Electroencephalogram signal acquisition system and method thereof

Abstract

The application relates to the field of brain function detection, and discloses an electroencephalogram signal collection system and a method thereof. The electroencephalogram signal collection system comprises a pretreatment device, a data selector and a digital filter which are connected in sequence. The pretreatment device is used for performing signal pretreatment on received various electroencephalogram signals to obtain pretreatment signals corresponding to the various electroencephalogram signals. The data selector is used for receiving the pretreatment signals corresponding to the various electroencephalogram signals sent by the pretreatment device, performing classification processing on the pretreatment signals corresponding to the various electroencephalogram signals to obtain first-type processing signals and / or second-type processing signals, sending the first-type processing signals to a data processing module through the digital filter, and sending the second-type processing signals to the data processing module through a data transmission channel. The digital filter is used for adjusting and processing the sampling rate and resolution of the first-type processing signals. The signal collection system has the characteristics of simple structure and multiple types of processing signals.

Description

Technical Field

[0001] This invention relates to the field of brain function detection, and in particular to an electroencephalogram (EEG) signal acquisition system and method. Background Technology

[0002] Brain-computer interfaces, also known as "brain ports" or "brain-computer fusion sensing," are direct connections established between the human or animal brain (or a culture of brain cells) and external devices. As a multidisciplinary technology, brain-computer interfaces have received widespread attention from the global scientific and industrial communities.

[0003] The signals acquired by brain-computer interfaces need to be converted, processed, and analyzed by brain electrical devices (e.g., electroencephalography). Different computer devices are typically used to convert, process, and analyze different brain signals, making the computer devices complex in structure. Summary of the Invention

[0004] The present invention aims to solve the technical problem of the complex structure of computer devices for processing electroencephalogram (EEG) signals in the prior art.

[0005] To address the aforementioned technical problems, this application discloses an electroencephalogram (EEG) signal acquisition system, which includes a preprocessing device, a data selector, and a digital filter connected in sequence.

[0006] The preprocessing device is used to preprocess multiple received EEG signals to obtain multiple preprocessed signals corresponding to the EEG signals;

[0007] The data selector is used to receive preprocessed signals corresponding to various EEG signals sent by the preprocessing device, and to classify the preprocessed signals corresponding to various EEG signals to obtain a first type of processed signal and / or a second type of processed signal; and to send the first type of processed signal to the data processing module through the digital filter; and to send the second type of processed signal to the data processing module through the data transmission channel.

[0008] Digital filters are used to adjust the sampling rate and resolution of signals processed in the first type.

[0009] Optionally, the first type of processed signal is a low-frequency signal;

[0010] The second type of processed signal is a high-frequency signal;

[0011] The amplitude of the first type of processed signal is smaller than the amplitude of the second type of processed signal.

[0012] Optionally, the EEG signal corresponding to the first type of processed signal includes EEG wave signals;

[0013] The EEG signals corresponding to this second type of processed signal include local field potential signals and action potential signals.

[0014] Optionally, the digital filter may include a smoothing filter or a finite impulse response filter.

[0015] Optionally, the smoothing filter is used to process the first type of processed signal using a smoothing algorithm to obtain the first type of processed signal with high resolution and low sampling rate.

[0016] Optionally, the digital filter is the finite impulse response filter;

[0017] The first-type processed signal output by the finite impulse response filter is determined based on the first-type processed signal input, the filter coefficients, and the number of filter coefficients.

[0018] Optionally, the preprocessing device includes an amplifier;

[0019] This amplifier is used to amplify various received EEG signals.

[0020] Optionally, the preprocessing device may also include a bandpass filter;

[0021] The bandpass filter is used to perform frequency band filtering on the various EEG signals received from the amplifier, thereby obtaining the target frequency band signals corresponding to the various EEG signals.

[0022] Optionally, the preprocessing device may also include an analog-to-digital converter;

[0023] The input of the analog-to-digital converter is connected to the output of the bandpass filter;

[0024] The output of the analog-to-digital converter is connected to the data selector;

[0025] The analog-to-digital converter has an sampling rate greater than 30 kHz and a resolution greater than or equal to 10 bits.

[0026] On the other hand, this application also discloses a signal acquisition method using the above-mentioned EEG signal acquisition system, which includes:

[0027] Receives preprocessed signals corresponding to various EEG signals sent by the preprocessing device;

[0028] The preprocessed signals corresponding to various EEG signals are classified and processed to obtain the first type of processed signal and / or the second type of processed signal;

[0029] The first type of processed signal is sent to the data processing module through the digital filter; the digital filter is used to adjust the sampling rate and resolution of the first type of processed signal.

[0030] The second type of processed signal is sent to the data processing module via the data transmission channel.

[0031] By adopting the above technical solution, the EEG signal acquisition system provided in this application has the following beneficial effects:

[0032] The EEG signal acquisition system includes a preprocessing unit, a data selector, and a digital filter connected in sequence. The preprocessing unit performs signal preprocessing on multiple received EEG signals to obtain preprocessed signals corresponding to each EEG signal. The data selector receives the preprocessed signals from the preprocessing unit and classifies them to obtain a first-class processed signal and a second-class processed signal. The first-class processed signal is then sent to the data processing module via the digital filter, and the second-class processed signal is sent to the data processing module via a data transmission channel. The digital filter adjusts the sampling rate and resolution of the first-class processed signal. In this configuration, the present application can perform signal processing on different types of EEG signals based on this EEG signal acquisition system. Furthermore, the system has only one preprocessing unit, offering advantages such as simple structure and the ability to process multiple signal types. Attached Figure Description

[0033] To more clearly illustrate the technical solutions in the embodiments of this application, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments of this application. For those skilled in the art, other drawings can be obtained based on these drawings without creative effort.

[0034] Figure 1 This is a schematic diagram of an optional electroencephalogram (EEG) signal acquisition system according to this application;

[0035] Figure 2 This is a schematic diagram of an optional signal data processing procedure according to this application;

[0036] Figure 3 This is a schematic diagram of another optional EEG signal acquisition system according to this application;

[0037] Figure 4 This is a schematic diagram of an optional finite impulse response filter according to this application;

[0038] Figure 5 This is a flowchart illustrating one possible signal acquisition method of this application.

[0039] The following is supplementary explanation of the attached figures:

[0040] 1-Preprocessing unit; 11-Amplifier; 12-Bandpass filter; 13-Analog-to-digital converter; 2-Data selector; 3-Digital filter; 4-Data processing module. Detailed Implementation

[0041] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of them. All other embodiments obtained by those skilled in the art based on the embodiments of this application without creative effort are within the scope of protection of this application.

[0042] The term "an embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of this application. In the description of this application, it should be understood that the terms "upper," "lower," "top," "bottom," etc., indicating orientation or positional relationships based on the orientation or positional relationships shown in the accompanying drawings, are only for the convenience of describing this application and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this application. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of that feature. Moreover, the terms "first," "second," etc., are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such data can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described herein.

[0043] See Figure 1 , Figure 1This is a schematic diagram of an optional EEG signal acquisition system according to this application. This application discloses an EEG signal acquisition system, which includes a preprocessing device 1, a data selector 2, and a digital filter 3 connected in sequence. The preprocessing device 1 is used to preprocess multiple received EEG signals to obtain multiple preprocessed signals corresponding to the EEG signals. The data selector 2 is used to receive the multiple preprocessed signals corresponding to the EEG signals sent by the preprocessing device 1, and classify the multiple preprocessed signals to obtain a first-class processed signal and / or a second-class processed signal. The first-class processed signal is then sent to a data processing module 4 via the digital filter 3. The second-class processed signal is also sent to the data processing module 4 via a data transmission channel. The digital filter 3 is used to adjust the sampling rate and resolution of the first-class processed signal. This system not only enables the acquisition and processing of multiple EEG signals but also has the advantage of a simple system structure.

[0044] Optionally, the system may also include multiple brain electrode structures, each of which corresponds to the acquisition of at least one type of brain electrical signal. For example, during the signal acquisition process, although the same type of signal is acquired, such as brain wave signals, a brain electrode structure may be set at different locations in the cerebral cortex due to the requirements of the acquisition site.

[0045] Optionally, the data transmission channel can be a data cable; the various devices and equipment in this embodiment can be connected via wired means.

[0046] In one feasible embodiment, the EEG signal corresponding to the first type of processed signal includes an electroencephalogram (EEG) signal; the EEG signal corresponding to the second type of processed signal includes a local field potential (LFP) signal and an action potential (Sipke) signal.

[0047] The brainwave signal is generally obtained by attaching brain structures to the scalp in a non-implantable manner; it is characterized by small amplitude (e.g., 10 microvolts), low frequency and narrow bandwidth (e.g., around 100 Hz), and the signal after subsequent preprocessing is a narrow-band, high-resolution signal with a low sampling rate.

[0048] The local field potential signal and action potential signal are generally brain signals obtained from the brain by implanting intracranial electrodes. The local field potential signal and action potential signal are characterized by high amplitude (e.g., 1 millivolt), high frequency and wide bandwidth (around 10 kHz). The signal after preprocessing is a wide bandwidth, low resolution and high sampling rate signal.

[0049] For EEG signals, due to their small amplitude and narrow bandwidth, a low-noise, high-precision digital-to-analog converter circuit is required, but the sampling rate requirement is not high. For local field potential signals and action potential signals, due to their large amplitude and wide bandwidth, a high sampling rate is required, but the requirements for noise and accuracy are not high. The signal acquisition circuits for these two types of brain signals are different and not interchangeable. The system provided in this application effectively achieves the acquisition and processing of the above-mentioned EEG signals while reducing the complexity of the system structure.

[0050] This application is not limited to the above-mentioned EEG signals. In one feasible embodiment, the first type of processed signal is a low-frequency signal, and the second type of processed signal is a high-frequency signal.

[0051] Optionally, the amplitude of the first type of processed signal is smaller than the amplitude of the second type of processed signal. Optionally, the difference between the two is 2 to 3 orders of magnitude. For example, the amplitude of the second type of processed signal is equal to 100 times the amplitude of the first type of processed signal. However, in practice, the difference between the two is not limited to the above-mentioned numerical limits based on the different signals.

[0052] In one possible embodiment, the digital filter 3 includes a smoothing filter or a finite impulse response filter.

[0053] In one feasible embodiment, the smoothing filter is used to perform data processing on the first type of processed signal using a smoothing algorithm to obtain the first type of processed signal with high resolution and low sampling rate.

[0054] Optional, see below Figure 2 , Figure 2 This is a schematic diagram of an optional signal data processing procedure according to this application. The method for processing the smoothing filter data includes: acquiring a first type of processed signal; performing sampling point quantization processing on the first processed signal to obtain a continuously distributed sampling dataset; the sampling dataset includes multiple sample values ​​and the sampling time corresponding to each of the multiple sample values; dividing the sample values ​​corresponding to every N adjacent sampling times into a group according to the sampling time order to obtain multiple groups of sampling sets; averaging the N sample values ​​of each group of sampling sets in the multiple groups of sampling sets to obtain the average value of each group of sampling sets; the sampling rate of the digital signal processed in this way is reduced, and its resolution is also improved due to the averaging calculation, thereby improving the signal-to-noise ratio of the signal.

[0055] Optionally, the relationship between the output signal y(n) of the smoothing filter of length N and the input signal x(n) of the input time series is as follows:

[0056]

[0057] Where N is an integer greater than 0.

[0058] In one feasible embodiment, the digital filter 3 is the finite impulse response filter, and the first type of processed signal output by the finite impulse response filter is determined based on the input first type of processed signal, the filter coefficients, and the number of filter coefficients.

[0059] Finite impulse response filters are also known as "non-recursive filters".

[0060] Optionally, the relationship between the output y(n) of a finite impulse response filter of length N and the input time series x(n) is as follows:

[0061]

[0062] in:

[0063] x(n) is the input signal;

[0064] y(n) is the filtered output signal;

[0065] h(n) is the filter coefficient of the finite impulse response filter;

[0066] N represents the number of taps in the finite impulse response filter, and the filter order is N-1; k = 0, 1, ..., N-1.

[0067] The above equation yields the implementation structure of the finite impulse response filter. It has N taps (filter coefficients), therefore consisting of N multipliers, N-1 accumulators, and N-1 delay units (Z-1). See [reference needed]. Figure 3 , Figure 3 This is a schematic diagram of an optional finite impulse response filter according to this application.

[0068] After using the above filter, the increase in resolution is Log2N. If N=16, then the resolution can be increased by 4 bits.

[0069] The approximate formula for calculating the reduction in signal bandwidth is BW≈0.433Fs / N (where Fs is the actual ADC sampling rate).

[0070] In one possible embodiment, see [reference] Figure 4 , Figure 4 This is a schematic diagram of another optional EEG signal acquisition system according to this application. The preprocessing device 1 includes an amplifier 11; the amplifier 11 is used to amplify and process the received various EEG signals.

[0071] Optionally, the amplifier 11 employs a low-noise operational amplifier and is capable of providing signal amplification of more than 100 times.

[0072] In one feasible embodiment, the preprocessing device 1 further includes a bandpass filter 12; the bandpass filter 12 is used to perform frequency band filtering processing on the various EEG signals received from the amplifier 11 to obtain target frequency band signals corresponding to the various EEG signals.

[0073] Optionally, the bandwidth of the bandpass filter 12 can be set between 0.1 Hz and 10 kHz, that is, the target frequency band is 0.1 Hz to 10 kHz.

[0074] In one feasible embodiment, the preprocessing device 1 further includes an analog-to-digital converter 13; the input of the analog-to-digital converter 13 is connected to the output of the bandpass filter 12; the output of the analog-to-digital converter 13 is connected to the data selector 2; the analog-to-digital converter 13 has an sampling rate greater than 30 kHz and a resolution greater than or equal to 10 bits.

[0075] On the other hand, see Figure 5 , Figure 5 This is a flowchart illustrating one possible signal acquisition method of this application. This application also discloses a signal acquisition method implemented using the above-mentioned EEG signal acquisition system, which includes:

[0076] S501: Receives preprocessing signals corresponding to various EEG signals sent by the preprocessing device 1.

[0077] S502: Classify and process the preprocessed signals corresponding to the various EEG signals to obtain the first type of processed signal and / or the second type of processed signal.

[0078] S503: The first type of processed signal is sent to the data processing module 4 through the digital filter 3; the digital filter 3 is used to adjust the sampling rate and resolution of the first type of processed signal.

[0079] S504: Send the second type of processing signal to the data processing module 4 via the data transmission channel.

[0080] In this embodiment, the subject of the signal acquisition method is the data selector 2. Since the relevant methods have been described in the discussion of the EEG signal acquisition system above, they will not be repeated here. Other implementation processes of this method are described above.

[0081] The above description is only an optional embodiment of this application and is not intended to limit this application. Any modifications, equivalent substitutions, improvements, etc., made within the spirit and principles of this application should be included within the protection scope of this application.

Claims

1. An electroencephalography signal acquisition system, characterized in that, It includes multiple brain electrode structures connected in sequence, a preprocessing device (1), a data selector (2), and a digital filter (3). The preprocessing device (1) is used to preprocess the received multiple EEG signals to obtain preprocessed signals corresponding to the multiple EEG signals; The data selector (2) is used to receive preprocessed signals corresponding to various EEG signals sent by the preprocessing device (1), and classify the preprocessed signals corresponding to various EEG signals to obtain a first type of processed signal and / or a second type of processed signal; and send the first type of processed signal to the data processing module (4) through the digital filter (3); and send the second type of processed signal to the data processing module (4) through the data transmission channel; the first type of processed signal is a brain signal obtained by attaching it to the scalp in a non-implantable manner; the second type of processed signal is a brain signal obtained from the brain by implantation. The digital filter (3) is used to adjust the sampling rate and resolution of the first type of processed signal; Each of the multiple brain electrode structures corresponds to the acquisition of at least one type of electroencephalogram (EEG) signal.

2. The EEG signal acquisition system according to claim 1, characterized in that, The first type of processed signal is a low-frequency signal; The second type of processed signal is a high-frequency signal; The amplitude of the first type of processed signal is smaller than the amplitude of the second type of processed signal.

3. The EEG signal acquisition system according to claim 2, characterized in that, The EEG signals corresponding to the first type of processed signals include EEG wave signals; The EEG signals corresponding to the second type of processed signals include local field potential signals and action potential signals.

4. The EEG signal acquisition system according to claim 1, characterized in that, The digital filter (3) includes a smoothing filter or a finite impulse response filter.

5. The EEG signal acquisition system according to claim 4, characterized in that, The smoothing filter is used to process the first type of processed signal using a smoothing algorithm to obtain the first type of processed signal with high resolution and low sampling rate.

6. The EEG signal acquisition system according to claim 4, characterized in that, The digital filter (3) is the finite impulse response filter; The first type of processed signal output by the finite impulse response filter is determined based on the input first type of processed signal, the filter coefficients, and the number of the filter coefficients.

7. The EEG signal acquisition system according to claim 1, characterized in that, The preprocessing device (1) includes an amplifier (11); The amplifier (11) is used to amplify the received multiple EEG signals.

8. The EEG signal acquisition system according to claim 7, characterized in that, The preprocessing device (1) further includes a bandpass filter (12); The bandpass filter (12) is used to perform frequency band filtering on the various EEG signals sent by the amplifier (11) to obtain the target frequency band signals corresponding to the various EEG signals.

9. The EEG signal acquisition system according to claim 8, characterized in that, The preprocessing device (1) also includes an analog-to-digital converter (13); The input of the analog-to-digital converter (13) is connected to the output of the bandpass filter (12); The output of the analog-to-digital converter (13) is connected to the data selector (2); The analog-to-digital converter (13) has a sampling rate greater than 30 kHz and a resolution greater than or equal to 10 bits.

10. A signal acquisition method using the electroencephalogram (EEG) signal acquisition system as described in any one of claims 1-9, characterized in that, include: Receive preprocessing signals corresponding to various EEG signals sent by the preprocessing device (1); The pretreatment device (1) is connected to multiple brain electrode structures; Each of the multiple brain electrode structures corresponds to the acquisition of at least one type of brain electrical signal; The preprocessed signals corresponding to the various EEG signals are classified and processed to obtain a first type of processed signal and / or a second type of processed signal; the first type of processed signal is a brain signal obtained by attaching it to the scalp in a non-implantable manner; the second type of processed signal is a brain signal obtained from the brain by implantation. The first type of processed signal is sent to the data processing module (4) through the digital filter (3); the digital filter (3) is used to adjust the sampling rate and resolution of the first type of processed signal. The second type of processed signal is sent to the data processing module (4) via the data transmission channel.

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