Method, device, equipment and medium for selecting excitation parameters for respiratory electrical impedance imaging

Abstract

The embodiments of the present disclosure disclose a method, device, equipment and medium for selecting excitation parameters for respiratory impedance imaging. The method for selecting excitation parameters for respiratory impedance imaging includes: an impedance signal quality acquisition step, in which multiple currents are used for excitation under certain excitation modes to obtain multiple impedance signal qualities under multiple excitation currents; an optimal excitation current selection step, in which multiple impedance signal qualities are compared and the excitation current corresponding to the best impedance signal quality is selected as the optimal excitation current; an impedance imaging effective timing diagram quality acquisition step, in which multiple excitation modes are used under the condition of using the optimal excitation current to obtain multiple impedance imaging effective timing diagram qualities under multiple excitation modes; and an optimal excitation mode selection step, in which multiple impedance imaging effective timing diagram qualities are compared and the excitation mode corresponding to the best impedance imaging effective timing diagram quality is selected as the optimal excitation mode.

Description

Technical Field

[0001] The present disclosure relates to the medical field, and in particular to a method, apparatus, device and medium for selecting excitation parameters for respiratory electrical impedance imaging. Background Art

[0002] Electrical impedance tomography (EIT) is an emerging imaging technology that applies weak electrical currents to the human body through electrodes and simultaneously collects surface voltage, thereby estimating the distribution and changes in the internal electrical impedance of the subject. Due to its portability, low cost, and non-invasive nature, EIT has shown promising application prospects in bedside dynamic monitoring. Currently, its most widely used application is real-time monitoring of pulmonary ventilation.

[0003] Obtaining high-quality human respiratory electrical impedance imaging (EI) signals is a primary prerequisite for the application of chest EIT. The excitation parameters for EI, including the excitation current and excitation method, are crucial for determining the quality of chest EI signals. Due to the varying application environments, such as those in the laboratory and clinical setting, the environmental impact on EI signal quality varies. The human body's internal environment is complex and not a fixed resistance. As the internal and external environments change, the impedance of each organ continuously fluctuates. Sometimes, signal quality is better with high currents, sometimes with lower currents; sometimes, signal quality is better with opposite excitation, sometimes with adjacent excitation. Therefore, selecting the optimal excitation current and excitation method is crucial. Therefore, analyzing the EI excitation parameters that achieve optimal signal quality, tailored to the specific environment, is crucial for the practical application of chest EIT. Summary of the Invention

[0004] In order to solve the problems in the related art, the embodiments of the present disclosure provide a method, apparatus, device and medium for selecting excitation parameters for respiratory electrical impedance imaging.

[0005] In a first aspect, an embodiment of the present disclosure provides a method for selecting excitation parameters for respiratory electrical impedance imaging, characterized by comprising:

[0006] an electrical impedance signal quality acquisition step, using multiple currents to perform excitation under a certain excitation mode, and acquiring multiple electrical impedance signal qualities under the multiple excitation currents;

[0007] an optimal excitation current selection step of comparing the multiple electrical impedance signal qualities and selecting the excitation current corresponding to the best electrical impedance signal quality as the optimal excitation current;

[0008] The step of obtaining the quality of the effective timing diagram of electrical impedance imaging is as follows: using a plurality of excitation modes under the condition of using the optimal excitation current, and obtaining the quality of the effective timing diagram of the electrical impedance imaging under the plurality of excitation modes;

[0009] The optimal excitation mode selection step compares the qualities of the multiple electrical impedance imaging effective timing diagrams and selects the excitation mode corresponding to the best electrical impedance imaging effective timing diagram quality as the optimal excitation mode.

[0010] According to an embodiment of the present disclosure, in a first implementation of the first aspect of the present disclosure,

[0011] The certain excitation method includes: any one of opposite excitation and adjacent excitation.

[0012] According to an embodiment of the present disclosure, in a second implementation of the first aspect of the present disclosure,

[0013] The electrical impedance signal quality acquisition step comprises:

[0014] Under a certain excitation mode, multiple currents are used for excitation, and a boundary voltage signal under each excitation current is obtained;

[0015] Calculating a normalized boundary voltage signal based on the boundary voltage signal;

[0016] Calculating a heart rate from the normalized boundary voltage signal, and filtering out a heartbeat signal from the normalized boundary voltage signal based on the heart rate to obtain a boundary voltage signal after the heartbeat is filtered out;

[0017] Extracting a respiratory voltage signal and an interference voltage signal from the boundary voltage signal after filtering out the heartbeat;

[0018] The electrical impedance signal quality is calculated based on the respiration voltage signal and the interference voltage signal.

[0019] According to an embodiment of the present disclosure, in a third implementation of the first aspect of the present disclosure,

[0020] The calculating a normalized boundary voltage signal based on the boundary voltage signal includes:

[0021] A normalized boundary voltage signal is calculated based on the maximum value of the boundary voltage signal.

[0022] According to an embodiment of the present disclosure, in a fourth implementation of the first aspect of the present disclosure,

[0023] Calculating the heart rate based on the normalized boundary voltage signal includes:

[0024] Calculating the spectrum of the normalized boundary voltage signal, calculating the heart rate based on the maximum value of the spectrum, and / or

[0025] The filtering out the heartbeat signal in the normalized boundary voltage signal based on the heart rate to obtain the boundary voltage signal after the heartbeat is filtered out includes:

[0026] Based on the heart rate, a band-stop filter is used to filter out the heartbeat signal in the normalized boundary voltage signal to obtain a boundary voltage signal after the heartbeat is filtered out.

[0027] According to an embodiment of the present disclosure, in a fifth implementation of the first aspect of the present disclosure,

[0028] The step of extracting the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after the heartbeat is filtered out comprises:

[0029] A low-pass filter is used to extract the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after the heartbeat is filtered out.

[0030] According to an embodiment of the present disclosure, in a sixth implementation of the first aspect of the present disclosure,

[0031] The boundary voltage signal, the normalized boundary voltage signal, the boundary voltage signal after heartbeat filtering, the respiratory voltage signal and the interference voltage signal are in matrix form.

[0032] According to an embodiment of the present disclosure, in a seventh implementation of the first aspect of the present disclosure,

[0033] The step of obtaining the quality of the effective timing diagram of electrical impedance imaging comprises:

[0034] Under the condition of using the optimal excitation current, use either opposite excitation or adjacent excitation to obtain the boundary voltage signal under the excitation mode;

[0035] Calculating respiratory electrical impedance imaging time-series image signals according to the boundary voltage signal under the excitation mode;

[0036] Calculating a normalized effective time-series image signal of respiratory electrical impedance imaging according to the time-series image signal of respiratory electrical impedance imaging;

[0037] The effective time sequence image quality of the electrical impedance imaging under the excitation mode is calculated according to the normalized effective time sequence image signal of the respiratory electrical impedance imaging.

[0038] According to an embodiment of the present disclosure, in an eighth implementation of the first aspect of the present disclosure,

[0039] Calculating the respiratory electrical impedance imaging time-series image signal according to the boundary voltage signal under the excitation mode includes:

[0040] According to the boundary voltage signal under the excitation mode, a reconstruction algorithm is used to calculate the respiratory electrical impedance imaging time series image signal.

[0041] According to an embodiment of the present disclosure, in a ninth implementation of the first aspect of the present disclosure,

[0042] Calculating the effective time-series image signal of respiratory electrical impedance imaging according to the time-series image signal of respiratory electrical impedance imaging comprises:

[0043] Calculating the root mean square value of each pixel point of the respiratory electrical impedance imaging time series image signal at the sampling moment;

[0044] Calculate the normalized value of the root mean square value to obtain the effective time series image signal of the respiratory electrical impedance imaging.

[0045] According to an embodiment of the present disclosure, in a tenth implementation of the first aspect of the present disclosure,

[0046] Calculating the effective timing image quality of the electrical impedance imaging under the excitation mode according to the effective timing image signal of the electrical impedance imaging comprises:

[0047] Calculating lung ventilation and non-ventilation areas according to the effective time-series image signals of the respiratory electrical impedance imaging;

[0048] The effective timing diagram quality of electrical impedance imaging under the excitation mode is calculated according to the lung ventilation area and the non-ventilation area.

[0049] In a second aspect, an embodiment of the present disclosure provides a device for selecting excitation parameters for respiratory electrical impedance imaging, characterized by comprising:

[0050] An electrical impedance signal quality acquisition module, configured to use a plurality of currents to perform excitation under a certain excitation mode and acquire a plurality of electrical impedance signal qualities under the plurality of excitation currents;

[0051] an optimal excitation current selection module, configured to compare the qualities of the plurality of electrical impedance signals and select an excitation current corresponding to the best electrical impedance signal quality as the optimal excitation current;

[0052] An electrical impedance imaging effective timing diagram quality acquisition module is used to obtain the qualities of various electrical impedance imaging effective timing diagrams under the conditions of using an optimal excitation current and using a plurality of excitation modes;

[0053] The optimal excitation mode selection module is used to compare the qualities of the multiple electrical impedance imaging effective timing diagrams and select the excitation mode corresponding to the best electrical impedance imaging effective timing diagram quality as the optimal excitation mode.

[0054] According to an embodiment of the present disclosure, in a first implementation of the second aspect of the present disclosure,

[0055] The certain excitation method includes: any one of opposite excitation and adjacent excitation.

[0056] According to an embodiment of the present disclosure, in a second implementation of the second aspect of the present disclosure,

[0057] The electrical impedance signal quality acquisition module is used for:

[0058] Under a certain excitation mode, multiple currents are used for excitation, and a boundary voltage signal under each excitation current is obtained;

[0059] Calculating a normalized boundary voltage signal based on the boundary voltage signal;

[0060] Calculating a heart rate from the normalized boundary voltage signal, and filtering out a heartbeat signal from the normalized boundary voltage signal based on the heart rate to obtain a boundary voltage signal after the heartbeat is filtered out;

[0061] Extracting a respiratory voltage signal and an interference voltage signal from the boundary voltage signal after filtering out the heartbeat;

[0062] The electrical impedance signal quality is calculated based on the respiration voltage signal and the interference voltage signal.

[0063] According to an embodiment of the present disclosure, in a third implementation of the second aspect of the present disclosure,

[0064] The calculating a normalized boundary voltage signal based on the boundary voltage signal includes:

[0065] A normalized boundary voltage signal is calculated based on the maximum value of the boundary voltage signal.

[0066] According to an embodiment of the present disclosure, in a fourth implementation of the second aspect of the present disclosure,

[0067] Calculating the heart rate based on the normalized boundary voltage signal includes:

[0068] Calculating the spectrum of the normalized boundary voltage signal, calculating the heart rate based on the maximum value of the spectrum, and / or

[0069] The filtering out the heartbeat signal in the normalized boundary voltage signal based on the heart rate to obtain the boundary voltage signal after the heartbeat is filtered out includes:

[0070] Based on the heart rate, a band-stop filter is used to filter out the heartbeat signal in the normalized boundary voltage signal to obtain a boundary voltage signal after the heartbeat is filtered out.

[0071] According to an embodiment of the present disclosure, in a fifth implementation of the second aspect of the present disclosure,

[0072] The step of extracting the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after the heartbeat is filtered out comprises:

[0073] A low-pass filter is used to extract the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after the heartbeat is filtered out.

[0074] According to an embodiment of the present disclosure, in a sixth implementation of the second aspect of the present disclosure,

[0075] The boundary voltage signal, the normalized boundary voltage signal, the boundary voltage signal after heartbeat filtering, the respiratory voltage signal and the interference voltage signal are in matrix form.

[0076] According to an embodiment of the present disclosure, in a seventh implementation of the second aspect of the present disclosure,

[0077] The electrical impedance imaging effective timing diagram quality acquisition module is used for:

[0078] Under the condition of using the optimal excitation current, use either opposite excitation or adjacent excitation to obtain the boundary voltage signal under the excitation mode;

[0079] Calculating respiratory electrical impedance imaging time-series image signals according to the boundary voltage signal under the excitation mode;

[0080] Calculating a normalized effective time-series image signal of respiratory electrical impedance imaging according to the time-series image signal of respiratory electrical impedance imaging;

[0081] The effective time sequence image quality of the electrical impedance imaging under the excitation mode is calculated according to the normalized effective time sequence image signal of the respiratory electrical impedance imaging.

[0082] According to an embodiment of the present disclosure, in an eighth implementation of the second aspect of the present disclosure,

[0083] Calculating the respiratory electrical impedance imaging time-series image signal according to the boundary voltage signal under the excitation mode includes:

[0084] According to the boundary voltage signal under the excitation mode, a reconstruction algorithm is used to calculate the respiratory electrical impedance imaging time series image signal.

[0085] According to an embodiment of the present disclosure, in a ninth implementation of the second aspect of the present disclosure,

[0086] Calculating the effective time-series image signal of respiratory electrical impedance imaging according to the time-series image signal of respiratory electrical impedance imaging comprises:

[0087] Calculating the root mean square value of each pixel point of the respiratory electrical impedance imaging time series image signal at the sampling moment;

[0088] Calculate the normalized value of the root mean square value to obtain the effective time series image signal of the respiratory electrical impedance imaging.

[0089] According to an embodiment of the present disclosure, in a tenth implementation of the second aspect of the present disclosure,

[0090] Calculating the effective timing image quality of the electrical impedance imaging under the excitation mode according to the effective timing image signal of the electrical impedance imaging comprises:

[0091] Calculating lung ventilation and non-ventilation areas according to the effective time-series image signals of the respiratory electrical impedance imaging;

[0092] The effective timing diagram quality of electrical impedance imaging under the excitation mode is calculated according to the lung ventilation area and the non-ventilation area.

[0093] In a third aspect, an embodiment of the present disclosure provides an electronic device comprising a memory and a processor, wherein the memory is used to store one or more computer instructions, and wherein the one or more computer instructions are executed by the processor to implement a method as described in any one of the first aspect, the first implementation manner of the first aspect to the tenth implementation manner of the first aspect.

[0094] In a fourth aspect, an embodiment of the present disclosure provides a computer-readable storage medium on which computer instructions are stored. When the computer instructions are executed by a processor, the methods described in the first aspect and the first implementation method of the first aspect to the tenth implementation method of the first aspect are implemented.

[0095] The technical solutions provided by the embodiments of the present disclosure may have the following beneficial effects:

[0096] According to the technical solution provided by the embodiment of the present disclosure, through the impedance signal quality acquisition step, under a certain excitation mode, multiple excitation currents are used to obtain multiple impedance signal qualities under multiple excitation currents; the optimal excitation current selection step compares multiple impedance signal qualities and selects the excitation current corresponding to the best impedance signal quality as the optimal excitation current; the impedance imaging effective timing diagram quality acquisition step uses multiple excitation modes under the condition of using the optimal excitation current to obtain multiple impedance imaging effective timing diagram qualities under multiple excitation modes; the optimal excitation mode selection step compares multiple impedance imaging effective timing diagram qualities and selects the excitation mode corresponding to the best impedance imaging effective timing diagram quality as the optimal excitation mode, thereby determining the optimal excitation parameters including the optimal excitation current and the optimal excitation mode, thereby improving the quality of respiratory impedance imaging.

[0097] It is to be understood that the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure. BRIEF DESCRIPTION OF THE DRAWINGS

[0098] Other features, objects and advantages of the present disclosure will become more apparent through the following detailed description of non-limiting embodiments in conjunction with the accompanying drawings. In the accompanying drawings:

[0099] Figure 1a An exemplary schematic diagram illustrating filtering out a heartbeat signal from a normalized boundary voltage signal according to an embodiment of the present disclosure is shown.

[0100] Figure 1b An exemplary schematic diagram of obtaining a respiratory voltage signal according to an embodiment of the present disclosure is shown.

[0101] Figure 1c An exemplary schematic diagram showing a time-series image signal of respiratory electrical impedance imaging according to an embodiment of the present disclosure is shown.

[0102] Figure 1d An exemplary schematic diagram showing normalized effective time-series image signals of respiratory electrical impedance imaging according to an embodiment of the present disclosure is shown.

[0103] Figure 1e An exemplary schematic diagram showing lung ventilation areas and non-ventilation areas according to an embodiment of the present disclosure.

[0104] Figure 2 A flowchart of a method for selecting excitation parameters for respiratory electrical impedance imaging according to an embodiment of the present disclosure is shown.

[0105] Figure 3 Show Figure 2 Specific flow chart of step S201 in the embodiment.

[0106] Figure 4 Show Figure 2 Specific flow chart of step S203 in the embodiment.

[0107] Figure 5 A structural block diagram of a device for selecting excitation parameters for respiratory electrical impedance imaging according to an embodiment of the present disclosure is shown.

[0108] Figure 6 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0109] Figure 7 A schematic diagram showing the structure of a computer system suitable for implementing the method according to an embodiment of the present disclosure is shown. Specific embodiments

[0110] Hereinafter, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings so that those skilled in the art can easily implement them. In addition, for the sake of clarity, parts not related to the description of the exemplary embodiments are omitted in the accompanying drawings.

[0111] In the present disclosure, it should be understood that terms such as "including" or "having" are intended to indicate the presence of labels, numbers, steps, actions, components, parts, or combinations thereof disclosed in the present specification, and are not intended to exclude the possibility that one or more other labels, numbers, steps, actions, components, parts, or combinations thereof exist or are added.

[0112] It should also be noted that, in the absence of conflict, the embodiments and labels in the embodiments of the present disclosure can be combined with each other. The present disclosure will be described in detail below with reference to the accompanying drawings and in combination with the embodiments.

[0113] Electrical impedance tomography (EIT) is an emerging imaging technology that applies weak electrical currents to the human body through electrodes and simultaneously collects surface voltage, thereby estimating the distribution and changes in the internal electrical impedance of the subject. Due to its portability, low cost, and non-invasive nature, EIT has shown promising application prospects in bedside dynamic monitoring. Currently, its most widely used application is real-time monitoring of pulmonary ventilation.

[0114] Obtaining high-quality human respiratory electrical impedance imaging (EI) signals is a primary prerequisite for the application of chest EIT. The excitation parameters for EI, including the excitation current and excitation method, are crucial for determining the quality of chest EI signals. Due to the varying application environments, such as those in the laboratory and clinical setting, the environmental impact on EI signal quality varies. The human body's internal environment is complex and not a fixed resistance. As the internal and external environments change, the impedance of each organ continuously fluctuates. Sometimes, signal quality is better with high currents, sometimes with lower currents; sometimes, signal quality is better with opposite excitation, sometimes with adjacent excitation. Therefore, selecting the optimal excitation current and excitation method is crucial. Therefore, analyzing the EI excitation parameters that achieve optimal signal quality, tailored to the specific environment, is crucial for the practical application of chest EIT.

[0115] In order to solve the problems in the related art, the embodiments of the present disclosure provide a method, apparatus, device and medium for selecting excitation parameters for respiratory electrical impedance imaging.

[0116] In the disclosed embodiment, EIT respiratory signal acquisition is performed on a 25-year-old healthy male subject with a height of 172 centimeters (cm) and a weight of 73 kilograms (kg). The signal acquisition frame rate is 20 frames per second, the device excitation current is 10-750 microamperes (uA), for example, 750uA, 360uA, 180uA, 90uA and 45uA, and the excitation mode is opposite excitation or adjacent excitation.

[0117] In the disclosed embodiment, the EIT signal acquisition device has 16 electrodes. When using a counter-excitation method, an excitation current can be applied to electrodes 1 and 9, and boundary voltage signals can be detected at the remaining adjacent electrode pairs. For example, boundary voltage signals can be detected at electrode pairs 2-3, 3-4, ..., and 15-16, for a total of 12 voltage values. Then, an excitation current is applied to electrodes 2 and 10, and boundary voltage signals are detected at electrode pairs 3-4, 4-5, ..., and 16-1, and so on. This results in 16 excitation groups, each with 12 boundary voltage signals, for a total of 192 boundary voltage signals.

[0118] When using proximity excitation, an excitation current can be applied to electrodes 1 and 2, and boundary voltage signals can be detected at the remaining adjacent electrode pairs. For example, boundary voltage signals can be detected at electrode pairs 3-4, 4-5, ..., and 15-16, for a total of 13 voltage values. Then, an excitation current can be applied to electrodes 2 and 3, and so on. This results in 16 excitation groups, each with 13 boundary voltage signals, for a total of 208 boundary voltage signals.

[0119] In the disclosed embodiment, either opposing excitation or proximity excitation is used, and one of the excitation currents, 750uA, 360uA, 180uA, 90uA, and 45uA, is sequentially used to obtain a boundary voltage signal. The electrical impedance signal quality under that excitation current is then determined from the boundary voltage signal. The excitation current corresponding to the optimal electrical impedance signal quality is selected as the optimal excitation current, for example, 750uA.

[0120] Those skilled in the art will appreciate that other current values may be used as the excitation current, or other objects to be measured may be used for EIT detection, and this disclosure does not limit this.

[0121] When using an optimal excitation current of, for example, 750 uA, using opposite excitation or adjacent excitation, the effective timing diagram quality of electrical impedance imaging under the excitation mode is obtained. The excitation mode corresponding to the better effective timing diagram quality of electrical impedance imaging is selected as the optimal excitation mode, such as opposite excitation.

[0122] By sequentially determining the optimal excitation current and the optimal excitation mode, optimal excitation parameters for respiratory electrical impedance imaging including the optimal excitation current and the optimal excitation mode are determined.

[0123] After determining the optimal excitation current and excitation method for each body type, these can be stored. Upon encountering the same or similar body types, the stored optimal excitation current and method can be directly retrieved for rapid EIT testing. Alternatively, the optimal excitation current and method can be determined for each body type, allowing for precise EIT testing.

[0124] In the embodiment of the present disclosure, C types of excitation currents can be selected and used to implement excitation respectively. The excitation mode can be selected from opposite excitation and adjacent excitation. At the same time, the boundary voltage is collected, and T*f is collected under each amplitude current. s data, where f s is the acquisition frame rate, T is the acquisition time, which is greater than 5 breathing cycles. The data collected under C current amplitudes are arranged in the order of the frame number to obtain C boundary voltage matrices, Y1, Y2, ..., Y i ,...Y C , Y i is N·(f s T), where N is the number of boundary voltage channels contained in each frame of data, which is determined by the excitation method.

[0125] Specifically, for the above-mentioned object under test, a counter-excitation method can be used, and one of the excitation currents of 750uA, 360uA, 180uA, 90uA and 45uA can be used in sequence. s = 20, the boundary voltage signal is collected for 15 seconds, and 5 boundary voltage signal matrices Y1, Y2, ..., Y i ,...Y5. Y i For N rows, f s · A matrix with T columns. N = 192, i.e. 192 channels, f s T = 20 * 15 = 300, that is, 300 sampling points per channel.

[0126] In the embodiment of the present disclosure, the boundary voltage signal matrix Y is obtained under the 750uA excitation current. i For example, the normalized boundary voltage signal, the boundary voltage signal after filtering out the heartbeat, the respiratory voltage signal, the interference voltage signal, and the electrical impedance signal quality are calculated.

[0127] In the embodiment of the present disclosure, the boundary voltage signal matrix Y i , normalize the boundary voltage signals of all channels separately to obtain the normalized boundary voltage signal matrix in

[0128]

[0129] Normalized boundary voltage signal matrix The value of each element in is less than or equal to 1.

[0130] In the disclosed embodiments, the respiratory electrical impedance imaging signal primarily includes respiration, heartbeat, and human interference signals. The heartbeat signal is near the heart rate, while the human interference signal is a high-frequency signal, both of which are interference. Therefore, to assess the quality of the electrical impedance signal, it is necessary to filter out the heartbeat signal and human interference signals.

[0131] Figure 1a An exemplary schematic diagram illustrating filtering out a heartbeat signal from a normalized boundary voltage signal according to an embodiment of the present disclosure is shown.

[0132] It can be understood by those skilled in the art that Figure 1a The example of filtering out the heartbeat signal from the normalized boundary voltage signal is shown, but does not constitute a limitation to the present disclosure.

[0133] In the embodiment of the present disclosure, the boundary voltage matrix corresponding to the i-th current can be selected The h-th measurement channel in the image is selected, and the measured voltage at its position is Fourier transformed to obtain the signal spectrum of the h-th measurement channel. The maximum amplitude is calculated within the range of 0.8-2 Hz of the spectrum, and this value is used as the center frequency f0. Based on experience, the heart rate range width is set to 0.5 Hz. Therefore, the heart rate range of the examined object is determined to be [f0-0.25, f0+0.25] Hz.

[0134] For example, the normalized boundary voltage signal matrix corresponding to the 750uA excitation current can be selected The first measurement channel in the , and the normalized boundary voltage signal in the first measurement channel is Fourier transformed to obtain the following Figure 1a The signal spectrum of channel 1 is shown in the figure. Within the 0.8-2 Hz range, the frequency corresponding to the maximum spectral amplitude is calculated to be 1.098 Hz. This value, after calibration, is used as the heart rate, 1.1 Hz. Furthermore, based on experience, the heart rate range width is set to 0.5 Hz, thus determining the subject's heart rate range to be [0.85, 1.35] Hz.

[0135] In the embodiment of the present disclosure, the normalized boundary voltage signal matrix For all channels, a band-stop filter with a cutoff frequency of [0.85, 1.35] is used, such as a 5th-order Butterworth band-stop filter to filter out the heartbeat signal, and the boundary voltage signal matrix after filtering out the heartbeat is obtained. Contains breathing-related signals and human interference signals.

[0136] For example, the normalized boundary voltage signal matrix for the first channel is Use a band-stop filter with a cutoff frequency of [0.85, 1.35], such as a 5th-order Butterworth band-stop filter, to filter out the heartbeat signal and obtain the boundary voltage signal matrix after filtering out the heartbeat. Contains breathing-related signals and human interference signals.

[0137] Those skilled in the art will appreciate that the band-stop filter may employ a Butterworth band-stop filter of other orders, a finite impulse response (FIR) filter, or other filter methods, and the present disclosure is not limited thereto. The heart rate range of the subject may also be set to other values, and the present disclosure is not limited thereto.

[0138] In the embodiment of the present disclosure, the boundary voltage signal after the heartbeat is filtered out is A 5th-order Butterworth low-pass filter with a cutoff frequency of 0.5 Hz is used for low-pass filtering to obtain the respiratory voltage signal. Boundary voltage signal after filtering out the heartbeat Subtract the respiratory voltage signal Get the interference voltage signal

[0139] For example, the boundary voltage signal after filtering out the heartbeat A 5th-order Butterworth low-pass filter with a cutoff frequency of 0.5 Hz is used for low-pass filtering to obtain the respiratory voltage signal. Boundary voltage signal after filtering out the heartbeat Subtract the respiratory voltage signal Get the interference voltage signal

[0140] Those skilled in the art will appreciate that the low-pass filter may be a Butterworth band-stop filter of other orders, a finite impulse response (FIR) filter, or other filter methods, and the present disclosure is not limited thereto. The low-pass filter cutoff frequency may also be set to other values, and the present disclosure is not limited thereto.

[0141] Figure 1b An exemplary schematic diagram of obtaining a respiratory voltage signal according to an embodiment of the present disclosure is shown.

[0142] It can be understood by those skilled in the art that Figure 1b The acquisition of the respiratory voltage signal is illustrated as an example, but does not constitute a limitation to the present disclosure.

[0143] exist Figure 1b In the figure, the original signal without additional labels is the original normalized boundary voltage signal containing heartbeat and human interference; the "after filtering out heartbeat" with a circle mark is the boundary voltage signal after filtering out the heartbeat; the "only retain respiratory signal" with a five-pointed star mark is the respiratory voltage signal after low-pass filtering.

[0144] In the embodiment of the present disclosure, the electrical impedance signal quality under 750uA current is calculated based on the respiratory voltage signal and interference voltage signal of each sampling moment and each channel.

[0145]

[0146] After calculation, Q1=24.7209.

[0147] In the embodiment of the present disclosure, excitation currents of 750uA, 360uA, 180uA, 90uA and 45uA are used respectively, and the corresponding electrical impedance signal qualities Q1=24.7209, Q2=21.8313, Q3=18.6967, Q4=14.0305, and Q5=10.2283 are calculated.

[0148] The corresponding impedance signal with the highest quality is Q1=24.7209, and the optimal excitation current I is 750uA. Optimal .

[0149] In the embodiment of the present disclosure, under the condition of using the optimal excitation current of 750uA, current excitation is performed using the opposite excitation and adjacent excitation methods respectively. Under each excitation method, 15 seconds of boundary voltage signals are collected. The boundary voltage signals contain more than 3 respiratory cycles. The boundary voltages collected under the two excitation methods are arranged in the order of frame number to obtain two boundary voltage signal matrices, X1, X2, X1 and X2 are N·(f s N is the number of boundary voltage channels contained in each frame of data. N = 192 for opposite excitation and N = 208 for adjacent excitation.

[0150] In the embodiment of the present disclosure, taking counter-excitation as an example, the process of calculating respiratory electrical impedance imaging time-series image signals, respiratory electrical impedance imaging effective time-series image signals, calculating lung ventilation areas and non-ventilation areas, and the quality of electrical impedance imaging effective time-series diagrams is explained.

[0151] Figure 1c An exemplary schematic diagram showing a time-series image signal of respiratory electrical impedance imaging according to an embodiment of the present disclosure is shown.

[0152] It can be understood by those skilled in the art that Figure 1c The respiratory electrical impedance imaging time-series image signals are shown as examples, but do not constitute a limitation to the present disclosure.

[0153] Specifically, Figure 1c The figure shows, by way of example, a respiratory electrical impedance imaging time-series image signal within a respiratory cycle.

[0154] In the embodiment of the present disclosure, for the boundary voltage signal X of the i-th channel corresponding to the opposite excitation mode, i , calculate the respiratory electrical impedance imaging time series image signal σ i =[σ i,1 ,σ i,2 ,…,σ i,t ,…,σ i,fS*L ], where σ i,t =B(X i,t -X i,1 ), X i,1 is the boundary voltage measured at the initial moment, X i,t is the boundary voltage signal measured at time t, and B is the reconstruction algorithm matrix.

[0155] For example, for the boundary voltage signal X1 corresponding to the opposite excitation mode, the respiratory electrical impedance imaging time series image signal σ1 is calculated as [σ 1,1 ,σ 1,2 ,…,σ 1,t ,…,σ 1,300 ], where σ 1,t =B(X 1,t -X 1,1 ), X 1,1 is the boundary voltage measured at the initial moment, X 1,t is the boundary voltage signal measured at time t, and B is a reconstruction algorithm matrix such as the GREIR algorithm. Figure 1c The pixel depth in corresponds to σ i,j The value of .

[0156] Those skilled in the art will appreciate that the reconstruction algorithm may also adopt other algorithms besides the GREIR algorithm, and this disclosure does not limit this.

[0157] Figure 1d An exemplary schematic diagram showing normalized effective time-series image signals of respiratory electrical impedance imaging according to an embodiment of the present disclosure is shown.

[0158] It can be understood by those skilled in the art that Figure 1d The normalized effective time-series image signals of respiratory electrical impedance imaging are shown as an example, but do not constitute a limitation to the present disclosure.

[0159] In the embodiment of the present disclosure, for the respiratory electrical impedance imaging time series image signal σ corresponding to the opposite excitation mode, i , calculate the effective time series image signal of respiratory electrical impedance imaging

[0160] in ne is the number of pixels in the imaging area. Perform normalization processing to obtain the normalized effective time series image signal of the respiratory electrical impedance imaging under opposite excitation in,

[0161]

[0162] For example, for the respiratory electrical impedance imaging time series image signal σ1 corresponding to the opposite excitation mode, the effective time series image signal of respiratory electrical impedance imaging is calculated in

[0163] ne is the number of pixels in the imaging area, ne = 1024, that is, the pixels in the imaging area are 32 rows and 32 columns. Perform normalization processing to obtain the normalized effective time series image signal of the respiratory electrical impedance imaging under opposite excitation in,

[0164] In the embodiment of the present disclosure, the specific normalized effective time series image signal of the respiratory electrical impedance imaging of the opposite excitation is as follows: Figure 1d shown.

[0165] Figure 1e An exemplary schematic diagram showing lung ventilation areas and non-ventilation areas according to an embodiment of the present disclosure.

[0166] It can be understood by those skilled in the art that Figure 1e The lung ventilation area and the non-ventilation area are shown as examples and do not constitute a limitation to the present disclosure.

[0167] In the embodiment of the present disclosure, for the normalized effective time series image signal of the counter-excitation respiratory electrical impedance imaging, All cells with a ventilation area greater than a certain threshold are determined as lung ventilation area A lung ,Right now Figure 1e The white area in the figure and the remaining area are non-ventilated areas A non-lung ,Right now Figure 1e Furthermore, the effective timing diagram quality of the electrical impedance imaging under the opposite excitation mode is calculated.

[0168] S is the lung ventilation area A lung The number of units in the non-ventilated area A non-lung The number of units within.

[0169] For example, for the normalized effective time series image signal of respiratory electrical impedance imaging with opposite excitation, All cells with a value greater than 80% of the maximum value are identified as lung ventilation area A. lung ,Right now Figure 1e The white area in the figure and the remaining area are non-ventilated areas Anon-lung ,Right now Figure 1e Furthermore, the effective timing diagram quality of the electrical impedance imaging under the opposite excitation mode is calculated. S is the lung ventilation area A lung The number of units in the non-ventilated area A non-lung The number of units in the. After calculation, G1=5.4068.

[0170] In the embodiment of the present disclosure, an optimal excitation current of 750 uA can be used, and a proximity excitation method can be adopted to obtain an effective timing diagram quality of 2.8968 for electrical impedance imaging under the proximity excitation method.

[0171] The quality of the effective timing diagram of electrical impedance tomography under opposite excitation and adjacent excitation is compared, and the larger value is taken. Therefore, the optimal excitation method is the opposite excitation method.

[0172] Those skilled in the art will appreciate that, for different human bodies, other excitation currents may be determined as the optimal excitation current, or adjacent excitation modes may be determined as the optimal excitation mode, and this disclosure does not limit this.

[0173] Figure 2 A flowchart of a method for selecting excitation parameters for respiratory electrical impedance imaging according to an embodiment of the present disclosure is shown.

[0174] like Figure 2 As shown, the method for selecting excitation parameters for respiratory electrical impedance imaging includes steps S201, S202, S203, and S204.

[0175] In step S201 , multiple currents are used to perform excitation in a certain excitation mode, and multiple electrical impedance signal qualities under the multiple excitation currents are obtained.

[0176] In step S202 , the qualities of multiple electrical impedance signals are compared, and the excitation current corresponding to the best electrical impedance signal quality is selected as the optimal excitation current.

[0177] In step S203, under the condition of using the optimal excitation current, multiple excitation modes are used to obtain the effective timing diagram qualities of multiple electrical impedance imaging under the multiple excitation modes.

[0178] In step S204, the qualities of the effective timing diagrams of the multiple electrical impedance imaging are compared, and the excitation mode corresponding to the best quality of the effective timing diagram of the electrical impedance imaging is selected as the optimal excitation mode.

[0179] Step S201 is a step for obtaining the quality of an electrical impedance signal, step S202 is a step for selecting an optimal excitation current, step S203 is a step for obtaining the quality of an effective timing diagram of electrical impedance imaging, and step S204 is a step for selecting an optimal excitation mode.

[0180] According to an embodiment of the present disclosure, through the impedance signal quality acquisition step, multiple currents are used for excitation under a certain excitation mode to obtain multiple impedance signal qualities under multiple excitation currents; the optimal excitation current selection step compares multiple impedance signal qualities and selects the excitation current corresponding to the best impedance signal quality as the optimal excitation current; the impedance imaging effective timing diagram quality acquisition step uses multiple excitation modes under the condition of using the optimal excitation current to obtain multiple impedance imaging effective timing diagram qualities under multiple excitation modes; the optimal excitation mode selection step compares multiple impedance imaging effective timing diagram qualities and selects the excitation mode corresponding to the best impedance imaging effective timing diagram quality as the optimal excitation mode, thereby determining the optimal excitation parameters and improving the quality of respiratory impedance imaging.

[0181] In the embodiment of the present disclosure, as mentioned above, the certain excitation method includes: any one of opposite excitation and adjacent excitation.

[0182] According to the embodiment of the present disclosure, the optimal excitation current is conveniently detected by using a certain excitation method including any one of opposite excitation and adjacent excitation.

[0183] Figure 3 Show Figure 2 Specific flow chart of step S201 in the embodiment.

[0184] like Figure 3 As shown, Figure 2 The specific process of step S201 includes: steps S301, S302, S303, S304, and S305.

[0185] In step S301 , under a certain excitation mode, multiple currents are used for excitation, and a boundary voltage signal under each excitation current is obtained.

[0186] In step S302 , a normalized boundary voltage signal is calculated based on the boundary voltage signal.

[0187] In step S303, the heart rate is calculated for the normalized boundary voltage signal, and the heartbeat signal in the normalized boundary voltage signal is filtered out based on the heart rate to obtain a boundary voltage signal after the heartbeat is filtered out.

[0188] In step S304, the respiratory voltage signal and the interference voltage signal are extracted from the boundary voltage signal after the heartbeat is filtered out.

[0189] In step S305 , the electrical impedance signal quality is calculated based on the respiratory voltage signal and the interference voltage signal.

[0190] In the embodiment of the present disclosure, as mentioned above, the normalized boundary voltage signal matrix corresponding to the 750uA excitation current is selected The first measurement channel in the , and the normalized boundary voltage signal in the first measurement channel is Fourier transformed to obtain the following Figure 1a The signal spectrum of channel 1 shown in the figure calculates the heart rate of 1.1Hz by the maximum value of the spectrum. A band-stop filter with a cutoff frequency of [0.85, 1.35], such as a 5th-order Butterworth band-stop filter, is used to filter out the heartbeat signal to obtain the boundary voltage signal matrix after filtering out the heartbeat.

[0191] The boundary voltage signal after filtering out the heartbeat A 5th-order Butterworth low-pass filter with a cutoff frequency of 0.5 Hz is used for low-pass filtering to obtain the respiratory voltage signal. Boundary voltage signal after filtering out the heartbeat Subtract the respiratory voltage signal Get the interference voltage signal

[0192] Based on the respiratory voltage signal and interference voltage signal at each sampling moment and each channel, calculate the quality of the electrical impedance signal under 750uA current

[0193]

[0194] After calculation, Q1=24.7209.

[0195] In the embodiment of the present disclosure, excitation currents of 750uA, 360uA, 180uA, 90uA and 45uA are used respectively, and the corresponding electrical impedance signal qualities Q1=24.7209, Q2=21.8313, Q3=18.6967, Q4=14.0305, and Q5=10.2283 are calculated.

[0196] The corresponding impedance signal with the highest quality is Q1=24.7209, and the optimal excitation current I is 750uA. Optimal .

[0197] According to an embodiment of the present disclosure, the steps for obtaining the quality of the electrical impedance signal include: using multiple currents for excitation under a certain excitation mode to obtain the boundary voltage signal under each excitation current; calculating the normalized boundary voltage signal based on the boundary voltage signal; calculating the heart rate for the normalized boundary voltage signal, filtering out the heartbeat signal in the normalized boundary voltage signal based on the heart rate, and obtaining the boundary voltage signal after the heartbeat is filtered out; extracting the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after the heartbeat is filtered out; calculating the quality of the electrical impedance signal based on the respiratory voltage signal and the interference voltage signal, thereby accurately calculating the quality of the electrical impedance signal and reasonably selecting the optimal excitation current.

[0198] According to an embodiment of the present disclosure, calculating a normalized boundary voltage signal based on the boundary voltage signal includes: calculating a normalized boundary voltage signal based on the maximum value of the boundary voltage signal, thereby accurately calculating the quality of the electrical impedance signal and reasonably selecting the optimal excitation current.

[0199] According to an embodiment of the present disclosure, calculating the heart rate by normalizing the boundary voltage signal includes: calculating the spectrum of the normalized boundary voltage signal, calculating the heart rate based on the maximum value of the spectrum, and / or filtering the heartbeat signal in the normalized boundary voltage signal based on the heart rate, and obtaining the boundary voltage signal after filtering out the heartbeat includes: based on the heart rate, using a band-stop filter to filter out the heartbeat signal in the normalized boundary voltage signal, and obtaining the boundary voltage signal after filtering out the heartbeat, thereby accurately filtering out the heartbeat signal, accurately calculating the quality of the electrical impedance signal, and reasonably selecting the optimal excitation current.

[0200] According to an embodiment of the present disclosure, extracting a respiratory voltage signal and an interference voltage signal from a boundary voltage signal after filtering out the heartbeat includes: using a low-pass filter to extract the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after filtering out the heartbeat, thereby accurately calculating the quality of the electrical impedance signal and reasonably selecting the optimal excitation current.

[0201] In the embodiment of the present disclosure, as mentioned above, the boundary voltage signal, the normalized boundary voltage signal, the boundary voltage signal after heartbeat filtering, the respiratory voltage signal and the interference voltage signal are in matrix form.

[0202] According to an embodiment of the present disclosure, the boundary voltage signal, the normalized boundary voltage signal, the boundary voltage signal after filtering out the heartbeat, the respiratory voltage signal and the interference voltage signal are in matrix form, thereby simplifying the calculation while accurately calculating the quality of the electrical impedance signal and improving the calculation speed.

[0203] Figure 4 Show Figure 2 Specific flow chart of step S203 in the embodiment.

[0204] like Figure 4 As shown, Figure 2 Step S203 in the process includes steps S401, S402, S403 and S404.

[0205] In step S401 , under the condition of using the optimal excitation current, either opposing excitation or adjacent excitation is used to obtain a boundary voltage signal under the excitation mode.

[0206] In step S402, a respiratory electrical impedance imaging time series image signal is calculated according to the boundary voltage signal under the excitation mode.

[0207] In step S403, an effective time-series image signal of respiratory electrical impedance imaging is calculated according to the time-series image signal of respiratory electrical impedance imaging.

[0208] In step S404, the effective time sequence image quality of the electrical impedance imaging under the excitation mode is calculated according to the effective time sequence image signal of the respiratory electrical impedance imaging.

[0209] In the embodiment of the present disclosure, as described above, the optimal excitation current of 750uA is adopted, the opposite excitation mode is adopted, the boundary voltage signal X1 is obtained, and the reconstruction algorithm such as the GREIR algorithm is used to calculate the respiratory electrical impedance imaging time series image signal σ1=[σ 1,1 ,σ 1,2 ,…,σ 1,t ,…,σ 1,300 ]; Calculate the effective time series image signal of respiratory electrical impedance imaging in right Perform normalization processing to obtain the normalized effective time series image signal of the respiratory electrical impedance imaging under opposite excitation in, Calculate lung ventilation area A lung and non-ventilated area A non-lung ; Calculate the quality of the effective timing diagram of electrical impedance tomography under the opposite excitation mode After calculation, G1=5.4068.

[0210] In the embodiment of the present disclosure, an optimal excitation current of 750 uA can be used, and a proximity excitation method can be adopted to obtain an effective timing diagram quality of 2.8968 for electrical impedance imaging under the proximity excitation method.

[0211] The quality of the effective timing diagram of electrical impedance tomography under opposite excitation and adjacent excitation is compared, and the larger value is taken. Therefore, the optimal excitation method is the opposite excitation method.

[0212] According to an embodiment of the present disclosure, the steps of obtaining the effective timing diagram quality of electrical impedance imaging include: under the condition of using the optimal excitation current, using any one of opposite excitation and adjacent excitation to obtain the boundary voltage signal under the excitation mode; calculating the respiratory electrical impedance imaging timing image signal based on the boundary voltage signal under the excitation mode; calculating the normalized effective timing image signal of respiratory electrical impedance imaging based on the respiratory electrical impedance imaging timing image signal; calculating the effective timing diagram quality of electrical impedance imaging under the excitation mode based on the normalized effective timing image signal of respiratory electrical impedance imaging, thereby accurately calculating the effective timing diagram quality of electrical impedance imaging and reasonably selecting the optimal excitation mode.

[0213] According to an embodiment of the present disclosure, calculating the effective time-series image signal of respiratory electrical impedance imaging based on the respiratory electrical impedance imaging time-series image signal includes: calculating the root mean square value of the sampling moment for each pixel point of the respiratory electrical impedance imaging time-series image signal; calculating the normalized value of the root mean square value to obtain the effective time-series image signal of respiratory electrical impedance imaging, thereby accurately calculating the quality of the effective time-series diagram of electrical impedance imaging and reasonably selecting the optimal excitation method.

[0214] According to an embodiment of the present disclosure, the effective timing diagram quality of the electrical impedance imaging under the excitation mode is calculated based on the effective timing image signal of the respiratory electrical impedance imaging, including: calculating the lung ventilation area and the non-ventilation area based on the effective timing image signal of the respiratory electrical impedance imaging; calculating the effective timing diagram quality of the electrical impedance imaging under the excitation mode based on the lung ventilation area and the non-ventilation area, thereby accurately calculating the effective timing diagram quality of the electrical impedance imaging and reasonably selecting the optimal excitation mode.

[0215] Figure 5 A structural block diagram of a device for selecting excitation parameters for respiratory electrical impedance imaging according to an embodiment of the present disclosure is shown.

[0216] like Figure 5 As shown, the respiratory electrical impedance imaging excitation parameter selection device 500 includes: an electrical impedance signal quality acquisition module 501, an optimal excitation current selection module 502, an electrical impedance imaging effective timing diagram quality acquisition module 503, and an optimal excitation mode selection module 504.

[0217] The electrical impedance signal quality acquisition module 501 is used to use multiple currents to perform excitation under a certain excitation mode and obtain multiple electrical impedance signal qualities under the multiple excitation currents;

[0218] The optimal excitation current selection module 502 is used to compare the qualities of multiple electrical impedance signals and select the excitation current corresponding to the best electrical impedance signal quality as the optimal excitation current;

[0219] The electrical impedance imaging effective timing diagram quality acquisition module 503 is used to acquire the effective timing diagram qualities of various electrical impedance imaging under various excitation modes under the condition of using the optimal excitation current;

[0220] The optimal excitation mode selection module 504 is used to compare the qualities of multiple electrical impedance imaging effective timing diagrams and select the excitation mode corresponding to the best electrical impedance imaging effective timing diagram quality as the optimal excitation mode.

[0221] According to an embodiment of the present disclosure, an impedance signal quality acquisition module is used to use multiple currents to perform excitation under a certain excitation mode to obtain multiple impedance signal qualities under multiple excitation currents; an optimal excitation current selection module is used to compare multiple impedance signal qualities and select the excitation current corresponding to the best impedance signal quality as the optimal excitation current; an impedance imaging effective timing diagram quality acquisition module is used to use multiple excitation modes under the condition of using the optimal excitation current to obtain multiple impedance imaging effective timing diagram qualities under multiple excitation modes; an optimal excitation mode selection module is used to compare multiple impedance imaging effective timing diagram qualities and select the excitation mode corresponding to the best impedance imaging effective timing diagram quality as the optimal excitation mode, thereby improving the quality of respiratory impedance imaging.

[0222] According to the embodiment of the present disclosure, the optimal excitation current is conveniently detected by using a certain excitation method including any one of opposite excitation and adjacent excitation.

[0223] According to an embodiment of the present disclosure, the electrical impedance signal quality acquisition module is used to: use multiple currents for excitation under a certain excitation mode to obtain the boundary voltage signal under each excitation current; calculate the normalized boundary voltage signal based on the boundary voltage signal; calculate the heart rate for the normalized boundary voltage signal, and filter the heartbeat signal in the normalized boundary voltage signal based on the heart rate to obtain the boundary voltage signal after the heartbeat is filtered out; extract the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after the heartbeat is filtered out; calculate the electrical impedance signal quality based on the respiratory voltage signal and the interference voltage signal, thereby accurately calculating the electrical impedance signal quality and reasonably selecting the optimal excitation current.

[0224] According to an embodiment of the present disclosure, calculating a normalized boundary voltage signal based on the boundary voltage signal includes: calculating a normalized boundary voltage signal based on the maximum value of the boundary voltage signal, thereby accurately calculating the quality of the electrical impedance signal and reasonably selecting the optimal excitation current.

[0225] According to an embodiment of the present disclosure, calculating the heart rate by normalizing the boundary voltage signal includes: calculating the spectrum of the normalized boundary voltage signal, calculating the heart rate based on the maximum value of the spectrum, and / or filtering the heartbeat signal in the normalized boundary voltage signal based on the heart rate, and obtaining the boundary voltage signal after filtering out the heartbeat includes: based on the heart rate, using a band-stop filter to filter out the heartbeat signal in the normalized boundary voltage signal, and obtaining the boundary voltage signal after filtering out the heartbeat, thereby accurately filtering out the heartbeat signal, accurately calculating the quality of the electrical impedance signal, and reasonably selecting the optimal excitation current.

[0226] According to an embodiment of the present disclosure, extracting a respiratory voltage signal and an interference voltage signal from a boundary voltage signal after filtering out the heartbeat includes: using a low-pass filter to extract the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after filtering out the heartbeat, thereby accurately calculating the quality of the electrical impedance signal and reasonably selecting the optimal excitation current.

[0227] According to an embodiment of the present disclosure, the effective timing diagram quality acquisition module of electrical impedance imaging is used to: under the condition of using the optimal excitation current, use any one of the opposite excitation and adjacent excitation to obtain the boundary voltage signal under the excitation mode; calculate the respiratory electrical impedance imaging timing image signal based on the boundary voltage signal under the excitation mode; calculate the normalized effective timing image signal of respiratory electrical impedance imaging based on the respiratory electrical impedance imaging timing image signal; calculate the effective timing diagram quality of electrical impedance imaging under the excitation mode based on the normalized effective timing image signal of respiratory electrical impedance imaging, thereby accurately calculating the effective timing diagram quality of electrical impedance imaging and reasonably selecting the optimal excitation mode.

[0228] According to an embodiment of the present disclosure, calculating the effective time-series image signal of respiratory electrical impedance imaging based on the respiratory electrical impedance imaging time-series image signal includes: calculating the root mean square value of the sampling moment for each pixel point of the respiratory electrical impedance imaging time-series image signal; calculating the normalized value of the root mean square value to obtain the effective time-series image signal of respiratory electrical impedance imaging, thereby accurately calculating the quality of the effective time-series diagram of electrical impedance imaging and reasonably selecting the optimal excitation method.

[0229] According to an embodiment of the present disclosure, the effective timing diagram quality of the electrical impedance imaging under the excitation mode is calculated based on the effective timing image signal of the respiratory electrical impedance imaging, including: calculating the lung ventilation area and the non-ventilation area based on the effective timing image signal of the respiratory electrical impedance imaging; calculating the effective timing diagram quality of the electrical impedance imaging under the excitation mode based on the lung ventilation area and the non-ventilation area, thereby accurately calculating the effective timing diagram quality of the electrical impedance imaging and reasonably selecting the optimal excitation mode.

[0230] Figure 6 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0231] like Figure 6 As shown, the electronic device 600 includes a memory 601 and a processor 602, wherein the memory 601 is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor 602 to implement the following steps:

[0232] an electrical impedance signal quality acquisition step, using multiple currents to perform excitation under a certain excitation mode, and acquiring multiple electrical impedance signal qualities under the multiple excitation currents;

[0233] an optimal excitation current selection step of comparing the multiple electrical impedance signal qualities and selecting the excitation current corresponding to the best electrical impedance signal quality as the optimal excitation current;

[0234] The step of obtaining the quality of the effective timing diagram of electrical impedance imaging is as follows: using a plurality of excitation modes under the condition of using the optimal excitation current, and obtaining the quality of the effective timing diagram of the electrical impedance imaging under the plurality of excitation modes;

[0235] The optimal excitation mode selection step compares the qualities of the multiple electrical impedance imaging effective timing diagrams and selects the excitation mode corresponding to the best electrical impedance imaging effective timing diagram quality as the optimal excitation mode.

[0236] In the embodiment of the present disclosure, the certain excitation mode includes: any one of opposite excitation and adjacent excitation.

[0237] In an embodiment of the present disclosure, the step of obtaining the quality of the electrical impedance signal includes:

[0238] Under a certain excitation mode, multiple currents are used for excitation, and a boundary voltage signal under each excitation current is obtained;

[0239] Calculating a normalized boundary voltage signal based on the boundary voltage signal;

[0240] Calculating a heart rate from the normalized boundary voltage signal, and filtering out a heartbeat signal from the normalized boundary voltage signal based on the heart rate to obtain a boundary voltage signal after the heartbeat is filtered out;

[0241] Extracting a respiratory voltage signal and an interference voltage signal from the boundary voltage signal after filtering out the heartbeat;

[0242] The electrical impedance signal quality is calculated based on the respiration voltage signal and the interference voltage signal.

[0243] In an embodiment of the present disclosure, calculating a normalized boundary voltage signal based on the boundary voltage signal includes:

[0244] A normalized boundary voltage signal is calculated based on the maximum value of the boundary voltage signal.

[0245] In an embodiment of the present disclosure, calculating the heart rate based on the normalized boundary voltage signal includes:

[0246] Calculating the spectrum of the normalized boundary voltage signal, calculating the heart rate based on the maximum value of the spectrum, and / or

[0247] The filtering out the heartbeat signal in the normalized boundary voltage signal based on the heart rate to obtain the boundary voltage signal after the heartbeat is filtered out includes:

[0248] Based on the heart rate, a band-stop filter is used to filter out the heartbeat signal in the normalized boundary voltage signal to obtain a boundary voltage signal after the heartbeat is filtered out.

[0249] In the embodiment of the present disclosure, extracting the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after filtering out the heartbeat includes:

[0250] A low-pass filter is used to extract the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after the heartbeat is filtered out.

[0251] In the embodiment of the present disclosure, the boundary voltage signal, the normalized boundary voltage signal, the boundary voltage signal after heartbeat filtering, the respiratory voltage signal and the interference voltage signal are in matrix form.

[0252] In an embodiment of the present disclosure, the step of obtaining the quality of the effective timing diagram of electrical impedance imaging includes:

[0253] Under the condition of using the optimal excitation current, use either opposite excitation or adjacent excitation to obtain the boundary voltage signal under the excitation mode;

[0254] Calculating respiratory electrical impedance imaging time-series image signals according to the boundary voltage signal under the excitation mode;

[0255] Calculating a normalized effective time-series image signal of respiratory electrical impedance imaging according to the time-series image signal of respiratory electrical impedance imaging;

[0256] The effective time sequence image quality of the electrical impedance imaging under the excitation mode is calculated according to the normalized effective time sequence image signal of the respiratory electrical impedance imaging.

[0257] In an embodiment of the present disclosure, calculating the respiratory electrical impedance imaging time-series image signal according to the boundary voltage signal under the excitation mode includes:

[0258] According to the boundary voltage signal under the excitation mode, a reconstruction algorithm is used to calculate the respiratory electrical impedance imaging time series image signal.

[0259] In an embodiment of the present disclosure, calculating the effective time-series image signal of respiratory electrical impedance imaging according to the time-series image signal of respiratory electrical impedance imaging includes:

[0260] Calculating the root mean square value of each pixel point of the respiratory electrical impedance imaging time series image signal at the sampling moment;

[0261] Calculate the normalized value of the root mean square value to obtain the effective time series image signal of the respiratory electrical impedance imaging.

[0262] In the embodiment of the present disclosure, calculating the effective timing image quality of the electrical impedance imaging under the excitation mode according to the effective timing image signal of the electrical impedance imaging includes:

[0263] Calculating lung ventilation and non-ventilation areas according to the effective time-series image signals of the respiratory electrical impedance imaging;

[0264] The effective timing diagram quality of electrical impedance imaging under the excitation mode is calculated according to the lung ventilation area and the non-ventilation area.

[0265] Figure 7 A schematic diagram showing the structure of a computer system suitable for implementing the method according to an embodiment of the present disclosure is shown.

[0266] like Figure 7 As shown, the computer system 700 includes a processing unit 701, which can execute various processes in the above-mentioned embodiments according to a program stored in a read-only memory (ROM) 702 or a program loaded from a storage unit 708 into a random access memory (RAM) 703. Various programs and data required for the operation of the system 700 are also stored in the RAM 703. The processing unit 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input / output (I / O) interface 705 is also connected to the bus 704.

[0267] The following components are connected to the I / O interface 705: an input section 706 including a keyboard, a mouse, etc.; an output section 707 including a cathode ray tube (CRT), a liquid crystal display (LCD), a speaker, etc.; a storage section 708 including a hard disk, etc.; and a communication section 709 including a network interface card such as a LAN card, a modem, etc. The communication section 709 performs communication processing via a network such as the Internet. A drive 710 is also connected to the I / O interface 705 as needed. A removable medium 711, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 710 as needed so that a computer program read therefrom can be installed into the storage section 708 as needed. Among them, the processing unit 701 can be implemented as a processing unit such as a CPU, a GPU, a TPU, an FPGA, an NPU, etc.

[0268] In particular, according to embodiments of the present disclosure, the methods described above can be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising computer instructions that, when executed by a processor, implement the method steps described above. In such embodiments, the computer program product can be downloaded and installed from a network via the communication portion 709 and / or installed from removable media 711.

[0269] The flowcharts and block diagrams in the accompanying drawings illustrate the possible implementation architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present disclosure. In this regard, each box in the flowchart or block diagram can represent a module, program segment or part of code, and the module, program segment or part of code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in an order different from that marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram and / or flowchart, and the combination of boxes in the block diagram and / or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or can be implemented using a combination of dedicated hardware and computer instructions.

[0270] The units or modules described in the embodiments of the present disclosure may be implemented in software or programmable hardware. The units or modules described may also be provided in a processor, and the names of these units or modules do not, in certain circumstances, limit the units or modules themselves.

[0271] As another aspect, the present disclosure further provides a computer-readable storage medium. This computer-readable storage medium may be included in the electronic device or computer system described in the above embodiments, or may be a standalone computer-readable storage medium not incorporated into the device. The computer-readable storage medium stores one or more programs, which are used by one or more processors to execute the methods described in the present disclosure.

[0272] The above description is merely a preferred embodiment of the present disclosure and an illustration of the technical principles employed. Those skilled in the art should understand that the scope of the invention herein is not limited to the technical solutions formed by the specific combination of the above-mentioned technical features, but also encompasses other technical solutions formed by any combination of the above-mentioned technical features or their equivalents without departing from the inventive concept. For example, a technical solution formed by replacing the above-mentioned features with (but not limited to) technical features with similar functions disclosed in this disclosure.

Claims

1. A method for selecting excitation parameters for respiratory electrical impedance tomography, characterized in that: include: an electrical impedance signal quality acquisition step, using a plurality of excitation currents to perform excitation under a certain excitation mode, and acquiring a plurality of electrical impedance signal qualities under the plurality of excitation currents; an optimal excitation current selection step of comparing the multiple electrical impedance signal qualities and selecting the excitation current corresponding to the best electrical impedance signal quality as the optimal excitation current; The step of obtaining the quality of the effective timing diagram of electrical impedance imaging is as follows: using a plurality of excitation modes under the condition of using the optimal excitation current, and obtaining the quality of the effective timing diagram of the electrical impedance imaging under the plurality of excitation modes; an optimal excitation mode selection step, comparing the qualities of the multiple electrical impedance imaging effective timing diagrams, and selecting the excitation mode corresponding to the best electrical impedance imaging effective timing diagram quality as the optimal excitation mode; Wherein, the electrical impedance signal quality acquisition step includes: Under certain excitation modes, multiple excitation currents are used for excitation, and the boundary voltage signal under each excitation current is obtained; Calculating a normalized boundary voltage signal based on the boundary voltage signal; Calculating a heart rate from the normalized boundary voltage signal, and filtering out a heartbeat signal from the normalized boundary voltage signal based on the heart rate to obtain a boundary voltage signal after the heartbeat is filtered out; Extracting a respiratory voltage signal and an interference voltage signal from the boundary voltage signal after filtering out the heartbeat; The electrical impedance signal quality is calculated based on the respiration voltage signal and the interference voltage signal.

2. The method according to claim 1, characterized in that The certain excitation method includes: any one of opposite excitation and adjacent excitation.

3. The method according to claim 1, characterized in that The calculating a normalized boundary voltage signal based on the boundary voltage signal includes: A normalized boundary voltage signal is calculated based on the maximum value of the boundary voltage signal.

4. The method according to claim 1, wherein Calculating the heart rate based on the normalized boundary voltage signal includes: Calculating the spectrum of the normalized boundary voltage signal, calculating the heart rate based on the maximum value of the spectrum, and / or The filtering out the heartbeat signal in the normalized boundary voltage signal based on the heart rate to obtain the boundary voltage signal after the heartbeat is filtered out includes: Based on the heart rate, a band-stop filter is used to filter out the heartbeat signal in the normalized boundary voltage signal to obtain a boundary voltage signal after the heartbeat is filtered out.

5. The method according to claim 1, wherein The step of extracting the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after the heartbeat is filtered out comprises: A low-pass filter is used to extract the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after the heartbeat is filtered out.

6. The method according to claim 1, characterized in that The boundary voltage signal, the normalized boundary voltage signal, the boundary voltage signal after heartbeat filtering, the respiratory voltage signal and the interference voltage signal are in matrix form.

7. The method according to claim 1, characterized in that The step of obtaining the quality of the effective timing diagram of electrical impedance imaging comprises: Under the condition of using the optimal excitation current, use either opposite excitation or adjacent excitation to obtain the boundary voltage signal under the excitation mode; Calculating respiratory electrical impedance imaging time-series image signals according to the boundary voltage signal under the excitation mode; Calculating a normalized effective time-series image signal of respiratory electrical impedance imaging according to the time-series image signal of respiratory electrical impedance imaging; The effective time sequence image quality of the electrical impedance imaging under the excitation mode is calculated according to the normalized effective time sequence image signal of the respiratory electrical impedance imaging.

8. The method according to claim 7, characterized in that Calculating the respiratory electrical impedance imaging time-series image signal according to the boundary voltage signal under the excitation mode includes: According to the boundary voltage signal under the excitation mode, a reconstruction algorithm is used to calculate the respiratory electrical impedance imaging time series image signal.

9. The method according to claim 7, characterized in that Calculating the effective time-series image signal of respiratory electrical impedance imaging according to the time-series image signal of respiratory electrical impedance imaging comprises: Calculating the root mean square value of each pixel point of the respiratory electrical impedance imaging time series image signal at the sampling moment; Calculate the normalized value of the root mean square value to obtain the effective time series image signal of the respiratory electrical impedance imaging.

10. The method according to claim 7, characterized in that Calculating the effective timing image quality of the electrical impedance imaging under the excitation mode according to the effective timing image signal of the electrical impedance imaging comprises: Calculating lung ventilation and non-ventilation areas according to the effective time-series image signals of the respiratory electrical impedance imaging; The effective timing diagram quality of electrical impedance imaging under the excitation mode is calculated according to the lung ventilation area and the non-ventilation area.

11. A device for selecting excitation parameters for respiratory electrical impedance imaging, characterized in that: include: An electrical impedance signal quality acquisition module, configured to use a plurality of excitation currents to perform excitation under a certain excitation mode, and acquire a plurality of electrical impedance signal qualities under the plurality of excitation currents; an optimal excitation current selection module, configured to compare the qualities of the plurality of electrical impedance signals and select an excitation current corresponding to the best electrical impedance signal quality as the optimal excitation current; An electrical impedance imaging effective timing diagram quality acquisition module is used to obtain the qualities of various electrical impedance imaging effective timing diagrams under the conditions of using an optimal excitation current and using a plurality of excitation modes; An optimal excitation mode selection module is used to compare the qualities of the multiple electrical impedance imaging effective timing diagrams and select the excitation mode corresponding to the best electrical impedance imaging effective timing diagram quality as the optimal excitation mode; Wherein, the electrical impedance signal quality acquisition module is used to: Under certain excitation modes, multiple excitation currents are used for excitation, and the boundary voltage signal under each excitation current is obtained; Calculating a normalized boundary voltage signal based on the boundary voltage signal; Calculating a heart rate from the normalized boundary voltage signal, and filtering out a heartbeat signal from the normalized boundary voltage signal based on the heart rate to obtain a boundary voltage signal after the heartbeat is filtered out; Extracting a respiratory voltage signal and an interference voltage signal from the boundary voltage signal after filtering out the heartbeat; The electrical impedance signal quality is calculated based on the respiration voltage signal and the interference voltage signal.

12. The device according to claim 11, characterized in that The certain excitation method includes: any one of opposite excitation and adjacent excitation.

13. The device according to claim 11, characterized in that The calculating a normalized boundary voltage signal based on the boundary voltage signal includes: A normalized boundary voltage signal is calculated based on the maximum value of the boundary voltage signal.

14. The device according to claim 11, characterized in that Calculating the heart rate based on the normalized boundary voltage signal includes: Calculating the spectrum of the normalized boundary voltage signal, calculating the heart rate based on the maximum value of the spectrum, and / or The filtering out the heartbeat signal in the normalized boundary voltage signal based on the heart rate to obtain the boundary voltage signal after the heartbeat is filtered out includes: Based on the heart rate, a band-stop filter is used to filter out the heartbeat signal in the normalized boundary voltage signal to obtain a boundary voltage signal after the heartbeat is filtered out.

15. The device according to claim 11, characterized in that The step of extracting the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after the heartbeat is filtered out comprises: A low-pass filter is used to extract the respiratory voltage signal and the interference voltage signal from the boundary voltage signal after the heartbeat is filtered out.

16. The device according to claim 11, characterized in that The boundary voltage signal, the normalized boundary voltage signal, the boundary voltage signal after heartbeat filtering, the respiratory voltage signal and the interference voltage signal are in matrix form.

17. The device according to claim 11, characterized in that The electrical impedance imaging effective timing diagram quality acquisition module is used for: Under the condition of using the optimal excitation current, use either opposite excitation or adjacent excitation to obtain the boundary voltage signal under the excitation mode; Calculating respiratory electrical impedance imaging time-series image signals according to the boundary voltage signal under the excitation mode; Calculating a normalized effective time-series image signal of respiratory electrical impedance imaging according to the time-series image signal of respiratory electrical impedance imaging; The effective time sequence image quality of the electrical impedance imaging under the excitation mode is calculated according to the normalized effective time sequence image signal of the respiratory electrical impedance imaging.

18. The device according to claim 17, characterized in that Calculating the respiratory electrical impedance imaging time-series image signal according to the boundary voltage signal under the excitation mode includes: According to the boundary voltage signal under the excitation mode, a reconstruction algorithm is used to calculate the respiratory electrical impedance imaging time series image signal.

19. The device according to claim 17, characterized in that Calculating the effective time-series image signal of respiratory electrical impedance imaging according to the time-series image signal of respiratory electrical impedance imaging comprises: Calculating the root mean square value of each pixel point of the respiratory electrical impedance imaging time series image signal at the sampling moment; Calculate the normalized value of the root mean square value to obtain the effective time series image signal of the respiratory electrical impedance imaging.

20. The device according to claim 17, wherein Calculating the effective timing image quality of the electrical impedance imaging under the excitation mode according to the effective timing image signal of the electrical impedance imaging comprises: Calculating lung ventilation and non-ventilation areas according to the effective time-series image signals of the respiratory electrical impedance imaging; The effective timing diagram quality of electrical impedance imaging under the excitation mode is calculated according to the lung ventilation area and the non-ventilation area.

21. An electronic device comprising a memory and a processor; wherein: The memory is configured to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method steps according to any one of claims 1 to 10.

22. A readable storage medium having computer instructions stored thereon, wherein when the computer instructions are executed by a processor, the method steps according to any one of claims 1 to 10 are implemented.

Images