CN113509188A

CN113509188A - Method and device for amplifying electroencephalogram signal, electronic device and storage medium

Info

Publication number: CN113509188A
Application number: CN202110426679.0A
Authority: CN
Inventors: 许敏鹏; 罗睿心; 吴乔逸; 明东
Original assignee: Tianjin University
Current assignee: Tianjin University
Priority date: 2021-04-20
Filing date: 2021-04-20
Publication date: 2021-10-19
Anticipated expiration: 2041-04-20
Also published as: CN113509188B

Abstract

The present disclosure provides an amplification method, an amplification device and a storage medium for an electroencephalogram signal, wherein the method comprises: acquiring an electroencephalogram signal, determining a first lead from a plurality of leads contained in the electroencephalogram signal, determining at least one second lead from the plurality of leads from which the first lead is removed to form a second lead set, and taking the first lead and the second lead set as a current arrangement combination form; respectively determining signals of a first lead under a plurality of first time segments as a plurality of corresponding first signals, respectively determining signals of a second lead set under a plurality of first time segments as a plurality of corresponding second signals, and respectively constructing a plurality of corresponding spatial filters according to the plurality of first signals and the plurality of second signals; respectively carrying out spatial filtering processing on the signals of the corresponding first time segment and the signals of the corresponding second time segment by utilizing a plurality of spatial filters to obtain amplified signals; and splicing and integrating a plurality of amplified signals respectively corresponding to the segmented electroencephalogram signals so as to amplify the electroencephalogram signals.

Description

Method and device for amplifying electroencephalogram signal, electronic device and storage medium

Technical Field

The present disclosure relates to the field of computer technologies, and in particular, to a method and an apparatus for amplifying an electroencephalogram signal, an electronic device, and a storage medium.

Background

Electroencephalography (EEG) is a general reflection of electrophysiological activity of brain neurons in the cerebral cortex and can be recorded by scalp electrodes (fig. 1 shows a schematic electrode placement). The time resolution of the electroencephalogram signal can reach the millisecond level or even higher level, and the brain-computer interface (BCI) is facilitated to effectively decode brain information in real time. However, the spatial resolution is limited by the number of channels of the acquisition device, typically only up to the order of centimeters.

The traditional signal processing method for electroencephalogram signals mainly comprises three steps of preprocessing, feature extraction and pattern recognition (as shown by a dotted line frame in fig. 2A), and is very important in practical application. The signal preprocessing can suppress noise signals, is beneficial to feature extraction and classification identification, and cannot increase effective component information of the signals. In recent years, the BCI system using EEG signals as a brain information acquisition method has been rapidly developed, and its performance has been continuously optimized. However, the decoding of the electroencephalogram signal still has the limitations of low spatial resolution, small data size, and the like. In order to effectively utilize existing electroencephalogram data, researchers desire to increase the effective information of signals by a data amplification method. EEG signals are multi-channel dynamic time series and are not suitable for geometric transformation methods using conventional image enhancement. The electroencephalogram signal amplification method in the current research has limited effect and poor robustness, so that the method cannot be widely used in the actual BCI system construction.

Disclosure of Invention

The present disclosure provides a method and an apparatus for amplifying an electroencephalogram signal, an electronic device, and a storage medium, and aims to solve at least one of the technical problems in the related art to some extent.

According to a first aspect, there is provided a method of amplifying an electroencephalogram signal, comprising: acquiring an electroencephalogram signal, determining a first lead from a plurality of leads contained in the electroencephalogram signal, determining at least one second lead from the plurality of leads from which the first lead is removed to form a second lead set, and taking the first lead and the second lead set as a current arrangement combination form; dividing the electroencephalogram signal into a plurality of segmented electroencephalogram signals, and dividing the plurality of segmented electroencephalogram signals into a plurality of corresponding signals of a first time segment and a plurality of corresponding signals of a second time segment; respectively determining signals of a first lead under a plurality of first time segments as a plurality of corresponding first signals, respectively determining signals of a second lead set under a plurality of first time segments as a plurality of corresponding second signals, and respectively constructing a plurality of corresponding spatial filters according to the plurality of first signals and the plurality of second signals; respectively carrying out spatial filtering processing on the signals of the corresponding first time segment and the signals of the corresponding second time segment by utilizing a plurality of spatial filters to obtain amplified signals; and splicing and integrating a plurality of amplified signals respectively corresponding to the segmented electroencephalogram signals so as to amplify the electroencephalogram signals.

According to a second aspect, there is provided an amplification apparatus for an electroencephalogram signal, comprising: the signal acquisition module is used for acquiring an electroencephalogram signal, determining a first lead from a plurality of leads contained in the electroencephalogram signal, determining at least one second lead from the plurality of leads without the first lead to form a second lead set, and taking the first lead and the second lead set as a current arrangement combination form; the signal dividing module is used for dividing the electroencephalogram signal into a plurality of segmented electroencephalogram signals, and respectively dividing the plurality of segmented electroencephalogram signals into a plurality of corresponding signals of a first time segment and a plurality of corresponding signals of a second time segment; the filter construction module is used for respectively determining the signals of the first lead under a plurality of first time segments as a plurality of corresponding first signals, respectively determining the signals of the second lead set under a plurality of first time segments as a plurality of corresponding second signals, and respectively constructing a plurality of corresponding spatial filters according to the plurality of first signals and the plurality of second signals; the filtering processing module is used for respectively carrying out spatial filtering processing on the signals of the corresponding first time segment and the signals of the corresponding second time segment by utilizing a plurality of spatial filters to obtain amplified signals; and the first amplification module is used for splicing and integrating a plurality of amplification signals respectively corresponding to the segmented electroencephalogram signals so as to amplify the electroencephalogram signals.

According to a third aspect, there is provided an electronic device comprising: at least one processor; and a memory communicatively coupled to the at least one processor; wherein the memory stores instructions executable by the at least one processor, the instructions being executable by the at least one processor to enable the at least one processor to perform the method for brain electrical signal amplification disclosed herein.

According to a fourth aspect, there is provided a non-transitory computer readable storage medium storing computer instructions for causing a computer to perform the method for amplification of brain electrical signals disclosed in the present disclosure.

According to the technical scheme, the electroencephalogram signals are filtered through the built and applied spatial filter to obtain the amplification signals, and the amplification signals are further spliced and integrated to amplify the electroencephalogram signals. Therefore, potential electroencephalogram information can be effectively discovered from the original electroencephalogram signals, the current electroencephalogram characteristics are reflected, the purpose of amplifying the electroencephalogram signals is achieved, and the technical effect of improving the reliability and effectiveness of the electroencephalogram information is achieved. The method further solves the technical problems that the existing electroencephalogram signal amplification method is limited in effect and poor in robustness, and therefore the existing electroencephalogram signal amplification method cannot be widely used in the actual BCI system construction.

Additional aspects and advantages of the disclosure will be set forth in part in the description which follows and, in part, will be obvious from the description, or may be learned by practice of the disclosure.

Drawings

The accompanying drawings, which are included to provide a further understanding of the disclosure and are incorporated in and constitute a part of this disclosure, illustrate embodiments of the disclosure and together with the description serve to explain the disclosure and not to limit the disclosure. In the drawings:

FIG. 1 is a schematic diagram of electrode placement for acquiring electroencephalogram signals in the prior art;

FIG. 2A is a schematic diagram of a prior art electroencephalogram signal processing process;

FIG. 2B is a schematic diagram of a process for processing an electroencephalogram signal according to an embodiment of the present disclosure;

FIG. 3 is a schematic flow chart diagram according to a first embodiment of the present disclosure;

FIG. 4 is a schematic flow chart diagram according to a second embodiment of the present disclosure;

FIG. 5 is a schematic diagram of partitioning of a brain electrical signal by a dynamic time window according to a third embodiment of the present disclosure;

FIG. 6 is an overall flow diagram according to an embodiment of the disclosure;

FIG. 7 is a schematic flow chart diagram according to a fourth embodiment of the present disclosure; and

fig. 8 is a block diagram of an electronic device for implementing the method for amplifying a brain electrical signal of an embodiment of the present disclosure.

Detailed Description

Reference will now be made in detail to the embodiments of the present disclosure, examples of which are illustrated in the accompanying drawings, wherein like or similar reference numerals refer to the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the drawings are exemplary only for the purpose of illustrating the present disclosure and should not be construed as limiting the same. On the contrary, the embodiments of the disclosure include all changes, modifications and equivalents coming within the spirit and terms of the claims appended hereto.

Aiming at the technical problems that the electroencephalogram signal amplification method in the prior art mentioned in the background art is limited in action effect and poor in robustness, and therefore cannot be widely used in the actual BCI system construction, the technical scheme provided by the embodiment provides the electroencephalogram signal amplification method, and referring to fig. 2B, before feature extraction is performed on the electroencephalogram signal, the signal can be amplified by the technical scheme provided by the disclosure. The process is described below with reference to specific examples.

It should be noted that an execution main body of the electroencephalogram signal amplification method of the present embodiment may be an electroencephalogram signal amplification device, the device may be implemented by software and/or hardware, the device may be configured in an electronic device, and the electronic device may include, but is not limited to, a terminal, a server, and the like.

Fig. 3 is a schematic diagram according to a first embodiment of the present disclosure. As shown in fig. 3, the method for amplifying an electroencephalogram signal includes:

s301: acquiring an electroencephalogram signal, determining a first lead from a plurality of leads contained in the electroencephalogram signal, determining at least one second lead from the plurality of leads from which the first lead is removed to form a second lead set, and taking the first lead and the second lead set as a current arrangement combination form.

Specifically, the method firstly acquires an electroencephalogram signal, wherein the electroencephalogram signal is, for example and without limitation, an epileptic electroencephalogram signal, a steady-state visual evoked potential signal and the like. The electroencephalogram signal can be an originally acquired electroencephalogram signal or can be an electroencephalogram signal after preprocessing. Also, the electroencephalogram signal may be in the form of a two-dimensional signal

Wherein N is_cAnd N_tThe channel number (namely the number of leads) of the electroencephalogram signals and the acquisition time point are respectively represented, the channel number and the acquisition time point are constants, and R represents a real number set.

Further, a first lead is determined from a plurality of leads contained in the brain electrical signal, and at least one second lead is determined from the plurality of leads after the first lead is removed to form a second lead set. In a specific example, taking an epileptic brain electrical signal as an example, the epileptic brain electrical signal includes three leads of FP1, C3 and O1, and the scheme needs to determine a first lead set and a second lead set from the three leads. In practice, a first lead (e.g., FP1) may be first identified, and then any number of second leads may be extracted from the leads remaining after the first lead is removed to form the second lead set, which in this embodiment includes { C3, O1}, { C3}, { O1 }.

In addition, the scheme also needs to determine a current permutation and combination form corresponding to the electroencephalogram signal, wherein the current permutation and combination form is a permutation and combination form of the first lead and the second lead set. In the above example, the permutation combination form of the first lead and the second lead set composed of the three leads of FP1, C3 and O1 is shown in table 1:

TABLE 1

Referring to table 1, the permutation combination form includes: nine of FP1 and { C3, O1}, FP1 and { C3}, FP1 and { O1}, C3 and { FP1, O1}, C3 and { FP1}, C3 and { O1}, O1 and { FP1, C3}, O1 and { FP1}, O1 and { C3 }. The scheme needs to determine a permutation combination form as the current permutation combination form, for example: the current permutation combination is FP1 and { C3, O1 }. The present embodiment will be described below with FP1 and { C3, O1} as the current permutation combination.

It should be understood that although the present solution is described by taking an electroencephalogram signal as an example, a person skilled in the art may also apply the signal amplification method to other application scenarios, such as an electrocardiograph signal. The form of the signal is not particularly limited.

S302: the electroencephalogram signal is divided into a plurality of segmented electroencephalogram signals, and the segmented electroencephalogram signals are respectively divided into a plurality of corresponding signals of a first time segment and a plurality of corresponding signals of a second time segment.

Specifically, under the condition of acquiring the electroencephalogram signal, the technical scheme of the embodiment needs to divide the electroencephalogram signal into a plurality of segmented electroencephalogram signals, that is: intercepting a segment of electroencephalogram signal into a plurality of segmented electroencephalogram signals, for example, dividing the electroencephalogram signal into: j segments of electroencephalogram signals are 1 segment of electroencephalogram signals and 2 segment of electroencephalogram signals, wherein j represents the serial number of the segment of electroencephalogram signals.

Further, the segmented brain electrical signals are respectively divided into a plurality of corresponding signals of the first time segments and a plurality of corresponding signals of the second time segments. In actual operation, one segmented electroencephalogram signal can be arbitrarily extracted from a plurality of segmented electroencephalogram signals, and then the extracted electroencephalogram signal is divided again according to time to obtain a signal of a first time segment and a signal of a second time segment. The lengths of the first time segment and the second time segment may be determined according to actual needs, the lengths of the two time segments may be the same or different, and the scheme is not particularly limited. And dividing each segmented electroencephalogram signal again according to the mode, wherein the dividing process is not described again. Therefore, the corresponding signals of the first time segment and the second time segment can be obtained for each segmented electroencephalogram signal.

S303: respectively determining the signals of the first lead under a plurality of first time segments as a plurality of corresponding first signals, respectively determining the signals of the second lead set under a plurality of first time segments as a plurality of corresponding second signals, and respectively constructing a plurality of corresponding spatial filters according to the plurality of first signals and the plurality of second signals.

Specifically, after determining the signals of the first time segment and the signals of the second time segment, further, the technical solution of the present embodiment determines the signals of the first lead under the multiple first time segments as corresponding multiple first signals, and determines the signals of the second lead set under the multiple first time segments as corresponding multiple second signals.

In actual operation, for each segmented brain electrical signal, the signals of the first lead set and the second lead set in the first time segment of the segment are respectively determined as a first signal and a second signal.

In one particular example, for example: the segmented electroencephalogram signal is j segmented electroencephalogram signal, the signal of the first lead FP1 in the first time segment of the j segmented electroencephalogram signal is the first signal, and the signal of the second lead C3 and O1 in the first time segment of the j segmented electroencephalogram signal is the second signal. The determination manner of the first signal and the second signal corresponding to other segmented electroencephalogram signals is similar to the determination manner of the j segmented electroencephalogram signals, and is not described herein again. Thus, for each segmented brain electrical signal (1 segmented brain electrical signal.. j segmented brain electrical signal), the first and second signals of the first and second leads under that segment can be determined.

Further, a plurality of corresponding spatial filters are respectively constructed according to the plurality of first signals and the plurality of second signals. Namely: and respectively constructing a spatial filter according to the first signal and the second signal under each segmented electroencephalogram signal, so that each segmented electroencephalogram signal corresponds to an independent spatial filter. The spatial filter in the technical solution of this embodiment may refer to, for example, a spatial filter construction principle in the prior art, and the spatial filter is not specifically limited herein.

S304: and respectively carrying out spatial filtering processing on the signals of the corresponding first time segment and the signals of the corresponding second time segment by utilizing a plurality of spatial filters to obtain amplified signals.

Further, when the spatial filter is constructed, the present solution performs spatial filtering processing on the corresponding signal of the first time slice and the signal of the second time slice by using a plurality of spatial filters, that is: and filtering the signals of the first time segment and the signals of the second time segment of the corresponding segmented brain electrical signals by using each spatial filter, thereby obtaining the amplified signals of the first time segment and the amplified signals of the second time segment of each segmented brain electrical signals.

S305: splicing and integrating a plurality of amplified signals respectively corresponding to the segmented electroencephalogram signals so as to amplify the electroencephalogram signals.

Finally, under the condition of obtaining the amplification signals, the present embodiment splices and integrates the amplification signals respectively corresponding to the segmented electroencephalogram signals. In the specific implementation, the amplified signals in different time segments can be spliced, and under the condition that the amplified signals in the first time segment and the second time segment of each segmented electroencephalogram signal are spliced, each spliced segmented electroencephalogram signal is integrated, so that the process of amplifying the electroencephalogram signals is completed.

According to the technical scheme of the embodiment, the electroencephalogram signals are filtered by constructing and applying the spatial filter to obtain the amplification signals, and the amplification signals are further spliced and integrated to amplify the electroencephalogram signals. Therefore, potential electroencephalogram information can be effectively discovered from the original electroencephalogram signals, the current electroencephalogram characteristics are reflected, the purpose of amplifying the electroencephalogram signals is achieved, and the technical effect of improving the reliability and effectiveness of the electroencephalogram information is achieved. The method further solves the technical problems that the existing electroencephalogram signal amplification method is limited in effect and poor in robustness, and therefore the existing electroencephalogram signal amplification method cannot be widely used in the actual BCI system construction.

The first embodiment can realize signal amplification of the brain electrical signals of leads (FP1 and { C3, O1} in a permutation and combination mode. However, in order to further amplify the brain electrical signal, the present disclosure also proposes a second embodiment, and fig. 4 is a schematic diagram according to the second embodiment of the present disclosure. As shown in fig. 4, the method for amplifying an electroencephalogram signal includes:

s401: acquiring an electroencephalogram signal, determining a first lead from a plurality of leads contained in the electroencephalogram signal, determining at least one second lead from the plurality of leads from which the first lead is removed to form a second lead set, and taking the first lead and the second lead set as a current arrangement combination form.

S402: the electroencephalogram signal is divided into a plurality of segmented electroencephalogram signals, and the segmented electroencephalogram signals are respectively divided into a plurality of corresponding signals of a first time segment and a plurality of corresponding signals of a second time segment.

S403: respectively determining the signals of the first lead under a plurality of first time segments as a plurality of corresponding first signals, respectively determining the signals of the second lead set under a plurality of first time segments as a plurality of corresponding second signals, and respectively constructing a plurality of corresponding spatial filters according to the plurality of first signals and the plurality of second signals.

S404: and respectively carrying out spatial filtering processing on the signals of the corresponding first time segment and the signals of the corresponding second time segment by utilizing a plurality of spatial filters to obtain amplified signals.

S405: splicing and integrating a plurality of amplified signals respectively corresponding to the segmented electroencephalogram signals so as to amplify the electroencephalogram signals.

For the description of S401 to S405, reference may be made to the above embodiments specifically, and details are not repeated here.

S406: and updating the current permutation and combination form, and amplifying the electroencephalogram signals corresponding to the updated current permutation and combination form.

Specifically, in connection with the first embodiment, after the signal amplification is completed for the current permutation and combination form (FP1 and { C3, O1}), the present scheme may also update the current permutation and combination form. In practical operation, the above nine permutation and combination forms may be traversed, the traversed permutation and combination form is taken as the current permutation and combination form, and the operations of steps S402-S405 are performed.

In one embodiment, for example, in the case of signal amplification of the current permutation combination (FP1 and { C3, O1}), the remaining eight permutation combination forms are traversed, for example, to the permutation combination of FP1 and { C3}, so that FP1 and { C3} are used as the updated current permutation combination. Further, the operations of S402-S405 are carried out for FP1 and { C3}, and finally the amplification of the brain electrical signals under the arrangement combination form of FP1 and { C3 }. And traversing the permutation and combination forms in sequence until the electroencephalogram signals under the nine permutation and combination forms are amplified.

If the amplification signal obtained in each permutation combination is y⁽ⁿ⁾Where n represents the number of the permutation combination, the amplification signals obtained in the above nine permutation combinations are shown in Table 2:

TABLE 2

Therefore, more amplification signals can be obtained through the method, and the purpose of amplifying the electroencephalogram signals is further achieved.

Optionally, dividing the electroencephalogram signal into a plurality of segmented electroencephalogram signals, and dividing the segmented electroencephalogram signals into a continuous first time slice signal and a continuous second time slice signal, includes: the electroencephalogram signal is divided into a plurality of segmented electroencephalogram signals by utilizing a dynamic time window, wherein the dynamic time window is expressed by a time range [ t-delta t ] with t as a center₁,t+Δt₂]Form of [ t- Δ t ]₁,t]Represents a first time segment, [ t, t + Δ t [ ]₂]Representing a second time segment.

Specifically, in the third embodiment of the present disclosure, in the operation of dividing the electroencephalogram signal into a plurality of segmented electroencephalogram signals and dividing the segmented electroencephalogram signals into continuous first time segment signals and second time segment signals, the scheme may divide the electroencephalogram signals by using a dynamic time window.

In one embodiment, as illustrated with reference to FIG. 5, the dynamic time window is, for example, [ t- Δ t ]₁,t+Δt₂]The dynamic time window with t as the center is shown, and the set of the center points of the time window t ═ t⁽¹⁾,t⁽²⁾...t^(j)Inner element t^(j)Represents each segmented electroencephalogram signal after division and needs to satisfy the condition delta t₁≤t^(j)≤T-Δt₂Step length between the centers of different time windows is t_s(ii) a j represents the number of the segmented electroencephalogram signals, namely: t is t⁽¹⁾,t⁽²⁾...t^(j)Sequentially corresponding to the 1-segment electroencephalogram signal and the 2-segment electroencephalogram signal; t represents the total duration of the brain electrical signal.

Furthermore, the segmented brain electrical signals can be divided by the dynamic time window. Specifically, referring to FIG. 5, t- Δ t may be utilized₁,t]The interval represents a first time segment (corresponding to segment of FIG. 5), using [ t, t + Δ t₂]The interval represents a second time segment (corresponding to the second segment in fig. 5).

Therefore, by the method, the electroencephalogram signals can be accurately divided to obtain the segmented electroencephalogram signals, and the process of dividing the segmented electroencephalogram signals into the first time segment and the second time segment is simpler and more convenient.

Optionally, in the process of constructing the spatial filter, the spatial filter may be constructed by using a target formula, where the target formula is:

target formula, representing spatial filter W corresponding to segmented electroencephalogram signal numbered j_jThe constraint of (1) | ventilation_pIs the P-norm of the vector, argmin functionThe numbers are used for: the variable value at which the target is minimized is searched,

as spatial filter W under constraint_jIs estimated, wherein U_j(i,: is a first signal, i represents the number of the first lead;

is a second signal, wherein

Represents a second set of leads that are,

representing the signal of the segmented brain electrical signal with the number j in the first time segment, where N_cThe number of multiple leads contained for an electroencephalogram signal, m represents the number of sampling points intercepted by a dynamic time window, and m is [ delta t [ ]₁×F_s]And m is an integer part not exceeding a real number, and Fs is the sampling frequency of the electroencephalogram signal.

The scheme can construct the spatial filter by utilizing the electroencephalogram signals, so that the constructed spatial filter can fully reserve the characteristics of the electroencephalogram signals, the robustness of the electroencephalogram signal amplification process is stronger, and the electroencephalogram signals obtained through amplification can reflect the current electroencephalogram characteristics.

It should be understood that the present solution only explains the process of constructing the spatial filter by taking the target formula as an example, but the construction of the spatial filter is not limited to the target formula, and may also be constructed by using other formulas or other forms, and is not limited specifically herein.

Optionally, in the operation of obtaining the amplified signal by performing spatial filtering on the signal of the first time segment and the signal of the second time segment of the segmented electroencephalogram signal by using a spatial filter, the disclosed technical solution may obtain the amplified signal according to the following formula:

wherein, χ_j∈R^1×mAnd gamma_j∈R^1×nRespectively represent a pair of U_jAnd V_jThe amplified signal obtained by the filtering process is processed,

representing the signal of the segmented electroencephalogram signal with the number j in the second time segment, n represents the number of sampling points intercepted by the dynamic time window, and n is [ delta t ═ t₂×F_s]And n is an integer part not exceeding a real number, V_j(i,: representing the signal of the first lead with the number i in the second time segment of the segmented brain electrical signal with the number j,

and representing the signals of a second lead set corresponding to the first lead with the number i in a second time segment of the segmented electroencephalogram signal with the number j.

Therefore, the signals under each time segment can be amplified respectively through the mode, and the signals obtained through amplification can better reflect the current electroencephalogram characteristics.

It should be understood that the present embodiment is only illustrative of the signal amplification process by taking the above formula as an example, but the signal amplification process includes but is not limited to the above method, and the signal amplification process can also be performed by using other formula or other form, and is not limited herein.

In order to describe the technical solution of the present disclosure more clearly, the present disclosure will be further explained by using an embodiment of an overall flow, and fig. 6 exemplarily shows an overall flow schematic diagram of the embodiment of the present disclosure, and with reference to fig. 6, the method includes the following steps:

1) inputting the preprocessed signal (corresponding to the electroencephalogram signal in the above-described embodiment)

2) The target lead (which corresponds to the first lead in the above-described embodiment) is determined, and an indefinite number of lead sets (which corresponds to the second lead set in the above-described embodiment) are arbitrarily extracted from the remaining leads other than the target lead. For the preprocessed data, several pieces of segmented data (corresponding to the segmented electroencephalogram signal of the above embodiment) are sequentially intercepted according to a dynamic time window, and the segmented data is divided into signals of two time segments (corresponding to the first time segment and the second time segment of the above embodiment).

The input pre-processed data can be represented as a two-dimensional signal

Wherein N is_cAnd N_tRespectively representing the channel number (namely the number of leads) of the electroencephalogram signals and the data point number (acquisition time point), and all the data points are constants, and R represents a real number set. Shown in connection with FIG. 5, the time range t- Δ t₁,t+Δt₂]Representing a dynamic time window centered at t, the set of time window center points t ═ t⁽¹⁾,t⁽²⁾...t^(j)Inner element t^(j)The condition Δ t needs to be satisfied₁≤t^(j)≤T-Δt₂Step length between the centers of different time windows is t_sWhere j represents the sequence number of the segment data and T represents the total duration of the signal.

The dynamic time window may divide the segmented data into: [ t-. DELTA.t₁,t]The time slice (r) signal within the interval (corresponding to the first time slice of the above embodiment) can be represented as j-th segment data

[t,t+Δt₂]The time slice within the interval (corresponding to the second time slice of the above embodiment) can be expressed as j-th segment data

Wherein m and n represent the sampling point number intercepted by the dynamic time window, and see the formulas (1) and (2):

m＝[Δt₁×F_s]m is a positive integer (1)

n＝[Δt₂×F_s]N is a positive integer (2)

Wherein Fs is the sampling frequency of the signal; [ x ] is a rounding function, representing the integer part not exceeding the real number x.

3) Any one of the segmented data is selected, a template signal (the template signal corresponds to the first signal of the above embodiment) and a fitting signal (the fitting signal corresponds to the second signal of the above embodiment) in two time segments are respectively determined according to the target lead and the decimated lead set, and a dynamic spatial filter is constructed by using the template signal and the fitting signal in the previous time segment.

The construction process of the spatial filter is as follows:

equation (3) represents a spatial filter W_jThe constraint of (1) | ventilation_pThe purpose of the argmin function is to find the variable value that minimizes the target, being the P-norm of the vector,

for spatial filter W under the constraint_jIs estimated.

In the formula of U_j(i,: is a template signal representing a time slice U_jThe signal of the lower target lead i;

is a fitting signal, representing a time slice U_jLower lead set

Of wherein

Is from N except the target lead i_c-1 of the remaining leads is arbitrarily extracted,An indefinite number of lead sets.

4) And (3) carrying out spatial filtering processing on the two time segment signals by using a spatial filter to respectively obtain amplification signals of different time segments under the segmented data.

The application process of the spatial filter is as follows:

in the formulae (4) and (5), χ_j∈R^1×mAnd gamma_j∈R^1×nRespectively represents U_jAnd V_jThe resulting amplified signal, all possible values of both and the extracted lead set

The number of the permutation and combination is consistent. Wherein, V_j(i,: is a time slice V)_jThe signal of the lower target lead i,

is representative of a time segment V_jLower lead set

Of the signal of (1).

5) And repeating the steps 3) and 4) until all the segmented data are processed. And splicing and integrating all the obtained segmented amplification signals, and outputting the final amplification signals obtained under the target lead and the lead group.

Traversing j segmental data under different time windows to obtain segmental amplification signals χ under different segmental data_j∈R^1×mAnd gamma_j∈R^1×n. For segmented amplification signals under different time windows, according to a set of central points of the time windows { t⁽¹⁾,t⁽²⁾...t^(j)Splicing and integrating to obtain the targetLabel i, lead set

New component signal of

(i.e., amplification signal).

When t is_s<Δt₁+Δt₂When the data is processed, the overlapped part can be subjected to the overlapping average processing; when t is_s≥Δt₁+Δt₂In this case, zero padding or interpolation may be performed for the missing part. It should be noted that if at [ t- Δ t ]₁,t]The time segment of the interval is (i) a task-independent signal at [ t, t + Δ t₂]The time slice of the interval is the task-related signal, in which case splicing and integration can be performed using only gamma_j∈R^1×nA portion of the signal.

Repeating the steps 2) to 5), traversing all permutation and combination of the target lead and the decimation lead set to obtain a plurality of new component signals. The new component signals and the original signals form a new electroencephalogram component space together.

Specifically, the target lead i is sequentially reselected, and the lead group is decimated

Repeating the steps 2) to 5) to obtain a plurality of new component signals

Wherein, y⁽ⁿ⁾Representing the nth new component signal. Set { y⁽¹⁾,y⁽²⁾...y⁽ⁿ⁾The new EEG component space is formed by the subset of the EEG component space and the original signal

N_sRepresents the amount of the components in the post-amplification space, and the maximum possible value thereof is determined by equation (6).

The method has wide application range in electroencephalogram signal processing and analysis and considerable practicability. The obtained amplification signal is used as a new electroencephalogram component, original data are mapped to a new component space, and potential electroencephalogram information can be effectively explored.

In addition, the amplification signal is obtained by constructing and applying the dynamic spatial filter, so that the obtained amplification signal can reflect the current electroencephalogram characteristic and has higher reliability and effectiveness.

The electroencephalogram signal amplification method provided by the disclosure can generate a large number of amplification signals, and the obtained new component space contains the original signals and the amplification signals. Described in more detail is: under the same target lead, from N_cArbitrarily extracted, variable-number lead set of 1 remaining leads

Can generate

And combinations are possible. To number of lead-in is N_cThe method produces

The segment amplification signals or the subsets and the original signals jointly form a new electroencephalogram component space.

Fig. 7 is a schematic diagram according to a fourth embodiment of the present disclosure.

As shown in fig. 7, the electroencephalogram signal amplification device 70 includes: the signal acquisition module 701 is configured to acquire an electroencephalogram signal, determine a first lead from a plurality of leads included in the electroencephalogram signal, determine at least one second lead from the plurality of leads from which the first lead is removed to form a second lead set, and use the first lead and the second lead set as a current arrangement combination form;

a signal dividing module 702, configured to divide the electroencephalogram signal into a plurality of segmented electroencephalogram signals, and divide the plurality of segmented electroencephalogram signals into a plurality of corresponding signals of a first time segment and a plurality of corresponding signals of a second time segment, respectively;

a filter constructing module 703, configured to respectively determine that the signals of the first lead in the multiple first time segments are the corresponding multiple first signals, respectively determine that the signals of the second lead set in the multiple first time segments are the corresponding multiple second signals, and respectively construct the corresponding multiple spatial filters according to the multiple first signals and the multiple second signals;

a filtering processing module 704, configured to perform spatial filtering processing on the signals of the corresponding first time segment and the signals of the corresponding second time segment by using a plurality of spatial filters, respectively, to obtain amplified signals; and

the first amplification module 705 is configured to splice and integrate a plurality of amplification signals corresponding to the plurality of segmented electroencephalogram signals, so as to amplify the electroencephalogram signals.

Optionally, the apparatus 70 further comprises: and the second amplification module is used for splicing and integrating a plurality of amplification signals respectively corresponding to the plurality of segmented electroencephalogram signals so as to amplify the electroencephalogram signals, updating the current permutation and combination form, and amplifying the electroencephalogram signals corresponding to the updated current permutation and combination form.

Optionally, the signal dividing module 702 includes: a signal dividing submodule for dividing the electroencephalogram signal into a plurality of segmented electroencephalogram signals by using a dynamic time window, wherein the dynamic time window is represented by a time range [ t-delta t ] with t as a center₁,t+Δt₂]Form of [ t- Δ t ]₁,t]Represents a first time segment, [ t, t + Δ t [ ]₂]Representing a second time segment.

Optionally, the filter constructing module 703 constructs the spatial filter by using a target formula, where the target formula is:

target formula, representing spatial filter W corresponding to segmented electroencephalogram signal numbered j_jThe constraint of (1) | ventilation_pFor the P-norm of the vector, the argmin function is used to: the variable value at which the target is minimized is searched,

is a second signal, wherein

Represents a second set of leads that are,

Optionally, the filtering processing module 704 obtains the amplified signal according to the following formula:

representing the signal of the segmented electroencephalogram signal with the number j in the second time segment, n represents the number of sampling points intercepted by the dynamic time window, and n is [ delta t ═ t₂×F_s]And n is an integer part not exceeding a real number, V_j(i,: represents the first lead numbered iThe signal at the second time segment of the segmented brain electrical signal numbered j,

It should be noted that the explanation of the electroencephalogram signal amplification method is also applicable to the apparatus of this embodiment, and is not repeated here.

The present disclosure also provides an electronic device and a readable storage medium according to an embodiment of the present disclosure.

Fig. 8 is a block diagram of an electronic device for implementing the method for amplifying a brain electrical signal of an embodiment of the present disclosure. Electronic devices are intended to represent various forms of digital computers, such as laptops, desktops, workstations, personal digital assistants, servers, blade servers, mainframes, and other appropriate computers. The electronic device may also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions, are meant to be examples only, and are not meant to limit implementations of the disclosure described and/or claimed herein.

As shown in fig. 8, the apparatus 800 includes a computing unit 801 that can perform various appropriate actions and processes according to a computer program stored in a Read Only Memory (ROM)802 or a computer program loaded from a storage unit 808 into a Random Access Memory (RAM) 803. In the RAM 803, various programs and data required for the operation of the device 800 can also be stored. The calculation unit 801, the ROM 802, and the RAM 803 are connected to each other by a bus 804. An input/output (I/O) interface 805 is also connected to bus 804.

A number of components in the device 800 are connected to the I/O interface 805, including: an input unit 806, such as a keyboard, a mouse, or the like; an output unit 807 such as various types of displays, speakers, and the like; a storage unit 808, such as a magnetic disk, optical disk, or the like; and a communication unit 809 such as a network card, modem, wireless communication transceiver, etc. The communication unit 809 allows the device 800 to exchange information/data with other devices via a computer network such as the internet and/or various telecommunication networks.

Computing unit 801 may be a variety of general and/or special purpose processing components with processing and computing capabilities. Some examples of the computing unit 801 include, but are not limited to, a Central Processing Unit (CPU), a Graphics Processing Unit (GPU), various dedicated Artificial Intelligence (AI) computing chips, various computing units running machine learning model algorithms, a Digital Signal Processor (DSP), and any suitable processor, controller, microcontroller, and the like. The calculation unit 801 executes the respective methods and processes described above, for example, an amplification method of brain electrical signals.

For example, in some embodiments, the method of amplification of brain electrical signals may be implemented as a computer software program tangibly embodied in a machine-readable medium, such as storage unit 808. In some embodiments, part or all of the computer program can be loaded and/or installed onto device 800 via ROM 802 and/or communications unit 809. When the computer program is loaded into the RAM 803 and executed by the computing unit 801, one or more steps of the method for amplifying an electroencephalogram signal described above may be performed. Alternatively, in other embodiments, the computing unit 801 may be configured to perform the method of amplification of the brain electrical signal by any other suitable means (e.g., by means of firmware).

Various implementations of the systems and techniques described here above may be implemented in digital electronic circuitry, integrated circuitry, Field Programmable Gate Arrays (FPGAs), Application Specific Integrated Circuits (ASICs), Application Specific Standard Products (ASSPs), system on a chip (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and/or combinations thereof. These various embodiments may include: implemented in one or more computer programs that are executable and/or interpretable on a programmable system including at least one programmable processor, which may be special or general purpose, receiving data and instructions from, and transmitting data and instructions to, a storage system, at least one input device, and at least one output device.

Program code for implementing the brain electrical signal amplification method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general purpose computer, special purpose computer, or other programmable brain signal amplification apparatus, such that the program codes, when executed by the processor or controller, cause the functions/operations specified in the flowchart and/or block diagram to be performed. The program code may execute entirely on the machine, partly on the machine, as a stand-alone software package partly on the machine and partly on a remote machine or entirely on the remote machine or server.

In the context of this disclosure, a machine-readable medium may be a tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. The machine-readable medium may be a machine-readable signal medium or a machine-readable storage medium. A machine-readable medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples of a machine-readable storage medium would include an electrical connection based on one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.

To provide for interaction with a user, the systems and techniques described here can be implemented on a computer having: a display device (e.g., a CRT (cathode ray tube) or LCD (liquid crystal display) monitor) for displaying information to a user; and a keyboard and a pointing device (e.g., a mouse or a trackball) by which a user can provide input to the computer. Other kinds of devices may also be used to provide for interaction with a user; for example, feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user may be received in any form, including acoustic, speech, or tactile input.

The systems and techniques described here can be implemented in a computing system that includes a back-end component (e.g., as a data server), or that includes a middleware component (e.g., an application server), or that includes a front-end component (e.g., a user computer having a graphical user interface or a web browser through which a user can interact with an implementation of the systems and techniques described here), or any combination of such back-end, middleware, or front-end components. The components of the system can be interconnected by any form or medium of digital data communication (e.g., a communication network). Examples of communication networks include: local Area Networks (LANs), Wide Area Networks (WANs), the internet, and blockchain networks.

The computer system may include clients and servers. A client and server are generally remote from each other and typically interact through a communication network. The relationship of client and server arises by virtue of computer programs running on the respective computers and having a client-server relationship to each other. The Server can be a cloud Server, also called a cloud computing Server or a cloud host, and is a host product in a cloud computing service system, so as to solve the defects of high management difficulty and weak service expansibility in the traditional physical host and VPS service ("Virtual Private Server", or simply "VPS"). The server may also be a server of a distributed system, or a server incorporating a blockchain.

It should be noted that, in the description of the present disclosure, the terms "first", "second", etc. are used for descriptive purposes only and are not to be construed as indicating or implying relative importance. Further, in the description of the present disclosure, "a plurality" means two or more unless otherwise specified.

Any process or method descriptions in flow charts or otherwise described herein may be understood as representing modules, segments, or portions of code which include one or more executable instructions for implementing specific logical functions or steps of the process, and the scope of the preferred embodiments of the present disclosure includes other implementations in which functions may be executed out of order from that shown or discussed, including substantially concurrently or in reverse order, depending on the functionality involved, as would be understood by those reasonably skilled in the art of the embodiments of the present disclosure.

It should be understood that portions of the present disclosure may be implemented in hardware, software, firmware, or a combination thereof. In the above embodiments, the various steps or methods may be implemented in software or firmware stored in memory and executed by a suitable instruction execution system. For example, if implemented in hardware, as in another embodiment, any one or combination of the following techniques, which are known in the art, may be used: a discrete logic circuit having a logic gate circuit for implementing a logic function on a data signal, an application specific integrated circuit having an appropriate combinational logic gate circuit, a Programmable Gate Array (PGA), a Field Programmable Gate Array (FPGA), or the like.

It will be understood by those skilled in the art that all or part of the steps carried by the method for implementing the above embodiments may be implemented by hardware related to instructions of a program, which may be stored in a computer readable storage medium, and when the program is executed, the program includes one or a combination of the steps of the method embodiments.

In addition, functional units in the embodiments of the present disclosure may be integrated into one processing module, or each unit may exist alone physically, or two or more units are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode. The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may also be stored in a computer readable storage medium.

The storage medium mentioned above may be a read-only memory, a magnetic or optical disk, etc.

In the description herein, references to the description of the term "one embodiment," "some embodiments," "an example," "a specific example," or "some examples," etc., mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the present disclosure. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.

Although embodiments of the present disclosure have been shown and described above, it is understood that the above embodiments are exemplary and should not be construed as limiting the present disclosure, and that changes, modifications, substitutions and alterations may be made to the above embodiments by those of ordinary skill in the art within the scope of the present disclosure.

Claims

1. A method for amplifying an electroencephalogram signal, the method comprising:

acquiring an electroencephalogram signal, determining a first lead from a plurality of leads contained in the electroencephalogram signal, determining at least one second lead from the plurality of leads after the first lead is removed to form a second lead set, and taking the first lead and the second lead set as a current arrangement combination form;

dividing the electroencephalogram signal into a plurality of segmented electroencephalogram signals, and dividing the plurality of segmented electroencephalogram signals into a plurality of corresponding signals of a first time segment and a plurality of corresponding signals of a second time segment;

respectively determining the signals of the first lead under the multiple first time segments as corresponding multiple first signals, respectively determining the signals of the second lead set under the multiple first time segments as corresponding multiple second signals, and respectively constructing corresponding multiple spatial filters according to the multiple first signals and the multiple second signals;

performing spatial filtering processing on the signals of the corresponding first time segment and the signals of the corresponding second time segment by using the plurality of spatial filters to obtain amplified signals; and

and splicing and integrating a plurality of amplified signals respectively corresponding to the plurality of segmented electroencephalogram signals so as to amplify the electroencephalogram signals.

2. The method of claim 1, wherein after said splicing and integrating a plurality of amplification signals respectively corresponding to said plurality of segmented brain electrical signals to amplify said brain electrical signals, further comprising:

and updating the current permutation and combination form, and amplifying the electroencephalogram signals corresponding to the updated current permutation and combination form.

3. The method of claim 1, wherein dividing the brain electrical signal into a plurality of segmented brain electrical signals, dividing the plurality of segmented brain electrical signals into a corresponding plurality of first time segments of signals, and a corresponding plurality of second time segments of signals, comprises:

dividing the electroencephalogram signal into a plurality of segmented electroencephalogram signals by using a dynamic time window, wherein the dynamic time window is represented by a time range [ t-delta t ] with t as a center₁,t+Δt₂]Form of [ t- Δ t ]₁,t]Represents a first time segment, [ t, t + Δ t [ ]₂]Representing a second time segment.

4. The method of claim 3, wherein the spatial filter is constructed using a target formula, wherein the target formula is:

the target formula represents a spatial filter W corresponding to the segmented electroencephalogram signal with the number of j_jThe constraint of (1) | ventilation_pFor the P-norm of the vector, the argmin function is used to: the variable value at which the target is minimized is searched,

for the spatial filter W under the constraint_jIs estimated, wherein U_j(i,: is said first signal, i represents the number of said first lead;

is the second signal, wherein

Represents the second set of leads and is,

representing the signal of the segmented brain electrical signal with the number j in the first time segment, where N_cThe number of a plurality of leads contained in the electroencephalogram signal, m represents the number of sampling points intercepted by the dynamic time window, and m is [ delta t [ ]₁×F_s]And m is an integer part not exceeding a real number, and Fs is the sampling frequency of the electroencephalogram signal.

5. The method of claim 4, wherein spatially filtering the signals of the first temporal segment and the signals of the second temporal segment of the segmented brain electrical signal with the spatial filter to obtain an augmented signal, comprises obtaining the augmented signal according to the following formula:

representing the signal of the segmented electroencephalogram signal with the number j in the second time segment, wherein n represents the number of sampling points intercepted by the dynamic time window, and n is [ delta t ═ t₂×F_s]And n is an integer part not exceeding a real number, V_j(i,: representing the signal of the first lead with the number i in the second time segment of the segmented brain electrical signal with the number j,

6. An electroencephalogram signal amplification apparatus, comprising:

the signal acquisition module is used for determining a first lead from a plurality of leads contained in the electroencephalogram signal, determining at least one second lead from the plurality of leads after the first lead is removed to form a second lead set, and taking the first lead and the second lead set as a current arrangement combination form;

the signal dividing module is used for dividing the electroencephalogram signal into a plurality of segmented electroencephalogram signals, and respectively dividing the plurality of segmented electroencephalogram signals into a plurality of corresponding signals of a first time segment and a plurality of corresponding signals of a second time segment;

a filter construction module, configured to respectively determine that the signals of the first lead in the multiple first time segments are multiple corresponding first signals, respectively determine that the signals of the second lead set in the multiple first time segments are multiple corresponding second signals, and respectively construct multiple corresponding spatial filters according to the multiple first signals and the multiple second signals;

the filtering processing module is used for respectively carrying out spatial filtering processing on the signals of the corresponding first time segment and the signals of the corresponding second time segment by utilizing the plurality of spatial filters to obtain amplified signals; and

the first amplification module is used for splicing and integrating a plurality of amplification signals respectively corresponding to the plurality of segmented electroencephalogram signals so as to amplify the electroencephalogram signals.

7. The brain electrical signal amplification apparatus of claim 6, further comprising: and the second amplification module is used for splicing and integrating a plurality of amplification signals respectively corresponding to the plurality of segmented electroencephalogram signals so as to amplify the electroencephalogram signals, updating the current permutation and combination form, and amplifying the electroencephalogram signals corresponding to the updated current permutation and combination form.

8. The brain electrical signal amplification apparatus of claim 6, wherein said signal division module comprises:

a signal dividing sub-module for dividing the electroencephalogram signal into a plurality of segmented electroencephalogram signals by using a dynamic time window, wherein the dynamic time window is represented by a time range [ t-delta t ] with t as a center₁,t+Δt₂]Form of [ t- Δ t ]₁,t]Represents a first time segment, [ t, t + Δ t [ ]₂]Representing a second time segment.

9. An electronic device, comprising:

at least one processor; and

a memory communicatively coupled to the at least one processor; wherein the content of the first and second substances,

the memory stores instructions executable by the at least one processor to enable the at least one processor to perform the method of any one of claims 1-5.

10. A non-transitory computer readable storage medium having stored thereon computer instructions for causing the computer to perform the method of any one of claims 1-5.