A detection method for evaluating CVAR based on MMNFC technology

Abstract

The present invention discloses a detection method for evaluating CVAR based on MMNFC technology, and relates to the technical field of stroke detection. Based on MMNFC technology, the present invention constructs a real-time monitoring device for CVAR capability consisting of a coil sensor array, an integrated monitoring hardware device, and a visual monitoring software. The coil sensor array is used as a detection device and is connected to the integrated monitoring hardware device through a radio frequency transmission line; the integrated monitoring hardware device is composed of a multi-way switch controller and a vector network analyzer to realize the acquisition of CVAR signals and send them to the visual monitoring software; the visual monitoring software is composed of a real-time monitoring unit and a multi-parameter near-field coupling data analysis unit, and the real-time monitoring unit can realize the functions of real-time display and storage of CVAR signals. Through a series of structural improvements, the present invention enables the system to solve the problems of large interference and little information in the traditional near-field coupling detection of CVAR capability when it is used.

Description

Technical Field

[0001] The present invention belongs to the technical field of stroke detection, and in particular relates to a detection method for evaluating CVAR based on MMNFC technology. Background Art

[0002] Cerebrovascular autoregulation refers to the response of the cerebrovascular system to maintain a constant cerebral blood flow, oxygen and energy delivery capacity through active dilation and contraction under the stimulation of changes in arterial blood pressure. Clinical studies have shown that stroke patients often experience a decrease in CVAR and are very susceptible to secondary brain damage when blood pressure is abnormal.

[0003] Imaging methods such as computed tomography, magnetic resonance imaging, and positron emission tomography can detect CVAR by measuring the absolute value of cerebral blood flow; however, CT, MRI, and PET are large in size and are generally fixed, so continuous bedside monitoring is not possible; transcranial Doppler uses the blood flow velocity in the cerebral vessels as an estimate of CBF to evaluate CVAR, has high temporal resolution, and is often used for intermittent monitoring; however, TCD has difficulty accurately measuring CBF when the diameter of the measured artery changes due to sympathetic nerve stimulation or infusion of vasoactive drugs; in addition, TCD cannot detect blood flow velocity in small intracranial vessels and capillaries; near-infrared spectroscopy can measure the blood content of blood vessels The changes in oxygen and deoxyhemoglobin enable continuous, non-invasive monitoring of CVAR, which presupposes that the amount of light scattering remains constant and changes in attenuation are only caused by changes in absorption. However, as time passes after a stroke, the composition of intracranial tissues changes significantly, causing changes in both light absorption and scattering. Since there is no convenient, continuous method to measure actual CBF, clinical practice uses intracranial pressure to indirectly reflect cerebral blood volume, and uses its correlation with ABP to propose the most classic and most commonly used pressure response index to achieve continuous bedside monitoring of CVAR. However, the invasiveness of intracranial pressure monitoring limits its use in neurocritical care environments.

[0004] Near-field coupling technology detects changes in the impedance characteristics of biological tissues and thus reflects the pathological conditions of biological tissues. This technology has the advantages of being non-invasive, highly penetrating, and capable of real-time continuous monitoring. CVAR produces an intracranial cerebral blood flow volume impedance response under the excitation of spontaneous oscillations of ABP, so near-field coupling technology can be used to detect CVAR capabilities. Multi-point-multi-parameter near-field coupling technology is a technology specifically built for CVAR capability detection based on the principle of near-field coupling technology. It aims to solve the problems of large interference and little information in the detection of CVAR using traditional near-field coupling technology, so as to improve the prognosis of stroke patients and reduce mortality and disability rates. Summary of the invention

[0005] The object of the present invention is to provide a detection method for evaluating CVAR based on MMNFC technology to solve the problems raised in the above background technology.

[0006] In order to solve the above technical problems, the present invention is achieved through the following technical solutions:

[0007] The present invention is a detection method for evaluating CVAR based on MMNFC technology. The method is based on MMNFC technology and constructs a real-time monitoring device for CVAR capability consisting of a coil sensor array, an integrated monitoring hardware device, and visual monitoring software;

[0008] The coil sensor array is used as a detection device and is connected to an integrated monitoring hardware device via a radio frequency transmission line;

[0009] The integrated monitoring hardware device is composed of a multi-way switch controller and a vector network analyzer, which can collect CVAR signals and send them to the visual monitoring software;

[0010] The visual monitoring software is composed of a real-time monitoring unit and a multi-parameter near-field coupling data analysis unit. The real-time monitoring unit can realize functions such as real-time display and storage of CVAR signals, and the multi-parameter near-field coupling data analysis unit can realize feature processing of CVAR signals.

[0011] Furthermore, the coil sensor array uses symmetrical independent transceiver coil sensors to form a 2×2 coil sensor array, and each coil has an excitation coil and a receiving coil.

[0012] Furthermore, the excitation coil is used to transmit the excitation signal, which passes through the subject to form a main field, and then the receiving coil receives the superposition of the main magnetic field directly coupled and the disturbance field generated by the biological tissue as a dielectric, and is connected to the multi-way switch controller through a radio frequency transmission line to realize multi-channel data acquisition through the multi-way switch controller.

[0013] Furthermore, the multi-channel switch controller adopts a one-transmit-multiple-receive method to collect signals, which can realize the collection of signals from different channels, and can quickly complete the collection and processing of multiple channels of signals with only one vector network analyzer.

[0014] Furthermore, the vector network analyzer, the excitation signal generated inside it is sent out from one of the ports, transmitted to the excitation coil of the transceiver coil, and produces a coupling effect under the action of the near field, so that the radio frequency signal received by the receiving coil is changed; the signal in the receiving coil is then transmitted into the analyzer through another port; the collected signal can be processed and displayed by connecting to the PC through the visual monitoring software.

[0015] Furthermore, the real-time monitoring unit is designed based on LabVIEW software and can realize multi-channel synchronous measurement.

[0016] Furthermore, the multi-parameter near-field coupling data analysis unit performs analysis according to the measured amplitude-frequency characteristics and phase-frequency characteristics of the MMNFC data.

[0017] Furthermore, the amplitude-frequency characteristic reflects the CVAR capability by analyzing the amplitude, frequency, and 3dB bandwidth changes of the trough / peak of the measurement signal;

[0018] The phase-frequency characteristic reflects the CVAR capability by analyzing the phase mean of the measurement signal and following the phase change.

[0019] The present invention has the following beneficial effects:

[0020] Through a series of structural improvements, the present invention enables the system to solve the problems of large interference and little information in the traditional near-field coupling detection CVAR capability when in use, and can be used for autonomous parameter setting, data collection, and real-time display. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the accompanying drawings required for describing the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other accompanying drawings can be obtained based on these accompanying drawings without paying creative work.

[0022] Figure 1 It is a schematic diagram of the multi-point-multi-parameter near-field coupling automatic acquisition system of the present invention;

[0023] Figure 2 This is a timing diagram of the system operation of the present invention. DETAILED DESCRIPTION

[0024] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0025] See also Figure 1-2 As shown, the present invention is a detection method for evaluating CVAR based on MMNFC technology.

[0026] Based on MMNFC technology, this method constructs a real-time monitoring device for CVAR capabilities consisting of a coil sensor array, integrated monitoring hardware equipment, and visual monitoring software. Figure 1 As shown,

[0027] Among them, the coil sensor array is used as a detection device and is connected to the integrated monitoring hardware equipment through a radio frequency transmission line;

[0028] Among them, the integrated monitoring hardware equipment is composed of a multi-way switch controller and a vector network analyzer, which can collect CVAR signals and send them to the visual monitoring software;

[0029] Among them, the visual monitoring software is composed of a real-time monitoring unit and a multi-parameter near-field coupling data analysis unit. The real-time monitoring unit can realize functions such as real-time display and storage of CVAR signals, and the multi-parameter near-field coupling data analysis unit can realize feature processing of CVAR signals.

[0030] Furthermore, the coil sensor array uses symmetrical independent transceiver coil sensors to form a 2×2 coil sensor array, each coil having an excitation coil and a receiving coil;

[0031] The excitation coil is used to transmit the excitation signal, which passes through the subject to form a main field, and then the receiving coil receives the superposition of the main magnetic field directly coupled and the disturbance field generated by the biological tissue as a dielectric, and then connects to the multi-way switch controller through the radio frequency transmission line, and realizes multi-channel data acquisition through the multi-way switch controller;

[0032] Among them, the multi-channel switch controller adopts a one-transmit-multiple-receive method to collect signals, which can realize the collection of signals from different channels. It can quickly complete the collection and processing of multiple channels of signals with only one vector network analyzer;

[0033] Among them, the excitation signal generated inside the vector network analyzer is sent out from port 1 and transmitted to the excitation coil of the transceiver coil, which produces a coupling effect under the action of the near field, causing the RF signal received by the receiving coil to change; the signal in the receiving coil is then transmitted to the analyzer through port 2; the collected signal can be processed and displayed through the visual monitoring software connected to the PC;

[0034] Among them, the real-time monitoring unit is designed based on LabVIEW software and can realize multi-channel synchronous measurement, such as Figure 2As shown; first connect A1B1, and after the switch is switched, perform the sweep-save operation to save the data; then switch to A1B2, and after the switch is switched, perform the sweep-save operation, and then switch to A1B3, A1B4, A2B1, ..., A4B4 in turn, and after the switch is completed, perform the sweep-save operation to save the data in each file in turn. After a measurement sequence is completed, wait for the time interval, and then start the next measurement sequence. The measured and saved data can be used by the multi-parameter near-field coupling analysis unit to realize the multi-parameter evaluation of CVAR capability.

[0035] Among them, the multi-parameter near-field coupling data analysis unit performs analysis based on the amplitude-frequency characteristics and phase-frequency characteristics of the measured MMNFC data;

[0036] Among them, the amplitude-frequency characteristic reflects the CVAR capability by analyzing the amplitude, frequency, and 3dB bandwidth changes of the trough / peak of the measurement signal;

[0037] Among them, the phase-frequency characteristic reflects the CVAR capability by analyzing the phase mean of the measurement signal and following the phase change; the multi-parameter evaluation of the CVAR capability can be achieved by analyzing the amplitude-frequency characteristic and the phase-frequency characteristic.

[0038] One of the embodiments of this system is: connect the coil sensor, multi-way switch controller, vector network analyzer through the radio frequency transmission line and connect to the computer through the port, run LabVIEW and MATLAB software programs in the computer; set the measurement parameters and calibrate the vector network analyzer, set the parameters in the LabVIEW interface: the starting frequency is 50MHz, the cut-off frequency is 60MHz, the bandwidth is 10KHz, the number of measurement points is 301, the scanning interval is 1S, and load the calibration file, control the switch, select S21, S11 waveform analysis, and then perform detection; use MATLAB software programming to extract features from the collected data, and the characteristic indicators of each trough / peak of the reflection parameter and each peak of the transmission parameter: amplitude-frequency characteristics: amplitude, frequency, and 3dB bandwidth of the trough / peak. Phase-frequency characteristics: phase mean, follow the phase mean; the five characteristic parameters can be analyzed, and then it can have the advantages of non-invasive, real-time continuous, and non-contact, so as to make up for the problems of large interference and little information in traditional near-field coupling detection methods. Provide a new solution to improve the prognosis of stroke patients;

[0039] As shown in Tables 1-5, CVAR capability was tested on 10 healthy volunteers in two states: Valsalva respiration and normal breathing. Taking subject 2 as an example, the P values ​​of characteristic parameters frequency, 3dB bandwidth, phase mean and follow-up phase mean were all less than the significant level of 0.05, indicating that the four characteristic parameters had significant differences in the two states, which means that this method can evaluate CVAR capability. Other subjects also showed significant differences in different characteristics to varying degrees. The statistical analysis results of CVAR capability in the two states showed that the device could detect CVAR capability, verifying the feasibility of the experiment using MMNFC to monitor CVAR capability.

[0040] Table 1 Test parameters of amplitude in two states

[0041]

[0042] Table 2 Test parameters of frequency points in two states

[0043]

[0044] Table 3 3dB bandwidth test parameters in two states

[0045]

[0046]

[0047] Table 4 Test parameters of phase mean in two states

[0048]

[0049]

[0050] Table 5 Test parameters of the following phase mean in two states

[0051]

[0052] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the present invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0053] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the present invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A detection method for evaluating CVAR based on MMNFC technology, characterized in that: The method uses MMNFC technology to build a real-time monitoring device for CVAR capabilities consisting of a coil sensor array, integrated monitoring hardware equipment, and visual monitoring software; The coil sensor array is used as a detection device and is connected to an integrated monitoring hardware device via a radio frequency transmission line; The integrated monitoring hardware device is composed of a multi-way switch controller and a vector network analyzer, which can collect CVAR signals and send them to the visual monitoring software; The visual monitoring software is composed of a real-time monitoring unit and a multi-parameter near-field coupling data analysis unit. The real-time monitoring unit realizes the real-time display and storage functions of the CVAR signal, and the multi-parameter near-field coupling data analysis unit realizes the feature processing of the CVAR signal; The coil sensor array uses symmetrical independent transceiver coil sensors to form a 2×2 coil sensor array, each coil having an excitation coil and a receiving coil; The excitation coil is used to transmit the excitation signal, pass through the subject to form a main field, and then the receiving coil receives the superposition of the main magnetic field directly coupled and the disturbance field generated by the biological tissue as a dielectric, and is connected to the multi-way switch controller through the radio frequency transmission line, and the multi-way switch controller is used to realize multi-channel data acquisition; The multi-channel switch controller uses a one-transmit-multiple-receive method to collect signals, thereby collecting signals from different channels, and quickly completing the collection and processing of multiple channels of signals with only one vector network analyzer. The multi-parameter near-field coupling data analysis unit performs analysis based on the measured MMNFC data amplitude-frequency characteristics and phase-frequency characteristics; The amplitude-frequency characteristic reflects the CVAR capability by analyzing the amplitude, frequency, and 3dB bandwidth changes of the trough / peak of the measurement signal; The phase-frequency characteristic reflects the CVAR capability by analyzing the phase mean of the measurement signal and following the phase change.

2. A detection method for evaluating CVAR based on MMNFC technology according to claim 1, characterized in that: The vector network analyzer generates an excitation signal from one of its ports and transmits it to the excitation coil of the transceiver coil, generating a coupling effect under the action of the near field, causing the radio frequency signal received by the receiving coil to change; the signal in the receiving coil is then transmitted into the analyzer through another port; the PC is connected to process and display the collected signal through visual monitoring software.

3. The detection method for evaluating CVAR based on MMNFC technology according to claim 1, characterized in that: The real-time monitoring unit is designed based on LabVIEW software to achieve multi-channel synchronous measurement.

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