normalized fitted slope vector:

[0097]

[0098] Calculate the normalized slope A N The mean M = mean(A) N ) and variance δ=std(A N The mean M of the normalized slope is used for temperature compensation of brain EIT data.

[0099] S4. Based on the temperature compensation coefficient obtained in step S3, correct the data to compensate for imaging, and realize the adaptive temperature compensation of the brain electrical impedance tomography system.

[0100] Based on the linear model, the temperature compensation method for electrical impedance measurement data is as follows:

[0101] V1 * =V1-M(T1-T0)V0

[0102] Based on the compensated data V1 * The reconstructed image at time t1 with time t0 as the background frame is:

[0103]

[0104] Where J is the sensitivity matrix, α is the regularization parameter, and R is the regularization matrix, typically taken as R = diag(J). T J).

[0105] Calculate the consistency index of temperature difference compensation coefficient The consistency index u is used to evaluate the consistency of the effect of temperature on the measured voltage; the smaller the u, the better the consistency.

[0106] In another embodiment of the present invention, an adaptive temperature compensation system for a brain electrical impedance tomography (EIT) system is provided. This system can be used to implement the adaptive temperature compensation method of the aforementioned EIT system. Specifically, the adaptive temperature compensation system for the EIT system comprises an electrical impedance tomography (EIT) acquisition module, a multi-channel temperature acquisition module, a signal processing and imaging module, and a compensation module. A typical application of the present invention is intraoperative dynamic monitoring of brain electrical impedance.

[0107] The acquisition module sets the excitation of the brain EIT system, measures the electrical impedance data, determines the cooling section, the deep low temperature section and the rewarming section, and uses the brain EIT system to synchronously acquire single-channel or multi-channel temperature data.

[0108] The synchronization module synchronizes the single-channel or multi-channel temperature data and electrical impedance data obtained by the acquisition module.

[0109] The signal processing and imaging module establishes a brain EIT temperature compensation model with individual differences. The model is trained using temperature data from the cooling phase after synchronous processing by the synchronization module, and the temperature compensation coefficient is calculated.

[0110] The compensation module collects multi-point temperature measurement data at the current and reference times, corrects the electrical impedance data obtained by the acquisition module based on the temperature compensation coefficient obtained by the signal processing and imaging module, and performs EIT imaging on the temperature-compensated data to achieve adaptive temperature compensation for the brain electrical impedance tomography system.

[0111] 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 merely 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.

[0112] In this embodiment, nasopharyngeal temperature and electrical impedance tomography (EIT) data are acquired simultaneously. Inserting a nasopharyngeal temperature probe into the subject is a simple and non-invasive method of temperature measurement. In major cardiovascular surgeries, nasopharyngeal temperature is often used to represent the average temperature of brain tissue to control the cooling rate of extracorporeal circulation.

[0113] In this implementation example, the brain electrical impedance tomography system employs a counter-excitation, proximity measurement mode with a total of 16 electrodes. The effective measurement channels per frame are 192.

[0114] First, we analyzed the relationship between the voltage data of each measurement channel of the electrical impedance tomography system and the changes in nasopharyngeal temperature.

[0115] Please see Figure 3 The linear fit between the channel 1 measurement data and the nasopharyngeal temperature is a1 = -0.2623. The fitting result for the temperature coefficient of this channel is the fitted R-squared value R. 2 =0.9869. The R-squared value approaches 1, indicating that the measurement boundary voltage of each channel is linearly related to the temperature.

[0116] Please see Figure 4 For each frame, calculate the linear fitting slope vector A = [a1, a2, ..., a] channel by channel. 192 ]. Figure 4 The dashed line represents the fitting slope between the measurement data for each channel and the nasopharyngeal temperature. It is evident that for electrical impedance tomography (EIT) systems, temperature exhibits a different fitting slope for each channel's measurement data, and the slope of voltage variation with temperature for each channel is also influenced by the measurement location. Figure 4 The solid line represents the measurement data for each channel at the reference time, showing that the fitting coefficient is proportional to the measured voltage value at the reference time.

[0117] First, based on the characteristics of linear variation and the correlation between the fitting slope of each channel and the measurement data at the initial time of the channel, the normalized fitting slope vector is calculated. Subsequently, the normalized slope A is calculated. N The mean M = mean(A) N ) and variance δ=std(A N In this implementation case, M = -0.0183 and δ = 0.00249. The value of M is the personalized temperature compensation factor for this implementation case. Finally, the consistency index of the temperature difference compensation coefficient is calculated.

[0118] Please see Figure 5 Based on adaptive temperature compensation, temperature compensation can be provided during the subsequent monitoring of the patient. Figure 5 The dashed line represents the uncompensated transmission impedance ATI. Figure 5 The solid line represents the transmission impedance (ATI) after adaptive temperature compensation. It is evident that this invention effectively eliminates temperature disturbances while retaining other relatively weak information that can cause impedance changes; based on the temperature compensation coefficient, temperature compensation can be applied to impedance measurement data, effectively compensating for impedance baseline drift caused by temperature variations.

[0119] Please see Figure 6 Because electrical impedance tomography (EIT) is sensitive to disturbances in boundary measurement data, in EIT monitoring applications with temperature variations, if temperature disturbances are not compensated for, the EIT results will be primarily dominated by temperature changes. Since the electrical impedance of biological tissues is easily affected by temperature, even a temperature change of 0.5 to 1°C can cause significant artifacts in the EIT image, affecting the extraction of clinical indicators. Temperature-compensated EIT images, however, can suppress artifacts caused by temperature disturbances, helping to extract significant clinical indicators such as intracranial hemorrhage or ischemia.

[0120] Since electrical impedance tomography (EIT) data represents the potential difference between two electrodes on the body surface, a 16-electrode EIT system using a counter-excitation mode generates 192 measurement data points per frame. Temperature variations can cause significant changes in boundary measurement data, leading to artifacts in the EIT image. An EIT algorithm based on a temperature factor correction can effectively suppress temperature artifacts in EIT images, reflecting even weak ischemic or hemorrhage information in the imaging region.

[0121] In summary, the present invention provides an adaptive temperature compensation method and system for brain electrical impedance tomography (EIT) systems. By utilizing the characteristics of controlled cooling, it achieves simultaneous acquisition of multi-point temperature measurement and brain EIT, and trains to obtain individualized temperature compensation coefficients. Experimental results show that the present invention can effectively compensate for the impact of temperature changes on EIT measurement and imaging, suppress temperature artifacts in EIT images, and make brain EIT images more effective in reflecting impedance changes caused by intracranial lesions.

[0122] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product embodied on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0123] This application is described with reference to flowchart illustrations and / or block diagrams of methods, apparatus (systems), and computer program products according to embodiments of this application. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart... Figure 1 a process or multiple processes and / or boxes Figure 1A device that provides the functions specified in one or more boxes.

[0124] These computer program instructions may also be stored in a computer-readable storage medium that can direct a computer or other programmable data processing device to function in a particular manner, such that the instructions stored in the computer-readable storage medium produce an article of manufacture including instruction means, which are implemented in a process Figure 1 a process or multiple processes and / or boxes Figure 1 The function specified in one or more boxes.

[0125] These computer program instructions may also be loaded onto a computer or other programmable data processing equipment to cause a series of operational steps to be performed on the computer or other programmable equipment to produce a computer-implemented process, thereby providing instructions that execute on the computer or other programmable equipment for implementing the process. Figure 1 a process or multiple processes and / or boxes Figure 1 The steps of the function specified in one or more boxes.

[0126] The above content is only for illustrating the technical concept of the present invention and should not be construed as limiting the scope of protection of the present invention. Any modifications made to the technical solution based on the technical concept proposed in this invention shall fall within the scope of protection of the claims of this invention.

Claims

1. An adaptive temperature compensation method for a brain electrical impedance tomography system, characterized in that, Includes the following steps: S1. Set the excitation of the brain EIT system, measure the electrical impedance data, determine the cooling section, deep low temperature section and rewarming section, and use the brain EIT system to synchronously collect single-channel or multi-channel temperature data. S2. Synchronize the single-channel or multi-channel temperature data and electrical impedance data obtained in step S1. S3. Establish a brain EIT temperature compensation model with individual differences. Use the temperature data of the cooling period after synchronous processing in step S2 to train the brain EIT temperature compensation model and calculate the temperature compensation coefficient. S4. By collecting multi-point temperature measurement data at the current time and the reference time, the electrical impedance data obtained in step S1 is corrected according to the temperature compensation coefficient obtained in step S3, and EIT imaging is performed on the temperature-compensated data to realize the adaptive temperature compensation of the brain electrical impedance tomography system.

2. The adaptive temperature compensation method for the brain electrical impedance tomography system according to claim 1, characterized in that, In step S1, the single-channel / multi-channel temperature data collected at time n is t[n], and the temperature data collected in N frames is t=[t[1],t[2],...,t[N]].

3. The adaptive temperature compensation method for the brain electrical impedance tomography system according to claim 1, characterized in that, In step S1, the brain EIT uses a counter-excitation and proximity measurement method. Under each excitation, the potential difference between two adjacent electrodes (excluding the excitation electrode) is measured to form impedance measurement data. The impedance data are as follows: V[n]=[v1[n],v2[n],...,v 192 [n]] T Where n is the frame sequence or frame number, v i [n] represents the measurement data of the i-th channel at time n, and T is the transpose.

4. The adaptive temperature compensation method for the brain electrical impedance tomography system according to claim 1, characterized in that, In step S2, multi-channel temperature data is acquired at the rising edge of the frame synchronization signal; and the frequency and data buffer of the brain EIT system are configured, and then 16 switching synchronization signals are generated to realize the synchronous acquisition of brain EIT and temperature.

5. The adaptive temperature compensation method for the brain electrical impedance tomography system according to claim 1, characterized in that, In step S3, curve fitting is performed on the boundary voltage time series of each channel. Based on the fitting results of each channel, the slope vector A of all channels is obtained, and the normalized fitting slope vector A is calculated. N Based on the normalized fitted slope vector A N The mean value M is used to determine the consistency index u of the temperature difference compensation coefficient, thus completing the temperature compensation of the brain EIT data.

6. The adaptive temperature compensation method for the brain electrical impedance tomography system according to claim 5, characterized in that, Normalized fitted slope vector A N for: in, The impedance measurement data is at time t0.

7. The adaptive temperature compensation method for the brain electrical impedance tomography system according to claim 5, characterized in that, The consistency index u of the temperature difference compensation coefficient is: Where δ is the variance of the normalized fitted slope vector.

8. The adaptive temperature compensation method for the brain electrical impedance tomography system according to claim 1, characterized in that, In step S4, based on the compensated data V1 * The reconstructed image x at time t1 with time t0 as the background frame is: Where J is the sensitivity matrix, α is the regularization parameter, R is the regularization matrix, and V1 * The data is after compensation, and V0 is the impedance measurement data at the reference time.

9. The adaptive temperature compensation method for the brain electrical impedance tomography system according to claim 8, characterized in that, Compensated data V1 * for: V1 * =V1-M(T1-T0)V0 Where M is the mean of the normalized fitted slope vector, V1 is the current impedance measurement data, T1 is the current time, and T0 is the reference time.

10. An adaptive temperature compensation system for a brain electrical impedance tomography system, characterized in that, include: The acquisition module sets the excitation of the brain EIT system, measures the electrical impedance data, determines the cooling stage, deep low temperature stage and rewarming stage, and uses the brain EIT system to synchronously acquire single-channel or multi-channel temperature data. The synchronization module synchronizes the single-channel or multi-channel temperature data and electrical impedance data obtained by the acquisition module. The signal processing and imaging module establishes a brain EIT temperature compensation model with individual differences. The model is trained using temperature data from the cooling phase after synchronous processing by the synchronization module, and the temperature compensation coefficient is calculated. The compensation module collects multi-point temperature measurement data at the current and reference times, corrects the electrical impedance data obtained by the acquisition module based on the temperature compensation coefficient obtained by the signal processing and imaging module, and performs EIT imaging on the temperature-compensated data to achieve adaptive temperature compensation for the brain electrical impedance tomography system.

Images