Electroencephalogram signal acquisition device and acquisition method

Abstract

According to the electroencephalogram signal collecting device and method, the common-mode rejection ratio is increased through the right leg driving module, high-frequency noise and low-frequency noise are filtered out through the band-pass filtering module, power frequency interference is eliminated through the notch module, and filtering processing is conducted on the power frequency interference and the power frequency multiple in a software mode through the power frequency filtering model; therefore, the radio frequency interference is improved, the anti-interference capability of electroencephalogram signal acquisition is greatly improved, and the accuracy and stability of electroencephalogram signal acquisition are improved.

Description

Technical Field

[0001] This disclosure relates to the field of electroencephalogram (EEG) signal acquisition technology, and in particular to an EEG signal acquisition device and acquisition method. Background Technology

[0002] Electroencephalography (sEMG) is a weak physiological electrical signal generated by the human body. Its signal amplitude is in the microvolt range, which is weaker than electromyography (EMG) signals and more susceptible to external interference. EEG acquisition is generally based on a simple conduction process: whenever the brain is in motion, electrical activity is generated. This electrical activity is conducted through adjacent tissues and bones and then recorded by electrodes on adjacent brain regions.

[0003] Because EEG signals are very weak, they are easily mixed with various noises during actual acquisition, including noise from the EEG signal itself, motion artifacts, and environmental electromagnetic interference. Existing EEG acquisition devices often use hardware-based power frequency filters for filtering, but power frequency filters cannot completely remove power frequency interference, leaving residual interference noise. Moreover, they also generate certain interference noise during operation. Furthermore, this residual interference noise has a significant impact on weak EEG signals. Therefore, existing EEG acquisition devices do not have the ability to acquire EEG signals stably and do not have a high resistance to external radio frequency and power frequency interference. Summary of the Invention

[0004] This disclosure addresses the aforementioned problems by proposing an electroencephalogram (EEG) signal acquisition device and acquisition method.

[0005] To solve at least one of the above-mentioned technical problems, this disclosure proposes the following technical solution:

[0006] In a first aspect, an electroencephalogram (EEG) signal acquisition device is provided, comprising:

[0007] The right leg drive module, bandpass filter module, notch filter module, and power frequency filter model are connected in sequence.

[0008] The right leg drive module is used to improve the common-mode rejection ratio;

[0009] The bandpass filter module is used to filter out high-frequency noise and low-frequency noise;

[0010] Notch filters are used to eliminate power frequency interference;

[0011] The power frequency filtering model uses software to filter power frequency interference and multiples of the power frequency.

[0012] In some implementations, the right leg drive module includes an operational amplifier U12. Pin 1 of the operational amplifier U12 is connected to a bias unit consisting of resistors R35, R32, and C48. Pins 1 and 4 of the operational amplifier U12 are connected to a feedback unit consisting of resistors R31, R33, and C45. Pin 3 of the operational amplifier U12 is grounded.

[0013] In some implementations, the bandpass filter module includes a high-pass filter unit and a low-pass filter unit, wherein the high-pass filter unit is used to filter out high-frequency noise in the EEG signal, and the low-pass filter unit is used to filter out low-frequency noise in the EEG signal.

[0014] In some implementations, the high-pass filter unit includes an operational amplifier U7B. The non-inverting input of the operational amplifier U7B serves as the signal input of the high-pass filter unit. A capacitor C41 is connected to the non-inverting input of the operational amplifier U7B. The inverting input of the operational amplifier U7B is connected to the output of the operational amplifier U7B. The output of the operational amplifier U7B serves as the signal output of the high-pass filter unit.

[0015] In some embodiments, the low-pass filter unit includes an operational amplifier U10C. The non-inverting input of the operational amplifier U10C serves as the input of the low-pass filter unit. Resistors R57 and R56 are connected in sequence to the non-inverting input of the operational amplifier U10C. The non-inverting input of the operational amplifier U10C is connected to the output of the operational amplifier U10C in sequence through resistor R57 and capacitor 55. The inverting input of the operational amplifier U10C is connected to the output of the operational amplifier U10C. The output of the operational amplifier U10C serves as the output of the low-pass filter unit.

[0016] In some implementations, the notch filter module includes operational amplifiers U10A and U10B. The inverting input terminal of operational amplifier U10A is connected to the signal input terminal of the notch filter module via capacitor C57 and parallel resistors R53 and R55. The inverting input terminal of operational amplifier U10A is connected to the output terminal of operational amplifier U10A via resistor R51. The inverting input terminal of operational amplifier U10A is connected to the output terminal of operational amplifier U10A via capacitors C57 and C56. The signal input terminal of the notch filter module is connected to the inverting input terminal of operational amplifier U10B via resistor R54. The output terminal of operational amplifier U10A is connected to the inverting input terminal of operational amplifier U10B via resistor R58. The inverting input terminal and the output terminal of operational amplifier U10B are connected via resistor R52. The output terminal of operational amplifier U10B serves as the output terminal of the notch filter module.

[0017] Secondly, a method for acquiring electroencephalogram (EEG) signals is provided, applied to any of the aforementioned EEG signal acquisition devices, comprising the following steps:

[0018] S1: Acquire raw EEG signals;

[0019] S2: Improves common-mode rejection ratio through the right leg drive module;

[0020] S3: High-frequency and low-frequency noise are filtered out using a bandpass filter module;

[0021] S4: Eliminate power frequency interference using a notch filter module;

[0022] S5: The power frequency and its multiples are filtered using a power frequency filtering model in software.

[0023] The power frequency filtering model uses autocorrelation function, Fourier transform function and inverse Fourier transform function to filter power frequency interference and power frequency multiples.

[0024] The beneficial effects of this disclosure are that by improving the common-mode rejection ratio through the right leg drive module, filtering out high-frequency and low-frequency noise through the bandpass filter module, eliminating power frequency interference through the notch filter module, and filtering the power frequency and its multiples through the power frequency filter model in software, the radio frequency interference is improved, thereby greatly enhancing the anti-interference capability of EEG signal acquisition and improving the accuracy and stability of EEG signal acquisition.

[0025] Furthermore, unless otherwise specified in this disclosure, all technical solutions can be implemented using conventional methods in the field. Attached Figure Description

[0026] To more clearly illustrate the technical solutions in the specific embodiments of this disclosure or the prior art, the drawings used in the description of the specific embodiments or the prior art will be briefly introduced below. Obviously, the drawings described below are some embodiments of this disclosure. For those skilled in the art, other drawings can be obtained from these drawings without creative effort.

[0027] Figure 1 This is a schematic diagram of the structure of an electroencephalogram (EEG) signal acquisition device provided in one embodiment of the present disclosure;

[0028] Figure 2 A circuit diagram of the right leg drive in an electroencephalogram (EEG) signal acquisition device provided in one embodiment of this disclosure;

[0029] Figure 3 A circuit diagram of a high-pass filter unit in an electroencephalogram (EEG) signal acquisition device provided in one embodiment of this disclosure;

[0030] Figure 4 A circuit diagram of a low-pass filter unit in an electroencephalogram (EEG) signal acquisition device provided in one embodiment of this disclosure;

[0031] Figure 5 A circuit diagram of a notch filter module in an electroencephalogram (EEG) signal acquisition device provided in one embodiment of this disclosure;

[0032] Figure 6 A flowchart of step S5 of an electroencephalogram (EEG) signal acquisition method provided in one embodiment of this disclosure;

[0033] Figure 7 This is a schematic diagram of an autocorrelation curve provided in one embodiment of the present disclosure;

[0034] Figure 8 A schematic diagram of the envelope markings of an autocorrelation curve provided in one embodiment of this disclosure;

[0035] Figure 9 This is a schematic diagram illustrating the processing of power frequency interference according to an embodiment of this disclosure;

[0036] Figure 10 This is a schematic diagram illustrating the removal of power frequency interference from electroencephalogram (EEG) signals according to an embodiment of this disclosure. Detailed Implementation

[0037] To make the objectives, technical solutions, and advantages of this disclosure clearer, the following detailed description is provided in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only some, not all, of the embodiments of this disclosure, and are used merely to explain this disclosure and are not intended to limit it. All other embodiments obtained by those skilled in the art based on the embodiments of this disclosure without inventive effort are within the scope of protection of this disclosure.

[0038] It should be noted that the terms “comprising” and “having”, and any variations thereof, are intended to cover non-exclusive inclusion, for example, a process, method, system, product, or server that includes a series of steps or units is not necessarily limited to those steps or units that are explicitly listed, but may include other steps or units that are not explicitly listed or that are inherent to such process, method, product, or device.

[0039] Example 1:

[0040] refer to Figures 1 to 5 A brainwave signal acquisition device, comprising:

[0041] The right leg drive module 10, bandpass filter module 11, notch filter module 12, and power frequency filter model 13 are connected in sequence.

[0042] The right leg drive module 10 is used to improve the common-mode rejection ratio;

[0043] Bandpass filter module 11 is used to filter out high-frequency noise and low-frequency noise;

[0044] Notch filter module 12 is used to eliminate power frequency interference;

[0045] Power frequency filtering model 13 uses software to filter power frequency interference and power frequency multiples.

[0046] refer to Figure 2 The right leg drive module 10 includes an operational amplifier U12, which is configured as a differential amplifier to amplify the voltage signal and output it back to the human body to cancel the common-mode voltage, thereby helping to improve the common-mode rejection ratio.

[0047] Pin 1 of operational amplifier U12 is connected to a bias unit consisting of resistors R35 and R32 and capacitor C48. The EEG signal is input through pin 1. A feedback unit consisting of resistors R31 and R33 and capacitor C45 is connected between pins 1 and 4 of operational amplifier U12. Pin 3 of operational amplifier U12 is grounded, for example, connected to the right leg, and the signal is output to the right leg. Capacitors C48 and C45 are also used for filtering.

[0048] Resistor R36 is matched with the input resistor. Pin 5 of operational amplifier U12 is connected to the +5V power supply, and pin 2 of operational amplifier U12 is connected to the -5V power supply. Capacitors C49 and C53 are used for filtering to reduce high-frequency noise; capacitor C52 is used to stabilize the circuit and prevent oscillation.

[0049] Therefore, the right leg drive module 10 forms negative feedback in the pre-stage of EEG signal acquisition and feeds it back to the human body to neutralize the common-mode signal on the human body in order to eliminate the common-mode voltage.

[0050] refer to Figure 3 and Figure 4 The bandpass filter module 11 includes a high-pass filter unit and a low-pass filter unit. The high-pass filter unit is used to filter out high-frequency noise in the EEG signal, and the low-pass filter unit is used to filter out low-frequency noise in the EEG signal.

[0051] The passband of the bandpass filter module 11 is 0.05Hz to 150Hz.

[0052] The high-pass filter unit may include operational amplifier U7B. The non-inverting input of operational amplifier U7B serves as the signal input of the high-pass filter unit, and capacitor C41 is connected to the non-inverting input of operational amplifier U7B. The inverting input of operational amplifier U7B is connected to its output, and the output of operational amplifier U7B serves as the signal output of the high-pass filter unit. The cutoff frequency of the high-pass filter unit is 0.05Hz.

[0053] The low-pass filter unit may include an operational amplifier U10C. The non-inverting input of operational amplifier U10C serves as the input of the low-pass filter unit. Resistors R57 and R56 are connected sequentially to the non-inverting input of operational amplifier U10C. The non-inverting input of operational amplifier U10C is connected to the output of operational amplifier U10C via resistor R57 and capacitor R55. The inverting input of operational amplifier U10C is connected to its output. The output of operational amplifier U10C serves as the output of the low-pass filter unit. The cutoff frequency of the low-pass filter unit is 150Hz.

[0054] refer to Figure 5 The notch filter module 12 may include operational amplifiers U10A and U10B. The inverting input terminal of operational amplifier U10A is connected to the signal input terminal of the notch filter module via capacitor C57 and parallel resistors R53 and R55. The inverting input terminal of operational amplifier U10A is connected to the output terminal of operational amplifier U10A via resistor R51. The inverting input terminal of operational amplifier U10A is connected to the output terminal of operational amplifier U10A via capacitors C57 and C56. The signal input terminal of the notch filter module is connected to the inverting input terminal of operational amplifier U10B via resistor R54. The output terminal of operational amplifier U10A is connected to the inverting input terminal of operational amplifier U10B via resistor R58. The inverting input terminal and the output terminal of operational amplifier U10B are connected via resistor R52. The output terminal of operational amplifier U10B serves as the output terminal of the notch filter module.

[0055] The notch filter module 12 can be a 50Hz notch filter circuit, thereby effectively eliminating power frequency interference.

[0056] Among them, operational amplifiers U7B, U10C, U10A and U10B can all be selected as operational amplifiers with the model number GS8634-TR.

[0057] The power frequency filtering model 13 achieves power frequency and power frequency multiple filtering through autocorrelation function, Fourier transform function and inverse Fourier transform function.

[0058] The power frequency filtering model 13 implements filtering through software, not hardware. This model is constructed using programming and mathematical formulas, for example, on a host computer. A host computer is a computer capable of centralized monitoring and management of the entire system, possessing functions such as human-computer interaction, data processing and storage, communication, programming, and configuration. The power frequency filtering model is then programmed and constructed on the host computer. Alternatively, the power frequency filtering model 13 can also be programmed and constructed using a microcontroller.

[0059] The beneficial effects of this disclosure are that the common-mode rejection ratio is improved by the right leg drive module 10, high-frequency noise and low-frequency noise are filtered out by the bandpass filter module 11, power frequency interference is eliminated by the notch filter module 12, and power frequency interference and power frequency multiples are filtered by the power frequency filter model 13 in software, thereby improving radio frequency interference and greatly improving the anti-interference ability of EEG signal acquisition, and improving the accuracy and stability of EEG signal acquisition.

[0060] Example 2:

[0061] A method for acquiring electroencephalogram (EEG) signals, used to execute the aforementioned EEG signal acquisition device, includes the following steps:

[0062] S1: Acquire raw EEG signals;

[0063] S2: Improve the common-mode rejection ratio by using the right leg drive module 10;

[0064] S3: High-frequency noise and low-frequency noise are filtered out by the bandpass filter module 11;

[0065] S4: Eliminate power frequency interference through notch filter module 12;

[0066] S5: The power frequency and its multiples are filtered using the power frequency filtering model 13 in software.

[0067] Among them, the power frequency filtering model 13 achieves power frequency and power frequency multiple filtering through autocorrelation function, Fourier transform function and inverse Fourier transform function.

[0068] The power frequency filtering model 13 implements filtering through software, not hardware. This model is constructed using programming and mathematical formulas, for example, on a host computer. A host computer is a computer capable of centralized monitoring and management of the entire system, possessing functions such as human-computer interaction, data processing and storage, communication, programming, and configuration. The power frequency filtering model is then programmed and constructed on the host computer. Alternatively, the power frequency filtering model 13 can also be programmed and constructed using a microcontroller.

[0069] Furthermore, step S5 specifically includes:

[0070] S51: Set low-frequency signal, high-frequency signal, 50Hz power frequency interference and white noise; set sampling frequency and signal length;

[0071] Specifically, the parameters are: 1Hz low-frequency signal, 100Hz or 150Hz high-frequency signal, 50Hz power frequency interference and white noise, sampling frequency fs = 1000, signal length N = 3000, sampling interval t = 1 / fs, etc. Of course, the above parameters can be set and adjusted appropriately according to the situation.

[0072] S52: Autocorrelation calculation is performed on 50Hz power frequency interference and white noise using the autocorrelation function (1-1) to obtain the autocorrelation curve, thereby identifying the periodic component of power frequency interference in the signal;

[0073]

[0074] in:

[0075] x(t) represents the signal;

[0076] τ(tau) is the time delay, representing the delay between the signal and itself at different points in time, and is usually a real number or an integer;

[0077] R(τ) autocorrelation function is a measure of the correlation between a signal and itself under a time delay τ;

[0078] Therefore, the autocorrelation function, also called serial correlation, is the cross-correlation between a signal and itself at different time points. The autocorrelation function is used to autocorrelate a 50Hz power frequency interference signal with a white noise signal, obtaining the autocorrelation value and delay time, thereby identifying the frequency (period) of the 50Hz power frequency interference, which can then be removed.

[0079] S53: Mark all the maximum points of the autocorrelation curve by the envelope to show the overall fluctuation trend and the fluctuation of the high-frequency signal, so as to better identify the periodic components of power frequency interference in the signal.

[0080] The arithmetic mean of all marked maxima is used to achieve period rounding, thus determining the period of the 50Hz power frequency interference.

[0081] S54: The EEG signal is converted from a time domain signal to a frequency domain signal through the Fourier transform function (1-2) in order to accurately remove 50Hz power frequency interference;

[0082]

[0083] in:

[0084] X(k) is a frequency domain signal;

[0085] x(n) is a time-domain signal;

[0086] N is the signal length;

[0087] n is the index of the time-domain signal, representing the position of the signal on the time axis. In discrete signal processing, n usually starts from 0, representing the nth sampling point of the signal.

[0088] k is the frequency index, which represents the position in the frequency domain. The value of k usually ranges from 0 to N-1.

[0089] S55: Remove the 50Hz frequency component from the frequency domain signal;

[0090] Find the frequency index k of 50Hz in the frequency domain signal. 50 k 50 = (50 / fs)×N, where fs is the sampling frequency and N is the signal length, representing X(k) in the frequency domain signal X(k). 50 ) and X(Nk 50 The value is set to 0, thereby eliminating 50Hz power frequency interference.

[0091] S56: The frequency domain signal with the 50Hz frequency component removed is subjected to inverse Fourier transform through the inverse Fourier transform function (1-3) to obtain the time domain signal after the 50Hz frequency component is removed, and the processed EEG signal is output.

[0092]

[0093] in:

[0094] x′(n) is the time-domain signal after removing the 50Hz frequency component;

[0095] N is the signal length;

[0096] k is the frequency index;

[0097] n is the index of the time-domain signal, representing the position of the signal on the time axis. In discrete signal processing, n usually starts from 0, representing the nth sampling point of the signal.

[0098] Therefore, the power frequency filtering model 13 uses autocorrelation function and Fourier transform to identify and remove 50Hz power frequency interference in EEG signals, enabling the processing of EEG signals by software or programming, removing 50Hz power frequency interference more meticulously and thoroughly, further removing noise, and improving the accuracy of EEG signals.

[0099] Similarly, power frequency filtering model 13 can remove interference at power frequency multiples such as 100Hz and 150Hz.

[0100] The beneficial effects of this disclosure are that the acquired EEG signal acquisition method first passes the raw EEG signal through the right leg drive module 10 to improve the common-mode rejection ratio, then the bandpass filter module 11 filters out high-frequency and low-frequency noise, then the notch filter module 12 eliminates power frequency interference, and finally, the power frequency filtering model 13 filters the power frequency and its multiples to improve radio frequency interference. The EEG signal undergoes multiple filtering processes, especially with hardware filtering at the front end and software filtering at the back end. This combined filtering method more effectively and thoroughly removes interference and noise, improving the accuracy and stability of EEG signal acquisition.

[0101] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of this disclosure, and are not intended to limit them. Although this disclosure has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this disclosure.

Claims

1. A brainwave signal acquisition device, characterized in that, include: The right leg drive module, bandpass filter module, notch filter module, and power frequency filter model are connected in sequence. The right leg drive module is used to improve the common-mode rejection ratio; The bandpass filter module is used to filter out high-frequency noise and low-frequency noise; The notch filter module is used to eliminate power frequency interference; The power frequency filtering model uses software to filter power frequency interference and power frequency multiples.

2. The electroencephalogram (EEG) signal acquisition device according to claim 1, characterized in that, The right leg drive module includes an operational amplifier U12. Pin 1 of the operational amplifier U12 is connected to a bias unit consisting of resistors R35 and R32 and capacitor C48. Pins 1 and 4 of the operational amplifier U12 are connected to a feedback unit consisting of resistors R31 and R33 and capacitor C45. Pin 3 of the operational amplifier U12 is grounded.

3. The electroencephalogram (EEG) signal acquisition device according to claim 1, characterized in that, The bandpass filter module includes a high-pass filter unit and a low-pass filter unit. The high-pass filter unit is used to filter out high-frequency noise in the EEG signal, and the low-pass filter unit is used to filter out low-frequency noise in the EEG signal.

4. The electroencephalogram (EEG) signal acquisition device according to claim 3, characterized in that, The high-pass filter unit includes an operational amplifier U7B. The non-inverting input terminal of the operational amplifier U7B serves as the signal input terminal of the high-pass filter unit. A capacitor C41 is connected to the non-inverting input terminal of the operational amplifier U7B. The inverting input terminal of the operational amplifier U7B is connected to the output terminal of the operational amplifier U7B. The output terminal of the operational amplifier U7B serves as the signal output terminal of the high-pass filter unit.

5. The electroencephalogram (EEG) signal acquisition device according to claim 3, characterized in that, The low-pass filter unit includes an operational amplifier U10C. The non-inverting input of the operational amplifier U10C serves as the input of the low-pass filter unit. Resistors R57 and R56 are connected sequentially to the non-inverting input of the operational amplifier U10C. The non-inverting input of the operational amplifier U10C is connected to the output of the operational amplifier U10C via resistor R57 and capacitor 55. The inverting input of the operational amplifier U10C is connected to the output of the operational amplifier U10C. The output of the operational amplifier U10C serves as the output of the low-pass filter unit.

6. The electroencephalogram (EEG) signal acquisition device according to claim 1, characterized in that, The notch filter module includes operational amplifiers U10A and U10B. The inverting input terminal of operational amplifier U10A is connected to the signal input terminal of the notch filter module via capacitor C57 and parallel resistors R53 and R55. The inverting input terminal of operational amplifier U10A is connected to the output terminal of operational amplifier U10A via resistor R51. The inverting input terminal of operational amplifier U10A is connected to the output terminal of operational amplifier U10A via capacitors C57 and C56. The signal input terminal of the notch filter module is connected to the inverting input terminal of operational amplifier U10B via resistor R54. The output terminal of operational amplifier U10A is connected to the inverting input terminal of operational amplifier U10B via resistor R58. The inverting input terminal and the output terminal of operational amplifier U10B are connected via resistor R52. The output terminal of operational amplifier U10B serves as the output terminal of the notch filter module.

7. A method for acquiring electroencephalogram (EEG) signals, applied to an EEG signal acquisition device according to any one of claims 1-6, the method comprising the following steps: S1: Acquire raw EEG signals; S2: Improves common-mode rejection ratio through the right leg drive module; S3: High-frequency and low-frequency noise are filtered out using a bandpass filter module; S4: Eliminate power frequency interference using a notch filter module; S5: Power frequency interference and power frequency multiples are filtered using a power frequency filtering model in software. in, The power frequency filtering model achieves power frequency and power frequency multiple filtering through autocorrelation function, Fourier transform function and inverse Fourier transform function.

8. The method for acquiring electroencephalogram (EEG) signals according to claim 7, characterized in that, Step S5 specifically includes: S51: Set low-frequency signal, high-frequency signal, 50Hz power frequency interference and white noise; set sampling frequency and signal length; S52: Autocorrelation calculation is performed on 50Hz power frequency interference and white noise using the autocorrelation function (1-1) to obtain the autocorrelation curve; S53: Mark all the maximum points of the autocorrelation curve using the envelope; calculate the arithmetic mean of all the marked maximum points; S54: Convert the EEG signal from the time domain to the frequency domain using the Fourier transform function (1-2); S55: Remove the 50Hz frequency component from the frequency domain signal; S56: The frequency domain signal with the 50Hz frequency component removed is subjected to inverse Fourier transform through the inverse Fourier transform function (1-3) to obtain the time domain signal after the 50Hz frequency component is removed, and the processed EEG signal is output.

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