Monitoring method and system based on holographic phase Hilbert spectrum analysis

Abstract

The invention provides a monitoring method based on holographic phase Hilbert spectrum analysis. The monitoring method comprises the following steps: introducing a stimulation signal; acquiring an electroencephalogram signal based on the stimulation signal; the holographic phase Hilbert spectrum analysis comprises the following steps: performing first-layer decomposition on the electroencephalogram signal by adopting a mode decomposition method to obtain a first-layer mode component which comprises a plurality of first-layer mode functions; calculating an envelope line of the first-layer mode function, and performing second-layer decomposition on the envelope line by adopting a mode decomposition method to obtain a second-layer mode component which comprises a plurality of second-layer mode functions; and constructing a holographic phase Hilbert spectrum for analyzing the relationship between the stimulation signal and the electroencephalogram signal.

Description

Technical Field

[0001] The present application belongs to the field of data monitoring, such as medical data monitoring, and relates to a monitoring method and system based on holographic phase Hilbert spectrum analysis. Background Art

[0002] Complex systems generate complex signals (see Oppenheim et al. 1997; Drazin 1992), in which amplitude modulation and cross-frequency coupling are inevitable. This is true for everything from coupled oscillators (Drazin 1992) to the Earth system (Cornell et al. 2012) and the human brain (Buzsaki 2006).

[0003] The brain is considered the most complex system in the universe. Existing evidence indicates that cross-frequency coupling (CFC) is closely related to various brain functions: cognition, perception, and memory. As an indicator of brain state, modulated EEG signals can be easily measured non-invasively. In response to stimulation with light, electricity, or sound, the brain's scalp EEG potential changes, a phenomenon widely used in brain-computer interfaces (BCIs) and medical applications. For example, the visual steady-state evoked potential (SSVEP) under light stimulation can be used for command recognition, as can the auditory steady-state evoked potential (ASSR) under sound stimulation. Furthermore, electrical stimulation can treat major depression. However, when the brain is stimulated by light, electricity, or sound, quantifying the relationship between the brain's response and the stimulus itself is a challenge. Unraveling the causal relationship between the stimulus and the brain's response allows feedback adjustments to obtain a better brain response.

[0004] Under stimulation conditions, the brain scalp EEG signals monitored can be analyzed using holographic Hilbert spectrum in the prior art (e.g., CN105095559A) to reveal the modulation phenomenon of the EEG signals, revealing all possible coupling frequency pairs involved in cross-frequency coupling (CFC). From the definition of holographic Hilbert spectrum, it can be seen that its core lies in the modulation frequency and amplitude modulation frequency. The modulation frequency is the frequency of the intrinsic mode function itself, and the amplitude modulation frequency is the frequency of the intrinsic mode function of the envelope of the intrinsic mode function. It is an adaptive data analysis method for analyzing the modulation state of the signal itself, but it cannot be used to analyze the relationship between two signals. Under specific stimulation conditions, how the stimulation signal affects the brain scalp EEG signals requires studying the relationship between the two signals, which has also become a difficult problem to analyze. Summary of the Invention

[0005] In order to overcome some problems existing in the prior art, the present application provides a monitoring method and system based on holographic phase Hilbert spectrum analysis, which can reflect the relationship between stimulation signals and EEG signals.

[0006] In a first aspect, the present application provides a monitoring method based on holographic phase Hilbert spectrum analysis, comprising the following steps:

[0007] Introduction of S100 stimulation signal;

[0008] S200: obtaining an EEG signal; stimulating the monitored subject with the stimulation signal to synchronously obtain an EEG signal of the monitored subject; and

[0009] S300 holographic phase Hilbert spectrum analysis, which includes the following steps:

[0010] First-layer decomposition: The modal decomposition method is used to perform the first-layer decomposition of the EEG signal to obtain the first-layer modal component, which contains multiple first-layer modal functions;

[0011] Second-level decomposition: Calculate the envelope of the first-level modal function to obtain an envelope line; perform a second-level decomposition of the envelope line using a modal decomposition method to obtain a second-level modal component, which contains multiple second-level modal functions; and

[0012] Constructing the holographic phase Hilbert spectrum to analyze the relationship between the stimulation signal and the EEG signal; specifically,

[0013] When the multi-dimensionality includes a reference phase, calculating the instantaneous phase of the amplitude modulation signal of the stimulation signal as the reference phase;

[0014] When the multi-dimensional matrix includes a modulation frequency, the instantaneous frequency of the first-layer modal function is calculated as the modulation frequency;

[0015] When the multi-dimensionality includes a frequency modulation phase, calculating the instantaneous phase of the first layer mode function as the frequency modulation phase;

[0016] When the multi-dimensional data includes an amplitude modulation frequency, the instantaneous frequency of the second-layer modal function is calculated as the amplitude modulation frequency;

[0017] When the multi-dimensionality includes an amplitude modulation phase, calculating the instantaneous phase of the second-layer modal function as the amplitude modulation phase; and

[0018] Based on at least two of the six dimensions of the reference phase, modulation frequency, frequency modulation phase, amplitude modulation frequency, amplitude modulation phase and time, a multidimensional spatial energy distribution about the at least two dimensions is obtained,

[0019] This energy is the amplitude of the envelope of the second-layer modal component; thus, the holographic phase Hilbert spectrum is obtained.

[0020] The multidimensional spatial energy distribution can be a multidimensional spatial energy distribution with respect to at least two dimensions of the reference phase, modulation frequency, FM phase, AM frequency, AM phase, and time. For example, it can be a two-dimensional spatial energy distribution with respect to the FM phase and reference phase, a two-dimensional spatial energy distribution with respect to the reference phase and time, a two-dimensional spatial energy distribution with respect to the FM phase, reference phase, and time, as well as other four, five, or all six dimensions. When only certain dimensions of spatial energy distribution are involved, the other dimensions do not need to be calculated in the step of constructing the holographic phase Hilbert spectrum. For example, when the obtained holographic phase Hilbert spectrum is a three-dimensional spatial energy distribution with respect to the reference phase, AM phase, and time, the modulation frequency, FM phase, and AM frequency do not need to be calculated. That is, the instantaneous frequency of the first-layer modal function, the instantaneous phase of the first-layer modal function, and the instantaneous frequency of the second-layer modal function do not need to be calculated in this step. This is easy to understand.

[0021] In one embodiment, in step S300:

[0022] In the second-layer decomposition, the envelope of at least one first-layer modal function in the first-layer modal components is calculated to obtain an envelope line; the envelope line is subjected to a second-layer decomposition using a modal decomposition method to obtain a second-layer modal component, which includes a plurality of second-layer modal functions; the at least one first-layer modal function is the most important component of the EEG signal;

[0023] as well as,

[0024] Constructing the holographic phase Hilbert spectrum specifically includes the following steps:

[0025] When the multi-dimensionality includes a reference phase, calculating the instantaneous phase of the amplitude modulation signal of the stimulation signal as the reference phase;

[0026] When the multi-dimensionality includes a modulation frequency, calculating the instantaneous frequency of the at least one first-layer modal function as the modulation frequency;

[0027] When the multi-dimensionality includes a frequency modulation phase, calculating the instantaneous phase of the at least one first-layer modal function as the frequency modulation phase;

[0028] When the multi-dimensional data includes amplitude modulation frequency, the instantaneous frequency of the second-layer modal component is calculated, and the instantaneous frequencies of several second-layer modal functions are selected as the amplitude modulation frequency;

[0029] When the multi-dimensionality includes an amplitude modulation phase, the instantaneous phase of the second-layer modal component is calculated, and the instantaneous phase of one of the second-layer modal functions is selected as the amplitude modulation phase; the period of the selected second-layer modal function is closest to the period of the amplitude modulation signal of the stimulation signal; and

[0030] Based on at least two of the six dimensions of the reference phase, modulation frequency, FM phase, AM frequency, AM phase and time, a multidimensional spatial energy distribution about the at least two dimensions is obtained, and the energy is the amplitude of the envelope of the second-layer modal component; thereby obtaining the holographic phase Hilbert spectrum; analyzing the holographic phase Hilbert spectrum to obtain the relationship between the stimulation signal and the EEG signal.

[0031] In one embodiment, the holographic phase Hilbert spectrum is a multidimensional spatial energy distribution with respect to at least one of a reference phase, an amplitude modulation phase, and a frequency modulation phase. Optionally, the holographic phase Hilbert spectrum is a multidimensional spatial energy distribution with respect to at least the reference phase. Optionally, the holographic phase Hilbert spectrum is a multidimensional spatial energy distribution with respect to at least the reference phase and the amplitude modulation phase. Optionally, the holographic phase Hilbert spectrum is a multidimensional spatial energy distribution with respect to at least the reference phase and the modulation frequency. Optionally, the holographic phase Hilbert spectrum is a multidimensional spatial energy distribution with respect to at least the reference phase and the amplitude modulation frequency.

[0032] In one embodiment, the stimulation signal is obtained by modulating a carrier signal with the amplitude modulation signal.

[0033] In one embodiment, the period of the selected at least one first layer modal function is closest to the period of the carrier signal of the stimulation signal.

[0034] In one embodiment, the stimulation signal is at least one of a light signal, a sound signal, and an electrical signal.

[0035] In one embodiment, in the step S200, the EEG signal may be preprocessed, and the preprocessing includes at least one of filtering, notching, outlier removal and electrical noise removal; and the step S300 performs holographic phase Hilbert spectrum analysis on the preprocessed EEG signal.

[0036] In one embodiment, in the first-layer decomposition step, EMD or EEMD is used to perform a first-layer decomposition of the EEG signal, and the obtained first-layer modal components include multiple intrinsic mode functions or multiple collective intrinsic mode functions, which are respectively used as the multiple first-layer modal functions; in the second-layer decomposition step, EMD or EEMD is used to perform a second-layer decomposition of the envelope line, and the obtained second-layer modal components include multiple intrinsic mode functions or multiple collective intrinsic mode functions, which are respectively used as the multiple second-layer modal functions.

[0037] In one embodiment, in step S300, a six-dimensional spatial energy distribution of AM frequency-modulation frequency-AM phase-FM phase-reference phase-time is obtained, where the energy is the amplitude of the envelope of the second-layer modal component, thereby obtaining the holographic phase Hilbert spectrum; the holographic phase Hilbert spectrum is integrated over N dimensions to obtain holographic phase Hilbert spectra for the remaining 6-N dimensions; N is a positive integer less than 6. The difference between this and the previous embodiment is that the previous solution may directly obtain a two-dimensional spatial energy distribution, a three-dimensional spatial energy distribution, a four-dimensional spatial energy distribution, a five-dimensional spatial energy distribution, or a six-dimensional spatial energy distribution; however, this embodiment first directly obtains a six-dimensional spatial energy distribution, and then obtains spatial energy distributions of other dimensions through integration; although the result is the same, the process is different.

[0038] In one embodiment, N=4.

[0039] In one embodiment, the 6-N dimensions include at least one of an amplitude modulation phase, a frequency modulation phase, and a reference phase. Optionally, the 6-N dimensions include at least a reference phase.

[0040] A second aspect of the present application provides a monitoring system based on holographic phase Hilbert spectrum analysis, capable of implementing the monitoring method described in any of the above embodiments, the monitoring system comprising:

[0041] A stimulation signal module is configured to generate a stimulation signal;

[0042] The data acquisition module is configured to: synchronously acquire an EEG signal of the monitored subject when the stimulation signal stimulates the monitored subject;

[0043] The data processing module is configured for holographic phase Hilbert spectrum analysis, specifically,

[0044] The modal decomposition method is used to decompose the EEG signal into the first layer to obtain the first layer modal component, which contains multiple first layer modal functions;

[0045] Calculate the envelope of the first-layer modal function to obtain an envelope line; perform a second-layer decomposition of the envelope line using a modal decomposition method to obtain a second-layer modal component, which contains multiple second-layer modal functions;

[0046] Calculating the instantaneous phases of the first layer modal function, the second layer modal function, and the amplitude modulation signal of the stimulation signal, respectively, and calculating the instantaneous frequencies of the first layer modal function and the second layer modal function, respectively; and,

[0047] Construct a holographic phase Hilbert spectrum to analyze the relationship between the stimulation signal and the EEG signal; specifically,

[0048] Selecting the instantaneous phase of the amplitude modulation signal of the stimulation signal as the reference phase;

[0049] Select the instantaneous frequency of the first layer modal function as the modulation frequency, and its instantaneous phase as the FM phase;

[0050] Selecting the instantaneous frequency of the second layer mode function as the amplitude modulation frequency, and its instantaneous phase as the amplitude modulation phase; and,

[0051] Obtaining a multidimensional spatial energy distribution in at least two dimensions of the six dimensions of reference phase, modulation frequency, frequency modulation phase, amplitude modulation frequency, amplitude modulation phase, and time, wherein the energy is the amplitude of the envelope of the second-layer modal component; thereby obtaining a holographic phase Hilbert spectrum; and

[0052] The result output module is configured to output the holographic phase Hilbert spectrum to display the monitoring results.

[0053] In one embodiment, the monitoring system further includes a data comparison module configured to compare the monitoring results, thereby analyzing the response ability of the monitored subject to the stimulation signal.

[0054] In one embodiment, the reaction capability includes one or more of reaction time, reaction intensity, and reaction threshold.

[0055] In addition, many embodiments of the monitoring method can also be reasonably combined with the monitoring system, which will not be described in detail here.

[0056] A third aspect of the present application provides an application of the monitoring method described in any of the foregoing embodiments, wherein the monitoring method can be used to monitor at least one of the reaction time, reaction intensity, and reaction threshold of a monitored subject to a stimulation signal.

[0057] In one embodiment, the monitoring method can be used for screening a monitored subject, or obtaining medical detection parameters of a monitored subject.

[0058] In a fourth aspect, the present application provides a computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the monitoring method as described in any of the foregoing embodiments when executing the computer program.

[0059] In a fifth aspect, the present application provides a computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the monitoring method as described in any of the above embodiments.

[0060] At least one embodiment of the present application provides a monitoring method or system based on holographic phase Hilbert spectrum analysis, which introduces the concept of phase and can solve the problem that the existing holographic Hilbert spectrum cannot solve the correlation between stimulus signals and response signals.

[0061] The monitoring method or system based on holographic phase Hilbert spectrum analysis provided by at least one embodiment of the present application can qualitatively and quantitatively judge the relationship between the five senses (such as vision, hearing, touch, smell, and taste) and brain electrical signals, thereby being able to judge a person's sensitivity to the five senses, as well as the intensity of the reaction, etc.; it can be used to screen talents for brain-computer interfaces and medical fields; for example, when a person is more sensitive to stimuli such as light and electricity, and the intensity is high, it largely indicates that the person is sensitive to reactions and is suitable for brain-computer interfaces, and the talent can be screened as a candidate for controlling drones, etc. BRIEF DESCRIPTION OF THE DRAWINGS

[0062] Figure 1 is a flow chart of a monitoring method according to one embodiment of the present application;

[0063] Figure 2 is a schematic diagram of a monitoring system according to one embodiment of the present application;

[0064] Figure 3 are the stimulation signal and its amplitude modulation signal, the EEG signal and its F-IMF3;

[0065] Figure 4a It is the result of the first-level decomposition of EEG signals;

[0066] Figure 4b It is the result of the second-level decomposition of the envelope of F-IMF3;

[0067] Figure 5a is the F-IMF3 and its envelope S-IMF3.3, as well as the amplitude modulation signal of the stimulus signal;

[0068] Figure 5b is the phase of F-IMF3 and its envelope S-IMF3.3, as well as the phase of the amplitude modulation signal of the stimulus signal;

[0069] Figure 6a is the instantaneous frequency of F-IMF3 and its S-IMFs;

[0070] Figure 6b is the instantaneous phase of the amplitude modulation signal of the stimulus signal, as well as the instantaneous phase of the F-IMF3 and its S-IMFs;

[0071] Figure 6c is the instantaneous amplitude of the S-IMFs of F-IMF3 (amplitude of the envelope);

[0072] Figure 7a is the FM-AM-holographic phase Hilbert spectrum of F-IMF3;

[0073] Figure 7b is the FM-RP-holographic phase Hilbert spectrum of F-IMF3;

[0074] Figure 7c is the AM-RP-holographic phase Hilbert spectrum of F-IMF3;

[0075] Figure 8a is the AMP-RP-holographic phase Hilbert spectrum of F-IMF3;

[0076] Figure 8b is the diagonalized-phase-holographic phase Hilbert spectrum;

[0077] Figure 8c is the centralization-phase-holographic phase Hilbert spectrum;

[0078] Figure 9 It is a connection diagram of computer equipment. DETAILED DESCRIPTION

[0079] In order to make the purpose, technical solutions and advantages of this application more clear, the following description and explanation of this application are made in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain this application and are not intended to limit this application. Based on the embodiments provided in this application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of this application.

[0080] Obviously, the drawings described below are merely examples or implementations of the present application. A person skilled in the art can apply the present application to other similar scenarios based on these drawings without inventive effort. Furthermore, it is understood that, although the effort involved in such a development process may be complex and lengthy, for a person skilled in the art related to the content disclosed in the present application, changes in design, manufacturing, or production based on the technical content disclosed in the present application are merely conventional technical means and should not be construed as an insufficiency of the content disclosed in the present application.

[0081] References to "embodiments" in this application mean that a particular feature, structure, or characteristic described in conjunction with the embodiment may be included in at least one embodiment of the application. The appearance of this phrase in various places in the specification does not necessarily refer to the same embodiment, nor does it refer to independent or alternative embodiments that are mutually exclusive with other embodiments. It is understood, both explicitly and implicitly, by those skilled in the art that the embodiments described in this application may be combined with other embodiments, unless there is a conflict.

[0082] Unless otherwise defined, the technical terms or scientific terms involved in this application should be understood by people with ordinary skills in the technical field to which this application belongs. The words "one", "a", "the" and the like involved in this application do not indicate a quantitative limitation and may represent the singular or plural. The terms "include", "comprise", "have" and any of their variations involved in this application are intended to cover non-exclusive inclusions; for example, a process, method, system, product or device that includes a series of steps or modules (units) is not limited to the listed steps or units, but may also include steps or units that are not listed, or may also include other steps or units that are inherent to these processes, methods, products or devices. The words "connect", "connected", "coupled" and the like involved in this application are not limited to physical or mechanical connections, but may include electrical connections, whether direct or indirect. The "multiple" involved in this application refers to two or more. "And / or" describes the association relationship of associated objects, indicating that three relationships can exist.

[0083] By observing the relationship between stimulus signals and EEG signals, the brain's sensitivity to these stimuli can be monitored. For example, by monitoring the relationship between the five senses (sight, hearing, touch, smell, and taste) and EEG signals, the relationship between the five senses and the brain's electrical signals can be qualitatively and / or quantitatively determined, thereby determining the reaction time and intensity of the monitored subject to the five senses. On this basis, it can be used to screen for talent suitable for brain-computer interfaces and other medical applications. For example, when a person being monitored is sensitive to stimuli such as light and electricity, and has a short reaction time and high intensity, it largely indicates that the person is responsive and suitable for brain-computer interfaces. This person can be screened as a candidate for controlling drones (i.e., using human EEG signals to control drones). Moreover, the EEG signals generally use non-invasive EEG signals (scalp EEG), which are very safe for the monitored subject.

[0084] The first embodiment of the present application provides a monitoring method based on holographic phase Hilbert spectral analysis (hereinafter referred to as the monitoring method). Figure 1This is a flow chart of the monitoring method according to the present embodiment. It should be noted that the steps shown in the flow chart of the monitoring method or the accompanying drawings can be executed in a computer system such as a set of computer executable instructions. This embodiment is mainly described by taking the six-dimensional spatial energy distribution of amplitude modulation frequency (AM)-modulation frequency (FM)-amplitude modulation phase (AMP)-frequency modulation phase (FMP)-reference phase (RP)-time (T) as an example. It is easy to understand that the corresponding subtraction can be performed for other dimensions. The monitoring method includes the following steps:

[0085] Introduction of S100 stimulation signal:

[0086] A stimulation signal is introduced; this stimulation signal can be light, sound, electricity, or other signals that can stimulate the human body's five senses. Because the stimulation signal is actively introduced, its parameters can be obtained, including but not limited to amplitude, frequency, and phase. The amplitude modulation signal and carrier signal of the stimulation signal can also be determined, and its amplitude, frequency, period, and other parameters can be obtained. The stimulation signal is generally simulated and has a corresponding generation formula, that is, it is generated through a control equation.

[0087] Acquisition of S200 EEG signals:

[0088] The monitored subject is stimulated by a stimulation signal, and the EEG signal of the monitored subject is synchronously acquired. Both the stimulation signal and the EEG signal are data about time T.

[0089] Furthermore, the obtained EEG signals can be pre-processed to reduce external interference. For example, data pre-processing can be performed by filtering, notching, outlier removal, and electrical noise removal.

[0090] S300 holographic phase Hilbert spectrum analysis:

[0091] S301: performing a first-layer decomposition on the preprocessed EEG signal using a modal decomposition method to obtain a first-layer modal component, which includes a plurality of first-layer modal functions (F-IMFs).

[0092] Specifically, the Empirical Mode Decomposition (EMD) or Ensemble Empirical Mode Decomposition (EEMD) method can be used to perform a first-level decomposition of the preprocessed EEG signal. The EMD or EEMD method for data decomposition can refer to CN119969961A, thereby obtaining the first-level modal components, which contain multiple intrinsic mode functions or multiple ensemble intrinsic mode functions as F-IMFs.

[0093] S302: Calculate the envelope of at least one of the multiple first-layer modal functions (F-IMFs) to obtain an envelope line; use a modal decomposition method to perform a second-layer decomposition on the envelope line to obtain a second-layer modal component, which includes multiple second-layer modal functions (S-IMFs).

[0094] The steps for calculating the envelope of any function and obtaining the envelope curve are as follows:

[0095] (1) Take the absolute value of the function;

[0096] (2) determine all the maximum values ​​of the absolute value of the function;

[0097] (3) The envelope is constructed by the natural spline function of all maximum values ​​to obtain the envelope line (F-IMFs-Envelope).

[0098] Therefore, for any first-layer modal function in this embodiment, (1) the absolute value of the first-layer modal function is taken; (2) all maximum values ​​of the absolute value of the first-layer modal function are determined; (3) an envelope is constructed through the natural spline function of all maximum values ​​to obtain the envelope line (F-IMFs-Envelope) of the first-layer modal function.

[0099] In one embodiment, after obtaining the envelope of the first-layer modal function, a second-layer decomposition can be performed using the empirical mode decomposition (EMD) method or the ensemble empirical mode decomposition (EEMD) method. The decomposition of data using the EMD or EEMD method can also refer to CN119969961A, thereby obtaining a second-layer modal component, which includes multiple intrinsic mode functions or multiple ensemble intrinsic mode functions as S-IMFs.

[0100] S303: Calculate the instantaneous phase of the first-layer modal function (F-IMFs), the second-layer modal function (S-IMFs) and the amplitude modulation signal of the stimulation signal respectively, and calculate the instantaneous frequency of the first-layer modal function (F-IMFs) and the second-layer modal function (S-IMFs) respectively.

[0101] When calculating the instantaneous phase, an instantaneous phase calculation method is used, such as Hilbert transform or direct quadrature method. Similarly, when calculating the instantaneous frequency, an instantaneous frequency calculation method is used, such as Hilbert transform or direct quadrature method.

[0102] Since the stimulation signal is generated by the control equation and its amplitude modulation signal is known, the instantaneous phase of the amplitude modulation signal of the stimulation signal can be directly obtained using the instantaneous phase calculation method.

[0103] S304: Constructing a holographic phase Hilbert spectrum for analyzing the relationship between the stimulation signal and the EEG signal; specifically:

[0104] (1) Select the instantaneous phase of the amplitude modulation signal of the stimulation signal as the reference phase (RP);

[0105] (2) selecting the instantaneous frequency of at least one first-layer modal function in the first-layer modal components as the modulation frequency (FM), and the instantaneous phase thereof as the frequency modulation phase (FMP);

[0106] In one embodiment, at least one selected first-layer modal function is the most important component of the EEG signal; for example, when one first-layer modal function is selected, it is the most important component of the EEG signal, and when two first-layer modal functions are selected, they are respectively the first and second most important components of the EEG signal, and so on.

[0107] In one embodiment, the stimulation signal is obtained by modulating a carrier signal with an amplitude modulation signal, and the period of the selected at least one first layer mode function is closest to the period of the carrier signal. Preferably, the stimulation signal is an optical signal.

[0108] (3) selecting the instantaneous frequency of all second-level modal functions (S-IMFs) corresponding to the at least one first-level modal function as the amplitude modulation frequency (AM);

[0109] selecting an instantaneous phase of one of the second-layer modal functions in the second-layer modal components as an amplitude modulation phase (AMP); wherein a period of the selected second-layer modal function is closest to a period of the amplitude modulation signal of the stimulation signal;

[0110] (4) The six-dimensional spatial energy distribution of amplitude modulation frequency (AM)-modulation frequency (FM)-amplitude modulation phase (AMP)-frequency modulation phase (FMP)-reference phase (RP)-time (T) is obtained, and the energy is the amplitude of the envelope of the second-layer modal component; thereby obtaining the holographic phase Hilbert spectrum, which contains phase information. Among them, the calculation method of the envelope of the second-layer modal component is the same as the calculation method of the envelope of any function described above, and the envelope of each second modal function is calculated separately. It is worth noting that since the stimulation signal and the EEG signal are data distributed over time (T), the various parameters such as frequency and phase obtained are also data distributed over time (T), which is well known or easy to understand to those skilled in the art.

[0111] Furthermore, the integrated holographic phase Hilbert spectrum can be obtained by integrating over one or more dimensions. For example, after integrating over the four dimensions of AMP, FMP, RP, and T, AM and FM remain. This integrated holographic phase Hilbert spectrum is called the "AM-FM-holographic phase Hilbert spectrum."

[0112] In one embodiment, the holographic phase Hilbert spectrum is integrated over N dimensions to obtain holographic phase Hilbert spectra over the remaining 6-N dimensions; N is a positive integer less than 6.

[0113] In one embodiment, N=4.

[0114] In one embodiment, the 6-N dimensions include at least one of an amplitude modulation phase (AMP), a frequency modulation phase (FMP), and a reference phase (RP). Preferably, at least the reference phase (RP) is included.

[0115] In one embodiment, the holographic phase Hilbert spectrum may be a holographic phase Hilbert spectrum corresponding to multiple first-layer modal functions of the first-layer modal components and multiple second-layer modal functions of the second-layer modal components; or one or more thereof. For example, the first-layer modal component has three first-layer modal functions, namely F-IMF1, F-IMF2 and F-IMF3; the envelope calculation of F-IMF1 obtains the envelope line, and the second-layer decomposition is performed on it, and the second-layer modal component obtained has two second-layer modal functions, namely S-IMF1.1 and S-IMF1.2; the envelope calculation of F-IMF2 obtains the envelope line, and the second-layer decomposition is performed on it, and the second-layer modal component obtained has four second-layer modal functions, namely S-IMF2.1, S-IMF2.2, S-IMFF2.3, and S-IMFF2.4; the envelope calculation of F-IMF3 obtains the envelope line, and the second-layer decomposition is performed on it, and the second-layer modal component obtained has three second-layer modal functions, namely S-IMF3.1, S-IMF3.2, and S-IMF3.3. When constructing the holographic phase Hilbert spectrum in S304, it can be constructed based on all the above data (that is, the holographic phase Hilbert spectrum includes all the data), or only a part of it can be used for construction, for example, only F-IMF1 and its S-IMF1.1, S-IMF1.2 can be selected for construction; or only F-IMF1 and its S-IMF1.2 can be selected for construction, mainly considering that their components are sufficiently dominant and representative.

[0116] In addition, it is worth understanding that the steps described above can be adjusted according to actual conditions, and the relevant processes do not necessarily have to be carried out according to the described steps.

[0117] The present application is described in detail below in conjunction with more specific embodiments. It is worth noting that these embodiments are merely preferred embodiments of the present application and are not to be construed as limiting the scope of protection of the present application.

[0118] Example: Monitoring method based on holographic phase Hilbert spectrum analysis

[0119] Introduction of S100 stimulation signal:

[0120] In this embodiment, a light signal (Flicker) is used as a stimulus signal, the monitored object is a human body, and its eyes receive the light signal as an example for analysis and explanation, so as to understand the technical solution of the present application in more detail. Figure 3 The blue curve in the figure is the light signal used as the stimulation signal. It is a known analog signal generated by the control equation with a frequency of 1000 Hz and a stimulation window of 2 seconds. Therefore, its time series length T is 2000 data points (referred to as time T = 2000).

[0121] Specifically, the optical signal (Flicker, Figure 3 The blue curve in the figure is a 16Hz sine wave (i.e., carrier signal) modulated by a 3Hz sine wave (i.e., amplitude modulated signal FlickerAM). Figure 3 The red curve in the figure shows that the modulation frequency of the optical signal is 16 Hz and the amplitude modulation frequency (envelope frequency) is 3 Hz, which is known information.

[0122] Acquisition of S200 EEG signals:

[0123] After the eyes receive the light signal (Flicker), the brain will react accordingly. Electrodes for collecting EEG signals are attached to the scalp (non-invasively) to collect EEG signals. Considering that light signal stimulation is highly correlated with the occipital lobe of the brain, Figure 2 Electrode Oz is placed near the occipital lobe of the brain. For other stimulation signals, EEG signals from other corresponding areas can be collected. For example, electrical stimulation is highly correlated with the frontal lobe of the brain, so the electrodes can be placed on the scalp near the frontal lobe.

[0124] One end of the amplifier connects to the electrodes to collect and amplify EEG signals, while the other end connects to the data interface of a computer (PC) for transmission. The PC includes a data interface, a data processing module, and a PC monitor (displaying real-time data and data analysis reports), all of which are standard features. Corresponding to the optical signal, the EEG signal sampling frequency is 1000 Hz, and the stimulation window is set to 2 seconds (5 seconds, 10 seconds, etc. can also be set according to actual needs). This means that the time series length T is 2000 data points, that is, the time T is 2000.

[0125] In order to reduce the drift effect of data and the messy high-frequency information, the obtained EEG data can also be preprocessed, such as performing a 0.5 Hz high-pass filter and a 50 Hz low-pass filter on the EEG.

[0126] Figure 3 The black curve in the figure is the data after preprocessing the collected EEG signal (preprocessed EEG); since it is an EEG signal stimulated by a light signal, it is also called a visual steady-state evoked potential (SSVEP).

[0127] S300 holographic phase Hilbert spectrum analysis:

[0128] S301: performing a first-layer decomposition of the pre-processed EEG using EEMD to obtain first-layer modal components, including multiple first-layer modal functions (F-IMFs). Figure 4a It is the first-layer modal component obtained after the first-layer decomposition, which contains six collective intrinsic mode functions, namely F-IMF1 to F-IMF6.

[0129] S302: Calculate the envelope of each F-IMFs to obtain the corresponding envelope line; use EEMD to perform a second-level decomposition on the envelope line of each F-IMFs to obtain the second-level modal components respectively; each second-level modal component contains multiple second-level modal functions (S-IMFs). Figure 4b Yes Figure 4a The second-level modal components obtained by performing the second-level decomposition of F-IMF3 in the formula include five collective intrinsic mode functions, namely S-IMF3.1 to S-IMF3.5. Other F-IMFs can also be decomposed accordingly to obtain the corresponding second-level modal components. Figure 4a As shown, since F-IMF3 is the most important component of the EEG signal and its period is closest to the period of the carrier signal of the stimulation signal, it is selected as the first-layer modal function in this embodiment; in addition, for the convenience of explanation, the following mainly uses F-IMF3 as an example.

[0130] In the above steps, the calculation of the envelope of each F-IMFs includes the following steps: taking the absolute value of each F-IMF, determining all the maximum values ​​of the absolute values ​​of the F-IMF, constructing the envelope through the natural spline function of all the maximum values, and obtaining the envelope.

[0131] S303: Calculate the instantaneous frequency and instantaneous phase of the F-IMFs and S-IMFs respectively using Hilbert transform or direct quadrature method; calculate the instantaneous phase of the amplitude modulation signal of the stimulation signal using Hilbert transform or direct quadrature method.

[0132] The instantaneous frequency and instantaneous phase of F-IMF3 and its S-IMFs are calculated respectively, as well as the instantaneous phase of the amplitude modulation signal (FlickerAM) of the optical signal. The results are shown in Figure 6a , Figure 6b and Figure 6c ;in,

[0133] Figure 6a The instantaneous frequency of F-IMF3 and the instantaneous frequencies of the S-IMFs (S-IMF3.1 to S-IMF3.4) of F-IMF3 are shown in Figure 2; S-IMF3.5 of F-IMF3 is omitted because it is a residual term.

[0134] Figure 6b The figure shows the instantaneous phase of FlickerAM, the instantaneous phase of F-IMF3, and the instantaneous phase of S-IMFs (S-IMF3.1 to S-IMF3.4) of F-IMF3; similarly, S-IMF3.5 is a residual term and is omitted.

[0135] Figure 6c Figure 3 shows the instantaneous amplitudes of the S-IMFs (S-IMF3.1 to S-IMF3.4) of F-IMF3, i.e., the amplitudes of the envelopes of each S-IMF. Similarly, the envelopes of each S-IMF are calculated in the same way as for any intrinsic mode function described above.

[0136] S304: Construct holographic phase Hilbert spectrum:

[0137] Select the instantaneous phase of FlickerAM as the reference phase (RP);

[0138] The instantaneous frequency and instantaneous phase of F-IMF3 are selected as the modulation frequency (FM) and frequency modulation phase (FMP), respectively;

[0139] The instantaneous frequency and instantaneous phase of the S-IMFs of F-IMF3 are selected as the amplitude modulation frequency (AM) and amplitude modulation phase (AMP), respectively;

[0140] The specific selection of the instantaneous frequency and instantaneous phase of the first-layer modal function in the first-layer modal component as FM and FMP mainly considers whether the selected first-layer modal function is the most important component in the first-layer modal component; in addition, for the optical signal in this embodiment, when selecting, it is also considered that the period of the first-layer modal function is closest to the period of the carrier signal of the stimulation signal.

[0141] The instantaneous frequencies of all S-IMFs (except the remainder) corresponding to the first-layer modal function are selected as AM; among these S-IMFs, the instantaneous phase of the S-IMF whose period is closest to the period of the amplitude modulation signal of the stimulus signal is selected as AMP.

[0142] For example, in this embodiment, because F-IMF3 is the most important component of the F-IMFs and its period is closest to the period of the carrier signal of the stimulus signal, the instantaneous frequency and instantaneous phase of F-IMF3 are used as FM and FMP, respectively. The instantaneous frequency of the S-IMFs (S-IMF3.1 to S-IMF3.4) of F-IMF3 is used as AM. Among them, the period of S-IMF3.3 is closest to the period of FlickerAM, so the instantaneous phase of S-IMF3.3 is selected as AMP. Of course, multiple F-IMFs can also be selected, such as selecting F-IMF2 and F-IMF3 at the same time. For the first-layer modal function with a small component proportion, it is also possible to not select it, because its subsequent impact is also very small and can be basically ignored. Moreover, in the case of large data, it can also save computer computing space and improve calculation speed.

[0143] After obtaining the above parameters, the six-dimensional spatial energy distribution of AM-FM-AMP-FMP-RP-T is constructed. The time T is the entire data length (i.e., 2000), and the corresponding energy is the instantaneous amplitude of the envelope of S-IMFs. Figure 6c ; Thus, the holographic phase Hilbert spectrum is obtained. In addition, it is possible to further integrate in one or more dimensions to obtain any holographic phase Hilbert spectrum.

[0144] The following is an example of the holographic phase Hilbert spectra in the remaining two dimensions obtained by integrating the F-IMF3 and its S-IMFs in four dimensions:

[0145] (1) By integrating over the four dimensions of amplitude modulation phase (AMP)-frequency modulation phase (FMP)-reference phase (RP)-time (T), we can obtain a two-dimensional energy spectrum about modulation frequency (FM)-amplitude modulation frequency (AM), which is called FM-AM-holographic phase Hilbert spectrum. Figure 7a As shown (expressed in the form of contour lines), the horizontal axis is the FM of EEG and the vertical axis is the AM of EEG. It can be seen that the energy of the FM of EEG (16Hz) is highest at AM (about 3Hz); it can be seen that the information of the processed EEG signal obtained by this monitoring method is consistent with the information of the optical signal, reflecting the corresponding relationship between the brain response and the optical signal (16Hz carrier signal, 3Hz amplitude modulation signal).

[0146] (2) By integrating over the four dimensions of amplitude modulation frequency (AM)-amplitude modulation phase (AMP)-frequency modulation phase (FMP)-time (T), we can obtain a two-dimensional energy spectrum about modulation frequency (FM)-reference phase (RP), which is called FM-RP-holographic phase Hilbert spectrum. Figure 7b As shown in the figure (using contour lines), the horizontal axis is RP and the vertical axis is EEG FM. It can be seen that the energy of EEG FM (16Hz) is highest at RP (3π / 2~7π / 4); the information reflected by EEG FM (16Hz) corresponds to the 16Hz carrier signal of the optical signal. For information about RP, for easy understanding, please refer to Figure 5b The red solid line with an asterisk in the figure represents the instantaneous phase of FlickerAM, which serves as the reference phase RP. The gray solid line represents the amplitude variation of F-IMF3. It can be seen that the maximum amplitude of F-IMF3 always occurs between approximately 3π / 2 and 7π / 4 of the instantaneous phase of FlickerAM. This phenomenon, observed with the naked eye, can ultimately be represented by the FM-RP-holographic phase Hilbert spectrum. This indicates that the brain's reaction lags behind the light signal, which is consistent with reality: the light signal comes first, followed by the brain's reaction, and the reaction time lags behind the light signal. Furthermore, by converting phase to period, the specific lag time can be directly calculated.

[0147] (3) Integrating over the four dimensions of modulation frequency (FM)-amplitude modulation phase (AMP)-frequency modulation phase (FMP)-time (T), we get a two-dimensional energy spectrum about amplitude modulation frequency (AM)-reference phase (RP), which is called the AM-RP-holographic phase Hilbert spectrum. Figure 7c As shown in FIG. 1 (represented by contour lines), the horizontal axis is RP and the vertical axis is EEG AM. The AM of EEG has the highest energy at 3 Hz, which corresponds to the amplitude modulation signal (3 Hz) of the optical signal.

[0148] (4) By integrating over the four dimensions of amplitude modulation frequency (AM)-modulation frequency (FM)-frequency modulation phase (FMP)-time (T), we can obtain a two-dimensional energy spectrum about amplitude modulation phase (AMP)-reference phase (RP), which is called AMP-RP-holographic phase Hilbert spectrum. Figure 8a As shown in the figure (represented by p-color diagram), it is the AMP-RP-holographic phase Hilbert spectrum of EEG, with RP on the horizontal axis and AMP on the vertical axis. The period of the second-layer modal function corresponding to AMP is closest to that of FlickerAM. Figure 5a As shown, the red solid line is FlickerAM, and the blue solid line is S-IMF3.3 of F-IMF3, whose period is closest to FlickerAM, but the two have different phases, that is, the peaks and troughs do not overlap; Figure 5bAs shown in Figure 2, the amplitude of F-IMF3 is always the largest when the FlickerAM phase is 3π / 2 to 7π / 4. Figure 8a It can also be seen in , but it is not intuitive enough. Therefore, the AMP-RP-holographic phase Hilbert spectrum is adjusted in terms of data. The part above the amplitude modulation phase (AMP) π is rotated 45 degrees to the right, and the part below the amplitude modulation phase (AMP) π is rotated 45 degrees to the left (i.e., diagonalization processing). It is called the diagonalization-phase-holographic phase Hilbert spectrum, as shown in Figure 8b As shown in the figure, it can be seen that there is a phase offset of 3π / 2 to 7π / 4 between RP and the amplitude modulation phase AMP (reflecting the hysteresis of the brain reaction, that is, the reaction time). The corresponding objective phenomenon can be seen from Figure 5b To further quantify how RP and AMP wrap the first-layer modal function (F-IMF3) of the EEG signal, the energy of RP and AMP in the two-dimensional space is arranged from the center to the outside in descending order (i.e., centralization is performed), and the centralization-phase-holographic phase Hilbert spectrum is obtained, as shown in Figure 8c As shown in the figure, when the energy is more concentrated in the center, the envelope of the amplitude modulation signal of the light signal (FlickerAM) and F-IMF3 (closest to the period of FlickerAM) wraps F-IMF3 more tightly, indicating that there is a strong causal relationship between FlickerAM and EEG signals, which can reflect the intensity of the brain's response to the light signal; Figure 5a As shown, the F-IMF3 wrapping of the EEG signal is achieved by moving the amplitude modulation signal of the stimulation signal and the envelope of the F-IMF3.

[0149] In the aforementioned two-dimensional energy spectrum, when RP is present, it can at least display the lag phase of the brain's response, thereby enabling the determination of the monitored subject's reaction time. A larger lag phase indicates a longer reaction time, a slower reaction, and a lower reaction sensitivity. The centralized RP-AMP can further determine the intensity of the reaction. The more concentrated the energy is in a certain area within the centralization-phase-holographic phase Hilbert spectrum space, the greater the intensity of the monitored subject's reaction. The shorter the reaction time and the greater the intensity of the reaction, the more suitable the monitored subject is for brain-computer interface control of external devices.

[0150] In addition, since people have different response thresholds to various stimulus signals, this monitoring method can also be used to obtain the response threshold of the monitored object to the stimulus signal. For example, when the light signal is very weak, the monitoring method can be used to find that the monitored object may not have any reaction to it. By continuously increasing the intensity of the light signal and using this monitoring method for monitoring, the response threshold of the monitored object to the light signal can be found. Similarly, it is also applicable in other fields. For example, when the sound signal is very weak, the monitoring method can be used to find that the monitored object may not have any reaction to it. By continuously increasing the intensity of the sound signal and using this monitoring method for monitoring, the response threshold of the monitored object to the sound signal can be found. The response threshold of the monitored object to the stimulus signal is very important information in some fields, especially the medical field, and can be used as an important parameter for related medical tests.

[0151] Through holographic phase Hilbert spectrum analysis, at least the amplitude modulation frequency and modulation frequency of the EEG signal under the stimulation signal, the phase offset of the EEG signal and the amplitude modulation signal of the stimulation signal, and the strength of the causal relationship between the amplitude modulation signal of the stimulation signal and the EEG signal are fully displayed, realizing the relationship analysis between the stimulation signal and the EEG signal, and filling the shortcomings of the holographic Hilbert spectrum analysis method in the existing technology.

[0152] Furthermore, the above results can be collated, the data and results can be archived, the results can be displayed on the screen, and a corresponding data analysis report can be generated.

[0153] The second embodiment of the present application provides a monitoring system based on holographic phase Hilbert spectrum analysis (hereinafter referred to as a monitoring system), which is used to implement the monitoring method described in any of the above embodiments. The monitoring system includes:

[0154] A stimulation signal module is configured to generate a stimulation signal; for example, it can be a flashing light source, a sound-generating device, etc.;

[0155] A data acquisition module is configured to collect and obtain EEG signals using electrodes;

[0156] The data processing module is configured as follows:

[0157] The modal decomposition method is used to decompose the EEG signal into the first layer to obtain the first layer modal component, which contains multiple first layer modal functions;

[0158] Calculating the envelope of at least one of the plurality of first-layer modal functions to obtain an envelope line; performing a second-layer decomposition on the envelope line using a modal decomposition method to obtain a second-layer modal component, which includes the plurality of second-layer modal functions;

[0159] respectively calculating the instantaneous phases of the first layer mode function, the second layer mode function, and the amplitude modulation signal of the stimulation signal, and respectively calculating the instantaneous frequencies of the first layer mode function and the second layer mode function;

[0160] Construct a holographic phase Hilbert spectrum to analyze the relationship between the stimulation signal and the EEG signal. Specifically:

[0161] (1) Selecting the instantaneous phase of the amplitude modulation signal of the stimulation signal as the reference phase;

[0162] (2) selecting the instantaneous frequency of at least one first-layer modal function in the first-layer modal component as the modulation frequency, and the instantaneous phase thereof as the frequency modulation phase;

[0163] (3) selecting the instantaneous frequency of all second-layer modal functions (residues may be removed) corresponding to at least one first-layer modal function as the amplitude modulation frequency, and selecting the instantaneous phase of one of the second-layer modal functions in the second-layer modal components as the amplitude modulation phase; wherein the period of the selected second-layer modal function is closest to the period of the amplitude modulation signal of the stimulation signal;

[0164] (4) The six-dimensional spatial energy distribution of AM frequency-modulation frequency-AM phase-FM phase-reference phase-time is obtained, where the energy is the amplitude of the envelope of the second-layer modal component, thereby obtaining the holographic phase Hilbert spectrum.

[0165] The result output module is configured to output the holographic phase Hilbert spectrum to display the monitoring results.

[0166] In some embodiments, integration may be performed in one or more dimensions to obtain an integrated holographic phase Hilbert spectrum.

[0167] In some embodiments, the monitoring system may further include:

[0168] The data comparison module is configured to compare the monitoring results to analyze the response ability of the monitored object to the stimulation signal, including but not limited to one or more of reaction time, reaction intensity, and reaction threshold.

[0169] The data archiving module is configured to store data for future reference.

[0170] The data display module is configured to display the monitoring results and the comparison results on a screen. Therefore, the data display module may include a PC monitor.

[0171] It is worth understanding that the technical features described in the monitoring method can also be reasonably applied to the monitoring system of this embodiment, and those that have been explained will not be repeated. It should be noted that the above-mentioned modules can be functional modules or program modules, and can be implemented by software or hardware. For modules implemented by hardware, the above-mentioned modules can be located in the same processor, or the above-mentioned modules can be located in different processors in any combination.

[0172] The third embodiment of the present application provides an application of the monitoring method described in any of the preceding embodiments, which can be used to monitor the reaction time, reaction intensity and reaction threshold of the monitored object to the stimulation signal, thereby screening the monitored objects suitable for the needs of different fields, and using the measured parameters as input parameters for medical examinations.

[0173] For example, by monitoring the human population, individuals with fast and high-intensity responses to certain stimuli can be selected as candidates for brain-computer interface operators. Another example is the ability to measure the response thresholds required for medical testing, enabling subsequent medical intervention and supporting medical care.

[0174] The fourth embodiment of the present application provides a computer device, which may include a processor 101 and a memory 102 storing computer program instructions, such as Figure 9 shown.

[0175] Specifically, the processor 101 may include a central processing unit (CPU), or an application specific integrated circuit (ASIC), or may be configured to implement one or more integrated circuits of the present application. The memory 102 may include a large capacity memory for data or instructions. By way of example and not limitation, the memory 102 may include a hard disk drive (HDD), a floppy disk drive, a solid state drive (SSD), a flash memory, an optical disk, a magneto-optical disk, a magnetic tape, or a universal serial bus (USB) drive or a combination of two or more of these. Where appropriate, the memory 102 may include a removable or non-removable (or fixed) medium. Where appropriate, the memory 102 may be inside or outside a data processing device.

[0176] The memory 102 may be used to store or cache various data files that need to be processed and / or used for communication, as well as possible computer program instructions executed by the processor 101 .

[0177] The processor 101 implements the monitoring method described in any of the above embodiments by reading and executing computer program instructions stored in the memory 102.

[0178] In some embodiments, the computer device may further include a communication interface 103 and a bus 104. Figure 9 As shown, the processor 101, memory 102, and communication interface 103 are connected via a bus 104 and communicate with each other. The communication interface 103 is used to implement communication between the various modules, devices, units, and / or equipment in the embodiments of the present application. The communication interface 103 can also implement data communication with other components.

[0179] A fifth embodiment of the present application provides a computer-readable storage medium having computer program instructions stored thereon; when the computer program instructions are executed by a processor, the monitoring method described in any of the above embodiments is implemented.

[0180] The various technical features of the above-described embodiments can be combined arbitrarily. To make the description concise, not all possible combinations of the various technical features in the above-described embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this specification.

[0181] The above-described embodiments merely represent several embodiments of the present application. While the descriptions are relatively specific and detailed, they should not be construed as limiting the scope of the present application. It should be noted that a person of ordinary skill in the art may make various modifications and improvements without departing from the spirit of the present application, and these modifications and improvements fall within the scope of protection of the present application. Therefore, the scope of protection of the present patent application shall be determined by the appended claims.

Claims

1. A monitoring method based on holographic phase Hilbert spectrum analysis, characterized in that: The following steps are involved: Introduction of S100 stimulation signal; S200: Acquiring an EEG signal; stimulating the monitored subject with the stimulation signal to synchronously obtain an EEG signal from the monitored subject; as well as, S300 holographic phase Hilbert spectrum analysis, which includes the following steps: First layer decomposition: Use the modal decomposition method to decompose the EEG signal into the first layer to obtain the first layer modal components. It contains multiple first-layer modal functions; Second-level decomposition: Calculate the envelope of the first-level modal function to obtain the envelope line; use the modal decomposition method to perform the second-level decomposition on the envelope line to obtain the second-level modal components, which contain multiple second-level modal functions; The holographic phase Hilbert spectrum is constructed to analyze the relationship between the stimulation signal and the EEG signal.

2. The monitoring method according to claim 1, characterized in that: In the step S300, the step of constructing the holographic phase Hilbert spectrum specifically includes: When the multi-dimensionality includes a reference phase, calculating the instantaneous phase of the amplitude modulation signal of the stimulation signal as the reference phase; When the multi-dimensional matrix includes a modulation frequency, the instantaneous frequency of the first-layer modal function is calculated as the modulation frequency; When the multi-dimensionality includes a frequency modulation phase, calculating the instantaneous phase of the first layer mode function as the frequency modulation phase; When the multi-dimensional data includes an amplitude modulation frequency, the instantaneous frequency of the second-layer modal function is calculated as the amplitude modulation frequency; When the multi-dimensionality includes an amplitude modulation phase, calculating the instantaneous phase of the second-layer modal function as the amplitude modulation phase; and Based on at least two of the six dimensions of the reference phase, modulation frequency, frequency modulation phase, amplitude modulation frequency, amplitude modulation phase and time, a multidimensional spatial energy distribution about the at least two dimensions is obtained, and the energy is the amplitude of the envelope of the second-layer modal component; thereby obtaining the holographic phase Hilbert spectrum.

3. The monitoring method according to claim 1, characterized in that In the step S300: In the second-layer decomposition, the envelope of at least one first-layer modal function in the first-layer modal components is calculated to obtain an envelope line; the envelope line is subjected to a second-layer decomposition using a modal decomposition method to obtain a second-layer modal component, which includes a plurality of second-layer modal functions; the at least one first-layer modal function is the most important component of the EEG signal; as well as, Constructing the holographic phase Hilbert spectrum comprises the following steps: When the multi-dimensionality includes a reference phase, calculating the instantaneous phase of the amplitude modulation signal of the stimulation signal as the reference phase; When the multi-dimensionality includes a modulation frequency, calculating the instantaneous frequency of the at least one first-layer modal function as the modulation frequency; When the multi-dimensionality includes a frequency modulation phase, calculating the instantaneous phase of the at least one first-layer modal function as the frequency modulation phase; When the multi-dimensional data includes amplitude modulation frequency, the instantaneous frequency of the second-layer modal component is calculated, and the instantaneous frequencies of several second-layer modal functions are selected as the amplitude modulation frequency; When the multi-dimensionality includes an amplitude modulation phase, the instantaneous phase of the second-layer modal component is calculated, and the instantaneous phase of one of the second-layer modal functions is selected as the amplitude modulation phase; the period of the selected second-layer modal function is closest to the period of the amplitude modulation signal of the stimulation signal; and Based on at least two of the six dimensions of the reference phase, modulation frequency, FM phase, AM frequency, AM phase and time, a multidimensional spatial energy distribution about the at least two dimensions is obtained, and the energy is the amplitude of the envelope of the second-layer modal component; thereby obtaining the holographic phase Hilbert spectrum; analyzing the holographic phase Hilbert spectrum to obtain the relationship between the stimulation signal and the EEG signal.

4. The monitoring method according to claim 2 or 3, characterized in that: The holographic phase Hilbert spectrum is a multi-dimensional spatial energy distribution with respect to at least one of a reference phase, an amplitude modulation phase, and a frequency modulation phase.

5. The monitoring method according to claim 3, characterized in that: The stimulation signal is obtained by modulating a carrier signal with the amplitude modulation signal; the period of the selected at least one first-layer modal function is closest to the period of the carrier signal of the stimulation signal.

6. The monitoring method according to any one of claims 1 to 5, characterized in that: The stimulation signal is at least one of a light signal, a sound signal, and an electrical signal; In the step S200, the EEG signal may be preprocessed, and the preprocessing includes at least one of filtering, notching, outlier removal, and electrical noise removal; and in the step S300, the preprocessed EEG signal is subjected to holographic phase Hilbert spectrum analysis. In the first-layer decomposition, EMD or EEMD is used to perform the first-layer decomposition of the EEG signal, and the obtained first-layer modal components include multiple intrinsic mode functions or multiple collective intrinsic mode functions, as the multiple first-layer modal functions; in the second-layer decomposition, EMD or EEMD is used to perform the second-layer decomposition of the envelope line, and the obtained second-layer modal components include multiple intrinsic mode functions or multiple collective intrinsic mode functions, as the multiple second-layer modal functions.

7. The monitoring method according to claim 2 or 3, characterized in that: In step S300, a six-dimensional spatial energy distribution of amplitude modulation frequency-modulation frequency-amplitude modulation phase-frequency modulation phase-reference phase-time is obtained, where the energy is the amplitude of the envelope of the second-layer modal component, thereby obtaining the holographic phase Hilbert spectrum; the holographic phase Hilbert spectrum is integrated over N dimensions to obtain holographic phase Hilbert spectra for the remaining 6-N dimensions; N is a positive integer less than 6; and the 6-N dimensions include at least the reference phase.

8. A monitoring system based on holographic phase Hilbert spectrum analysis, capable of implementing the monitoring method according to any one of claims 1 to 7, characterized in that: include: A stimulation signal module is configured to generate a stimulation signal; The data acquisition module is configured to: synchronously acquire an EEG signal of the monitored subject when the stimulation signal stimulates the monitored subject; The data processing module is configured for holographic phase Hilbert spectrum analysis, specifically, The modal decomposition method is used to decompose the EEG signal into the first layer to obtain the first layer modal component, which contains multiple first layer modal functions; Calculate the envelope of the first-layer modal function to obtain an envelope line; perform a second-layer decomposition of the envelope line using a modal decomposition method to obtain a second-layer modal component, which contains multiple second-layer modal functions; Calculating the instantaneous phases of the first layer modal function, the second layer modal function, and the amplitude modulation signal of the stimulation signal, respectively, and calculating the instantaneous frequencies of the first layer modal function and the second layer modal function, respectively; and, Constructing a holographic phase Hilbert spectrum to analyze the relationship between the stimulation signal and the EEG signal; specifically, selecting the instantaneous phase of the amplitude modulation signal of the stimulation signal as the reference phase; Select the instantaneous frequency of the first layer modal function as the modulation frequency, and its instantaneous phase as the FM phase; Selecting the instantaneous frequency of the second layer mode function as the amplitude modulation frequency, and its instantaneous phase as the amplitude modulation phase; and, Obtaining a multidimensional spatial energy distribution in at least two dimensions of the six dimensions of reference phase, modulation frequency, frequency modulation phase, amplitude modulation frequency, amplitude modulation phase, and time, wherein the energy is the amplitude of the envelope of the second-layer modal component; thereby obtaining a holographic phase Hilbert spectrum; and The result output module is configured to output the holographic phase Hilbert spectrum to display the monitoring results.

9. The monitoring system according to claim 8, characterized in that It also includes a data comparison module, which is configured to compare the monitoring results to analyze the response ability of the monitored object to the stimulation signal.

10. The monitoring system according to claim 9, characterized in that: The reaction capability includes one or more of reaction time, reaction intensity, and reaction threshold.

11. An application of the monitoring method based on holographic phase Hilbert spectrum analysis according to any one of claims 1 to 7, wherein the monitoring method can be used to monitor at least one of the reaction time, reaction intensity and reaction threshold of a monitored subject to a stimulus signal.

12. The use according to claim 11, characterized in that It can be used for screening the monitored object or obtaining medical detection parameters of the monitored object.

13. A computer device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the computer program, the monitoring method based on holographic phase Hilbert spectrum analysis as described in any one of claims 1 to 7 is implemented.

14. A computer-readable storage medium having a computer program stored thereon, wherein when the program is executed by a processor, the monitoring method based on holographic phase Hilbert spectrum analysis according to any one of claims 1 to 7 is implemented.

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