Background signal suppression methods, epilepsy EEG signal display system

Abstract

The present invention belongs to the technical field of physiological electrical signal detection, and specifically relates to a background signal suppression method and an epileptic EEG signal display system. The background signal suppression method comprises: determining the energy proportion of the background signal in the signal to be processed; when the energy proportion meets the expected result, the background signal is not processed; when the energy proportion does not meet the expected result, the background signal is de-backgrounded according to the baseline range. The background noise activity in the epileptic EEG can be suppressed, and the pathological abnormal signals can be highlighted.

Description

Technical Field

[0001] The present invention belongs to the technical field of physiological electrical signal detection, and in particular relates to a background signal suppression method and an epileptic EEG signal display system. Background Art

[0002] EEG time-frequency spectrum analysis is an important tool used clinically for detailed analysis of EEG activity during epileptic seizures. By combining the time and frequency domains through methods such as Fourier transform or wavelet transform, the frequency changes of the brain at different time points can be accurately captured, providing more comprehensive information on dynamic changes in EEG. In related technologies, for example, the Wide-Band Analysis function in Nihon Kohden software provides an advanced time-frequency spectrum tool specifically designed for epileptic EEG analysis. Compared with traditional time domain or frequency domain analysis, this tool suppresses background noise and highlights weak signals by removing the baseline, and can more accurately locate the starting time and frequency characteristics of abnormal epileptic discharges. However, there are still some problems, such as the inability to suppress the background or highlight the target rhythm signal in a targeted manner, resulting in excessive suppression of epileptic rhythm waves, unclear display, and easy misjudgment of the starting position, causing deviations in the location of epilepsy. Summary of the invention

[0003] The invention provides a background signal suppression method and an epileptic electroencephalogram signal display system.

[0004] In order to solve the above technical problems, the present invention provides a method for suppressing background signals, including: determining the energy proportion of the background signal in the signal to be processed; when the energy proportion meets the expected result, the background signal is not processed; when the energy proportion does not meet the expected result, the background signal is de-backgrounded according to the baseline range.

[0005] Furthermore, the background removal process includes: obtaining a baseline range of the signal to be processed; obtaining a background frequency range of the background signal; and removing the background signal within the baseline range based on the background frequency range.

[0006] Further, the obtaining of the baseline range of the signal to be processed includes: selecting a time period from the signal to be processed [ , ] as the baseline time, and calculate the power spectrum of the corresponding signal within the baseline time , then [ , ] as the baseline range corresponding to the baseline time; , ; represents the lower limit frequency within the baseline time, represents the upper frequency limit within the baseline time, represents the sampling rate, Indicates frequency resolution.

[0007] Further, when the signal to be processed is configured as an original acquisition signal, the background frequency range of the background signal obtained includes: extracting the background signal , Will The corresponding energy value is used as the third energy threshold ; Extract background signal Will The corresponding energy value is used as the fourth energy threshold ; Get Not less than the third energy threshold The corresponding frequency value , get Not less than the fourth energy threshold Frequency , and take the union of the two as the background frequency range, that is, .

[0008] Further, removing the background signal in the baseline range based on the background frequency range includes: based on A stopband filter is designed to perform stopband filtering on the original signal; the stopband filter includes at least one of an IIR filter, a FIR filter, and a wavelet filter.

[0009] Further, when the signal to be processed is configured as a time-frequency graph signal of the original acquired signal, the removal of the background signal in the baseline range based on the background frequency range includes: obtaining a first time-frequency result of the time-frequency graph signal; obtaining a second time-frequency result of the background signal in the baseline range based on the background frequency range; and combining the first time-frequency result with the second time-frequency result to obtain a third time-frequency result without background.

[0010] Further, obtaining the background frequency range of the background signal is configured to detect the frequency range of the background signal based on the time-frequency spectrum distribution characteristics of the first time-frequency result, including: extracting The energy spectrum corresponding to each time t , right Sort by energy value-added and take the corresponding first quantile The corresponding energy value is used as the first energy threshold ;extract The energy spectrum corresponding to each time t right Sort by energy value added and take the corresponding second quantile The corresponding energy value is used as the second energy threshold ; Get energy value Not less than the first energy threshold The corresponding frequency value , get the energy value Not less than the second energy threshold Frequency , and the union of the two is taken as the background frequency range at time t, that is, .

[0011] Further, obtaining a second time-frequency result of the background signal in the baseline range based on the background frequency range includes: setting a coefficient matrix For size and Equal matrices, the matrix elements are ;but

[0012] ; Based on the coefficient matrix Get the second time-frequency result , including: transforming the coefficient matrix Calculate the second time-frequency result along the time dimension ; or based on the coefficient matrix The statistical distribution results of the second time-frequency results are calculated .

[0013] Further, combining the first time-frequency result with the second time-frequency result to obtain a third time-frequency result without background includes: using the first time-frequency result Divide by the second time-frequency result , and obtain the background-free third time-frequency result, namely .

[0014] In a second aspect, the present invention provides an epileptic EEG signal display system, comprising: a processor, which runs the steps of the method to obtain a time-frequency graph signal after removing the background; and a display, which is used to display the epileptic rhythm signal in the time-frequency graph signal.

[0015] In a third aspect, the present invention provides a computer device, comprising a memory, a processor and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method.

[0016] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program implements the steps of the method when executed by a processor.

[0017] In a fifth aspect, the present invention provides a computer program product, comprising a computer program, which implements the steps of the method when executed by a processor.

[0018] The beneficial effect of the present invention is that the background signal suppression method and epileptic EEG signal display system of the present invention use the energy ratio of the background signal to select whether to perform de-backgrounding processing, suppress the background signal according to the baseline range, suppress the background noise activity in the epileptic EEG, and highlight the pathological abnormal signals.

[0019] Other features and advantages of the present invention will be described in the following description, and partly become apparent from the description, or understood by practicing the present invention. The purpose and other advantages of the present invention are realized and obtained by the structures particularly pointed out in the description, claims and drawings.

[0020] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, preferred embodiments are given below and described in detail with reference to the accompanying drawings. BRIEF DESCRIPTION OF THE DRAWINGS

[0021] In order to more clearly illustrate the specific implementation methods of the present invention or the technical solutions in the prior art, the drawings required for use in the specific implementation methods or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are some implementation methods of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative work.

[0022] Figure 1 This is a process flow chart of the suppression method of Example 2.

[0023] Figure 2 It is a time-frequency signal diagram that needs to be suppressed.

[0024] Figure 3 It is a time-frequency signal diagram that does not require suppression processing.

[0025] Figure 4 It is an energy spectrum diagram that automatically detects the background frequency range based on the distribution characteristics of the time-frequency spectrum.

[0026] Figure 5 This is the time-frequency signal diagram of epileptic EEG in Experimental Example 1.

[0027] Figure 6 This is the suppression process flow chart for test condition 1.

[0028] Figure 7 This is the processing flow chart of test condition 2.

[0029] Figure 8 This is the suppression process flow chart for test condition 3.

[0030] Fig. 9 This is the third time-frequency result diagram of experimental condition 1.

[0031] Fig.10 This is the time-frequency result diagram of experimental condition 2.

[0032] Fig.11 This is the time-frequency result diagram of experimental condition 3.

[0033] Fig.12 This is a process flow chart of the suppression method of Example 3.

[0034] Fig.13 This is the time-frequency result diagram of experimental condition 4.

[0035] Fig.14 This is the energy spectrum of the automatically detected background frequency range in test condition 4. DETAILED DESCRIPTION

[0036] In order to make the purpose, technical solution and advantages of the embodiments of the present invention clearer, the technical solution of the present invention will be clearly and completely described below in conjunction with the accompanying drawings. Obviously, the described embodiments are 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.

[0037] Example 1.

[0038] See Fig.12 , this embodiment 1 provides a method for suppressing background signals, hereinafter collectively referred to as the suppression method, including: determining the energy ratio of the background signal in the signal to be processed; when the energy ratio meets the expected result, the background signal is not processed; when the energy ratio does not meet the expected result, the background signal is de-backgrounded according to the baseline range. Specifically, whether to perform de-backgrounding processing needs to consider the energy intensity of the interference signal. The judgment method is, for example, but not limited to, a manual inspection, such as Figure 2 As shown in the figure, when the interference signal is so strong that only the time-frequency result corresponding to the interference signal frequency can be seen on the time-frequency diagram of a signal, and other signals are submerged and cannot be displayed or their display effect affects signal judgment, it is considered that the energy proportion of the background signal does not meet the expected results. After setting the baseline range, consider choosing automatic or manual methods to suppress the background signal. Otherwise, you can consider not doing any processing, such as Figure 3 shown.

[0039] Furthermore, the background removal process includes: obtaining a baseline range of the signal to be processed; obtaining a background frequency range of the background signal; and removing the background signal within the baseline range based on the background frequency range.

[0040] Optionally, obtaining the baseline range includes the following process: selecting a time period in the signal to be processed [ , ] as the baseline time, and calculate the power spectrum of the corresponding signal within the baseline time , then [ , ] as the baseline range corresponding to the baseline time; , , , represents the lower limit frequency within the baseline time, represents the upper frequency limit within the baseline time, represents the sampling rate of the signal to be processed, Indicates the start time of the signal to be processed, Indicates the end time of the signal to be processed. represents the time resolution, Optionally, since the baseline is used to remove background signals, the baseline time can be generally set to a period of time when signal collection begins, or manually modified to a period of time when the target signal accounts for a small proportion.

[0041] Optionally, if the background frequency range is too large, it may overlap with the target signal frequency range, resulting in partial suppression of the target signal frequency; if the background frequency range is too small, the unsuppressed background signal will still be very strong, which is reflected in the time-frequency diagram as the color concentrated at the background frequency, covering up the target signal. Therefore, whether the signal to be processed is the original acquisition signal or the time-frequency diagram signal of the original acquisition signal, the frequency band for background suppression can be manually or automatically selected according to the time-frequency spectrum characteristics of the data. The manual method is that professional and experienced personnel manually determine the background frequency range according to the type of background signal, which is at least one frequency interval. For example, the background signal is at least one of electromagnetic interference with a constant frequency and low-frequency artifact noise. The electromagnetic interference with a constant frequency is, for example, but not limited to, the power frequency and its multiples. When the signal has strong energy at the power frequency and the color at other frequencies is monotonous, a frequency range [45,55] Hz near the power frequency 50 Hz can be selected as the background frequency; if there is a strong power frequency multiple, a frequency range [95,105] Hz near the multiple is also selected as the background frequency, and the set of these background frequencies is taken as the background frequency range Freq={[45,55],[95 105]}. The manual setting of the background frequency is selected for the entire time, because there is only one set of background frequency ranges. When the power frequency is 60 Hz or other values, the same reasoning is used.

[0042] Example 2.

[0043] Based on Example 1, the time-frequency diagram signal after the original collected signal is processed is taken as an example. Figure 1In Example 2, the background removal processing includes: obtaining a first time-frequency result of the time-frequency graph signal; obtaining a baseline range of the signal to be processed; obtaining a background frequency range of the background signal; obtaining a second time-frequency result of the background signal in the baseline range based on the background frequency range; combining the first time-frequency result and the second time-frequency result to obtain a third time-frequency result of background removal to remove the background signal in the baseline range.

[0044] Optionally, obtaining the first time-frequency result of the time-frequency graph signal includes: obtaining the time-frequency result of the time-frequency graph signal as the first time-frequency result based on a time-frequency calculation method; wherein the time-frequency calculation method includes at least one of short-time Fourier transform, wavelet transform, and complex demodulation. Specifically, a signal for analysis is selected , is the signal sample length, and the sampling rate is Fs; the time-frequency result of the signal is calculated based on the time-frequency calculation method The time-frequency calculation method can be selected from short-time Fourier transform / wavelet transform / complex demodulation, etc. represents the time resolution, Indicates frequency resolution.

[0045] Optionally, the specific process of obtaining the baseline range of the signal to be processed is as described above, the only difference is that when the signal to be processed is a time-frequency graph signal after the original acquisition signal is processed, the first time-frequency result of the time-frequency graph signal can be used. Or the power spectrum PSD_base(f) of the signal selects the baseline range.

[0046] Optionally, the background frequency range of the background signal can be obtained manually or automatically. The automatic method is to automatically detect the frequency range of the background activity based on the distribution characteristics of the time-frequency spectrum. Figure 4 , including: Extract The energy spectrum corresponding to each time t , right Sort by energy value-added and take the corresponding first quantile The corresponding energy value is used as the first energy threshold (like Figure 4 1) Extract the threshold value The energy spectrum corresponding to each time t right Sort by energy value added and take the corresponding second quantile The corresponding energy value is used as the second energy threshold (like Figure 4 Threshold 2 in); Get energy value Not less than the first energy threshold The corresponding frequency value , get the energy value Not less than the second energy threshold Frequency , and the union of the two is taken as the background frequency range at time t, that is, . and It is a parameter that can be adjusted by the user, and 95% is selected by default. The manual method is as described above and will not be repeated here.

[0047] Optionally, obtaining a second time-frequency result of the background signal in the baseline range based on the background frequency range includes: setting a coefficient matrix For size and Equal matrices, the matrix elements are ;but

[0048] ; Based on the coefficient matrix Get the second time-frequency result , including: transforming the coefficient matrix Calculate the second time-frequency result along the time dimension ; or based on the coefficient matrix The statistical distribution results of the second time-frequency results are calculated .

[0049] Optionally, combining the first time-frequency result with the second time-frequency result to obtain a third time-frequency result without background includes: using the first time-frequency result Divide by the second time-frequency result , and obtain the background-free third time-frequency result, namely .

[0050] Example 3.

[0051] Based on Example 1, taking the original collected signal as an example, Fig.12 In Example 3, the background removal processing includes: obtaining a baseline range of the signal to be processed; obtaining a background frequency range of the background signal; and removing the background signal within the baseline range based on the background frequency range.

[0052] Optionally, the specific process of obtaining the baseline range of the signal to be processed is as described above, the only difference being that when the signal to be processed is the original acquired signal, the baseline range can be selected based on the power spectrum PSD_base(f) of the signal.

[0053] Optionally, obtaining the background frequency range of the background signal includes: extracting the background signal , Will The corresponding energy value is used as the third energy threshold ; Extract background signal Will The corresponding energy value is used as the fourth energy threshold ; Get Not less than the third energy threshold The corresponding frequency value , get Not less than the fourth energy threshold Frequency , and take the union of the two as the background frequency range, that is, .

[0054] Optionally, removing the background signal in the baseline range based on the background frequency range includes: based on A stopband filter is designed to perform stopband filtering on the original signal; the stopband filter includes at least one of an IIR filter, a FIR filter, and a wavelet filter.

[0055] Example 4.

[0056] Based on Example 2 or 3, this Example 4 provides an epileptic EEG signal display system, including: a processor, which runs the steps of the method to obtain a time-frequency graph signal after removing the background; and a display, which is used to display the epileptic rhythm signal in the time-frequency graph signal.

[0057] Example 5.

[0058] Based on Embodiment 2 or 3, this Embodiment 5 provides a computer device, including a memory, a processor, and a computer program stored in the memory, wherein the processor executes the computer program to implement the steps of the method.

[0059] Example 6.

[0060] On the basis of Embodiment 2 or 3, this Embodiment 6 provides a computer-readable storage medium on which a computer program is stored, and the computer program implements the steps of the method when executed by a processor.

[0061] Example 7.

[0062] On the basis of Embodiment 2 or 3, this Embodiment 7 provides a computer program product, including a computer program, and when the computer program is executed by a processor, the steps of the method are implemented.

[0063] Test example 1.

[0064] The time domain waveform of the scalp EEG signal during an epileptic seizure (e.g. Figure 5 Taking the time-frequency diagram as an example, the time-frequency diagram signals were processed under various experimental conditions, and the prominence of epileptic rhythm signals (theta rhythm and / or gamma activity) in the processed time-frequency diagrams was compared.

[0065] Test condition 1: Select a 20s data segment with Fs=500Hz and a frequency resolution of , time resolution , baseline range , , , the background frequency selection method is automatic selection, the time-frequency diagram display range is .See Figure 6 , the background signal is suppressed by the method described in Example 1, and the third time-frequency result is as follows Fig. 9 shown.

[0066] Test condition 2: Select a 20s data segment with Fs=500Hz and a frequency resolution of , time resolution , time-frequency diagram display range .See Figure 7 , without any processing of the background signal, the result is as follows Fig.10 shown.

[0067] Test condition 3: Select a 20s data segment with Fs=500Hz and a frequency resolution of , time resolution , baseline range , , , background frequency selection ={[1 100]}, time-frequency graph display range .See Figure 8 , the background signal is suppressed by the existing technology, and the processing result is as follows Fig.11 shown.

[0068] Test results: Combined Fig. 9 , 10 , 11It can be seen that

[0069] (1) Compared with not processing the background signal (experimental condition 2), the suppression of the background signal according to the baseline range in this case (experimental condition 1) can effectively suppress the background activity and highlight the abnormal epileptic EEG activity.

[0070] (2) Compared with the processing of background signals by the prior art (experimental condition 3), although both can effectively suppress background activity and highlight abnormal epileptic EEG activity, the third time-frequency results after processing in this case highlight abnormal low-frequency rhythms more significantly (e.g. Fig. 9 , Fig.11 shown in the box).

[0071] Test example 2.

[0072] Taking the original collected scalp EEG signal of epileptic seizure as an example, the signal was processed under various experimental conditions, and the prominence of epileptic rhythm signals (theta rhythm and / or gamma activity) in the processed time-frequency diagram was compared.

[0073] Test condition 4: Select a 20s data segment with Fs=500Hz and a frequency resolution of , time resolution , baseline range , , , the background frequency selection method is automatic selection, the time-frequency diagram display range is .See Fig.14 , the background signal is suppressed by the time domain method described in Example 3, and the third time-frequency result is as follows Fig.13 shown.

[0074] Test results: Combined Fig.13 , 10 , 11It can be seen that

[0075] (1) Compared with not processing the background signal (experimental condition 2), the background signal suppression processing based on the baseline range in this experimental example (experimental condition 4) can effectively suppress background activity and highlight abnormal epileptic EEG activity.

[0076] (2) Compared with the processing of background signals by the prior art (experimental condition 3), although both can effectively suppress background activity and highlight abnormal epileptic EEG activity, the third time-frequency results after processing in this case highlight abnormal low-frequency rhythms more significantly (e.g. Fig.13 shown in the box).

[0077] In the description of the embodiments of the present invention, unless otherwise clearly specified and limited, the terms "installed", "connected", and "connected" should be understood in a broad sense, for example, it can be a fixed connection, a detachable connection, or an integral connection; it can be a mechanical connection or an electrical connection; it can be a direct connection or an indirect connection through an intermediate medium, or it can be the internal communication of two components. For ordinary technicians in this field, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0078] In the description of the present invention, it should be noted that the terms "center", "upper", "lower", "left", "right", "vertical", "horizontal", "inner", "outer", etc., indicating the orientation or positional relationship, are based on the orientation or positional relationship shown in the drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as limiting the present invention. In addition, the terms "first", "second", and "third" are used for descriptive purposes only, and cannot be understood as indicating or implying relative importance.

[0079] In the several embodiments provided in this application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. The device embodiments described above are only schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed.

[0080] Based on the above ideal embodiments of the present invention, the relevant staff can make various changes and modifications without departing from the technical concept of the present invention through the above description. The technical scope of the present invention is not limited to the contents of the specification, and its technical scope must be determined according to the scope of the claims.

Claims

1. A method for suppressing background signals in physiological electrical signals, characterized in that: include: Determine the energy ratio of the background signal in the signal to be processed; When the energy ratio meets the expected result, the background signal is not processed; When the energy ratio does not meet the expected result, the background signal is de-backgrounded according to the baseline range; The decontextualization process includes: Obtain the baseline range of the signal to be processed; Get the background frequency range of the background signal; Remove background signals within the baseline range based on the background frequency range; The baseline range of obtaining the signal to be processed includes: Select a time period from the signal to be processed [ , ] as the baseline time, and calculate the power spectrum of the corresponding signal within the baseline time , then [ , ] as the baseline range corresponding to the baseline time; , ; represents the lower limit frequency within the baseline time, represents the upper frequency limit within the baseline time, represents the sampling rate, Indicates frequency resolution; When the signal to be processed is configured as an original acquisition signal, the background frequency range of the acquired background signal includes: Extracting background signals , Will The corresponding energy value is used as the third energy threshold ; Extracting background signals Will The corresponding energy value is used as the fourth energy threshold ; Get Not less than the third energy threshold The corresponding frequency value , get Not less than the fourth energy threshold Frequency , and take the union of the two as the background frequency range, that is, .

2. The method according to claim 1, characterized in that The method of removing the background signal in the baseline range based on the background frequency range includes: A stopband filter is designed to perform stopband filtering on the original signal; the stopband filter includes at least one of an IIR filter, a FIR filter, and a wavelet filter.

3. The method according to claim 1, characterized in that When the signal to be processed is configured as a time-frequency diagram signal of the original acquisition signal, removing the background signal within the baseline range based on the background frequency range includes: Obtaining a first time-frequency result of a time-frequency graph signal; Acquire a second time-frequency result of the background signal in the baseline frequency range based on the background frequency range; The first time-frequency result is combined with the second time-frequency result to obtain the decontextualized third time-frequency result.

4. The method according to claim 3, characterized in that The acquiring the background frequency range of the background signal is configured to detect the frequency range of the background signal based on the time-frequency spectrum distribution feature of the first time-frequency result, including: Extract the first time-frequency result The energy spectrum corresponding to each time t , right Sort by energy value-added and take the corresponding first quantile The corresponding energy value is used as the first energy threshold ; Extract the first time-frequency result The energy spectrum corresponding to each time t right Sort by energy value added and take the corresponding second quantile The corresponding energy value is used as the second energy threshold ; Get energy value Not less than the first energy threshold The corresponding frequency value , get the energy value Not less than the second energy threshold Frequency , and the union of the two is taken as the background frequency range at time t, that is, .

5. The method according to claim 3, characterized in that: Acquiring a second time-frequency result of the background signal in the baseline range based on the background frequency range includes: Set the coefficient matrix For size and Equal matrices, the matrix elements are ;but ； Based on the coefficient matrix Get the second time-frequency result ,include: The coefficient matrix Calculate the second time-frequency result along the time dimension Or based on the coefficient matrix The statistical distribution results of the second time-frequency results are calculated .

6. The method according to claim 3, characterized in that: The third time-frequency result obtained by combining the first time-frequency result with the second time-frequency result includes: Using the first time-frequency results Divide by the second time-frequency result , and obtain the background-free third time-frequency result, namely .

7. An epileptic EEG signal display system, comprising: A processor, executing the steps of the method according to any one of claims 1 to 6 to obtain a time-frequency diagram signal behind the background signal; A display is used to display the epileptic rhythm signal in the time-frequency diagram signal.

8. A computer device comprising a memory, a processor and a computer program stored in the memory, characterized in that: The processor executes the computer program to implement the steps of the method according to any one of claims 1 to 6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 6 are implemented.

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